Acute Kidney Injury

 

Title: Acute Pyelonephritis, Acute Kidney Injury. Scenario: A 75-year-old female with a history of asthma and type 2 diabetes mellitus began to experience burning upon urination, lower abdominal pain, and frequent urination a few days ago.

After trying to manage her symptoms by increasing fluids, she arrived at the emergency department with her daughter with complaints of right flank pain, fever, and malaise. Her daughter said that the patient who is normally alert and oriented is now experiencing some confusion. Urinalysis results show bacteriuria, hematuria, and white blood cell casts. The nurse documents the following assessment findings:

____ Temperature 102.2◦F (39◦C)

____ Heart rate = 94 bpm

____ Blood pressure = 138/76 mmHg

____ Respirations = 20 breaths per minute

____ Right sided costovertebral angle tenderness

____ Patient reports malaise

____ Reports 1 pack per day cigarette use

____ Patient not oriented to place and time

____ Patient reports nausea

 

Cognitive Skill: Recognize Cues

 

 

 

 

 

 

1. NGN Item Type: Extended Multiple Response

Place a check mark next to the assessment findings that require follow-up by the nurse.

 

Answer s:

___ Temperature 102.2◦ F (39◦C)

____ Heart rate = 94 bpm

____ Blood pressure = 138/76 mm Hg

____ Respirations = 20 breaths per minute

___ Right sided costovertebral angle tenderness

___ Patient reports malaise

____ Reports 1 pack per day cigarette use

___ Patient not oriented to place and time

____ Patient reports nausea

 

Rationale for your choices :

 

Cognitive Skill: Recognize Cues

 

 

 

 

 

 

 

 

 

2. NGN Item Type: Cloze

Choose the most likely options (by highlighting your choices) for the information missing from the statement below by selectin from the list of options provided.

Based on the patient’s assessment data, the nurse determines that the patient is currently at risk for complications, including _______, _______, and _______.

Options

Acute kidney injury

Lower urinary tract infection

Fluid overload

Urosepsis

Chronic kidney failure

Allergic reaction

Hypoglycemia

Septic shock

 

Rationale :

Cognitive Skill: Analyze Cues

 

 

 

 

Scenario: The patient is transferred to a medical unit 2 hours after arriving at the emergency department with an admitting diagnosis of pyelonephritis. She has a history of asthma and type 2 diabetes mellitus. The admitting nurse is assessing the patient and reviewing orders and diagnostic studies to develop a plan of care. The patient is awake, alert, and pleasant but is not oriented to place and time. She reorients easily with frequent reminding. She is complaining of pain but is not able to use the pain intensity scale. Ibuprofen is prescribed for pain every 6 hours as needed. Vital signs are temperature 101.4◦ F, pulse 100 bpm, respirations 22 breaths per minute, blood pressure 138/74 mm Hg. The patient is receiving intravenous normal saline at 100 mL/hour. A urine specimen was sent to the lab for culture and sensitivity. She is tolerating her clear liquid diet well. The nurse began an infusion of an extended spectrum cephalosporin as soon as the urine specimen was obtained and sent to the lab. The patient is voiding frequently and although instructed to do so, does not ask for assistance to ambulate to the bathroom.

 

1. NGN Item Type: Extended Response

Based on the patient’s current treatment plan, the patient’s priority needs will be to prevent which of the following? Select all that apply.

____Patient injury

____Pain

____Aspiration

____Constipation

____Hyperglycemia

____Urosepsis

____Skin breakdown

 

_____ G. Pressure wound

 

Rationale for your choices :

Cognitive Skill: Prioritize Hypotheses

 

 

 

 

2. NGN Item Type: Extended Drag and Drop

Indicate which nursing response listed in the far-left column is appropriate for each client question. Note that not all responses will be used.

Nurse’s Responses

Patient Questions

Appropriate Nurse’s Response for each Patient Question

“You may walk in the hallway as long as you are not feeling weak or dizzy.”

“How much longer will I have this pain in the side of my back?”

 

  • “We can remove your IV needle as soon as you begin to feel better.”

“Why do I have to pass my water so frequently?”

 

  • “The medications given to you through your IV are rapidly absorbed and will begin to kill the bacteria sooner than oral medications would.”

“When will this needle be removed from my arm?”

 

  • “We are giving you a lot of fluids so that you do not become dehydrated and also to dilute your urine to help flush out the bacteria that is in your urinary system. The extra fluids cause you to pass your water frequently.”

“Will I be able to walk around in my room today?”

 

  • “The IV needle will need to remain in your arm as long as you need to receive medications and fluids to treat your kidney infection.”

“Can I take this medicine as a pill instead of through the needle in my arm?”

 

  • “You may only walk in your room with the assistance of one of our healthcare team members.”

 

 

  • “The pain in the side of your back should go away as soon as the infection subsides.”

 

 

  • “I can give you some pain medication, which would provide you with pain relief. Please notify me if you continue to have pain and I will ask your healthcare provider to increase or change your pain medication.”

 

 

 

Rationale for your choices :

Cognitive Skill: Generate Solutions

 

 

 

The patient has now been on the medical unit for 3 days. She was diagnosed with pyelonephritis on admission. Vital signs this morning: Temperature 98.8 (37.1◦C ), blood pressure 100/50 mm Hg, pulse 110 bpm, respirations 24 breaths per minute. The patient is oriented to self only but is awake and alert. Her daughter is at her bedside. The urine culture results showed enterococci, and therefore the broad-spectrum antibiotic the patient was receiving was replaced with sensitivity-guided antibiotic therapy. Abnormal serum laboratory results are as follows: WBC = 14500/mm3 (normal=5000-10000/mm3), BUN = 27 mg/dL (normal = 7-20 mg/dL), creatinine 2.0 mg/dL (normal = 0.5-1.1 mg/dL). She has now been diagnosed with acute kidney injury.

 

NGN Item Type: Matrix

Use an X for the nursing actions listed below that are Indicated (appropriate or necessary), Contraindicated (could be harmful), or Nonessential (makes no difference or not necessary) for the patient’s care at this time. Only one selection can be made for each nursing action.

Nursing Action

Indicated

Contraindicated

Nonessential

Consult with dietician to provide a low caloric diet.

 

 

 

Obtain daily weights.

 

 

 

Medicate with ibuprofen every 6 hours as needed for complaint of pain.

 

 

 

Focus on providing holistic nursing care to patient.

 

 

 

Carefully consider the type, frequency, and dosage of the patient’s prescribed antibiotic therapy.

 

 

 

Assess for the presence of bowel sounds every 4 hours.

 

 

 

 

 

 

Rationale :

 

Cognitive Skill: Take Action

 

 

 

 

 

 

 

 

 

 

 

Scenario: A 75-year-old female was admitted to the hospital 3 weeks ago with a history of a urinary tract infection at home and was diagnosed with pyelonephritis upon admission. Despite treatment, her kidney infection progressed, and she developed acute kidney injury. After her antibiotic therapy was adjusted she recovered well enough to be discharged to her daughter’s home. The patient and her daughter were given discharge instructions to manage her prescriptions and health maintenance at home. She is now at the urology clinic for a 1-week follow-up appointment. Urine and blood samples were analyzed prior to her appointment. The nurse evaluates the effectiveness of actions.

 

NGN Item Type: Extended Multiple Response

Which of the following findings indicate effectiveness? Select all that apply.

_____ 1. The patient reports that she wipes front to back after urinating

_____ 2. The urinalysis report shows WBC >5/hpf (high), RBCs >4/hpf (high)

_____ 3. The patient reports that she drinks 4-5 glasses of fluid per day.

_____ 4. The patient voids approximately 3 times a day.

____ 5. The patient reports that she has stopped taking her antibiotic medication since she is now feeling “fine.”

_____ 6. The patient reports no flank pain.

_____ 7. Serum creatinine level is 1.0 mg/dL.

_____ 8. The patient states that she rests frequently.

 

 

Rationale for your choices :

 

Cognitive Skill: Evaluate Outcomes

 

 

Review the Suicide protocol at your hospital unit

 

Mental Health Chapter 25-27 Assignment. Locate and review the suicide protocol at your hospital unit or community center. Are there any steps you anticipate having difficulty carrying out? Discuss these difficulties with your peers or clinical group.

 

2. How would you respond to another staff member who expresses guilt over the suicide of a patient on your unit?

 

3. Identify three common and expected emotional reactions that a nurse might have when initially working with persons who manifest suicidal behavior disorder.

 

a. How do you think you might react?

 

b. What actions could you take to deal with the event and obtain support?

 

 

2. Taylor is 21 years old and a junior in nursing school. She tells her nursing instructor that her 45-year-old father has been drinking heavily for years and recently lost his job. Adding to the family’s stress is that her mother has multiple sclerosis with worsening symptoms. Taylor plans to quit school to take care of her.

 

a. How many different types of crises are going on in this family? Discuss the crises from the viewpoint of each family member.

 

b. If this family came for crisis counseling, what areas would you assess? What kinds of questions would you ask to evaluate each member’s individual needs and the needs of the family as a unit (perception of events, social supports, coping styles)?

 

c. Identify specific referral agencies in your area that would be helpful if members of this family were willing to expand their use of outside resources and to stabilize the situation.

 

 

3. Jenea admits a 24-year-old man with mania to an inpatient unit. She notes that the patient is irritable, has trouble sitting during the interview, and has a history of assault.

 

a. Identify appropriate responses the nurse can make to the patient.

 

b. What interventions should be built into the care plan?

 

c. Identify at least three long-term outcomes to consider when planning care.

 

4. What are the two indications for the use of seclusion and restraint rather than verbal interventions? Provide rationales for your answers.

 

Acute Pyelonephritis, Acute Kidney Injury

Title: Acute Pyelonephritis, Acute Kidney Injury. Scenario: A 75-year-old female with a history of asthma and type 2 diabetes mellitus began to experience burning upon urination, lower abdominal pain, and frequent urination a few days ago.

After trying to manage her symptoms by increasing fluids, she arrived at the emergency department with her daughter with complaints of right flank pain, fever, and malaise. Her daughter said that the patient who is normally alert and oriented is now experiencing some confusion. Urinalysis results show bacteriuria, hematuria, and white blood cell casts. The nurse documents the following assessment findings:

____ Temperature 102.2◦F (39◦C)

____ Heart rate = 94 bpm

____ Blood pressure = 138/76 mmHg

____ Respirations = 20 breaths per minute

____ Right sided costovertebral angle tenderness

____ Patient reports malaise

____ Reports 1 pack per day cigarette use

____ Patient not oriented to place and time

____ Patient reports nausea

 

Cognitive Skill: Recognize Cues

 

 

 

 

 

 

1. NGN Item Type: Extended Multiple Response

Place a check mark next to the assessment findings that require follow-up by the nurse.

 

Answer s:

___ Temperature 102.2◦ F (39◦C)

____ Heart rate = 94 bpm

____ Blood pressure = 138/76 mm Hg

____ Respirations = 20 breaths per minute

___ Right sided costovertebral angle tenderness

___ Patient reports malaise

____ Reports 1 pack per day cigarette use

___ Patient not oriented to place and time

____ Patient reports nausea

 

Rationale for your choices :

 

Cognitive Skill: Recognize Cues

 

 

 

 

 

 

 

 

 

2. NGN Item Type: Cloze

Choose the most likely options (by highlighting your choices) for the information missing from the statement below by selectin from the list of options provided.

Based on the patient’s assessment data, the nurse determines that the patient is currently at risk for complications, including _______, _______, and _______.

Options

Acute kidney injury

Lower urinary tract infection

Fluid overload

Urosepsis

Chronic kidney failure

Allergic reaction

Hypoglycemia

Septic shock

 

Rationale :

Cognitive Skill: Analyze Cues

 

 

 

 

Scenario: The patient is transferred to a medical unit 2 hours after arriving at the emergency department with an admitting diagnosis of pyelonephritis. She has a history of asthma and type 2 diabetes mellitus. The admitting nurse is assessing the patient and reviewing orders and diagnostic studies to develop a plan of care. The patient is awake, alert, and pleasant but is not oriented to place and time. She reorients easily with frequent reminding. She is complaining of pain but is not able to use the pain intensity scale. Ibuprofen is prescribed for pain every 6 hours as needed. Vital signs are temperature 101.4◦ F, pulse 100 bpm, respirations 22 breaths per minute, blood pressure 138/74 mm Hg. The patient is receiving intravenous normal saline at 100 mL/hour. A urine specimen was sent to the lab for culture and sensitivity. She is tolerating her clear liquid diet well. The nurse began an infusion of an extended spectrum cephalosporin as soon as the urine specimen was obtained and sent to the lab. The patient is voiding frequently and although instructed to do so, does not ask for assistance to ambulate to the bathroom.

 

1. NGN Item Type: Extended Response

Based on the patient’s current treatment plan, the patient’s priority needs will be to prevent which of the following? Select all that apply.

____Patient injury

____Pain

____Aspiration

____Constipation

____Hyperglycemia

____Urosepsis

____Skin breakdown

 

_____ G. Pressure wound

 

Rationale for your choices :

Cognitive Skill: Prioritize Hypotheses

 

 

 

 

2. NGN Item Type: Extended Drag and Drop

Indicate which nursing response listed in the far-left column is appropriate for each client question. Note that not all responses will be used.

Nurse’s Responses

Patient Questions

Appropriate Nurse’s Response for each Patient Question

“You may walk in the hallway as long as you are not feeling weak or dizzy.”

“How much longer will I have this pain in the side of my back?”

 

  • “We can remove your IV needle as soon as you begin to feel better.”

“Why do I have to pass my water so frequently?”

 

  • “The medications given to you through your IV are rapidly absorbed and will begin to kill the bacteria sooner than oral medications would.”

“When will this needle be removed from my arm?”

 

  • “We are giving you a lot of fluids so that you do not become dehydrated and also to dilute your urine to help flush out the bacteria that is in your urinary system. The extra fluids cause you to pass your water frequently.”

“Will I be able to walk around in my room today?”

 

  • “The IV needle will need to remain in your arm as long as you need to receive medications and fluids to treat your kidney infection.”

“Can I take this medicine as a pill instead of through the needle in my arm?”

 

  • “You may only walk in your room with the assistance of one of our healthcare team members.”

 

 

  • “The pain in the side of your back should go away as soon as the infection subsides.”

 

 

  • “I can give you some pain medication, which would provide you with pain relief. Please notify me if you continue to have pain and I will ask your healthcare provider to increase or change your pain medication.”

 

 

 

Rationale for your choices :

Cognitive Skill: Generate Solutions

 

 

 

The patient has now been on the medical unit for 3 days. She was diagnosed with pyelonephritis on admission. Vital signs this morning: Temperature 98.8 (37.1◦C ), blood pressure 100/50 mm Hg, pulse 110 bpm, respirations 24 breaths per minute. The patient is oriented to self only but is awake and alert. Her daughter is at her bedside. The urine culture results showed enterococci, and therefore the broad-spectrum antibiotic the patient was receiving was replaced with sensitivity-guided antibiotic therapy. Abnormal serum laboratory results are as follows: WBC = 14500/mm3 (normal=5000-10000/mm3), BUN = 27 mg/dL (normal = 7-20 mg/dL), creatinine 2.0 mg/dL (normal = 0.5-1.1 mg/dL). She has now been diagnosed with acute kidney injury.

 

NGN Item Type: Matrix

Use an X for the nursing actions listed below that are Indicated (appropriate or necessary), Contraindicated (could be harmful), or Nonessential (makes no difference or not necessary) for the patient’s care at this time. Only one selection can be made for each nursing action.

Nursing Action

Indicated

Contraindicated

Nonessential

Consult with dietician to provide a low caloric diet.

 

 

 

Obtain daily weights.

 

 

 

Medicate with ibuprofen every 6 hours as needed for complaint of pain.

 

 

 

Focus on providing holistic nursing care to patient.

 

 

 

Carefully consider the type, frequency, and dosage of the patient’s prescribed antibiotic therapy.

 

 

 

Assess for the presence of bowel sounds every 4 hours.

 

 

 

 

 

 

Rationale :

 

Cognitive Skill: Take Action

 

 

 

 

 

 

 

 

 

 

 

Scenario: A 75-year-old female was admitted to the hospital 3 weeks ago with a history of a urinary tract infection at home and was diagnosed with pyelonephritis upon admission. Despite treatment, her kidney infection progressed, and she developed acute kidney injury. After her antibiotic therapy was adjusted she recovered well enough to be discharged to her daughter’s home. The patient and her daughter were given discharge instructions to manage her prescriptions and health maintenance at home. She is now at the urology clinic for a 1-week follow-up appointment. Urine and blood samples were analyzed prior to her appointment. The nurse evaluates the effectiveness of actions.

 

NGN Item Type: Extended Multiple Response

Which of the following findings indicate effectiveness? Select all that apply.

_____ 1. The patient reports that she wipes front to back after urinating

_____ 2. The urinalysis report shows WBC >5/hpf (high), RBCs >4/hpf (high)

_____ 3. The patient reports that she drinks 4-5 glasses of fluid per day.

_____ 4. The patient voids approximately 3 times a day.

____ 5. The patient reports that she has stopped taking her antibiotic medication since she is now feeling “fine.”

_____ 6. The patient reports no flank pain.

_____ 7. Serum creatinine level is 1.0 mg/dL.

_____ 8. The patient states that she rests frequently.

 

 

Rationale for your choices :

 

Cognitive Skill: Evaluate Outcomes

International Journal of Law and Psychiatry

 

International Journal of Law and Psychiatry 36 (2013) 11–17. Contents lists available at SciVerse ScienceDirect

International Journal of Law and Psychiatry

Misinformation can influence memory for recently experienced, highly stressful events☆

C.A. Morgan III a,⁎, Steven Southwick a, George Steffian b, Gary A. Hazlett c, Elizabeth F. Loftus d

a Department of Psychiatry, Yale University School of Medicine, United States b FASOTRAGRULANT, United States Navy, United States c Woodard-Cody Specialty Consulting, Inc., Durham, NC, United States d Department of Psychology and Social Behavior, University of California, Irvine, United States

☆ The authors wish to thank the staff at the Survival S facilitated the completion of this project. Funding for thi National Center for Post Traumatic Stress Disorder, VA Systems and by the US Government. The views expres those of the authors and do not represent those of the are free of financial ties or conflict of interest. All data a ration were performed by the authors and independent ⁎ Corresponding author.

E-mail address: charles.a.morgan@yale.edu (C.A. Mo

0160-2527/$ – see front matter. Published by Elsevier L http://dx.doi.org/10.1016/j.ijlp.2012.11.002

a b s t r a c t

a r t i c l e i n f o

Available online 6 December 2012

Keywords: False memory Military Cognition Survival School Eyewitness recall Interrogation

A large body of research has demonstrated that exposure to misinformation can lead to distortions in human memory for genuinely experienced objects or people. The current study examined whether misinformation could affect memory for a recently experienced, personally relevant, highly stressful event. In the present study we assessed the impact of misinformation on memory in over 800 military personnel confined in the stressful, mock POW camp phase of Survival School training.

Misinformation introduced after the negatively affected memory for the details of the event (such as the presence of glasses or weapons), and also affected the accuracy of identification of an aggressive interrogator. In some conditions more than half of the subjects exposed to a misleading photograph falsely identified a different individual as their interrogator after the interrogation was over.

These findings demonstrate that memories for stressful events are highly vulnerable to modification by exposure to misinformation, even in individuals whose level of training and experience might be thought to render them relatively immune to such influences.

Published by Elsevier Ltd.

1. Introduction

Over the past three decades, a large body of research has provided strong evidence that human eyewitness memory is not fixed or indel- ible but rather is malleable and subject to substantial alteration over time (Cutler & Penrod, 1995).

