RESEARCH ARTICLE Effects of a Lag Schedule with Progressive Time Delay on Sign Mand Variability in a Boy with Autism

Bryant C. Silbaugh1 & Terry S. Falcomata2

Published online: 18 September 2018 # Association for Behavior Analysis International 2018

Abstract For some children with autism, mand training can produce highly repetitive manding unless the environment is arranged in a manner that promotes mand variability.

Prior research demonstrated that mand training using a lag schedule and progressive time delay increased variability in vocal manding in children with autism. Whether lag schedules have similar effects on sign mand topographies is unknown.

The current study evaluated the effects of mand training with a Lag 1 schedule of reinforcement and progressive time delay (TD) on topographical variability and the development of a sign mand response class hierarchy in a boy with autism. The results suggest independent use of all sign mand topographies occurred, a mand response class hierarchy was developed, and topographically variant sign manding increased under the Lag 1 + TD schedule compared to a Lag 0 schedule of reinforcement. Implications for practitioners, limitations, and directions for future research are discussed.

Keywords Lag schedule . Mand . Operant variability . Response class hierarchy . Time delay

During mand training for individuals with language delays or deficits (e.g., autism), a response such as saying “juice” is taught by presenting a relevant establishing operation (EO; e.g., giving access to salty popcorn and withholding juice) and using prompting, rapid prompt fading, and differential reinforcement to transfer control over the target response from the prompt to the EO and contingent access to juice (Sundberg & Partington, 1998; see Shafer, 1994, and Wallace, 2007, for reviews of common procedures and concepts). However, un- less the environment is arranged to support a variety of re- quests from the speaker, procedures commonly used in mand training for some children with autism can produce invariant (i.e., repetitive) manding (e.g., Carr & Kologinsky, 1983; Silbaugh, Falcomata, & Ferguson, 2017).

Behavioral variability is critical for contacting reinforce- ment in a changing environment (e.g., Sidman, 1960).

Invariant manding may disadvantage a speaker when rein- forcement mediated by a listener requires saying something differently by either (a) failing to obtain reinforcement or (b) exhibiting resurgence of challenging behavior as the listener withholds reinforcement for invariant responding (e.g., Volkert, Lerman, Call, & Trosclair-Lasserre, 2009). At least two general types of invariant manding are com- monly observed.

First, invariance may occur across mands, such as when a child repeatedly emits mands for only one of multiple rein- forcers concurrently available. For example, in the presence of playdoh, juice, and a book, invariant manding may take the form of the child repeatedly asking only for the playdoh across trials. Alternatively, invariance may occur within a given mand response class for a single reinforcer. For example, a child may invariantly emit the vocal mand topography “playdoh” across repeated instances of taking turns playing with playdoh with a peer.

For some children, topographically invariant instances of a mand emitted over time may be due to extinction of alternative mand topographies during training or to a lack of sufficient response exemplars incorporated into training (Lee, Sturmey, & Fields, 2007; Rodriguez & Thompson, 2015). For example, to establish a topographically variant mand response class, instead of only teaching the child to say “playdoh,” the child may benefit from being simulta- neously or sequentially taught to say “want,” “toy,” or

* Bryant C. Silbaugh bryant.silbaugh@utsa.edu

1 Department of Interdisciplinary Learning and Teaching, College of Education and Human Development, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA

2 Department of Special Education, University of Texas at Austin, Austin, TX, USA

Behavior Analysis in Practice (2019) 12:124–132 https://doi.org/10.1007/s40617-018-00273-x

“playdoh” under the control of the EO for access to playdoh, with contingencies that support variation across instances of turn taking. Wolfe, Slocum, and Kunnavatana (2014) proposed general guidelines for increasing operant variability in children with autism, but specific procedures and guidelines for reinforcing mand variability in practice requires more research.

Multiple studies have evaluated procedures that increase variability or novelty across concurrently available reinforcers (i.e., across mands) during mand training for individuals with intellectual disability (e.g., Duker & van Lent, 1991) or autism (Bernstein & Sturmey, 2008; Betz, Higbee, Kelley, Sellers, & Pollard, 2011; Brodhead, Higbee, Gerencser, & Akers, 2016; Carr & Kologinsky, 1983; Drasgow, Martin, Chezan, Wolfe, & Halle, 2015; Sellers, Kelley, Higbee, & Wolfe, 2015). For example, Bernstein and Sturmey (2008) compared the effects of continuous and intermittent schedules of reinforcement on the emission of alternative mands by two children with autism and vocal manding repertories. A single high-rate mand was placed on an intermittent schedule of reinforcement (e.g., FR10 or FR25), whereas all other mands were reinforced on an FR1 schedule in the presence of four different reinforcers for both children.