Although there are myriad reasons for such alterations, one particular etiology of memory distortion has been well studied and is referred to as the “misinformation effect”. The term refers to the errors in recalling the details of a past event made by individuals who were subsequently exposed to false or erroneous information about the event.

The misinformation effect appears to operate largely outside a person’s awareness. That is, when people claim erroneously that they have seen the misinformation details, they seem to truly believe that they did (Loftus & Palmer, 1974; Scoboria, Mazzoni, & Kirsch, 2006).

In a typical ‘misinformation effect’ study, participants come to a lab- oratory setting where they witness a simulated event (e.g., a filmed

chool whose assistance greatly s research was provided by the New England VA Health Care sed in this manuscript reflect U.S. Government. All authors

nalyses and manuscript prepa- ly of funding entities.

rgan).

td.

automobile accident and a staged crime). Sometime later, participants are exposed to false information that might be presented in the form of a suggestive questioning or erroneous details from another witness, among other sources.

When subsequently asked to provide an accurate recollection about the original event, those participants who were exposed to misinformation frequently include the false information in their recollection.

The findings from misinformation studies demonstrate that expo- sure to misinformation can lead to distortions in memory for genuinely experienced objects or people — such as misremembering as ‘blue’ a getaway car that was actually green, or mis-recalling a man as having a mustache and curly hair when he was actually clean shaven with straight hair. Exposure to misinformation can lead people to recall see- ing objects that did not appear or occur in the original event (i.e. broken glass, tape recorders, buildings or animals) (Nourkova, Bernstein, & Loftus, 2004). Studies dating back to the mid-1970s have consistently shown this.

But more recently, researchers have shown that they can also persuade people to recall the existence of people or experiences that are completely fictitious (i.e. the experience of being lost in a mall) (Loftus & Pickrell, 1995). Using various forms of suggestion, researchers have led people to believe they have, in the distant past, been hospitalized, nearly drowned or attacked by a vicious animal or uncomfortably and repeatedly licked on the ear by a Disney character (Berkowitz, Laney, Morris, Garry, & Loftus, 2008; Heaps & Nash, 2001; Hyman, Husband, & Billings, 1995; Hyman & Pentland, 1996; Porter, Yuille, & Lehman, 1999).

 

 

12 C.A. Morgan III et al. / International Journal of Law and Psychiatry 36 (2013) 11–17

Based on the studies of false memory, researchers have proposed a sort-of recipe for how false memories are created in the mind of an individual. First, convincing the individual in whom one wishes to create a false memory that the “false event” is plausible; Second, lead- ing said individual to believe the false event was personally experi- enced; Third, creating a false memory that is rich in detail through the use of false feedback or manipulations of information (Loftus, 2003).

For the most part the memory distortion studies have tended to focus on either impersonal events, or on personal ones that are chro- nologically distant. Although the data from such studies provide com- pelling evidence for a potential mechanism by which false memories for highly stressful events (child abuse, physical assaults, real crimes) might be produced, it remains to be shown that such suggestive tech- niques could affect memory for a recently experienced, personally relevant, highly stressful event. Such a demonstration might go a long way towards helping clinicians who work with adult victims of trauma to appreciate that the data from false memory studies may be relevant to their clinical work. Since the laboratory simulations do not involve the high degree of personal “threat” or “alarm” experi- enced during actual life threatening events — and presumably do not activate neurobiological systems in the same manner as realistic events (Morgan et al., 2004; Penrod, Fulero, & Cutler, 1995), they are easy to dismiss, especially by those who feel uncomfortable with their findings.

The present study was designed to assess whether human memory for recently experienced, personally relevant, high stress events would be altered by exposure to suggestive misinformation. We conducted the present study in U.S.

military personnel enrolled in Survival School training. This on-going training offers a unique opportunity to study the impact of realistic stress on human neuro-physiology, cognition and eyewitness memory (Morgan, Doran, Steffian, Hazlett, & Southwick, 2006; Morgan et al., 2000, 2001, 2004). The realistic nature of the stress at Survival School, the presence of ground truth for the events, and relatively homogenous group of participant undergoing the training, made survival school an ideal setting for testing hypotheses about the real-world impact of misinformation for personally relevant, highly stressful events.

In this study, we hypothesized that:

1) Exposure to misinformation at an individual level would result in false memories related to specific stressful event (i.e. mock interrogation) that each participant experienced individually while at survival school;

2) Group exposure to misinformation would result in false memories about an event that participants experienced together as a group.

2. Methods

2.1. Participants

Participants in this study were 861 active duty military personnel recruited for participation in the study (649 male; 192 female). All participants were enrolled in U.S. Navy Survival School training. The mean age of participants was 26 (SD=5). As designated by their military branch, all were active duty navy or marine personnel.

3. Design and procedure

All participants were randomly assigned to one of four experimen- tal groups (see Fig. 1). Participants in each group completed memory assessment questionnaires at the conclusion of Survival School train- ing. The Control Group (N=158) consisted of participants who were NOT exposed to any misinformation during Survival School training and who were NOT exposed to any misinformation in the memory assessment questionnaire. Members of Misinfo-Questionnaire group (N=372) were exposed to post event misinformation embedded in

the memory questionnaire; Members of the Misinfo-Photo group (N= 85) were exposed to photographic misinformation which was presented to them during the period of time they were in mock captivity; Members of the Misinfo-Video group (N=246) were exposed to a videotape concerning a specific event that participants all experienced – as a group – while in the mock POW camp. This last group was further divid- ed into three sub-groups (N=81, 90 and 75) who were exposed to somewhat different versions of the misinformation-videotape.

The three versions of the videos differed in whether, or to what degree they contained misinformation (see below for details). [Note: The large differences in the numbers between the groups reflected class size differ- ences and enrollment differences per class during the data collection period of the study.]

3.1. The targeted events for memory assessment and misinformation

Although previous descriptions of the phases of Survival school are available (Morgan, Wang, et al., 2001; Morgan et al., 2000, 2004, 2006), the following brief description is provided to assist the reader in understanding the context of the study. Fig. 1 helps to illustrate the methodology.

The Survival training begins with a didactic phase after which participants are given, in as highly realistic manner as possible, an experience of wilderness evasion, followed by a mock-captivity in a prisoner of war camp (POWC). The types of stressors experienced by participants are modeled from the experiences of actual military personnel who have been prisoners of war.

Due to the classified nature of the course, a complete description of all components of the training is not possible, but suffice it to say the experience is high- ly stressful. The venue has been validated as a model for the study of acute stress in humans (Morgan, Hazlett, et al., 2001; Morgan, Wang, et al., 2001; Morgan et al., 2000, 2004, 2006). The portions of the training that were directly related to the focus of this study are described below.

3.2. Interrogation stress

Approximately 12 h after being placed in the POWC, participants experience, on an individual basis, a highly stressful interrogation. Due to the fact that interrogations are experienced individually and are conducted by a number of instructors, no individual student is knowledgeable about the identity of the interrogator who has inter- rogated another student. This results in students being unable to cue other students as to interrogator identity at the conclusion of the course when memory of this event is assessed.

Each student experiences interrogation while alone in a room with a survival school instructor who is not known to the student. During the interrogation, the room is illuminated and the students are able to see and hear the instructor. Throughout the interrogation the student is required to face the instructor and must maintain eye contact. In addition, the student must always adopt a height that is less than that of the instructor by bending or straightening his or her knees.

Failure to comply with this rule results in physical punish- ment to the student by the interrogator. Thus, students must be attentive to the face and relative height of the instructor. During this phase, the interrogator asks questions and physically confronts the student if he or she does not appear to be answering the questions or complying with the interrogator’s requests.

The various types of physical confrontation have been made public by the US Congress during their inquiries into the relationship of SERE tactics and US Government activities at Guantanamo Bay, Cuba (Joint Personnel Recovery Association (JPRA) Memorandum for the Office of the Secretary of Defense Chief Counsel, 2002) and include facial slaps, abdominal punches, walling (slamming the student into the wall) and stress positions. Interrogations are approximately 30 min in duration.

 

 

Classroom instruction

Interrogation Stress [30 mins]

Isolation Stress [4 hrs]

Assessment Of Descriptive & Eyewitness

Memory In All Test Groups

Group 1: No misinformation

Evasion Stress

[4 days]

Group Propaganda Stress

[30 mins]

Release &

Gear Return

Confinement in mock-POW camp [72 hours]*

Experiential Phase [1 week] Didactics Phase [4 days]

Debriefing Phase [12 hrs post mPOW]

Class debrief

Group 2: Misinformation questionnaire

Group 3: Photographic

misinformation

Group 4: Video Misinformation

time-point of exposure to misinformation

Fig. 1. Timeline of memory assessment and exposure to misinformation.

13C.A. Morgan III et al. / International Journal of Law and Psychiatry 36 (2013) 11–17

The interrogation stress experienced by participants at Survival School is intense and elicits profound alterations in psychological and neurobiological indices (Morgan, Wang, et al., 2001; Morgan et al., 2000). Norepinephrine and cortisol levels are elevated to a degree that is higher than that observed in many real world, threat-to-life events such as landing on an aircraft carrier at night for the first time or sky diving for the first time. In addition, gonadal hormone suppression is observed. Psychological symptoms of dissociation are also observed as are alterations in cognitive function as measured by standardized psychological testing (Rey Osterrieth Complex Figure [ROCF]) (Morgan, Hazlett, et al., 2001; Morgan et al., 2006).

Following interrogation stress exposure, all participants were exposed to the stress of isolation, as well as sleep and food depriva- tion for approximately the next 36 h. During this time, and after sev- eral hours of isolation stress, all participants were exposed as a group to an event in Survival School called the “Propaganda Speech.”

3.3. The propaganda speech

During this event all participants sat as a group on the floor of a building in the mock POW camp and listened to a “Commandant” of the camp give a lecture extolling the virtues of a non-US friendly political system. The event is provocative and designed to provide students in Survival School with a realistic experience as to how exposure to such events has led genuine US POWs in the past to pro- vide useful propaganda to the enemy. The Propaganda Speech lasts approximately 30 min.

In the past we have not specifically evaluated the impact of this mock POW event on human physiology and hormone responses and, therefore, cannot comment specifically on the degree of stress experienced by participants during this event. We included this event in the current study so that we could assess memory for, and the impact of misinformation on, an event that participants experi- enced as a group.

Upon release from the POWC, all subjects were given access to food, clean clothing and the opportunity to collect their personal effects and gear. Following this memory testing occurred.

3.4. The assessment of memory (no misinformation)

As noted in Fig. 1, approximately 4 4 h after release from the mock POW camp (i.e. 36 h after exposure to Interrogation stress and approximately 20 h after exposure to the Propaganda Speech), partic- ipants in the No-Misinformation Control Group assembled in the classroom and completed a non-leading, proctored, questionnaire designed to assess memory for the events described above. All partic- ipants were told explicitly by the proctor that the focus of the questionnaire was the interrogation that each had experienced. In addition, they were reminded that if they were not sure of their mem- ory they should indicate this on their form and not ‘guess’ when answering the questions. Each completed the questionnaire in silence; participants were not allowed to discuss with each other their responses. When each had completed the questionnaire, the participant put his/her head on their desk and waited quietly until the entire group had completed testing.

The initial section of the questionnaire asked participants to select descriptive characteristics of the interrogator who conducted their interrogation. These 11 descriptive categories were based on a consen- sus assessment derived from the Instructor Cadre at the Survival School (see Data analysis section) and were the following: Sex/Gender (Male; Female); Race (Asian, African American, Caucasian, Hispanic); Height (Tall, Medium, Short); Build (Big, Average, Thin); Hair Length (Bald, Short Hair, Long Hair); Hair Color (Red, Brown, Blond, Gray, None); Face Shape (Round, Square, Oval, Long); Facial Hair (Clean Shaven, Mustache, Goatee, Beard); Eye Color (Blue, Brown, Green, Hazel); Ear Appearance (Ears Stick Out, Ears Flat to Head, Ears Normal); and Teeth (Straight, Crooked, Missing Teeth). Participants were instructed to circle, within each category the word that best described their interrogator. They were instructed to write “I don’t know” if they did not remember.

After completing this section, participants moved to the second page to complete the second section of the questionnaire on which there were series of open-ended questions about emotionally neutral items for mili- tary personnel [i.e., glasses; telephone] and about items that would likely carry emotional valence for military personnel [i.e., military uniforms; weapons] (see Table 1). The open-ended nature of the questionnaire provided participants with the opportunity to endorse, deny the

 

 

Table 1 Assessing misinformation: non-leading and leading questions.

Questions regarding relatively neutral item

Non leading: “Did your interrogator wear glasses? If so, what type?” Leading: “Did your interrogator remove his glasses before interrogating you? Please describe the glasses worn by your interrogator.”

Non leading: “Was there a telephone in the interrogation booth? If so, what color was it?”

Leading: “Did your interrogator allow you to make a phone call? Describe the telephone in the interrogation room.”

Questions regarding non neutral items Non leading: “Please describe the uniform and rank of your interrogator.” “If you do not remember, please indicate that you do not remember.” Leading: “If your prisoner number was an odd number, please answer this question, if not please skip this one and answer the next question.”

Was the uniform worn by your interrogator green with red boards or blue with orange boards? [the alternate question gave the options of ‘black with yellow boards or gray with green boards’]

Non leading: “Did your interrogator carry or have a weapon?” “If so, please describe it?” Leading: “When the interrogator wearing the weapon interrupted your interrogator [note: a fictitious event] and argued with him, what did they argue about?”

“Describe the weapon worn by your interrogator.”

14 C.A. Morgan III et al. / International Journal of Law and Psychiatry 36 (2013) 11–17

presence of the items and also, if endorsed, to describe them. Participants were also told that they could indicate a response of “I don’t remember” or of “I don’t know” when completing the questionnaire.

The third section of the questionnaire was given next. This section consisted of an 8 and 1/2×11 in. sheet of paper on which was printed a color photo-spread type Eyewitness array. This photo-spread was composed of nine “mug shot,” photographs of former Survival School instructor/interrogators, each one two inch×two inch color.

Unlike the photo-spread used our previous studies of Eyewitness Accuracy (Morgan et al., 2004, 2007) this one was “target absent.” This means the array DID NOT contain a photograph of any interroga- tor encountered by ANY participant. Participants were instructed to indicate whether his or her interrogator was depicted in the photo-spread by placing an ‘X’ on the [ONE] relevant photograph. All were explicitly told that their interrogator ‘might not’ be present in the array and that it was permissible to write “not present” or “I don’t remember” on the photo array.1 After responding to the photo spread each participant put his/her head down and waited quietly for the forms to be collected by the research team.

3.5. Misinformation conditions — assessment of memory

Participants in the Misinformation-Questionnaire Group received identical instructions to those described above for participants who were in the No-Misinformation Control group. In both, participants were asked to describe their interrogator by selecting descriptive adjec- tives. In the section that followed, the questionnaire given to partici- pants in the Misinformation-Questionnaire group, differed from that given to the No-Misinformation Control Group in that it contained statements containing misinformation as well as leading questions (see Table 1; see Fig. 1). After completing this section participants in the Misinformation-questionnaire group made an eyewitness identifi- cation from a photo-spread.

As noted in Fig. 1, participants in the Misinformation-Photo Group were exposed to misinformation in the form of a photograph prior to their release from the mock POW camp and approximately 1 h after they had been exposed to interrogation stress. The presentation of misinformation occurred while participants were confined in individual

1 The target-negative nature of the array meant that only “Not Present” responses were coded as correct or ‘true negative’ responses. “I don’t know” type responses were not coded as errors, but were recorded to reflect the lack of recall.

isolation cells. A member of the research team entered the isolation cell and handed the participant an 8×10 color, mug shot type photograph of a Caucasian male (later referred to in this paper as the ‘Foil’). While holding the photograph, each was told to “look at this photograph” and while they viewed the photograph, each was asked the following questions by the research team member: “Did your interrogator give you anything to eat? Did your interrogator give you a blanket? Did your interrogator let you speak with any other prisoners?” After asking each of these questions, the research team member paused in order to let the participant answer the question. Once this was completed, the research team member took the photograph and left the isolation cell.

After release from the mock POW camp, participants in the Misinformation-Photo Group assembled in the classroom and com- pleted a non-leading questionnaire that was identical to the question- naire given to participants in the No-Misinformation Control Group. Following this, they viewed the eyewitness identification photo- spread shown to participants in the other groups. The inclusion of the ‘Foil’ in the array [i.e., the photograph to which participants in Group Three had been exposed while in isolation] made it possible to assess whether exposure to misinformation would lead to more false identifications of the Foil as the person who conducted their interrogation (relative to the other groups).

In order to assess the impact of misinformation delivered at the level of the group, participants in the Misinformation-Video Group were exposed – as a group – to misinformation in the form of a video prior to individually completing their memory questionnaires (Fig. 1).

After watching the video as a group, participants in this group completed a non-leading questionnaire that differed from the non leading ques- tionnaire used with other groups in the following way:

Instead of presenting non-leading questions related to the interrogation event, the questionnaire included a non leading question related to the Propa- ganda Speech event: “Did the instructors carry or wear weapons during the Propaganda Speech? If so, please describe them.”

In order to assess the impact of misinformation presented in the form of a videotape, we created three eight-minute videotapes about a group event from Survival School called the Propaganda Speech.

Dur- ing this event all participants sat as a group on the floor and listened to a speaker extolling the virtues of a non-US friendly political system. In each of the three versions, the video depicted the students being brought into the mock POW camp and then as they sat, as a group, lis- tening to the propaganda speech. With the aid of Adobe Software, we altered two of the three videos so that they contained ‘misinformation.’ In each of the misinformation videos the survival school staff depicted during the Propaganda Speech wore automatic weapons and/or carried Rocket Propelled Grenade devices (RPGs).

The two misinformation videotapes differed from each other in whether or not the instructors depicted in the videotape were familiar or unfamiliar to the participants.

Finally, all participants completed the self-report portion of the Clinician Administered Dissociative Symptom Scale (CADSS). The CADSS is a reliable, valid, self-report instrument designed to assess state symptoms of dissociation in response to a specified stressor (Bremner et al., 1998).

4. Data analysis

4.1. Initial descriptive section of questionnaire

The 11 descriptive categories were derived from a standard list of adjectives used in military debriefing assessments of eyewitness statements. The cadre of Survival School staff (N=20) were each given this initial descriptive section and asked to rate themselves and each of the nine interrogators to which the students would be exposed.

For several of the categories (Sex, Race, Build, Hair Length, Hair Color, Facial Hair, Eye Color, and Teeth) there was 100% agree- ment among the staff. However, for three of the nine instructors, there was no agreement within the group of 20 staff members with

 

 

15C.A. Morgan III et al. / International Journal of Law and Psychiatry 36 (2013) 11–17

respect to the following categories (Height, Ear Appearance and Face Shape). These disagreements were resolved by group discussion.2

4.2. Second portion of the questionnaire

Responses to the open ended and leading questionnaires were man- ually reviewed and scored by two separate teams from our research group. This was done to permit a ‘blind’ assessment of the question- naires, the eyewitness identification form and the questions related to the videotapes.

Responses of participants in the No-Misinformation Control Group were coded so as to indicate whether or not subjects responded to the question (0=no response; 1=response) and whether their answer was correct (0=incorrect; 1=correct; 2=I don’t know/I don’t remember).

The responses of subjects in the Misinformation-Questionnaire Group, the Misinformation-Photo Group and the Misinformation-Video Group were similarly coded to indicate whether subjects responded to the misinformation and endorsed recalling such information, or whether they denied experiencing the suggested stimuli, or did not remember the information (0=no endorsement; 1=endorsed misinformation; 2=I don’t know/I don’t remember). Chi-square analyses were used to exam- ine whether the distributions of endorsements to questions were signif- icantly greater in participants exposed to misinformation.

Sign tests were used [for the Misinformation-Questionnaire Group] in order to assess whether there was a relationship between the endorsement of the different types of misinformation (neutral/non-neutral). General Linear Model Univariate Analyses of Variance were used to determine whether and to what degree endorsements of false information were significantly greater between the three comparison groups [Misinformation-Video Group].

5. Results

861 participants completed the initial section of the questionnaire (the description of the interrogator). [Note: one subject in Group Three did not provide a response on the eyewitness identification task and is removed from the denominator of this category.]

With respect to the Descriptive Categories, all 861 subjects correctly reported the Gender of their Interrogator. 836/861 (97%) of participants correctly described the Race of their interrogator, and 26 (3%) were mis- taken. Of these 26 participants, 20 described their Caucasian interroga- tor as African American, two described their Caucasian interrogator as Asian and four described their Caucasian interrogator as Hispanic.

With respect to the categories of Height and Build, 621/861 (72%) and 474/861 (55%), respectively, correctly described their interrogator. Of the 240 erroneous descriptions within the category of Height, 194/240 (81%) were those in which the [Short] interrogator was described as “Tall;” the remaining represented those who labeled the [Medium] interrogator as “Tall.” Of the 387 (45%) participants who erred within the category of “Build,” 120 (31%) reflected a choice of “Medium” over the correct response “Thin” and 267 (69%) reflected the choice of “Big” over the cor- rect response “Medium.”

2 With respect to two interrogators, three staff members could not decide whether or not the description of the category Height was best described as “Tall” or “Medium.” For a third instructor, a fourth staff member was unsure as to whether or not the Face Shape for on interrogator was best described as “Oval” or “Long.” In addition, this staff rater was unsure as to whether the description of Ear Appearance for an interrogator was best described as “Flat to Head” or “Normal.” To resolve these uncertainties, the staff engaged in a group discussion and came to a group consensus about which de- scriptor (or both) would be acceptable to them in a real world setting.

In the end, the group consensus was that for category of Height, the term “Medium” would be the correct response for the two interrogators in question; with respect to the interro- gator about whom there was disagreement about Face Shape and Ear Appearance, the group agreed to accept either “Oval” or “Long” and “Flat to Head” and “Normal” as cor- rect responses, respectively for that particular interrogator.

When providing descriptions related to the head/face appearance of the interrogators, participants were incorrect in the majority of categories. Exceptions to this were noted for the categories of Teeth and Hair Length for which the majority of participants were correct. The types of errors committed were as follows: Hair Length (Of the 112 participants who erroneously endorsed hair length, 65 selected the attribute Long when the interrogators hair was Short and 47 selected the attribute Short when the interrogator was Bald); Hair Color (Of the 490 participants who erred in hair color, 100 selected Red [the interrogator was Blond], 256 selected Brown [the interroga- tor was Gray] and 134 selected Gray [the interrogator was Brown); Facial Shape (Of the 499 participants who provided erroneous responses, 218 selected Round [the interrogator was Square],

41 selected Round [the interrogator was Long] 19 selected Square [the interrogator was Oval], and 221 selected Long [the interrogator was Round]); Facial Hair (Of the 517 participants who erred, 192 selected Clean Shaven [the interrogator had a Mustache], 158 selected Beard [the interrogator was Clean Shaven], 117 selected Goatee [the instructor was Clean Shaven], 11 selected Mustache [the instructor was Clean Shaven] and 39 selected Beard [the interrogator had a Mustache]); Teeth (Of the 344 participants who erred, all selected Crooked

[the interrogators’ teeth were Straight]); Eye Color (Of the 542 who erred on this item, 83 selected Green [the interrogator’s eyes were Blue], 248 selected Brown [the interrogators’ eyes were Blue], 192 selected Hazel [the interrogator’s eyes were Green] and 19 selected Blue [the interrogator’s eyes were Brown]); Ears (Of the 637 participants who erred on this item, 324 selected Normal [the interrogator’s ears Stuck Out], and 313 selected Normal [the interro- gators ears were Flat to Head]).

As shown in Table 2, compared to those who were not exposed to misinformation, participants who were exposed to misinformation were more likely to endorse false memories for their experience at Survival School. As noted below, these differences in endorsement were statistically significant.

5.1. Misinformation questionnaire condition (group two)

As noted in Table 2, exposure to misinformation increased false memory for both neutral and non neutral items. [Neutral items: Glasses: no misinformation, 4/158 (2.5%); misinformation, 74/372 (20%); Chi-square=2.6; df=1, pb0.001; Telephone: no misinformation, 16/ 158 (10%); misinformation: 365/372 (98%); Chi-square=4.2; df=1, pb0.001. Non neutral items: Military Uniform: No misinformation, 35/158 (22%); Misinformation, 316/372 (85%); Chi-square=1.9; df=1; pb0.001. Weapons: No misinformation, 5/158 (3%); Misinformation, 100/372 (27%); Chi-square=3.9; df=1; pb0.001.]

5.2. Misinformation-photo condition (group three)

As noted in Table 2, exposure to misinformation in the form of a pho- tograph (Fig. 2) resulted in a significant increase in false positive eye- witness identifications: No misinformation, Eyewitness Identification False Positive endorsement rate: 84/158 (53%); Misinformation, Eye- witness Identification False Positive rate: 77/85 (91%); Chi-square= 4.5; df=1; pb0.001.

In addition, the majority of individuals exposed to the misinformation about the identity of the interrogator selected the false information (i.e., the “Foil”) when performing the eyewitness identification task: No misinformation, Foil selection: 13/84 (15%); Misinformation, Foil selection: 65/77 (84%); Chi-square=7.6; df=1; pb0.001.

5.3. Misinformation-videotape condition (group four)

Impact of misinformation on the endorsement of weapons present during the Propaganda Speech. [No misinformation, familiar staff in video: 4/75 (5%); Misinformation, unfamiliar staff in video: 10/90

 

 

Table 2 Impact of misinformation on memory for events.

Misinformation given at the individual level

Questionnaire: No misinf N (%)

Misinf. N (%)

Neutral items Glasses 4/158 (2.5%) 74/372 (20%)⁎

Telephone 16/158 (10%) 365/372 (98%)⁎

Non neutral items Uniform 35/158 (22%) 316/372 (85%)⁎

Weapon 5/158 (3%) 100/372 (27%)⁎

Photograph False Pos. (FP) Eyewitness ID 84/158 (53%) 77/85 (91%)⁎

Foil selection among FP IDs 13/84 (15%) 65/77 (84%)⁎

Misinformation given at a group level via videotape

N (%)

Endorsement of weapons in group event (no misinformation) (5%)

4/75 (5%)

Endorsement of weapons in group event (misinformation and unfamiliar staff)

10/90 (11%)

Endorsement of weapons in group event (misinformation and familiar staff) (51%)⁎

41/81 (51%)⁎

⁎ Significant at a level of pb0.001.

16 C.A. Morgan III et al. / International Journal of Law and Psychiatry 36 (2013) 11–17

(11%); Misinformation, familiar staff in video: 42/81 (51%); Chi- square=5.9; df=2; pb0.001. General Linear Model Univariate Anal- ysis of Variance using endorsements as the dependent variable and Group as the independent variable (i.e., the ‘between subject’ factor) indicated that there was a significant between-subjects effect (F (1,2)=38; pb0.001. As shown in Table 2, post-hoc comparisons (Tukey) indicated that this effect was due to the fact that endorse- ment rates {0=no endorsement; 1=endorsement} for weapons were significantly higher only in group exposed to the misinfor- mation video containing familiar staff members [mean difference group 3 (Misinformation with familiar staff) and groups 1 (No misin- formation, familiar staff) and 2 (Misinformation, unfamiliar staff)= .465; pb0.001].

With respect to dissociation scores, no differences in stress- induced dissociation symptoms were observed between the four groups: No-Misinfo Control Group, CADSS mean score: 18.8 (SD=14); Misinfo-Questionnaire Group: 17.5 (SD=13); Misinfo-Photo Group: 19.4 (SD=12); Misinfo-Video Group: 18.1 (15). No significant relation- ships were observed between dissociation scores and vulnerability to misinformation.

6. Discussion

The present data confirm our previously published data showing that human memory for realistic, recently experienced stressful events is subject to substantial error. In addition, however, the present data confirm that memories for stressful events are also high- ly vulnerable to modification by exposure to misinformation. Indeed,

Fig. 2. Misinformation photograph.

with very little effort we were able to create false memories in a pop- ulation of military personnel who are trained to resist propaganda and misinformation. The endorsement rates in this study raise the possibility that, until now, professionals have underestimated the impact of misinformation. To wit, false memory endorsements about non-trivial items (i.e., weapons) were observed in at least 27% of participants. Even higher endorsement rates, upwards of 80% of participants, occurred with respect to misinformation about uniforms or human faces. That we were able to alter memory for such non triv- ial events in military personnel trained to resist propaganda and exploitation techniques extends the applicability of false memory research to a wider population than heretofore examined, and suggests that these observations should be taken seriously by profes- sionals who work with victims of traumatic stress and who interact with the criminal justice system. Given the myriad ways in which real world victims of stressful events may be exposed to misinformation (through the media, police interviews, talking to attorneys or friends, etc.), it is possible that the present data under-represent the true risk of, and prevalence of, false memories.

We found that misinformation, when presented at a group level, was effective at creating false memories in a large number of partici- pants. Consistent with previous reports suggesting that misinformation is more readily accepted by a person when the misinformation is paired with someone who is trusted or who is familiar to that person, the impact of the videotape based misinformation was significantly enhanced when we included the faces of instructors who were known to the students watching the videotape. In all three versions of the vid- eotape we included a snippet that showed the participants’ own faces.

Although this may have influenced endorsement rates somewhat, this seems not likely to have been a major factor leading to the endorsement of the false information in that the greatest number of endorsements occurred when we paired familiar staff faces with the misinformation about weapons.

Thus, it may be that misinformation is more likely to be accepted when presented in association with persons perceived, by the recipients, to be in positions of authority.

With respect to eyewitness identifications, we observed that approximately 50% of participants, when presented a target-absent eyewitness array and asked to identify their interrogator, gave false positive identifications. This surprisingly high false positive rate is very similar to that observed in our previous eyewitness identifica- tion study (Morgan et al., 2004).

Unlike our previous studies in which we only asked participants to perform an eyewitness face identification task, in this study we also asked participants to describe their interrogator by selecting adjec- tives that might accurately characterize that person. Taken together, the majority of participants were correct when describing characteris- tics about their interrogator that one might observe from a distance (i.e. race, gender, height, build).

Yet, the majority of participants were incorrect when describing other characteristics that might be more discriminating in nature (i.e., one’s facial hair, eye color, or shape of face). The etiology of this finding is not known. Similarly, we observed that when making errors in describing the build or height of their interrogator, participants erred in describing the inter- rogator as larger and as taller than was the case rather than describ- ing them as smaller or shorter. At present the etiology of this is not known.

With respect to the descriptive memory data in this study, keep in mind that the reported percentage of correct responses may actually over-represent eyewitness accuracy.

These percentages have not been corrected for guessing. For example, when selecting from the category hair color, participants were able to choose their answer from five options. This means participants who were just guessing had a one in five chance of being correct on this category simply by guessing.

We freely acknowledge that the method of asking participants to select adjectives in order to describe their interrogator has limitations. Time constraints prevented us from being able to assess a free-recall, open

 

 

17C.A. Morgan III et al. / International Journal of Law and Psychiatry 36 (2013) 11–17

narrative type memory in participants. Future research with Surviv- al School participants might profitably use open-ended, free recall procedures.

The observation that memory for recent events can be altered by misinformation has a number of implications for a number of profes- sionals. First, physicians and psychotherapists who may work with victims of trauma and who may engage in associated legal advocacy or forensic work (i.e., Evaluations for Asylum;

Forensic criminal evaluations; Debriefings) would be well advised to videotape their evaluations and to take great care to use non-leading, open ended information gathering interviewing techniques.

Although videotaping evaluations may not prevent the alteration of memory for traumatic events, it may provide an objective means by which the source of such false memories can be identified. Given the present data it is reasonable to believe that the social status of physicians and therapists may significantly facilitate – albeit unintentionally – the acceptance of misinformation and alter memories on the part of victims.

Law enforcement professionals would do well to take great care in both interviewing methods as well as the degree to which inter- viewees are exposed to information that might alter their memory. Based on the current study, one might anticipate that the use of lead- ing questions, exposing witnesses to photographs or statements may significantly alter subsequent recollections.

In the interest of not con- taminating evidence (or of documenting how inconsistencies in wit- ness recollections may have come about) it may be prudent to videotape all interviews and to also control the level of exposure wit- nesses may have to photographs, comments, or other information related to a past experience. Further, and although we would not dis- agree with the current police practice of assessing eyewitness memo- ry as soon after the events of interest as possible, we believe it prudent to hold to the view that event memory for events that have “just occurred” are also vulnerable to misinformation.

There were a number of limitations in the present study. First, the time constraints of the training environment and limited access to participants prevent us from conducting a debriefing to explore whether the alterations in reported memory represent altered ‘beliefs’ or altered ‘remembering’. In addition, we were not able to assess the impact of the various types of misinformation in each participant; this meant we were not able to test whether vulnerability to one type of misinformation would indicate that a person was more likely to be vulnerable to another type of misinformation. This issue awaits further study. In addition, all participants at Survival School experienced significant food and sleep deprivation during their time in the mock POW camp environment. These stressors may have influenced the accuracy of memory recall or vulnerability to misinformation.

 

This said, given the uniform application of sleep and food deprivation across participants, these factors are not a likely explanation of the differences in memory recall between subjects. Finally, the rates of false memory endorsements in these military par- ticipants may not reflect those of the general population due to the relative homogeneity of the sample. This said, given that these mili-

tary personnel represent individuals who are specially trained to re- sist exploitation and propaganda efforts, it seems unlikely that they are more susceptible than general civilians. This too, however awaits future testing in studies that include both civilian and military participants.

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  • Misinformation can influence memory for recently experienced, highly stressful events
    • 1. Introduction
    • 2. Methods
      • 2.1. Participants
    • 3. Design and procedure
      • 3.1. The targeted events for memory assessment and misinformation
      • 3.2. Interrogation stress
      • 3.3. The propaganda speech
      • 3.4. The assessment of memory (no misinformation)
      • 3.5. Misinformation conditions — assessment of memory
    • 4. Data analysis
      • 4.1. Initial descriptive section of questionnaire
      • 4.2. Second portion of the questionnaire
    • 5. Results
      • 5.1. Misinformation questionnaire condition (group two)
      • 5.2. Misinformation-photo condition (group three)
      • 5.3. Misinformation-videotape condition (group four)
    • 6. Discussion
    • References

 

The Impact of Peer Social Networks on Adolescent

 

The Impact of Peer Social Networks on Adolescent. Alcohol Use Initiation Marlon P. Mundt, PhD. From the Department of Family Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, Wis No direct support was received from grant P01-HD31921 for this analysis. Address correspondence to Marlon P. Mundt, PhD, Department of Family Medicine, 1100 Delaplaine Ct, Madison, Wisconsin 53715 (e-mail:

marlon.mundt@fammed.wisc.edu).Received for publication February 23, 2011; accepted May 16, 2011.

 

ABSTRACT

A C

OBJECTIVE: Early adolescent alcohol use is a major public health problem. Drinking before the 14th birthday is associated with a fourfold increase in risk of alcohol dependence in adult- hood.

The objective of this study is to evaluate the association between adolescent social network characteristics and alcohol initiation prospectively over time. METHODS: The study analyzes data from the National Longi- tudinal Study of Adolescent Health, a nationally representative survey of 7th- through 11th-grade students enrolled between 1995 and 1996.

Generalized estimating equations are used to model the risk of alcohol use initiation at 1-year follow-up among nondrinkers at wave 1 of the study. RESULTS: Both an adolescent’s friends’ alcohol use and the adolescent’s social network characteristics displayed an inde- pendent main effect on alcohol initiation. In comparison with abstainers, alcohol initiators had more popular friends as measured by more peer nominations as friends (indegree)

CADEMIC PEDIATRICS opyright ª 2011 by Academic Pediatric Association 414

and having more friends up to 3 steps removed (3-step reach), and more friends who drank. An adolescent’s risk of alcohol use onset increased 13% (95% CI, 4%–22%) for every additional friend with high indegree, 3% (95% CI, 0.3%–6%) for every additional 10 friends within 3-step reach, and 34% (95% CI, 14%–58%) for each additional friend who drank alcohol, and after controlling for confounders. CONCLUSION:

The findings suggest that, in addition to well- established demographic risk factors, adolescents are at height- ened risk of alcohol use onset because of their position in the social network in relationship to their friends and the friends of their friends.

KEYWORDS: alcohol; adolescent; social network; peer

ACADEMIC PEDIATRICS 2011;11:414–421

WHAT’S NEW

Peer social networks impact adolescent alcohol use onset. Alcohol initiators have more friends and friends of friends who drink, are in closer proximity to more popular individuals, and interact with more friends, and more friends of friends, than abstainers.

ADOLESCENT ALCOHOL INITIATION is a major public health problem. One quarter of all adolescents begin drinking alcohol by the age of 13 years old.1 Drinking before the 14th birthday is associated with a fourfold increase in risk of becoming alcohol dependent in adulthood.2 Early alcoholinitiationleadstoavarietyofriskyadolescentbehav- iors, including marijuana and cocaine use, having sex with multiple partners, and academic underperformance.3

Peer influence has been shown to play a large role in adolescent alcohol initiation. Peer alcohol use and a best friend’s alcohol drinking behavior predict alcohol initia- tion among middle and high school students.

4,5 Middle

schoolers are more likely to begin using alcohol if they perceive a higher prevalence of alcohol use among other students in their grade.6,7

Social network analysis is the optimal research tool for studying the peer dynamics of adolescent alcohol use,8–10

because it maps out peer dyadic interdependencies in a larger social group (ie, network) context. In the social network analysis framework, adolescents and their friends indicate their friendships by naming a list of friends. The friendships are then represented by social tie connections on a graph.

As a result, the individuals (ie, egos) are directly linked to their friends (ie, alters) and indirectly to the friends of their friends. Thus, they form a large social network of relationships.

The unique feature of social network analysis is that it relies on friendship ties reported by each adolescent and not on perceived, reputational, or idealized social connections from one person’s point of view.

11,12 Adolescent social networks are ideally suited for social network analysis as they have naturally occurring friendship boundaries (ie, schools). There is no clear agreement on how social network

effects influence alcohol drinking among adolescents.8, 13–17

Some studies have found that isolates, teenagers who have relatively few or no friends, are more likely to consume alcohol.14,15,17 Other investigations indicate higher drinking prevalence among liaisons, school-age students who have friends but are not connected primarily to a single group of friends.

13 Popular adolescents, those who receive more friendship nominations from other students (ie, high indegree) appear to enjoy greater social status if they drink.

18 Individuals who are more centrally

Volume 11, Number 5 September–October 2011

 

 

ACADEMIC PEDIATRICS ADOLESCENT ALCOHOL USE IN PEER GROUPS 415

located in the social network (ie, higher centrality), by virtue of having more social ties and more thoroughly in- terconnected friends, are more likely to use alcohol if their friends drink.8,19 Social proximity (ie, 3-step reach) via friends of friends’ ties to other alcohol users is also linked to adolescent alcohol use.8 Dense social networks with more interconnected individuals are associated with alcohol use.8

Although adolescent social network characteristics are shown to play a role in adolescent alcohol consumption, little is known on how these factors lead to the onset of adolescent alcohol use.