Relatively higher total counts of alternative mands emitted within sessions were observed when the inter- mittent schedules were in effect. Although prior research dem- onstrated procedures that can be used to predict and control topographical variation across mands, other procedures may be needed to establish a topographically variant mand re- sponse class, which is one focus of the current study.

Operant variability can be brought under discriminative control and reinforced (Page & Neuringer, 1985). Lag sched- ules of reinforcement can increase operant variability by de- livering reinforcement for a response if it differs from n prior instances, with n equal to the value of the lag. For example, under a Lag 3 schedule, a response is reinforced if it differs from the preceding three responses (e.g., Susa & Schlinger, 2012). Potential advantages of using lag schedules over other procedures that increase mand variability is that they may facilitate generalization through the reinforcement of multiple response exemplars (Silbaugh et al., 2017) and may mitigate challenging behavior when treatment involves reinforcing mand variability (e.g., Adami, Falcomata, Muething, & Hoffman, 2017). A growing body of applied research has demonstrated that lag schedules reinforce variability in verbal behavior for individuals with developmental disorders (Wolfe et al., 2014), and three studies have shown lag schedules can increase variability in manding.

Brodhead et al. (2016) combined script training with lag schedules of reinforcement to bring variability in manding for edible items under discriminative control for three children with autism. Sessions during the treatment evaluation includ- ed three different concurrently available edible reinforcers, which were alternated across sessions based on the results of

preference assessments. During baseline, all mands were rein- forced on an FR1 schedule of reinforcement. Following base- line, script training was used to teach participants to indepen- dently use new mand frames, such as “May I have [reinforc- er]?” and “I would like [reinforcer].” Also during script train- ing, discriminative control over mand frame variability was established by alternating conditions with two different col- ored place mats.

A green place mat was correlated with rein- forcement for varying mand frames under a Lag 2 or Lag 3 schedule, and a red place mat was correlated with reinforce- ment for repeating the mand frame (i.e., “I want [reinforcer].”) that existed in each participant’s repertoire before treatment. Discriminated mand frame variability was the dependent var- iable and the dependent measure was the number of different mand frames emitted per session. The results showed that participants emitted relatively more different mand frames per session under a lag schedule.

However, the dependent measure may have been insensitive to the var- iant dimension of manding because it differed from the response dimension on which reinforcement was contin- gent under the lag schedule (De Souza Barba, 2012a, b). That is, reinforcement was not contingent on the number of different mand frames emitted within session, but rather mand frames that differed from n different mand frames emitted within session.

Additionally, the use of multiple types of reinforcers in a concurrent-operants ar- rangement does not allow for the assessment of varia- tions in functionally equivalent manding (i.e., multiple topographies or stimulus selections maintained by a sin- gle reinforcer).

Adami et al. (2017) evaluated the effects of a Lag 1 sched- ule of reinforcement combined with functional communica- tion training (FCT; Carr & Durand, 1985) on varied nonvocal manding and challenging behavior in two males with autism diagnoses. The authors used reversal designs consisting of three conditions (i.e., baseline, FCT/Lag 0, and FCT/Lag 1), 5-min sessions, and 30-s reinforcer durations for target re- sponses. During baseline, no mand modality equipment was available and challenging behavior produced the maintaining consequence identified in a prior functional analysis on a con- tinuous schedule of reinforcement. During FCT/Lag 0, three different mand modalities were available (i.e.,

a card to ex- change, a microswitch, and a tablet) and the reinforcer was delivered contingent on the independent selection of any mand modality. The FCT/Lag 1 condition was similar except that the reinforcer was contingent on instances of manding in which the participant selected a mand modality that differed from the last mand modality selected within the session.

For example, if on Trial 3 the participant used the tablet to mand, then on Trial 4 he was required to mand by pressing the mi- croswitch or exchanging the card to produce the reinforcer. The results indicated that FCT with lag schedules replaced challenging behavior with manding and that the addition of

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the Lag 1 schedule of reinforcement increased mand variability across modalities.