To fill this gap in the literature, the present study will investigate the association between adolescent social network characteristics identified in the previous studies, such as social status, social embedded- ness, social proximity to alcohol users, and overall network interconnectedness, to adolescent alcohol initiation prospectively over time. The present study will explore the following research questions:

1. Is social status, as measured by indegree, associated with adolescent alcohol initiation?

2. Is social embeddedness in the social network, as measured by centrality, linked to adolescent alcohol onset?

3. Is proximity to alcohol users, as measured by 3-step reach, correlated with adolescent alcohol inception?

4. Is overall network connectedness, as measured by network density, related to the start of adolescent alcohol drinking?

METHODS

DATA SOURCE

The data source for this study is the National Longitu- dinal Study of Adolescent Health (Add Health).20 Add Health is a longitudinal, school-based study of adolescents in grades 7 to 12. Sample schools were selected through stratified sampling to be representative of high schools nationwide based on region of the country, urbanicity, school funding, and racial composition.

Middle school or junior high feeder schools for the participating high schools were also recruited. The Add Health study was approved by the institutional review board of the Univer- sity of North Carolina at Chapel Hill, and the current analysis was approved by the institutional review board at the University of Wisconsin–Madison.

An in-school survey was given to all 7th through 12th graders at the 132 participating schools. Students who re- sponded to the in-school survey (N ¼ 90 118), were eligible to be randomly selected for an in-home interview and parent survey (wave 1, n ¼ 20 745).

Wave 1 was con- ducted from April 1995 to December 1995. In-home inter- view respondents participated in wave 2 (n ¼ 14 738) of the study 1 year later, from April 1996 to August 1996.

A novel aspect of Add Health is the collection of peer social network data as a means of understanding adolescent health. Respondents named up to 5 male and 5 female friends from their school roster. To construct social

network variables, 21 Add Health excluded nominations

of students who did not complete the survey or whose name did not appear on the school roster. The Add Health publicly available social network data set provides individual and school-level network data on 75 781 adoles- cents.

SAMPLE

Wave 1 of Add Health surveyed 20 745 individuals. Of the wave 1 sample, 4039 (19%) were in 12th grade and excluded from the wave 2 sample. Of the remaining 16 706 students eligible for wave 2, 1968 students (11.8%) were lost to follow-up or refused participation, for a total wave 2 sample size of 14 738 students. The total sample size for the analysis was 2610 students.

The sample includes Add Health subjects who 1) completed in-home interviews at both wave 1 and wave 2, 2) had never drunk alcohol outside of the presence of a parent or adult family member prior to the wave 1 in- home survey, and 3) named at least 1 friend who also completed an in-home interview at wave 1.

A total of 1592 students (11%) were excluded from the analysis sample because they had already initiated alcohol use at wave 1, and 10 536 students (71%) were excluded because they did not name as a friend any student who completed a wave 1 survey.

MEASURES

ALCOHOL USE INITIATION

At both wave 1 and wave 2, adolescents were asked if they had ever drunk beer, wine, or liquor when they were not with their parents or other adult family member. Alcohol use initiators were defined as adolescents who had not consumed alcohol outside their family group at wave 1, but who at wave 2 had drunk alcohol without the presence of their relatives.

SOCIAL NETWORKS

Social network variables were based on friendship nomi- nations from the initial in-school survey and were provided in the Add Health dataset. The Add Health social network measures were calculated using social network analysis methodology.21 Indegree is the number of friendship nomi- nations received by the respondent from the other study participants.

Centrality (Bonacich b) is the relative number of connections that an individual’s friends have within the adolescent social network. 3-step reach is the degree to which a member of the peer social network can make contact with other members of the network through 3 steps of friendship connections.

A school-level measure, density, is the number of ties in the total school peer social network divided by the number of possible network ties.

DEMOGRAPHICS

Student gender, age, and race were collected in the in- home interview. Age was calculated to the nearest month. As a proxy for cognitive skills, participants completed a 5-minute picture vocabulary test. Respondents were

 

 

416 MUNDT ACADEMIC PEDIATRICS

also asked how often in the past week they participated in team sports.

FAMILY CHARACTERISTICS

Adolescents naming only 1 parent in their current house- hold roster were defined as living in a single parent house- hold. Study participants indicated how much fun they have with their family and whether they had gone shopping or to a movie or event with a parent in the past 4 weeks.

In the in- home interview at wave 1, parents offered information on how often they drink alcohol and how many times they had 5 or more drinks on a single occasion in the past month.

CENSUS BLOCK CHARACTERISTICS

The Add Health study used geocoding of addresses to link subject data to US census block data. Census block data included the percentage of families in the block who were at or below the poverty level, the percentage over age 25 who had completed a college degree, and the percentage in the block who reported themselves to be religious adherents.

SCHOOL CHARACTERISTICS

Schools were characterized as urban, suburban, or rural, and from the northeast, midwest, south, or east portion of the United States. Schools were listed as public or private, and either small (400 or less students), medium (401–1000 students), or large (1001 or more students).

School admin- istrators indicated if school staff had training in alcohol/ drug prevention.

FRIEND CHARACTERISTICS

The Add Health alcohol use of adolescents’ friends, grade point average, delinquency scale score, and parent alcohol use were derived directly from the friends’ answers to the Add Health in-home interviews. The delinquency scale was constructed in a manner similar to prior research using the Add Health data.22 Add Health respondents were provided with a 15-item delinquency scale and were asked to indicate how often they had engaged in each behavior in the past year. Items included vandalism, physical fighting, stealing, lying, joyriding, breaking and entering, and drug use, among others.

Responses to individual questions were coded as 0 being never, 1 being 1 or 2 times, 2 being 3 or 4 times, and 3 being 5 or more times. The delinquency scale score was created by summing together responses to each of the 15 items.

STATISTICAL ANALYSIS

Each observation in the data set represented a single adolescent-friend pair. A dichotomous variable indicated whether the adolescent initiated alcohol use in wave 2 of the study.

Multilevel modeling using generalized esti- mating equations (GEE) adjusted for a friend having multiple nominations. An independent working correlation structure was applied for the clusters.

First, the analysis estimated a reduced-form GEE model of adolescent characteristics associated with alcohol use

initiation. The model included demographics, parent and family characteristics, census block characteristics, area of the country, school size and funding, school staff training in alcohol prevention, and school-wide social network density. Second, the study estimated the impact of friend charac-

teristics on alcohol use initiation while including all of the reduced-form variables as control variables. Friend charac- teristics included grade point average, delinquency scale score, parent drinking, and friend drinking at wave 1. Third, a GEE model was constructed to test the influence

of friends’ social network characteristics on the adoles- cent’s alcohol initiation status, while excluding friend drinking from consideration. The model included social network parameters of indegree, centrality and 3-step reach. These social network measures were chosen a priori based on research findings regarding friend influence.

8

A fourth GEE model analyzed both friend drinking char- acteristics and friend social network characteristics while controlling for confounders. This model sought to deter- mine the independent main effect of social network charac- teristics on an adolescent’s alcohol use initiation after controlling for the friend’s drinking status.

Increased likeli- hood of alcohol initiation was calculated by exponentiating the beta coefficients in the model. Additional analyses tested various model interaction terms. Next, alcohol initiator social network characteristics

(in-degree, centrality, and 3-step reach) were compared with abstainer social network characteristics. T tests and chi-square tests contrasted the social network characteris- tics and the prevalence of alcohol use for the friends of initiators and abstainers. Friends were classified as being 1, 2, or 3 steps away from the initiator or abstainer based on the minimum number of friendship steps it took to reach the friend from the study participant.

For example, a directly named friend is 1 step away from an individual. A friend of a friend who is not directly named by the indi- vidual is 2 steps away. A friend of a friend of a friend who cannot be reached in the 1-step or 2-step manner described above is defined as being 3 steps away. All analyses were carried out with SAS statistical software (SAS 9.1.3, SAS Institute Inc, Cary, NC). Finally, the friendship networks for a sample initiator

and abstainer from the same grade were plotted using NetDraw software (Analytic Technologies, Lexington, KY). The diagram provides an indication of the 3-step reach of both adolescents and the degree of alcohol use within their networks.

RESULTS The study sample consisted of 2610 seventh through

eleventh grade students (Table 1). Subjects ranged from 12 to 19 years of age, with a mean age of 15. Forty-five percent of participants were minorities.

Over a quarter of respondents lived in single parent households. More than 40% had parents who consumed alcohol and 9% had a parent who consumed 5 or more drinks in a single sitting in the past month. A greater part of the respondents lived in a suburban area, were from the South, and attended a large

 

 

Table 1. Descriptive Statistics of School-Age Students Who Had

Not Initiated Alcohol Drinking in National Longitudinal Study of

Adolescent Health, Wave 1, 1995 (N ¼ 2610) Characteristic

Demographics

Male, % 48.8 Age, mean (SE) 15.0 (0.3) Age, range 12–19 Grade level, %

7th grade 19.9 8th grade 18.7 9th grade 17.2 10th grade 24.1 11th grade 20.1

Race, % Non-Hispanic white 54.6 Black 19.5 Native American 1.6 Asian 10.0 White Hispanic 12.5

Add Health picture vocabulary test, mean (SE) 100.9 (0.3) Participate in team sports, % 76.7 Family Characteristics

Parent consumed alcohol, past year, % 43.9 Parent consumed 5þ drinks, past month, % 9.0 Single parent household, % 25.4 Family has fun together (quite a bit/very much), % 70.1 Shopped together, past 4 weeks, % 75.6 Went to movie/event together, past 4 weeks, % 29.0 Census Block Characteristics

Families with income below poverty level, % 10.7 Population aged 25þ years with college degree, % 22.9 Proportion who are religious adherents, % 56.4 School Characteristics

Urbanicity, % Urban 24.0 Suburban 51.4 Rural 24.6

Region of residence, % Northeast 11.9 Midwest 28.4 South 31.7 West 28.0

School funding, % Public 87.1 Private 12.9

School size, % Small (1–400 students) 30.2 Medium (401–1000 students) 28.5 Large ($1001 students) 41.3

School staff training in alcohol/drug prevention, % 78.7 Friend Characteristics

Male, % 47.3 Age, y, mean (SE) 15.2 (0.3) Age, y, range 12–19 Drink alcohol, wave 1, % 35.1 Drink alcohol, wave 2, % 33.9

ACADEMIC PEDIATRICS ADOLESCENT ALCOHOL USE IN PEER GROUPS 417

public school (>1000 students). Over three quarters of the participants’ schools provided training for staff in alcohol and drug prevention.

Table 2 presents the results from the 4 multivariate GEE models for alcohol initiation. Twenty percent (n ¼ 523) of the 2610 adolescents who were nondrinkers in wave 1 initi- ated alcohol use by wave 2 of the study. The analysis data set comprised 5096 friendship pairs, for an average of 1.95 nominated friends for each individual in the sample. In the

reduced form model 1, significant predictors of alcohol use initiation were older age, white race, participating in team sports, heavy drinking by a parent, and higher social networkdensityin the school.Variablesthat wereassociated with a reduced likelihood of alcohol use initiation were having family fun together and being in a private school. Model 2 added friend characteristics to the model of

alcohol use initiation. Friend drinking at wave 1 increased the risk of alcohol use initiation. Having a friend with a higher delinquency score also increased likelihood of alcohol use initiation. Model 3 included the social network characteristics of the nominated friend while removing friend drinking from consideration. Having more popular friends, as measured by peer nominations (indegree) and being able to reach a greater number of friends (3-step reach), was highly predictive of alcohol use initiation. Model 4 presents the full model results, which include

both the friend’s network characteristics and the friend’s alcohol use. Two of the 3 friend social network character- istics (ie, indegree, 3-step reach) increased the risk for the student to initiate alcohol use. For every additional friend with high indegree, the likelihood that an adolescent initi- ated alcohol use increased by 13% (95% CI, 4%–22%). For every additional 10 friends within 3-step reach of a nomi- nated friend, risk of alcohol initiation by a nondrinker increased by 3% (95% CI, 0.3%–6%). Risk of alcohol use onset increased 34% (95% CI, 14%–58%) for each additional friend who drank alcohol. Additional analyses revealed that neither the interaction term between friend 3-step reach and drinking status nor the interaction between friend indegree and drinking behavior added significantly to the explanatory power of the model. Of note, friend centrality was not significant in the model. More network ties, as opposed to being highly embedded in a tight network, appeared to be the factor that had the strongest impact on alcohol initiation. Table 3 presents the social network characteristics of the

alcohol initiators’ friends up to 3 steps removed compared with the abstainers’ friends at 3 degrees of separation. These analyses were performed post hoc based on the significant social network variables found in the GEE models. The results indicate that drinking initiators have more friends within 3 steps of them (3-step reach) prior to starting drinking. The drinking initiator’s extended circle of friends also has more popular (indegree), more connected (3-step reach), and more alcohol drinking friends within 3 steps. The Figure provides a visual representation at wave 1 of

the 3-step networks of 2 adolescents at wave 1 from the same grade: one who initiates alcohol use by wave 2, and the other who remains an abstainer. The initiator has access to more social ties 3 steps removed from him/her and more alcohol drinking friends. The abstainer has fewer friends within 3-step reach.

DISCUSSION The objective of this study is to evaluate the association

between adolescent social network characteristics and

 

 

Table 2. GEE Model for Alcohol Use Initiation Among Adolescents in National Longitudinal Study of Adolescent Health (N ¼ 2610)†

Parameter

Model 1 Model 2 Model 3 Model 4

Beta SE P Value Beta SE P Value Beta SE P Value Beta SE P Value

Demographics Male 0.142 0.075 .058 0.077 0.075 .307 0.108 0.076 .155 0.080 0.076 .288

Age 0.086 0.031 .005 0.081 0.031 .008 0.089 0.031 .004 0.083 0.031 .007

Race, white 0.278 0.112 .013 0.297 0.112 .008 0.255 0.113 .024 0.257 0.112 .022

AH picture vocabulary‡ 0.001 0.003 0.660 0.002 0.003 .401 0.002 0.003 .472 0.002 0.003 .456

Team sports 0.084 0.033 .011 0.091 0.033 .006 0.084 0.033 .012 0.085 0.034 .011

Family characteristics

Parent drinking frequency 0.068 0.036 .060 0.069 0.036 .060 0.063 0.037 .086 �0.005 0.035 .893 Parent heavy drinking 0.113 0.056 .042 0.104 0.055 .060 0.112 0.056 .046 0.087 0.056 .122

Single parent household 0.011 0.088 .902 �0.020 0.089 .823 �0.010 0.088 .909 �0.017 0.089 .845 Family fun together �0.146 0.038 <.001 �0.136 0.038 <.001 �0.142 0.038 <.001 �0.138 0.038 <.001 Shopped together �0.101 0.086 .241 �0.072 0.088 .414 �0.090 0.087 .304 �0.073 0.088 .406 Movie/event together �0.012 0.084 .888 �0.002 0.086 .986 �0.010 0.086 .895 �0.012 0.086 .889

Census block characteristics

Below poverty percentage 0.421 0.429 .326 0.514 0.430 .232 0.548 0.426 .198 0.572 0.425 .179

College educated 0.387 0.323 .230 0.494 0.324 .127 0.522 0.323 .107 0.552 0.323 .087

Religious adherents 0.105 0.382 .784 0.143 0.380 .707 0.156 0.384 .684 0.136 0.381 .721

Geography

Urban 0.029 0.145 .841 0.082 0.147 .577 0.123 0.149 .408 0.173 0.150 .247 Suburban 0.010 0.121 .938 0.066 0.123 .593 0.085 0.121 .484 0.116 0.122 .344

West �0.262 0.168 .119 �0.216 0.169 .200 �0.143 0.170 .399 �0.136 0.169 .423 Midwest �0.101 0.139 .468 �0.079 0.140 .570 �0.119 0.140 .398 �0.106 0.140 .450 South �0.127 0.145 .383 �0.064 0.146 .664 �0.127 0.149 .397 �0.115 0.149 .441

School characteristics

Private �0.385 0.160 .016 �0.335 0.160 .036 �0.374 0.161 .020 �0.358 0.161 .027 Small �0.200 0.139 .151 �0.159 0.139 .252 �0.105 0.147 .478 �0.093 0.147 .530 Medium �0.127 0.126 .315 �0.103 0.127 .417 �0.129 0.126 .305 �0.111 0.127 .381 Staff training in alcohol prevention �0.040 0.112 .724 �0.053 0.111 .633 �0.091 0.112 .416 �0.081 0.112 .466 Social network density 0.912 0.383 .017 0.885 0.386 .022 1.083 0.389 .005 1.069 0.391 .006

Friend characteristics

Friend grade point average �0.082 0.055 .141 �0.116 0.056 .037 �0.105 0.056 .059 Friend delinquency 0.020 0.007 .004 0.027 0.007 <.001 0.019 0.007 .007

Friend parent drinking 0.000 0.035 .995 0.006 0.035 .873 �0.005 0.035 .893 Friend parent heavy drinking 0.071 0.057 .208 0.082 0.056 .142 0.087 0.056 .122

Friend drinking, wave 1 0.320 0.082 <.001 0.295 0.082 <.001

Friend social network characteristics

Friend indegree 0.034 0.011 .001 0.032 0.010 .002

Friend centrality �0.098 0.088 .266 �0.093 0.088 .288 Friend reach, per 10 friends 0.031 0.013 .014 0.030 0.013 .020

Intercept �2.814 0.712 <.001 �3.015 0.727 <.001 �3.252 0.731 <.001 �2.992 0.725 <.001 Deviance 4981.6 4943.0 4934.9 4925.7

df 5071 5066 5064 5063

Bold items are significant at the p < .05 level.

†GEE ¼ generalized estimating equations. ‡AH ¼ National Longitudinal Study of Adolescent Health.

4 1 8

M U N D T

A C A D E M IC

P E D IA T R IC S

 

 

Table 3. Social Network Characteristics of Adolescent Drinking Initiators’ Friends in National Longitudinal Study of Adolescent Health

(N ¼ 2610)

Social Network Variable, Wave 1

Drinking Initiator at Wave 2

(n ¼ 523) Mean (SD) Abstainer at Wave 2

(n ¼ 2087) Mean (SD) One step away friends†

Indegree 6.28** (0.12) 5.71** (0.06) Centrality (Bonacich b) 0.98 (0.02) 0.96 (0.01) Reach (3-step) 62.39** (1.25) 56.01** (0.60) Drank alcohol, wave 1, % 44.6** 32.0**

Two steps away friends‡ Indegree 6.89** (0.13) 6.41** (0.06) Centrality (Bonacich b) 1.02 (0.02) 1.01 (0.01) Reach (3-step) 71.57** (1.39) 62.08** (0.71) Drank alcohol, wave 1, % 45.9** 39.6**

Three steps away friends§ Indegree 6.95** (0.08) 6.54** (0.05) Centrality (Bonacich b) 1.04 (0.01) 1.04 (0.01) Reach (3-step) 78.38** (0.93) 71.33** (0.53) Drank alcohol, wave 1, % 46.3* 43.9*

*Significant at p < .05 level.

†Friend directly named by the individual.

‡Friend of a friend who is not directly named as friend by the individual.

§Friend of a friend of a friend who is not 1 or 2 steps away from the individual.

**Significant at p < .001 level.

ACADEMIC PEDIATRICS ADOLESCENT ALCOHOL USE IN PEER GROUPS 419

alcohol initiation prospectively over time. The study results demonstrate that both the friend’s alcohol use and the adolescent’s social network characteristics display an independent main effect on alcohol initiation. In line

Figure. 3-step reach at wave 1 of an alcohol initiator and an alcohol absta

wave 1. Alcohol initiator began using alcohol by wave 2.

with previous research,8,23 a best friends’ drinking at wave 1 was a significant predictor of alcohol initiation at wave 2. Similar to other investigations, the study findings demonstrate that, in addition to well-established

iner. Both alcohol initiator and alcohol abstainer were nondrinkers at

 

 

420 MUNDT ACADEMIC PEDIATRICS

demographic risk factors (eg, age, race, team sports), peers’ immediate drinking friends are risk factors for alcohol use inception.

Interestingly, having friends with more friends, regard- less of their drinking status, impacts the likelihood of alcohol initiation. For every additional 10 friends within 3-step reach of an adolescent, risk of alcohol initiation increases by 3%. The findings are in concordance with the results of the Framingham Heart Study, where adults up to 3 degrees removed from the individual influence weight gain, cigarette cessation, and alcohol use.

24–26

Similar clustering effects are demonstrated in studies of health behavior, such as vaccination decisions among college students who coordinate their flu shots with their friends.

27

The findings suggest that potentially limiting the size of adolescent groupings may have a positive effect on delay- ing alcohol initiation. In this case, the study results argue for smaller schools, as they provide a smaller number of peers an adolescent can reach on their own or through their friends. This reasoning may also explain why private schools show protective effects against alcohol initiation in the model. Interestingly, a new generation of on-line social networks (Path, GroupMe, Rally Up, Shizzlr) focuses on limiting the size of the friendship group.

28

In this study, adolescents in higher density school networks were more likely to initiate alcohol use. More dense networks exhibit more interconnected clusters that magnify the spread of influence. Notably, the results come to light in view of computer simulations showing that more dense networks amplify the dynamics of influ- ence cascades.

29,30 Future research may want to explore how the density of virtual social communities (eg, Facebook), which connect a great number of adolescents on-line, influence alcohol drinking among adolescents.

It should be noted that, in the current sample, alcohol initiators are closer through their friendship connections to more popular adolescents—defined here as individuals with more peer nominations (indegree)—than abstainers. For every additional friend with high-popularity status (in-degree), the likelihood that an adolescent initiates alcohol use increases by 13%. Our findings are in line with research showing popularity status and conforming to peer alcohol use are linked.

18 More desirable students with more social connections may serve as positive or negative opinion leaders who could influence the behavior of others. They may be critical in efforts to delay alcohol initiation. Studies on the immunization of complex networks (eg, sexual partnership Web, the Internet) confirm that immunization/intervention efforts targeting highly connected nodes (eg, most promiscuous individuals or high-traffic routers) will greatly reduce a networks’ vulnerability to virus outbreaks.

31–33

These data demonstrate that parental modeling of respon- sible alcohol use and having fun together as a family offer protective benefit against adolescent alcohol initiation. The results are similar to previous research showing that low family bonding and parental drinking are linked to the onset of alcohol consumption.34,35 Health care

professionals may wish to establish community partnerships for building stronger families that encompass spending quality time together. More research on fostering conditions for families to have fun together is warranted. Future studies may wish to explore how cascades

of influence to initiate drinking are driven, whether temporal patterns of the social network matter for alcohol initiation, and how adolescent social networks can be exploited to promote healthy choices with regard to alcohol. This study has several limitations. First, it relies on

participant self-report of alcohol initiation, although self-reported substance consumption is generally perceived as a valid measure.

36,37 Second, although the study design takes advantage of longitudinal data, it is not possible to distinguish between 2 potential causes of behavioral clustering: induction, or the direct influence of one individual on another, and homophily, the tendency of persons to choose to associate with similar individuals. This is left for future investigation. Third, this study is limited to individuals who provided school peer group data. For many adolescents, the peer network includes students outside of their particular school, which were not available for the analysis. Finally, the study results are susceptible to potential selection and sample biases. Subjects were excluded from the analysis if they had no friends who completed the Add Health wave 1 survey. This study does not attempt to draw conclusions about students who are isolated from their school peer group. Subjects were also excluded if they did not complete the wave 2 survey. Over 88% of eligible participants completed wave 2 in-home interviews, making it unlikely that the results suffer from significant response bias. Nonresponse has been investigated by the Survey Research Unit at the University of North Carolina, and findings showed that bias for measures of health and risk behaviors rarely ex- ceeded 1% in either wave 1 or wave 2.

38

CONCLUSION The findings suggest that, in addition to well established

demographic risk factors, adolescents are at heightened risk of alcohol use onset because of their position in the social network in relationship to their friends and the friends of their friends.

ACKNOWLEDGMENT I wish to thank Add Health, a program project directed by Kathleen

Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and

Kathleen Mullan Harris at the University of North Carolina at Chapel

Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver

National Institute of Child Health and Human Development, with cooper-

ative funding from 23 other federal agencies and foundations for the use of

the data. Special acknowledgment is due Ronald R. Rindfuss and Barbara

Entwisle for assistance in the original design. This research was funded by

grant P01-HD31921 from the Eunice Kennedy Shriver National Institute

of Child Health and Human Development, with cooperative funding from

23 other federal agencies and foundations. This work was supported by

a grant to Marlon Mundt from the National Institute on Alcohol Abuse

and Alcoholism, NIAAA 1K01 AA018410-01.

 

 

ACADEMIC PEDIATRICS ADOLESCENT ALCOHOL USE IN PEER GROUPS 421

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Proceedings of the Joint Statistical Meetings, American Statistical

Association, Alexandria, VA.

 

  • The Impact of Peer Social Networks on Adolescent Alcohol Use Initiation
    • Methods
      • Data Source
      • Sample
      • Measures
        • Alcohol Use Initiation
        • Social Networks
        • Demographics
        • Family Characteristics
        • Census Block Characteristics
        • School Characteristics
        • Friend Characteristics
      • Statistical Analysis
    • Results
    • Discussion
    • Conclusion
    • Acknowledgment
    • References

 

Hypotheses and conceptual Models from nursing

Assess hypotheses and conceptual models from nursing and related areas for utilize in progressed nursing practice.

Your introductory post ought to be at slightest 550 words, organized and cited in current APA fashion with back from at slightest 3 scholarly sources

LINKING DEVELOPMENTAL EXPERIENCES TO LEADER EFFECTIVENESS

 

LINKING DEVELOPMENTAL EXPERIENCES TO LEADER EFFECTIVENESS AND PROMOTABILITY: THE MEDIATING ROLE OF LEADERSHIP SELF-EFFICACY AND MENTOR NETWORK

SCOTT E. SEIBERT University of Iowa

LEISA D. SARGENT University of Melbourne

MARIA L. KRAIMER University of Iowa

KOHYAR KIAZAD Monash University

We developed and tested a model linking developmental experiences to leadership effectiveness and promotability through 2 mediating pro- cesses based on social cognitive and social capital theories.

We hypoth- esized that a manager’s exposure to 3 types of developmental expe- riences (formal development programs, developmental job challenges, and developmental supervision) would positively relate to supervisor’s assessment of the manager’s leadership effectiveness in the current job role and promotability within the organization through the manager’s leadership self-efficacy and size and quality of the manager’s mentor network.

Results based on a sample of 235 retail managers showed that leadership self-efficacy and mentor network fully mediated the rela- tionship between job challenges and promotability, whereas leadership self-efficacy also fully mediated the relationship between job challenges and leadership effectiveness. Developmental supervision was indirectly related to promotability through mentor network.

In addition, a 3-way interaction analysis revealed that participation in formal development ac- tivities had a positive indirect relationship with leadership effectiveness and promotability mediated by leadership self-efficacy when a manager experienced either lower levels of job challenge and developmental su- pervision, or higher levels of both. Our findings contribute to leadership

This research was supported by an Australian Research Council Linkage Grant LP0882114 in partnership with Deloitte Touche Tohmatsu Australia. We thank Lisa Barry from Deloitte for her sustained support for this research along with the participating orga- nizations.

The paper was partly completed while Maria Kraimer was a Professorial Fellow in the Department of Management and Marketing, University of Melbourne.

Correspondence and requests should be addressed to Scott E. Seibert, Department of Management & Organizations, 108 John Pappajohn Business Building, University of Iowa, Iowa City, IA 52242; scott-seibert@uiowa.edu.

C© 2015 Wiley Periodicals, Inc. doi: 10.1111/peps.12145

357

 

 

358 PERSONNEL PSYCHOLOGY

knowledge by examining how both formal and informal developmental experiences relate to leadership effectiveness and promotability through social processes.

Introduction

A recent survey of over 500 executives found that two-thirds identi- fied leadership development as their number one “human capital” priority (The Conference Board and McKinsey, 2012). This concern is reflected in reports indicating that over $13 billion is spent annually on leadership training in the U.S. alone (Loew & O’Leonard, 2012).

Although schol- arly discussions and reviews of leadership development practice continue to proliferate (Avolio, Reicherd, Hannah, Walumbwa, & Chan, 2009; Day, 2000, 2012; Day, Fleenor, Atwater, Sturm, & McKee, 2014; Galli & Müller-Stewens, 2012), most of this work reviews formal leadership train- ing interventions or lacks empirical testing. To date, organizations lack an evidence-based understanding of the way formal development programs and informal employee work experiences work together to develop more effective leaders.

This is an important oversight because informal expe- riences at work are likely to be a major influence on development due to being pervasive and ongoing. The field also lacks a clear understanding of how or why developmental practices and experiences develop more effec- tive and promotable leaders, limiting our ability to target developmental experiences to the individual’s developmental needs. We begin to address this issue by testing a mediated model, grounded in social cognitive and social capital theories, linking employees’ formal and informal develop- mental experiences to their leadership effectiveness and promotability.

Three broad sources of developmental experience have been identified in the leadership literature (Day, 2012; McCauley, Moxley, & Van Vel- sor, 1998; Yukl, 2010). Formal development programs include off-the-job training and educational activities designed to promote leader develop- ment and effectiveness. Developmental job challenges reflect the extent to which leaders face new or unique issues, problems, or responsibilities during the performance of their regular job duties (McCauley, Ruderman, Ohlott, & Morrow, 1994; McCauley, Van Velsor, & Ruderman, 2010).

Fi- nally, developmental supervision is informal coaching and role modeling provided by one’s direct supervisor during the performance of one’s job duties (Arnold, Arad, Rhoades, & Drasgow, 2000).

Because these devel- opmental experiences reflect three primary contextual influences found in organizations: formal organizational programs, the job itself, and supervi- sors (Katz & Kahn, 1978; Kozlowski & Klein, 2000), we include all three in our model.

 

 

SCOTT E. SEIBERT ET AL. 359

The purpose of this study is to test a mediated model that links man- agers’ exposure to these three types of developmental experiences, formal development programs, developmental job challenges, and developmen- tal supervision, to their leadership effectiveness and promotability. We propose that leadership self-efficacy and the quality and size of man- agers’ mentor networks mediate the relationship between the develop- mental experiences and leadership outcomes. We also examine whether job challenges and developmental supervision moderate the effects of participation in formal development programs on leadership self-efficacy, expecting formal development programs to have their strongest effect when the other two experiences are low. A test of our theoretical model contributes to the leadership development literature by addressing three limitations in the existing literature.

First, to date, the three sources of leadership development have not been examined together in a single model (Avolio, 2007; Day, 2000), which means we do not know the unique effect of each developmen- tal practice on leadership outcomes when experienced together, as they are likely to be in field settings (Avolio, 2007). Furthermore, it is the- oretically reasonable to expect these three sources of development to interact to supplement or inhibit each other when experienced simultane- ously. For example, formal development programs may be less impactful when the individual has already faced many developmental challenges and received developmental supervision. Thus, we currently have a lim- ited understanding of how to best configure a collection of leadership development experiences to have the strongest impact.

By incorporating the three developmental experiences in a single model, we can examine the unique effect of each source after accounting for the effects of the other two in addition to theorizing and testing for the moderating effects among the three sources of development. In short, our study makes an important contribution to the literature by allowing us to examine the way these three sources of development work together to promote effective leadership.

A second limitation of the leadership development literature that we address is the lack of theoretical knowledge regarding the underlying mechanisms that explains how and why leadership development activi- ties relate to leadership effectiveness (Day, 2012; Day & Zaccaro, 2004; Van Velsor, Moxley, & Bunker, 2004). Indeed, Day (2000) describes re- search on leadership development as a collection of best practices that, as a set, lack theoretical coherence.

Day (2012) further suggests that the field has failed to answer the basic question, what develops in leader- ship development? Failure to understand the mediating mechanisms that link participation in developmental activity with effectiveness in a lead- ership role is thus an important theoretical shortcoming of the current

 

 

360 PERSONNEL PSYCHOLOGY

literature. Based on social cognitive theory (Bandura, 2001) and social capital theory (Coleman, 1990; Burt, 1992), we propose leadership self- efficacy and the size and quality of the individual’s network of mentors as the explanatory mechanisms linking developmental experiences to the leadership outcomes. These two mechanisms represent two broad sets of individual and interpersonal resources that previous theorists argue under- lie the development of leadership effectiveness (e.g., Avolio, 2007;

Day, 2012; Mumford, Campion, & Morgeson, 2007). Understanding the mech- anisms that link developmental practices to leadership effectiveness and promotability will provide a more integrated theoretical understanding of the leadership development process and allow organizations to design and generate more potent leadership development interventions.

Finally, a third limitation of the leadership development literature is that the two informal sources of development—developmental job chal- lenge and developmental supervision—have not been empirically linked to the leadership effectiveness of individuals in a leadership role, as we do here.

Developmental job challenges have been shown to positively re- late to leadership role attainment (e.g., Arvey, Zhang, Avolio, & Krueger, 2007) and supervisor ratings of subordinates’ skills and competencies, such as cognitive skills, interpersonal skills, and strategic business knowl- edge (e.g., DeRue & Wellman, 2009; Dragoni, Tesluk, Russell, & Oh, 2009) but not to the manager’s effectiveness in a leadership role. Like- wise, developmental supervision and empowering leadership (a broader construct that includes developmental supervision as one dimension) has been positively related to time spent leading others (Dragoni, Park, Soltis, & Forte-Trammell, 2014) and ratings of the empowering leader by the subordinate (Amundsen & Martinsen, 2014; Hassan, Mahsud, Yukl, & Prussia, 2013) but not to the leadership effectiveness of followers who themselves hold leadership roles. This is an important gap because ef- fectiveness in a leadership role is the ultimate criteria against which to evaluate leadership development activities (Day et al., 2014).

In sum, by testing a mediated model linking the three sources of developmental experiences to leadership effectiveness and promotability through social cognitive and social capital mediators, we answer the call for more in- tegrated approaches to leadership development (Avolio, 2007; Avolio & Gardner, 2005; Day et al., 2014).

Theoretical Model

Our theoretical model links three sources of developmental expe- riences to leadership capacity, which we define in terms of supervi- sor ratings of the subordinate manager’s effectiveness as a leader and promotability to higher levels of responsibility, reflecting both current and

 

 

SCOTT E. SEIBERT ET AL. 361

Promotability Ratings

Leadership Effectiveness

Ratings .23**

.23**

Formal Development

Programs

Developmental Supervision

Developmental Job Challenges

Leadership Self-efficacy

Mentor Network

.10

.03

.22**

.20*

.28**

.16*

.11

.69**

Motivation to Lead (control variable)

.39**

High Potential Participant

(control variable)

Age (control variable)

.14* -.23**

Figure 1: Results for Hypothesized Model.a

Note. aCompletely standardized path estimates are shown from the model including “supervisor” as a Level 2 variable. For the sake of clarity, only the significant paths for the control variables are shown; N = 235. *p < .05. **p < .01.

future leadership potential (see Figure 1). Our model seeks to encompass the two major capabilities that previous models of leader development have identified as the target of development efforts: individual leadership skills and capabilities and interpersonal resources (Day et al., 2014; Galli & Müller-Stewens, 2012; Marshall-Mies et al., 2000; Mumford et al., 2007). We ground our model in two theories, social cognitive theory (Bandura, 2001) and social capital theory (Burt, 1992; Coleman, 1990; Lin, Ensel & Vaughn, 1981), which focus on these capabilities and pro- vide the theoretical explanation for the relationship of the developmental experiences to the leadership outcomes. These theories are captured in two mediating constructs: leadership self-efficacy and size and quality of the individual’s mentor network. According to social cognitive theory, it is self-efficacy that allows one to apply what one has learned to new situations and challenges. Likewise, according to social capital theory, it is one’s social network of relationships that allows one to take productive action within a social context. Together, these two constructs explain how and why developmental experiences are linked to leadership effectiveness

 

 

362 PERSONNEL PSYCHOLOGY

and promotability. We next introduce the key constructs of our model in detail before proposing the specific hypotheses to be tested.

Developmental Experiences

Formal development programs. Formal training and development pro- grams are perhaps the most widely used leadership developmental practice in organizations (Loew & O’Leonard, 2012), yet the evidence supporting their effectiveness as a source of leadership development is modest. Burke and Day (1986) and Collins and Holton (2004) meta-analyzed previous research on leadership and managerial training and reported moderate ef- fects for leadership development (“human relations”) interventions on a range of criteria but located very few studies that included performance or leadership effectiveness as an outcome. Instead, the studies they reviewed focused primarily on learning, expertise, or knowledge acquisition related to the content of the program itself. Avolio et al. (2009) meta-analyzed over 200 experimental or quasi-experimental leadership interventions and found that training programs (a subset of the studies) have a positive, but modest, effect on followers’ affective, behavioral, and cognitive out- comes. The authors of all three articles note the need for further research to determine both mediating constructs that explain what is developed as a result of formal leadership development programs and moderating constructs that explain when formal training may be more or less strongly related to leadership outcomes. We therefore include participation in for- mal development programs as an important but as yet not fully understood developmental experience, which we expect to be related to leadership capacity through its relationship with leadership self-efficacy. We further expect the strength of the association between formal development pro- grams and leadership self-efficacy to be moderated by the extent to which the individual engages in other developmental activities.

Developmental Job Challenges. We also include on-the-job experience as an informal developmental experience we expect to be linked to leader- ship capacity. Experience is considered one of the most potent sources of learning related to leadership (DeRue & Wellman, 2009; Dragoni et al., 2009). However, experience is not equivalent to simple time on a job; rather, it is variety in the qualitative types of challenges faced on the job that provides opportunities for new learning (Tesluk & Jacobs, 1998). Leadership researchers (e.g., DeRue & Wellman, 2009; McCall, Lom- bardo, & Morrison, 1988; McCauley et al., 1994) have identified five dimensions of developmental challenge: unfamiliar responsibilities, high levels of responsibility, creating change, managing boundaries, dealing with employee problems, and managing diversity. Empirical studies have shown the experience of job challenge relates to a number of important out- comes among middle- to senior-level managers, including self-reported

 

 

SCOTT E. SEIBERT ET AL. 363

learning (McCauley et al., 1994; Ohlott, 2004), supervisors’ perceptions of leadership skill development (i.e., cognitive, business, interpersonal, and strategic skills; DeRue & Wellman, 2009), supervisors’ ratings of broad managerial competencies (Dragoni et al., 2009), and subordinates’ ratings of leaders’ transformational leadership behaviors (Courtright, Colbert, & Choi, 2014). Among junior managers, exposure to job challenges has been related to managers’ promotability (De Pater, Van Vianen, Bechtoldt, & Klehe, 2009; Dong, Seo & Bartol, 2014). However, the experience of developmental job challenge has not been empirically linked to effective- ness in the leadership role nor have the mechanisms explaining this link been empirically examined. As our model shows, we include developmen- tal job challenge as an important developmental experience, linking it to leadership capacity through its relationships with leadership self-efficacy and the manager’s mentor network.