Silbaugh et al. (2017) investigated the effects of lag sched- ules on mand variability in two young children with autism. For each participant, a mand topography invariance assess- ment was used to identify two mands emitted invariantly across trials and to identify two new topographies to target for each mand during the treatment evaluation.

A multiple- baseline design across mands with embedded withdrawal was used to evaluate the effects of a Lag 1 schedule of reinforce- ment with progressive time delay (TD) on topographical vocal mand variability. Sessions were 5 min in duration. During the Lag 0 condition (i.e., baseline), 25 s of reinforcement was delivered contingent on any emitted vocal mand topography. During the Lag 1 condition, 25 s of reinforcement was deliv- ered contingent on independent or prompted variant vocal mand topographies. A vocal mand topography was variant if it differed from the immediately preceding vocal mand topog- raphy emitted within the session.

Specifically, if the partici- pant did not emit an independent variant vocal mand topog- raphy within 2 s of the EO (i.e., the onset of a trial), the experimenter delivered an echoic prompt for a target variant vocal mand topography. If the participant did not emit a var- iant vocal mand topography for six consecutive trials under a given TD (e.g., 2 s), the TD was increased by 2 s on the seventh trial. Mand variability training increased variability in multiple functionally equivalent vocal mand topographies for both participants and all four mands.

The results of a post hoc analysis of relative latencies showed that vocal mand to- pographies were emitted in a temporally predictably order, suggesting that mand response class hierarchies (Baer, 1982) were modified by incorporation of new mand topographies during treatment. The purpose of the current study was to extend Silbaugh et al. (2017) by (a) evaluating the effects of a Lag 1 schedule of positive reinforcement combined with a progressive TD on the acquisition and variability of multiple sign mand topographies in a boy with autism and (b) analyz- ing relative response latencies to assess mand response class structure formation.

Method

Participants and Setting

Allen was a 5-year-old boy with a diagnosis of autism who attended a special day school for children with developmental disabilities and received social and academic instruction using applied behavior analysis. Based on information collected during observation and interviews with caregivers and teachers, Allen was selected for participation in this study for three reasons. First, he demonstrated a largely deficient verbal repertoire, consisting mostly of a few spontaneous

vocal mands (e.g., for a preferred stuffed animal) and physi- cally guiding adults by hand to request reinforcers. Second, he demonstrated good fine motor skills and generalized gross motor imitation of actions without objects (e.g., clapping) during an informal clinical assessment by the first author. Third, his caregivers and teachers indicated that most prior attempts at expanding Allen’s verbal repertoire had been un- successful at establishing mands used spontaneously and con- sistently.

Per their report, he had not received prior instruction in sign mand training but had received vocal-, picture ex- change-, and tablet-based instruction based on Skinner’s anal- ysis of verbal behavior (Skinner, 1957). The study was con- ducted in the school kitchen, which contained common kitch- en appliances, tables, chairs, a piano, and standard research equipment (e.g., toys, camera), shortly after lunch hours.

Response Definitions and Measurement

The primary dependent variables were (a) variant and (b) in- variant manding. We measured independent variant sign mand topographies, independent invariant sign mand topographies, and prompted variant sign mand topographies. We collected count data on instances of sign manding from session video recordings using a computer-based data-collection program and converted the count to a rate (i.e., signs per minute) to enable visual analysis. An independent variant sign mand topography was defined as an unprompted sign mand topog- raphy that differed from the last sign mand topography emit- ted within the session.

For example, if the sign for “toy” was emitted following the independently emitted sign “want,” then the sign for “toy” was considered variant. Measurement of variant sign mand topographies in each session began with the second emitted sign mand topography because the first sign mand topography emitted within a session was used by the experimenter to discriminate between invariant and variant manding.

All distinguishable gestures toward the reinforcer, other than a reach, were measured (e.g., clap, point). An inde- pendent invariant sign mand topography was defined as an unprompted sign mand topography that did not differ from the last sign mand topography emitted within the session. A prompted variant sign mand topography was one that was evoked by a model prompt provided by the experimenter and topographically different from the last sign mand topog- raphy emitted within the session.