Developmental supervision. Another source of informal development is developmental supervision. Many scholars have argued that one’s im- mediate supervisor is one of the most important sources of development available within an organization (Dragoni et al., 2014; Kraimer, Seibert, Wayne, Liden, & Bravo, 2011; McCauley et al., 2010). However, super- visors are likely to vary considerably in the extent to which they provide developmental support and may provide different levels of support to dif- ferent followers (Frankovelgia & Riddle, 2010; Scandura & Williams, 2004). Two leader behaviors that have been identified with developmental supervision are leading by example (i.e., role modeling) and coaching (Arnold et al., 2000; Bass & Avolio, 1995; Yukl, 2010). Leading by ex- ample involves supervisor behavior that demonstrates that the supervisor sets high personal standards and is committed to the work of the team or work unit (Arnold et al., 2000). Coaching refers to behaviors designed to improve the skills and self-reliance of followers, such as identifying areas in need of improvement and providing suggestions on strategies the follower can use to improve his or her performance (Arnold et al., 2000). Although these leadership behaviors have been associated with the effec- tiveness of the leader using them, they have not been empirically linked with the leadership effectiveness or potential of the junior manager that is the target of development (Amundsen & Martinsen, 2014; Hassan et al., 2013). We included developmental leadership in our model because we expect it to be related to the junior manager’s leadership capacity through both mediators.

Mediating Mechanisms

Leadership self-efficacy. Social cognitive theory is a learning theory based on the idea that individuals learn from the observation of others in a social context (Bandura, 1986, 1997). A central component of the

 

 

364 PERSONNEL PSYCHOLOGY

theory is self-efficacy, which is one’s belief in one’s capability to execute the courses of action necessary to perform successfully in a particular context or situation. It is, according to social cognitive theory, the de- velopment of higher self-efficacy that allows one to learn the behavioral strategies necessary to face new challenges and achieve difficult goals. Leadership self-efficacy refers to leaders’ beliefs about their “perceived capabilities to organize the positive psychological capabilities, motiva- tion, means, collective resources, and courses of action required to at- tain effective, sustainable performance across their various leadership roles, demands, and contexts” (Hannah, Avolio, Luthans, & Harms, 2008, p. 2). Researchers have identified a number of specific activities involved in leadership, which include planning, setting overall direction, delegat- ing, coordinating tasks, communicating, and motivating others (Chemers, Watson, & May, 2000; Ng, Ang, & Chan, 2008). Leadership self-efficacy captures the individual’s beliefs about his or her own capability to perform these activities effectively and is likely to provide the drive and persis- tence to get better at these activities over time. We propose that leadership self-efficacy is one important mediator in our model because it captures the manager’s confidence in his/her leadership abilities and is likely to be shaped by developmental experiences (e.g., Day et al., 2014; Mumford et al., 2007).

Mentor network. Scholars have argued that leadership development must involve the acquisition of not only individual skills but also social resources because both are necessary to take effective action in a social context (Avolio, 2007; Day, 2012; Mumford et al., 2007). Social capi- tal theory is concerned with the way the pattern of social relationships provides access to social resources (Burt, 1992; Coleman, 1990; Lin, et al., 1981). According to this perspective, one’s network of social re- lationships provides timely access to information, resources, and support (Burt, 1992; Lin, 1982; Seibert, Kraimer & Liden, 2001). A growing body of research examines the ways one’s social network facilitates effective leadership. For example, empirical research has shown that one’s social network is related to perceived charisma and reputation as an effective leader (Balkundi, Kilduff & Harrison, 2011; Kilduff & Krackhardt, 1994; Mehra, Dixon, Brass & Robertson, 2006), perceived power and influence (Brass & Burkhardt, 1992, 1993), and the performance of the leader’s team (Balkundi et al., 2011).

One way to assess one’s social capital is through the examination of that individual’s ego network, which is the network of relationships or ties around a single individual (e.g., Lin, 1982; Seibert et al., 2001). In this study, we focus on the size and quality of one’s mentor network within the organization. The quality of the mentor network is defined as the amount of career and psychosocial support received from the set of people who act as

 

 

SCOTT E. SEIBERT ET AL. 365

one’s mentors (Kram, 1983; Noe, 1988). The mentor network is expected to be an important mediator in our model because it provides access to the types of social resources likely to facilitate leadership effectiveness and is likely to be shaped by developmental experiences.

Hypotheses

Mediating Role of Leadership Self-Efficacy

We expect leadership self-efficacy to mediate the relationship of for- mal development programs to leadership capacity. Social cognitive theory suggests that self-efficacy is the mechanism through which learning is translated into effective behavior in new and challenging situations (Ban- dura, 2001). According to the theory, self-efficacy plays a major role in how new and challenging tasks are approached and goals accomplished. Leadership self-efficacy will determine the extent to which new leader- ship behaviors acquired from formal development programs are initiated, how much effort will be expended to apply these newly acquired behav- iors, and how long such efforts will be sustained in the face of leadership challenges and setbacks (Hannah et al., 2008). We expect these efforts to apply one’s learning to be related to performance in the leadership role. Below we explicate the specific steps in this mediation process.

First, we expect participation in formal development programs to build one’s leadership self-efficacy. According to social cognitive the- ory, four processes influence self-efficacy perceptions: enactive mastery, role modeling, social persuasion, and one’s ability to manage emotional states during task performance (Bandura, 1986, 2001). Formal develop- ment programs may be a positive source for all four of these efficacy- enhancing processes. For example, many formal development programs include case studies, discussions, and interactions with teachers/trainers, and/or coaches, which provide opportunities for participants to engage in vicarious learning about leadership from the leadership role models they read about (Conger, 2010). Some formal training programs and ed- ucational courses may provide opportunities for participants to practice leadership skills through in-class role plays and group discussions. The abstract concepts and principles taught in development programs and pos- itive feedback from teachers or trainers should also provide participants in formal programs with greater confidence in their own abilities and de- crease their anxiety about their capabilities, reflecting the social persuasion and physiological processes of self-efficacy enhancement (Conger, 2010).

Second, we expect leadership self-efficacy to be related to leader- ship effectiveness and promotability. Managers with higher leadership self-efficacy will accurately perceive themselves to have the skills and

 

 

366 PERSONNEL PSYCHOLOGY

capabilities necessary to be effective leaders and will exert more effort in a more sustained manner to perform effectively in leadership roles based on this belief (Anderson, Krajewski, Goffin, & Jackson, 2008). So- cial cognitive theory suggests that self-efficacy predicts not only effort, but the willingness to approach new and more challenging situations re- lated to the domain tapped by the self-efficacy construct (Bandura, 2001). Thus, managers higher on leadership self-efficacy are also likely to seek promotion to higher levels of leadership responsibility and to demon- strate confidence, persistence, and an ability to learn and grow as leaders. Indeed, empirical evidence demonstrates that leadership self-efficacy is related to a range of positive leader outcomes, including leader and man- agerial effectiveness (e.g., Anderson et al., 2008; Lester, Hannah, Harms, Vogelgesang, & Avolio, 2011), attempts to lead or assume leadership roles (McCormick, Tanguma, & Lopex-Forment, 2002; Paglis & Green, 2002), motivation to lead, and ratings of leadership potential (Chan & Dras- gow, 2001; Chemers et al., 2000). These two links taken together explain how leadership self-efficacy is the mechanism through which participa- tion in formal development programs influences leadership effectiveness and promotability.

Hypothesis 1: Leadership self-efficacy mediates the relationships be- tween participation in formal development programs and supervisor ratings of (a) leadership effectiveness and (b) promotability.

We also expect leadership self-efficacy to mediate the relationship of developmental job challenges to leadership capacity. According to social cognitive theory, self-efficacy is the mechanism through which the learning associated with previous experience is translated into effective behaviors in new and more challenging situations (Bandura, 2001). Below we explain the specific links in this mediated relationship.

Experience, or enactive attainment, is the most important factor driving self-efficacy (Bandura, 2001). Challenging on-the-job experiences offer a potent opportunity for enactive mastery. Managers who face critical developmental challenges related to leadership have both the opportu- nity to experiment with different behavioral strategies and to observe the impact of their behavior on important outcomes in the actual work set- ting. Because they are in their workplaces and are likely to experience real-world consequences from their performance, they should also have greater motivation to engage in learning and growth in response to the novel challenges of their jobs (Kanfer & Ackerman, 1989). Facing devel- opmental challenges in one’s job will also lead to reductions in anxiety related to the future enactment of effective leadership behaviors, another source of leadership self-efficacy beliefs. Recent research has also linked

 

 

SCOTT E. SEIBERT ET AL. 367

developmental experiences to promotability through positive emotional states, providing further support for the link between arousal, one of the antecedents of efficacy, and advancement potential (Dong et al., 2014). Enhanced skill and confidence should be reflected in the managers’ ratings of their own leadership self-efficacy (Bandura, 1986), which, as discussed above, should in turn be related to leadership capacity.

Hypothesis 2: Leadership self-efficacy mediates the relationships be- tween developmental job challenge and supervisor ratings of (a) leadership effectiveness and (b) promotability.

Turning to our third source of development, we expect leadership self-efficacy to mediate the relationship of developmental supervision to leadership capacity. Developmental supervisors are likely to be role models for the junior employee. According to social cognitive theory (Bandura, 2001), it is through enhanced self-efficacy that the individ- ual has the confidence to implement in their own context the successful behaviors displayed by a high-status role model.

In particular, according to Bandura (2001), observational learning is the second most powerful source of self-efficacy beliefs. A supervi- sor who leads by example provides the junior manager with a visible, high status model from whom to learn effective leadership behaviors. Further, coaching is a form of social persuasion that provides feed- back, advice, and verbal support the junior manager can use to enact more effective leadership. Both observational learning and social persua- sion are important sources of information shaping self-efficacy beliefs (Bandura, 1986; Conger & Kanungo, 1988). Indeed, previous research shows that developmental supervision relates positively to employees’ job self-efficacy beliefs (Ahearne, Mathieu, & Rapp, 2005), job knowl- edge (Dragoni et al., 2014), and psychological empowerment, a mul- tidimensional construct that includes competency beliefs (e.g., Seibert, Wang, & Courtright, 2011; Zhang & Bartol, 2010). Thus, we expect de- velopmental supervision to build greater leadership self-efficacy through which it is in turn related to leadership capacity. These two links to- gether explain how leadership self-efficacy is the mechanism through which developmental supervision relates to leadership effectiveness and promotability.

Hypothesis 3: Leadership self-efficacy mediates the relationships be- tween developmental supervision and supervisor ratings of (a) leadership effectiveness and (b) promotability.

We also expect an interaction effect among the three developmental experiences, such that participation in formal development programs will be more strongly related to leadership effectiveness and promotability

 

 

368 PERSONNEL PSYCHOLOGY

through leadership self-efficacy when both of the informal developmental experiences, developmental job challenges and developmental supervi- sion, are low. This interaction is due to the mediating role of leadership self-efficacy. As we have argued previously, a formal development pro- gram can provide all four sources of efficacy enhancing information. However, informal, on-the-job experiences are likely to provide more salient self-efficacy cues because they provide opportunities to learn and practice skills in one’s actual performance context. Thus, when both of the informal, on-the-job developmental experiences are low, the individual will attend to the efficacy enhancing cues provided from participation in formal development activities resulting in a stronger positive indirect re- lationship between formal development and leadership effectiveness and promotability. However, when either or both of the informal, on-the-job sources of development are high, the individual is likely to attend to the ability cues they provide and is likely to pay less attention to the cues provided by formal development activities, undermining the influence of formal development on leadership self-efficacy. As such, formal devel- opment will have a weaker positive indirect relationship to leadership effectiveness and promotability when developmental job challenges and developmental supervision are both high.

Previous research provides support for this hypothesis. For example, the tutorial approach typical of much formal training has been shown to be less effective at building self-efficacy than more active approaches that emphasize enactive mastery and role modeling, the core mechanisms of developmental job challenge and developmental supervision, respectively (Bandura, 2001; Gist, 1989; Gist, Schwoerer, & Rosen, 1989). Formal training must also overcome the “transfer of training” problem (Aguinis & Kraiger, 2009; Baldwin & Ford, 1988) because it occurs away from the job, unlike informal development activities. Thus, the self-efficacy enhancing cues provided by participation in formal development programs are likely to have their strongest effect when both informal sources of development are low and competing cues from other, possibly more salient sources, are not present. Formal development will have weaker effects when developmental job challenges or developmental supervision, or both, are high.

Hypothesis 4: The indirect effect of formal development programs on (a) leadership effectiveness and (b) promotability via leader- ship self-efficacy will be stronger when developmental job challenges and developmental supervision are both low, compared to when developmental job challenges and/or developmental supervision are high.

 

 

SCOTT E. SEIBERT ET AL. 369

Mediating Role of Mentor Network

We also expect the manager’s mentor network to mediate the relation- ship of developmental job challenges and developmental supervision with leadership capacity. Because leadership is an inherently social activity, de- velopmental experiences must enhance the individual’s social capabilities if they are to be successful (Day, 2012). Social capabilities are reflected in the individual’s ability to gather and mobilize social resources in the pursuit of organizational goals. We do not expect the mentor network to mediate the effects of participation in formal development programs be- cause formal programs take place off-the-job and leave little opportunity to make connections with others in the organization. For the other two sources of developmental experience, however, social capital theory (Burt, 1992; Lin, et al., 1982) suggests that one’s social network is the mecha- nism through which one’s human capital is effectively applied in pursuit of one’s goals. The size and quality of one’s mentor network represents the extent to which the social capabilities acquired from developmental experiences are translated into a social network of supportive relationships within the organization that enables higher levels of leadership effective- ness. One’s support network will also allow one to communicate to others one’s reputation as an effective and promotable leader. Next, we detail the links in this mediated effect.

Several theoretical arguments from mentoring theory lead us to expect developmental job challenges to be related to the size and quality of one’s mentor network. First, high levels of job challenge, such as higher level managerial responsibility, the need to create change, or managing across organizational boundaries, are likely to expose the junior manager to a wider range of more senior managers within the organization; exposure increases the chances of forming supportive relationships (McPherson, Smith-Lovin, & Cook, 2001; Monge & Eisenberg, 1987; Podolny & Baron, 1997). Second, Higgins, Chandler, and Kram (2007) argue that developmental networks form when junior managers proactively engage in development-seeking behavior. Although the antecedents of such be- havior are not well understood, higher levels of job challenge are likely to provide junior managers with the legitimate need to seek information, advice, feedback, or material help and thus to initiate developmental rela- tionships (Higgins et al., 2007; Mullen, 1994). Finally, high levels of job challenges may make junior managers more attractive as protégés because senior managers may view junior managers who face more challenging responsibilities as rising stars within the organization (Allen, Poteet & Russell, 2000; Singh, Ragins, & Tharenou, 2009).

Based on social resources theory (Lin et al., 1981), we expect the size and quality of one’s mentor network to in turn be positively related to

 

 

370 PERSONNEL PSYCHOLOGY

leadership effectiveness and promotability. This is because a larger net- work of high-quality developmental relationships provides higher levels of instrumental and psychosocial support to the junior manager. Such a network is likely to provide information, career advice, material support, exposure to upper echelons in the organization, protection, and other types of social resources that should help the manager be more effective in their leadership role (Bartol & Zhang, 2007; Higgins & Kram, 2001; Seibert et al., 2001). Being a recipient of such career advice and support should also help the junior manager be perceived as having a higher potential for promotion into positions of greater leadership responsibility. For exam- ple, Seibert et al. (2001) showed that individuals with more developmental contacts at higher organizational levels received more career mentoring, which in turn positively related to the number of promotions over the individual’s career. Together, these arguments suggest that the size and quality of one’s mentor network partially mediates the relationship of developmental job challenges with leadership capacity.

Hypothesis 5: Mentor network mediates the relationships of develop- mental job challenge to supervisor ratings of (a) leader- ship effectiveness and (b) promotability.

We also expect developmental supervision to be related to the size and quality of a manager’s network of supportive relationships. First, compared to managers who receive less developmental supervision, we expect managers who are provided with more role modeling and coaching from their supervisors to be more likely to become incorporated into the social network of relationships maintained by their supervisor (Sparrowe & Liden, 1997, 2005). This is because followers who have close rela- tionships with their supervisor are more likely to be seen as influential, high performing, and legitimate members of the organization (Burt, 1997; Kilduff & Krackhardt, 1994; Venkataramani, Green, & Schleicher, 2010). Junior managers incorporated into their supervisors’ networks are likely to have more access to managers at higher levels and thus more support from senior colleagues (Bartol & Zhang, 2007). Second, they are also likely to receive higher levels of mentoring support from senior managers because they are more likely to be seen as competent and trustworthy, important determinants of a mentor’s willingness to provide support to a protégé (De Janasz & Sullivan, 2004; Singh et al., 2009; Wang, Tomlinson, & Noe, 2010). As discussed above, we expect the mentor network to be, in turn, related to one’s leadership effectiveness and promotability.

Hypothesis 6: Mentor network mediates the relationships of develop- mental supervision to supervisor ratings of (a) leadership effectiveness and (b) promotability.

 

 

SCOTT E. SEIBERT ET AL. 371

We do not predict a three-way interaction among the developmen- tal experiences through mentor network, as a parallel to Hypothesis 4, because we do not expect formal development programs to predict men- tor network under any conditions. At the company participating in this study, formal training offered no opportunities to interact with senior managers.

Method

Sample and Procedure

We collected survey data from managers and their supervisors in a large Australian retail organization. The company has approximately 190 stores. Each store has multiple departments, with a store management team composed of a store manager, the department managers, and assis- tant department managers. Although external hires are occasionally used for management positions, the company is committed to a promotion- from-within policy. They provide a variety of management development programs including formal management skills training, specialized off- site leadership training, and a high potential manager program. A typical management career path would begin as an assistant manager of a de- partment, progress through various department manager positions, and lead eventually to store manager. The focus of our study is on the first- line managers within the retail operations (e.g., the assistant department manager positions) because these managers currently exercise leadership and are the initial source for the talent pipeline that leads to higher-level manager positions.

Through the assistance of a representative from the human resources department, we obtained a list of first-line managers and sent them a survey through the company’s internal mail system. This survey included mea- sures for the developmental experiences, leadership self-efficacy, mentor network, potential control variables, and demographics. Our contact per- son also provided the names of each manager’s immediate supervisor so we could obtain supervisors’ ratings of the managers’ leadership effec- tiveness and promotability. The supervisor surveys were also sent through the company’s internal mail system. We precoded all surveys to match in- dividual manager responses to their corresponding supervisor responses. The survey packet included a letter of support from the HR manager of the company, a postage-paid reply envelope, a letter of informed consent, and the survey itself. Completed surveys were returned directly to the researchers.

The manager survey was distributed to all 439 first-line managers. We received a total of 334 completed surveys, yielding a response rate

 

 

372 PERSONNEL PSYCHOLOGY

of 76.1%. Two months later, we distributed the supervisor surveys to the immediate supervisors of those participating managers. We received 235 completed supervisor surveys for a response rate of 71%. This represented 117 unique supervisors, as some managers reported to the same supervisor: 44% of the supervisors rated only one manager and on average each supervisor rated 2.01 managers. All of the returned supervisor surveys could be matched to a manager with complete data. Thus, our final sample size is 235 manager–supervisor dyads (for an overall manager response rate of 54%).

To check for supervisor nonresponse bias, we tested for differences in our manager-reported study variables between the group of focal man- agers whose supervisors responded and managers whose supervisors did not respond. A MANOVA revealed no significant mean differences (F = .91, ns) in formal development programs, developmental job chal- lenges, developmental supervision, leadership self-efficacy, or mentor net- work. Of the 235 managers included in the final sample, 67% were male, their average age was 37 years, and 83% were married or in a de facto relationship. In terms of highest level of education, 45% had a high school diploma, 19% had an associate’s degree, 34% had a bachelor’s degree, and 2% had a master’s degree. All of these managers were full-time em- ployees and their average job tenure was 3.02 years. The demographic breakdown of the supervisor respondents is as follows: average age was 42 years, 94% were male, and 92% were married. In terms of highest-level of education, 44% had a high school diploma, 27% an associate’s degree, 26% a bachelor’s degree, and 3% a master’s degree.

Measures

Formal development programs. We used Kraimer, Seibert, Wayne, Li- den, and Bravo’s (2006) four-item measure of participation in formal training and development to assess manager’s participation in formal de- velopment programs. Respondents indicated (1 = not at all to 5 = to a very large extent) the extent to which they had participated in four types of developmental activities in the past 12 months: training courses to develop managerial skills, training courses to develop technical/functional skills, career strategy workshops, and educational courses that qualified for tu- ition reimbursement. The company offers all of these formal programs to their employees. Specifically, the company offers online training on safety, customer service, product knowledge, and personal development as well as classroom-based training on selling skills, customer service skills, and leadership behavior. It also supports participation in accredited programs that lead to advanced degrees at partner universities. The four items were averaged to form a composite (α = .74).

 

 

SCOTT E. SEIBERT ET AL. 373

Developmental job challenges. We assessed developmental job chal- lenges with eight items created for this study based on the Job Challenge Profile (JCP) scale by McCauley, Ohlott, and Ruderman (1999). We did not use the 50-item JCP scale for several reasons: We were not interested in examining subdimensions of the scale, thus, the long length of their scale was not justified; we and our contact person at the company wanted to minimize respondent fatigue in answering an overly long survey; and McCauley et al. (1999) have copyright restrictions that require a per sur- vey fee. To capture a range of job challenges appropriate for first-level managers, we initially developed 10 items, two items each to capture the five dimensions of the JCP scale (McCauley et al., 1999). We provide the 10 items that compose our scale, along with scale validity evidence, in the Appendix. Our developmental job challenges measure (10-item) correlates positively and significantly with the 50-item JCP (r = .71, p < .01) and (r = .69, p < .01; eight items discussed below), providing evidence for the construct validity of our measure.

Using data from the full sample of managers who responded to the manager survey (n = 331), we conducted a principal axis factor analysis (promax rotation) of the 10 items to assess unidimensionality of the scale. The results revealed two factors: Factor 1 had an eigenvalue of 3.90 and had eight-scale items loading above .44; Factor 2 had an eigenvalue of 1.37 and had two items loading above .60. All of the cross-loadings were below .20. The two items that significantly loaded on the second factor also had low mean scores and little variability among our respondents suggesting these items were not relevant to the first-line managers in this company. Thus, we dropped those two items from our scale. Respondents indicated the extent to which they experienced the job challenge since starting work at the company on a scale from 1 = not at all to 5 = a great deal. Responses to the eight items were averaged to form a composite (α = .83).

Developmental supervision. Developmental supervision was assessed from managers with 14 items from the Empowering Leadership Question- naire (Arnold et al., 2000). Consistent with our definition of developmental supervision, we used only the items measuring the coaching and leading- by-example dimensions. The scale items were reworded to focus on the individual rather than the work team. Five items asked respondents to indicate the extent to which their supervisors lead by example (e.g., “sets high standards for his/her own behavior”) and nine items referred to the supervisor’s coaching behavior (e.g., “helps me see areas in which I need more training”). Respondents were instructed to think about how often their supervisor had demonstrated these behaviors over the past 6 months (1 = never to 5 = always). We averaged the 14 items to form a composite score for developmental supervision (α = .96).

 

 

374 PERSONNEL PSYCHOLOGY

Leadership Self-Efficacy. Managers rated their leadership self-efficacy with Ng et al.’s (2008) 11-item scale. Respondents were asked to rate on a scale (1 = not at all confident to 5 = very confident): “How confident are you in your ability to do the following types of tasks?” Two example tasks include “set the overall direction for a project team or work unit” and “motivate others to perform at their best.” Based on our conversations with senior organizational managers, we added an additional item deemed to be an important leadership task for our sample: “deal with day-to-day politics.” Adding this item to the leadership self-efficacy scale did not change the pattern of relationships found between self-efficacy and the other study variables: The six correlations between the study variables and the original 11-item scale were virtually identical to the correlations obtained using all 12 items. Thus, responses to the 12 items were averaged to form a composite (α = .94).

Mentor network. We asked managers to indicate (by initials) people at work with whom they socialize, discuss important work or nonwork related matters, and/or who have contributed to their professional develop- ment. This broad question was designed to elicit their work-based social network. Based on previous research regarding the size of professional support networks (Marsden, 1990; Seibert et al., 2001), managers were provided with the option to list up to 12 people. For each of the network contacts listed, we then asked three questions specific to mentoring sup- port as defined in the literature (e.g., Kram, 1983; Noe, 1988): “Does this person share personal insights with you, act as a counsellor, and provide you with friendship and support?” “Does this person open doors for you, provide you with visibility, and help you gain access to opportunities that stretch you professionally?” “Do you consider this person to be a men- tor for you?” These three questions capture, respectively, psychosocial mentoring support, career mentoring support, and the number of mentors within their work-based network. The first two questions were measured on a scale from 1 = never to 5 = always. For each of these two questions, we summed the responses across all network contacts within the current organization to obtain a measure for amount of psychosocial mentoring received (mean was 11.16, range was 0–46) and amount of career men- toring received (mean was 9.55, range was 0–35). The third question had a “yes” or “no” response option. We added up the total number of “yes” responses to measure number of mentors (mean was 1.94, range was 0–9). After standardizing the three scores, we formed a composite measure for mentor network by averaging the scores (α = .93). This composite mea- sure thus captures the size of the manager’s mentor network as well as the amount of psychosocial and career mentoring support received from their work-based network.

 

 

SCOTT E. SEIBERT ET AL. 375

Leadership effectiveness. We obtained supervisor ratings of managers’ leadership effectiveness in their current job role with the four “effective- ness” items from the Multifactor Leadership Questionnaire (Avolio & Bass, 2004). Two example items are “This manager is effective in meet- ing others’ job-related needs” and “This manager leads a group and/or projects that are effective.” Responses to the four items (1 = not at all to 5 = frequently if not always) were averaged to form a composite (α = .85).

Promotability. Supervisors rated the managers’ promotability with three items taken from Wayne, Liden, Kraimer, and Graf’s (1999) four- item scale: we dropped one item that had the lowest factor loading in their data due to survey length restrictions by the company. An example item is: “I believe that this manager has what it takes to be promoted to a higher-level position.” We averaged responses to the three items (1 = strongly disagree to 5 = strongly agree) to form a composite (α = .87).

Control variables. To rule out individual differences in motivation or potential as a leader as alternative explanations for our observed effects, we included several relevant control variables. First, we controlled for the manager’s motivation to lead in predicting leadership self-efficacy, leadership effectiveness, and promotability ratings, as research has found leadership motivation to be one of the most important individual differ- ence factors predicting leadership advancement (Bray, 1982; Day, 2012). Motivation to lead was measured with Chan and Drasgow’s (2001) five affective-identity items (α = .73; e.g., “I usually want to be the leader in the teams that I work in”) that were validated by Bobbio and Rattazzi (2006). Age (self-reported in years) was included as a control predicting mentor network and promotability, because previous research has found that age negatively relates to mentoring support (Finkelstein, Allen, & Rhoton, 2003) as well as promotions and assessments of promotability (e.g., Ng., Eby, Sorensen, & Feldman, 2005; Wayne et al., 1999). Finally, to account for baseline levels of leadership potential, we controlled for whether the manager had already been selected for the company’s high potential program prior to our survey administration. Managers selected for the high potential program commence one of three formally designed training programs lasting several months. Our contact person provided us with the list of managers invited to a high potential training program prior to our survey. The high potential program participant variable was coded 1 = yes or 0 = no. We included it as a control predicting mentor network and promotability ratings based on the significant correlations for these relationships. Finally, we also considered controlling for sex, job tenure, and level of education, but correlations indicated that these three demo- graphic variables did not significantly relate to any of our study variables (see Table 1).

 

 

376 PERSONNEL PSYCHOLOGY

T A

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SCOTT E. SEIBERT ET AL. 377

Analyses and Results

Descriptive statistics and correlations for all study variables are pro- vided in Table 1.

Confirmatory Factor Analyses

We first conducted a confirmatory factor analysis (CFA) to demonstrate discriminant validity among our five theoretical constructs collected from the managers. Given the number of scale items (41), we created parcels for any variables measured with more than four items to obtain stable estimates. We used the commonly accepted cut-off values (Comparative Fit Index (CFI) > .90, Root Mean Square Error of Approximation (RM- SEA) < .08, Standardized Root Mean Square Residual (SRMR) < .06) as indicative of good fit (Dulac, Coyle-Shapiro, Henderson, & Wayne, 2008; Hair, Anderson, Tatham, & Black, 1998; Kelloway, 2015). We then compared our hypothesized five-factor model to alternative nested models using the χ 2 difference test to determine the best-fitting model (Kelloway, 2015).

The hypothesized model of five correlated latent factors fit the data well (χ 2[109, N = 334] = 360.32, p < .05; CFI = .93, RMSEA = .08, SRMR = .05). We first compared our five-factor model to a two- factor model consisting of a developmental experiences factor (e.g., formal development programs, job challenge, and developmental supervision as one factor) and a social cognitive and social capital factor (e.g., leadership self-efficacy and mentor network as a second factor). The five-factor model fit significantly better than the 2-factor model (�χ 2[4, N = 334] = +121.89, p < .05; CFI = .90, RMSEA = .10, SRMR = .49). We then compared the five-factor model to all possible, nested, four-factor models, and the five-factor model was superior in all cases (�χ 2 ranged from +51.41 to +131.69, �df = 1, p < .05). Overall, these results provide evidence that our five variables measured distinct theoretical constructs.

To assess the extent to which common method variance (CMV) was a concern, we ran a second CFA specifying the five theoretical construct (e.g., trait) latent factors and a sixth CMV latent factor (e.g., Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). CMV loadings were specified for items in all of the scales but not for every item in every scale, as such a model produces unidentifiable solutions (Spector & Brannick, 2009). Our measurement plus methods factor model converged with the following fit statistics (χ 2[96, N = 334] = 165.49, p < .05; CFI = .98; RMSEA = .05; SRMR = .05). Although three of the scale items had a significant loading (p < .05) on the common method factor, in all cases the items loaded significantly on the theoretical trait factor and the standardized trait factor

 

 

378 PERSONNEL PSYCHOLOGY

loading was at least twice the magnitude of the loading with the common method factor. Most importantly, we found that the theoretical trait factors explained 63.4% of the variance in our scale items and the method factor explained only 3.8% of the variance, well below the 50% cut-off that is suggested as indicating the presence of a single substantive factor (Hair et al., 1998). These results therefore suggest that CMV is not a significant source of the relationships among the theoretical variables in our model.

Finally, we conducted a CFA of the leadership effectiveness and pro- motability scale items rated by the supervisors. The two-factor model in which the seven items are loaded only on their hypothesized factor and the two factors are allowed to correlate, fit the data very well (χ 2[13, N = 235] = 17.60, p < .05; CFI = 1.00; RMSEA = .04; SRMR = .04). Importantly, the two-factor model fit significantly better than a one-factor model (�χ 2[1, N = 235] = +20.15, p < .05), providing support for the discriminant validity of the two leadership outcomes.

Hypothesis Testing

Because managers are nested within supervisors, we calculated ICC(1) and design effect scores to determine if there was significant variability in our dependent variables based on supervisor groupings (Bliese & Hanges, 2004; Kline, 2011). These authors have suggested that failure to model group-level effects may overestimate standard errors when testing Level-1 relationships and thus introduce Type II error. The loss of power may be substantial when ICC(1) scores are greater than .15 and/or design effects are substantially larger than 1.0 (Bliese & Hanges, 2004; Kline, 2011). In our data, ICC(1) = .03 and the design effect = 1.03 for leadership effectiveness ratings. For promotability ratings, ICC(1) = .16 and the design effect = 1.16. As the ICC for promotability exceeds the cut-off level suggesting standard errors may be overestimated due to nonindependence in supervisor ratings, we tested our hypothesized model incorporating “supervisor” as a Level 2 clustering variable. We note that the results are substantively the same when testing the hypotheses with or without modeling supervisor as a Level 2 clustering variable.

We ran two separate analyses to test our six hypotheses. Hypotheses 1– 3, 5, and 6 were tested simultaneously with multilevel structural equation modeling (SEM) in MPLUS. SEM is appropriate for testing models with multiple mediators and/or outcome variables, as it is a full information estimation technique that accounts for the relationships among all the variables (Kelloway, 2015). The MPLUS program allows testing structural models at the individual-level while specifying a cluster variable (i.e., supervisor) at Level 2. Because existing research provides little guidance for incorporating three-way interactions within SEM (e.g., Cortina, Chen,

 

 

SCOTT E. SEIBERT ET AL. 379

& Dunlap, 2001), we used the PROCESS macro for SPSS (Hayes, 2012) to test the conditional indirect effect of participation in formal development programs to the two outcomes via leadership self-efficacy as specified in Hypothesis 4.

Multilevel SEM Analysis. For this analysis, we used MLR estima- tion, as it is more robust to violations of multivariate normality (Kel- loway, 2015), and conducted a two-level analysis specifying supervisor as the clustering variable. All paths were estimated within groups (i.e., at the individual level). So that the fit of the structural model would not be confounded with the fit of the measurement model, we used single-score indicators to measure the latent variables (Anderson & Gerbing, 1988). In doing so, the path from the latent variable to the indicator was set equal to one and appropriate adjustments for measurement error were entered (Williams & Hazer, 1986). In addition, supervisors’ ratings of leadership effectiveness and promotability were allowed to correlate. We compared the hypothesized mediated model to a partially mediated model, as it is theoretically plausible that relationships may be direct (unmediated) or mediated by constructs not included in the model (Kelloway, 2015). The Satorra-Bentler Scaled Chi-square difference test was used to determine the best-fitting model, as the two models are nested.

Our hypothesized mediated model fit the data very well (χ 2[19, N = 235] = 36.40, p < .05; CFI = .96; RMSEA = .06; SRMR = .04). We then compared this model to the partially mediated model such that, in addition to our hypothesized paths, all the direct paths from the developmental experience variables to leadership effectiveness and promotability ratings were estimated. The chi-square difference test suggested that the partially mediated model did not fit significantly better than the mediated model (�χ 2[6, N = 235] = −6.18, p < .05). We thus retained the hypothesized model as the most parsimonious best-fitting model (see Figure 1) to test Hypotheses 1–3, 5, and 6.

Hypotheses 1–3 predicted that leadership self-efficacy would medi- ate the relationships between the three developmental experiences and two leadership outcomes. With respect to Hypothesis 1, the indirect effect from formal development programs to leadership effectiveness (β = .02, p > .05) and to promotability (β = .03, p > .05) through leadership self-efficacy failed to reach significance. Examination of the path estimates (see Figure 1) shows that leadership self-efficacy had a sta- tistically significant relationship with leadership effectiveness (β = .22, p < .01) and promotability (β = .28, p < .01), but the path estimate from formal development programs to leadership self-efficacy was not statisti- cally significant (β = .10, p > .05). Thus, Hypothesis 1 is not supported. Hypothesis 2, however, was fully supported: The positive indirect path estimates from job challenges to (a) leadership effectiveness (β = .05, p

 

 

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< .05) and (b) promotability (β = .06, p < .05) via leadership self-efficacy were statistically significant. Finally, Hypothesis 3 was not supported: The indirect effects from developmental supervision to leadership effective- ness or promotability, via self-efficacy (β = .01 and .01, respectively, p > .05) failed to reach significance. Examination of Figure 1 shows the path estimate from developmental supervision to leadership-self-efficacy was not statistically significant (β = .03, p > .05).

Hypotheses 5 and 6 predicted that managers’ mentor network would mediate the relationships between developmental job challenges (Hy- pothesis 5) and both outcomes, and between developmental supervision (Hypothesis 6) and both outcomes. Although both developmental job challenges and developmental supervision are significantly related to the size and quality of the mentor network (β = .23, p < .01 and β = .20, p < .05, respectively), the parameter estimate from the mentor network to leadership effectiveness was not statistically significant (β = .11, p > .05), rendering the indirect effect for both nonsignificant (β = .03, p > .05 and β = .02, p > .05, respectively). Thus, Hypothesis 5a and Hypothesis 6a are not supported. With respect to Hypothesis 5b, developmental job challenges had a significant indirect effect on promotability via mentor network (β = .04, p < .05), supporting Hypothesis 5b. Finally, the indirect effect of developmental supervision to promotability ratings via mentor network did not quite reach statistical significance (β = .03, p = .10). Thus, Hypothesis 6b was not supported.

Finally, consistent with recommendations by Spector and Brannick (2011), we reran our hypothesized model without the control variable paths estimated to rule out the possibility that our results can be at- tributed to the control variables. In this “no control variables” model, the significance of the indirect effects are consistent with the results when including control variables, with the one exception being that the indi- rect effect from developmental supervision to promotability via mentor network (H6b) was significant in this model (β = .04, p < .05). Without the control variable paths estimated, our model explains 24% of the vari- ance in leadership self-efficacy, 11% in mentor network, 7% in ratings of leadership effectiveness, and 15% in ratings of promotability.

Test of conditional indirect effects. Hypothesis 4 predicted that the in- direct effect of formal development programs on (a) leadership effective- ness and (b) promotability via leadership self-efficacy would be stronger at low levels of both developmental job challenges and developmental supervision. As noted above, leadership self-efficacy significantly related to both outcomes, suggesting mediation is possible (see Figure 1). A moderated regression analysis also found that the three-way interaction significantly predicted leadership self-efficacy (b = .17, p < .05). To test the indirect effects, we used the PROCESS macro for SPSS (Hayes,

 

 

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2012; Preacher & Hayes, 2008). We used 5,000 resampling iterations to generate 95% bias corrected bootstrap confidence intervals around the conditional indirect effects via leadership self-efficacy, with manager’s motivation to lead, age, and nomination to the high potential program included as covariates. The results of the analysis are summarized in Table 2.

Supporting Hypothesis 4a, the indirect effect of formal development programs on leadership effectiveness via leadership self-efficacy was sig- nificant when there were low levels of both developmental job challenges and developmental supervision (B = .06, SE = .04, 95% CI [.0050, .1517]). Likewise, in support of Hypothesis 4b, there was a signifi- cant indirect effect of formal development programs on promotability via leadership self-efficacy when there were low levels of both devel- opmental job challenges and supervision (B = .13, SE = .07, 95% CI [.0125, .2869]). Unexpectedly, there was also a significant indirect ef- fect of formal development on leadership effectiveness (B = .03, SE = .02, 95% CI [.0036, .0847]) and promotability (B = .06, SE = .04, 95% CI [.0097, .1589]) via leadership self-efficacy, at high levels of both developmental job challenges and developmental supervi- sion. We revisit this finding in the Discussion.

We also probed for the nature of the three-way interaction effect on leadership self-efficacy by plotting the simple slopes for the effects of par- ticipation in formal developmental programs on leadership self-efficacy at low (1 SD below the mean) and high (1 SD above the mean) lev- els of developmental job challenge, separately, for low and high lev- els of developmental supervision (Aiken & West, 1991). As shown in Figure 2, participation in formal developmental programs positively re- lated to leadership self-efficacy (β = .25, p < .01) at low levels of both developmental job challenge and developmental supervision.1 Taken to- gether, these results support Hypotheses 4a and 4b. In addition, formal development was positively related to leadership self-efficacy at high levels of both developmental job challenge and developmental supervi- sion (β = .13, p < .05).

In sum, we found support for Hypotheses 2a, 2b, 4a, 4b, and 5b. Hypothesis 6b was also supported in the model when control variables were not included.

1In order to examine the relative strength of each developmental experience on the outcome variables, we calculated the conditional indirect effect for each developmental experience when the other two developmental experiences are low, the condition in which each source of development has its strongest effect. Our results show that developmental job challenges has the strongest conditional indirect effect, followed by formal development programs. Full results are available from the first author.

 

 

382 PERSONNEL PSYCHOLOGY

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Leadership Self-Efficacy.

Discussion

Fifteen years ago, Day (2000) argued that a full understanding of the way managers become effective leaders would require theoretical atten- tion to both human and social capital. To our knowledge, we offer the first empirical test of a model that integrates multiple sources of devel- opment with both individual and interpersonal mediating processes to explain how developmental experiences relate to leader effectiveness and promotability. Consistent with social cognitive and social capital theories, we found that developmental job challenges relate to leadership effec- tiveness and promotability indirectly through leadership self-efficacy and one’s mentor network. Our findings also support the idea that leader- ship self-efficacy mediates the relationship between formal development programs and leadership capacity, but only when leaders experience ei- ther low levels of both developmental job challenges and developmen- tal supervision, or high levels of both. Taken together, our results con- tribute to our theoretical understanding of how and why developmental experiences nurture the development of more effective and promotable leaders.

Theoretical Implications

Our study makes several important contributions to the literature on leadership development. First, our work extends existing understanding

 

 

384 PERSONNEL PSYCHOLOGY

of the processes and outcomes associated with leadership development activity. As we noted earlier, the underlying theoretical mechanisms that explain how developmental practices and experiences relate to leader effectiveness and promotability are not well understood. Based on social cognitive and social capital theories, we proposed that developmental experiences supply psychological (i.e., confidence in one’s leadership capabilities) and social (a network of mentors who offer support and career advice) resources that enable leaders to be more effective in their roles. Our results demonstrate that both mediating processes are important, although the results for leadership self-efficacy were more robust.

Specifically, both developmental job challenges and the conditional ef- fect of formal development programs (when both developmental job chal- lenges and developmental supervision were low or both were high) were mediated through leadership self-efficacy. One previous study (Aryee & Chu, 2012) has linked challenging job experiences to job self-efficacy and task performance, but that study was with nonsupervisory employees. Our study extends the social-cognitive perspective to the domain of leader- ship development and effectiveness. Our results suggest that challenging on-the-job experiences enhance leadership capacity partly by building leaders’ belief in their ability to perform successfully in a leadership role. In addition, self-efficacy acts as a motivational mechanism, enhancing effort, persistence in the face of obstacles, and the willingness to take on new and more challenging leadership tasks and responsibilities. Lead- ership self-efficacy is a construct that has taken on growing importance in the literature, and our work shows that it is an important mechanism in the leadership development process linked to specific development experiences.

Our findings regarding the mentor network as a mediating mechanism were less robust than we expected. Although both developmental job chal- lenges and developmental supervision were related to the quality of one’s mentor network, only the indirect effect from job challenges through men- tor network to promotability reached statistical significance. Nevertheless, these findings broaden our theoretical understanding of the interpersonal processes that underlie leadership development. Specifically, our results suggest that challenging job assignments and developmental supervisors enable leaders to develop higher quality networks of supportive mentors within the organization. A network of mentors can provide visibility and exposure that enhances the leader’s potential for promotion into positions of greater leadership responsibility. Even though the size of the indirect effect was small, the cumulative effects of this network advantage can be substantively important over time, leading to more promotions, higher salary, and greater career success (Seibert et al., 2001). At the same time, our results extend the growing literature on social networks and

 

 

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leadership (Kilduff & Krackhardt, 2008). Network properties have been related to a number of processes central to effective leadership, including the accumulation of power and influence (e.g., Brass & Burkhardt, 1992, 1993), a positive reputation for leadership (Balkundi et al., 2011; Kilduff & Krackhardt, 1994; Mehra et al., 2006), and the ability to establish effec- tive working relationships with subordinates (Sparrowe & Liden, 2005; Venkataramani et al., 2010). Much less attention has been devoted to the antecedents of social networks in organizations (Kilduff & Krackhardt, 2008). Although our results are based on cross-sectional data, they suggest that developmental experiences may shape one’s social network, helping nascent leaders establish relationships beyond their immediate work group to gain support in the larger organization.

A second way we contribute to the leadership development literature is by examining the three sources of developmental experience—formal development, job challenges, and developmental supervision—together in a single model. Although each of these developmental experiences has been previously examined separately, our results suggest it is nec- essary to examine them together to have a correctly specified estimate of their effects. Most notably, formal development positively related to both leadership effectiveness and promotability indirectly via leadership self-efficacy when the manager experienced low levels of on-the-job de- velopment. This result is consistent with the notion that learning that takes place either within the context of one’s work role or from one’s immedi- ate supervisor may nullify the effects of learning through formal methods; yet, in the absence of these informal learning experiences, participating in formal development programs can positively contribute to leadership capacity by raising one’s self-efficacy beliefs.

Our unexpected finding that participation in formal development pro- grams related positively to leadership capacity indirectly via leadership self-efficacy when leaders also experienced high levels of both devel- opmental job challenges and developmental supervision suggests that a synergistic effect may occur when high levels of all three sources of de- velopment are experienced together. That is, formal training may also be beneficial when coupled with both high job challenges and a developmen- tal supervisor. Presumably, this is because each developmental experience provides unique types of information, feedback, or support that enhances the learning one derives from the other two sources of development. For example, formal training provides information and conceptual tools one can use to generate more varied and more effective behavioral pat- terns, whereas developmental job challenges provide the opportunity to practice these behaviors and developmental supervision provides encour- agement to experiment and feedback to better reflect upon and learn from those experiences. Indeed, accurate feedback about the cause and effect

 

 

386 PERSONNEL PSYCHOLOGY

relationship while dealing with challenging work assignments increases the probability of self-correction and is likely to trigger a positive efficacy– leadership effectiveness spiral (Lindsley, Brass & Thomas, 1995). Taken together, our synergistic interaction findings suggest that, although any isolated leadership development activities can be effective, the use of these three leadership development activities together simultaneously is likely to be most effective.

A third contribution to the leadership development literature is our finding that developmental job challenge has a positive indirect effect on leadership effectiveness (through leadership self-efficacy). Previous researchers have shown developmental challenge to be related to self- perceived learning (McCauley et al., 1994), supervisor-rated managerial competency, or skill development (DeRue & Wellman, 2009; Dragoni et al., 2009), but these outcomes are leadership skills that are thought to relate to leadership effectiveness, not leadership effectiveness itself. We are aware of no research that links the experience of developmental job challenge to supervisors’ ratings of leadership effectiveness in one’s current leadership role, as we do here. Thus, our findings extend the work on developmental job challenge to arguably the most important outcomes in the leadership literature.

Practical Implications

Our results have important implications for leadership programs in or- ganizations and individuals seeking to become leaders. In particular, the results suggest that combinations or bundles of developmental experiences can have supplemental and synergistic effects. Formal training, challeng- ing job responsibilities, and developmental supervision together will have the greatest potential consequences for developing leaders. However, if few informal development experiences are available, then formal training by itself can build new leaders’ confidence and prepare them for future challenges.

On their own, informal, on-the-job development experiences are more important than formal development programs, such as training classes. Through developmental job challenges, managers may build their lead- ership self-efficacy and expand their mentor network, all of which con- tribute to supervisors’ assessments of their promotability. Job challenges include such responsibilities as executing a new strategy within one’s work unit and dealing with difficult personnel problems. Organizations may thus want to incorporate such responsibilities into a promising man- ager’s job duties, and managers should seek them out even if they are not offered. Further, when organizations seek to fill leadership positions, they should consider the way a particular assignment will help to develop the

 

 

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leadership capacity of the individual assigned. The other informal develop- mental experience examined here, developmental supervision, positively related to the manager’s network of supportive relationships. Thus, organi- zations should also train their supervisors to engage in role modeling (e.g., setting a positive example with their own leader behavior), and in coaching behavior (e.g., challenging thinking and assumptions, driving results, and creating accountability for goals). To truly embed these activities, it may be crucial to make them part of senior managers’ key performance indi- cators. Likewise, individuals interested in becoming leaders should seek out developmental supervision from their managers. Initiating develop- mental discussions with their supervisors may also help junior managers establish mentor–protégé relationships with others more senior in the organization.

Knowing key senior managers and having interpersonal sources of support can help leaders have influence and impact in the organization (Balkundi et al., 2011; Kilduff & Krackhardt, 1994; Mehra et al., 2006). It is therefore important for lower-level managers to build a network of senior managers within the organization who are willing to mentor them. Our results suggest that developmental job challenges and developmen- tal supervisors are likely to help leaders build this type of social capital. Although the formal development programs that we examined were not associated with better mentor networks, programs that incorporate senior managers as trainers may facilitate network development in a way similar to organizational socialization tactics that incorporate this serial feature (Van Maanen & Schein, 1979). In addition, this type of social capital is likely to be “sticky” in the sense that it may bind employees to the organization because it does not easily transfer to a new organization. Thus, the company is likely to benefit from this kind of human resource development investment in three ways: first, through the improved lead- ership potential of its employees, second through greater retention of the employees in which they have made investments, and third by creating a more effective network of senior manager and mentors throughout the organization.

Strengths, Limitations, and Future Research

A strength of our study is that we collected data from two sources, focal managers and their immediate supervisors. This helped minimize common source bias as an explanation of the relationship between the mediators and outcomes. In addition, the use of theoretically grounded constructs allowed us to better distinguish between the manager’s leader- ship capabilities (e.g., self-rated leadership self-efficacy) and performance in the leadership role (e.g., supervisor-rated leadership effectiveness).

 

 

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Collecting data from a single organization also helped us control for con- founding factors that may be due to organizational or industry differences, such as differing promotion and retention rates or the organization’s talent pool. A final strength of the study is that we developed and validated a shorter, 10-item scale to measure developmental job challenges that can be used in future academic research.

However, these strengths should be considered in light of some lim- itations. One limitation is potential common method bias and an inabil- ity to draw strict causal conclusions. These problems arise because we collected the data to measure the developmental experiences, leadership self-efficacy, and mentor network from the same source at the same time. To minimize these concerns, we asked respondents to report the extent to which they engaged in the developmental experiences in the past but to re- port their current levels of self-efficacy and their current mentor network, although we recognize the current network may have been established earlier in time. To more directly address the causality issue, we tested an SEM model switching the roles of the developmental experiences and our hypothesized mediators, such that leadership self-efficacy and mentor network predicted the three developmental experiences, which in turn predicted the two leader outcomes. This model had poor fit (χ 2[19, N = 235] = 85.16, p < .05; CFI = .85; RMSEA = .11; SRMR = .08) and did not support the proposition that developmental experiences mediate between leadership self-efficacy (mentor network) and leadership effectiveness and promotability because none of the parameter estimates among the developmental experiences and the leadership outcomes were statistically significant. Although this does not rule out the possibility that mentor networks and leadership self-efficacy may lead to more partic- ipation in developmental experiences, the results of this reverse-causal model do support our proposition that self-efficacy and mentor network are the more proximal variables predicting leadership effectiveness and promotability. Future research may consider using a longitudinal research design to examine changes in leadership skills and changes in leader ef- fectiveness. We also tested for the effect of common method variance and found little evidence that this should be considered a major concern for our study. Finally, we also included two control variables to test for a ma- jor alternative explanation that the initial ability or leadership motivation of the manager explained our effects and not the development practices. We found support for our hypothesized model even after controlling for perceived potential of the manager, as indicated by his/her nomination to the high potential program and his/her motivation to take on leadership responsibilities.

A second limitation is that the focus only on first-line managers in a single retail organization may mean that our results may not generalize

 

 

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to other management levels or firms. Thus, future research should examine these relationships using samples from different sectors. A third limitation is that we did not measure whether, or to what ex- tent, the formal development programs included the four self-efficacy enhancing processes—enactive mastery, role-modeling, social persua- sion, and emotions management—identified by social cognitive theory. Nor did our measure focus exclusively on leadership training, but in- stead, it captured a range of developmental programs including tech- nical skills training and educational courses. Both of these measure- ment deficiencies may explain why Hypothesis 1 was not supported. We encourage future research to examine the social cognitive explanation for why formal leadership development should be related to leadership self-efficacy by focusing more specifically on leadership training and to measure the self-efficacy enhancing processes of the training program. However, it is noteworthy that, in combination with the two other de- velopment experiences, formal development programs positively related to leadership self-efficacy and indirectly to leadership effectiveness and promotability.

Finally, although not examined here, there may be moderating factors that condition the beneficial (or even create detrimental) effects of job challenges on outcomes (e.g., Courtright et al., 2014; Dong et al., 2014). For example, it is possible that successfully meeting (or not meeting) developmental challenges is one moderator that will determine whether exposure to job challenges nurtures or hinders the development of lead- ership self-efficacy. Indeed, leaders who do not successfully navigate the developmental challenges they are exposed to may feel less confident in their ability to deal with leadership challenges. Thus, exploring the mod- erating role of successful handling of job challenges would be one way for future researchers to extend our findings.

Conclusion

Our study answers calls for more theoretically integrative research on the process of building managers’ leadership capacity (Avolio, 2007). Our model helps to establish a stronger evidence-based understanding of the types of developmental experiences that relate to leadership effectiveness and promotability and uncovers two mediating mechanisms—leadership self-efficacy and the size and quality of one’s mentor network—to explain these relationships. We hope to forge stronger links between the leadership development, social cognitive and social capital literatures, and provide human resource practitioners with direction on ways to cultivate leadership talent in their organizations.

 

 

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APPENDIX

Job Challenge Scale Validity Study

We collected data through an Australian commercial national panel of survey volunteers to assess the validity of our developmental job chal- lenges scale. Past studies have used similar firms to recruit participants (e.g., Long, Bendersky, & Morrill, 2011; Montes & Zweig, 2009). The firm sent solicitations calling for panelists who were 18 years of age or over and currently employed in supervisory positions. Two hundred and twenty-seven panelists clicked into the survey. We screened out 25 respondents who left the survey without completing any items. We re- moved an additional 35 respondents with a clear pattern of insufficient effort responding (e.g., selected 5 for all items), leaving a usable sam- ple of 167 (73% response rate). Sixty-five percent of respondents were male, and average age was 36.6 years (SD = 10.96 years). Our survey included the job challenge profile (McCauley et al., 1999), and other study constructs (leadership self-efficacy, formal development programs, devel- opmental supervision, and motivation to lead). Table A1 lists the items and Table A2 shows the results from this validity study. Both the 10- and 8-item

 

 

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versions of the job challenge scale developed for this study are strongly correlated with McCauley et al.’s (1999) job challenge profile scale (r = .71, p < .01 and r = .69, p < .01, respectively). In addition, all three scales show a similar pattern of correlation with the other variables in the study.

TABLE A1 Developmental Job Challenges Scale Items

Item 1. I have been required to work with a product, market, or technology I have not worked with before.

2. I have been required to use technical or functional skills for which I lacked previous training or experience.

3. I was made responsible for executing a significant change, such as a new strategy, a reorganization, or a turn-around, in an organizational unit

4. I have been made responsible for instituting new policies, procedures, systems, or technology in an organizational unit.

5. I have had to handle significant managerial problems with my team members for the first time.

6. I have had to deal with significant performance problems among key members of my staff.

7. I have been given significant managerial responsibility. 8. I have been given direct responsibility for an entire project, product, service, function, or other identifiable unit of this magnitude.

9. I have had to exert influence over peers or superiors over whom I have no direct authority in order to achieve my work objectives.

10. I have had to manage relations with external constituencies, such as clients, customers, suppliers, or government agencies.

Note. Items in boldface were dropped from the scale used in this study.

TABLE A2 Means, Standard Deviations, Correlations, and Reliabilities for Validity Study

Variables

Mean SD 1 2 3 4 5 6 7

1. Developmental job challenges (10-item)

3.30 .69 (.87)

2. Developmental job challenges (8-item)

3.29 .69 .98∗ ∗ (.83)

3. McCauley et al.’s (1999) job challenge profile

3.11 .80 .71∗ ∗ .69∗ ∗ (.98)

4. Leadership self-efficacy 3.67 .70 .32∗ ∗ .31∗ ∗ .35∗ ∗ (.91) 5. Developmental supervision 3.57 .74 .19∗ .17∗ .22∗ ∗ .45∗ ∗ (.93) 6. Formal development

programs 3.18 1.01 .44∗ ∗ .46∗ ∗ .60∗ ∗ .24∗ ∗ .50∗ ∗ (.90)

7. Motivation to lead 3.53 .63 .44∗ ∗ .44∗ ∗ .37∗ ∗ .42∗ ∗ .54∗ ∗ .51∗ ∗ (.64)

Note. n = 167. Alpha reliabilities are given in parentheses. ∗∗p < .01.

 

 

Formal paper about a Nursing theory

GUIDELINES: Each STUDENT will hand in one formal paper about a nursing theory. The paper is to be a five to six (5-6) pages total (double-spaced, 12 font, 1-inch margins).

Follow APA guidelines for a cover sheet, headers, pagination, references, etc.

Use APA format and label each section using the evaluation outline below.

The criteria guidelines below will evaluate your paper.

Components of the Paper and possible points

 

SECTIONPOSSIBLE POINTS
Introduction

Identification of theorist including a brief background of the theorist (accomplishments, career, accolades, research efforts)

5
Analysis of basic components/concepts and major relationships in the theory.

 

· Briefly discuss the theory’s core concepts.

· Use a secondary source like your textbook that covers the selected nursing theory, you must have at least 3 references from nursing literature (only one from a non-article source like a secondary source/text) to support your discussion in this section.

5
Relevance

· Personal relevance if the authors described (connect the theorist to the theory)

· Relevance to healthcare and the client discussed. (connect the theory to healthcare today)

· Application to research and/or practice provided (connect the theory to current research/practice)

· Use at least two peer-reviewed/research articles that detail the nursing theory being applied in clinical practice/research and summarize key findings of both articles including results and implications for future practice.

 

10
Summary

· Include theory strengths and limitation in the summary

5
Format

· Precise APA style, headers, and professional writing

5
Total30

Key things you have learned about Student affairs

 

This paper should summarize the key things you have learned about student affairs, specifically answering two (2) questions: What is student affairs and is its existence a necessity within higher education. The paper should be 3 – 5 pages (double spaced). what is student affairs and is it still viable/necessary on college campuses today”?

 

 

Please discuss inside the paper· Academic Advising

· Career Service

· Enrollment Management

· Counseling Service

· Student Conduct

· Multicultural Affairs and Support Services & First Year Experience

· Residence Life & Programming in Student Life

· Greek Life & Campus Recreation

· Student Health Service

 

Personality and Paraphilic Disorders

Assignment: Controversy Associated with Personality and Paraphilic Disorders. Between 10% and 20% of the population experience personality disorders. They are difficult to treat as individuals with personality disorders are less likely to seek help than individuals with other mental health disorders. Treatment can be challenging as they do not see their symptoms as painful to themselves or others.

 

Photo Credit: Joe Houghton – www.joehoughtonphotography.ie / Moment / Getty Images

Paraphilic disorders are far more common in men than in women, and generally quite chronic, lasting at least two years. Treatment of these disorders usually involves both psychotherapeutic and pharmacologic treatments.

In this Assignment, you will explore personality and paraphilic disorders in greater detail. You will research potentially controversial elements of the diagnosis and/or treatment and explain ethical and legal considerations when working with these disorders.

To Prepare

· Review this week’s Learning Resources and consider the insights they provide on assessing, diagnosing, and treating personality and paraphilic disorders.

· Select a specific personality or paraphilic disorder from the DSM-5-TR to use for this Assignment.

· Use the Walden Library to investigate your chosen disorder further, including controversial aspects of the disorder, maintaining the therapeutic relationship, and ethical and legal considerations.

The Assignment

In 2–3 pages:

· Explain the controversy that surrounds your selected disorder.

· Explain your professional beliefs about this disorder, supporting your rationale with at least three scholarly references from the literature.

· Explain strategies for maintaining the therapeutic relationship with a patient that may present with this disorder.

· Finally, explain ethical and legal considerations related to this disorder that you need to bring to your practice and why they are important.