Secondary dependent variables were (a) different across- session sign mand topographies and (b) different within- session sign mand topographies. Different across-session sign mand topography was defined as a sign mand topography that differed from all previous sign mand topographies emitted in prior sessions and was measured by adding each new emitted sign mand topography during a session to a cumulative total. Different within-session sign mand topography was defined as an emitted sign mand topography that differed from all prior

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emitted sign mand topographies within a session and was measured by counting the number of different signs emitted each session.

Interobserver Agreement and Procedural Fidelity

Interobserver agreement (IOA) and procedural fidelity were assessed by trained observers who viewed videos and inde- pendently collected trial-by-trial (i.e., each instance of the pro- grammed EO) data on 33% of sessions randomly selected across all phases. Data collected on variant, invariant, and prompted sign mand topographies were assessed using exact count-per-interval IOA (Cooper, Heron, & Heward, 2007).

To calculate IOA, each recording period was divided into 10-s intervals, the total number of intervals with exact agreement was divided by the total number of intervals, and the quotient was multiplied by 100. Mean IOA was 94% (range 85%– 100%). Mean fidelity for each select procedural component was calculated by dividing the number correct by the number correct plus the number incorrect and multiplying the quotient by 100. Overall mean procedural fidelity was calculated by dividing the sum of the individual means for each procedural component implemented correctly by the number of compo- nents (i.e., 4) and converting the quotient to a percentage. Overall mean procedural fidelity was 100% for the immediacy and duration of reinforcer delivery, response-reinforcer con- tingency, descriptive praise, and prompt immediacy.

Design and Procedure

Following pretreatment assessment and training, an A-B-A-B withdrawal design was used to evaluate the effects of sign mand variability training on variant signs under a Lag 1 + TD schedule of positive reinforcement (Silbaugh et al., 2017). Three to four sessions per day were conducted with the experimenter, approximately two to three days per week. The participant was given a choice between three different colors of playdoh every 2 to 3 days to minimize reinforcer satiation. A treatment evaluation session was terminated and excluded if no independent sign mand topography was emit- ted within 1 min of the onset of the first programmed EO of the session.

This occurred only once, during the final Lag 1 + TD phase. Allen was given a break for 1–2 min consisting of interaction with the experimenter between sessions of the as- sessment, training, and the treatment evaluation.

Pretreatment Assessment

The experimenter presented an array of toys and snacks and conducted an approximately 30-min semistructured play ses- sion (a) to identify potentially reinforcing toys or activities and (b) to briefly assess Allen’s responsiveness to sign mand train- ing. Playdoh was identified as a potential reinforcer based on

Allen’s sustained engagement and repeated reaches for the playdoh as the experimenter took brief turns. A hand over hand–to–sign mand stimulus transfer procedure with errorless prompting, prompt fading (physical, model, no prompt), and differential reinforcement with reinforcer intervals of 20–30 s was used to teach Allen “clapping” as an arbitrary mand re- sponse topography. Following approximately 20–30 trials, Allen emitted multiple consecutive independent responses to brief turns taken by the experimenter.

The results of the as- sessment suggested Allen would rapidly acquire additional sign mand topographies for playdoh during the treatment eval- uation using a motor imitation–to–sign mand stimulus transfer procedure. The experimenter’s playdoh and associated toys (e.g., plastic plate, spoons) were not available to Allen be- tween sessions.

Next, the experimenter selected three novel sign mand to- pographies to be targeted during the treatment evaluation. The form of each sign was modified from American Sign Language to minimize response effort. The sign “want” was defined as extending one arm with palms up and bringing the hand toward the body while forming a half fist once or repeat- edly. The sign “playdoh” was defined as extending one arm out, hand flat, palm down, and moving the hand toward and away from one’s own body once or repeatedly.

The sign “toy” was defined as orienting one arm at approximately a 90- degree angle toward the ceiling and tucking the thumb be- tween pointer and middle finger with the tip of thumb pointing up, then twisting the hand clockwise or counterclockwise once or repeatedly. Reasonable approximations of the signs were reinforced throughout the treatment evaluation. Allen’s right hand was targeted for sign acquisition.

Pretreatment Sign Mand Training

After the pretreatment assessment was complete, a series of 5- min training sessions were conducted to teach Allen to inde- pendently mand for playdoh using the sign “want.” Clapping and poorly articulated vocalizations were placed on extinc- tion. During each session, the experimenter repeated the train- ing procedures described in the prior assessment. The exit criterion for training was a single independent instance of the sign “want” within a training session. Allen met the exit criterion at the beginning of Training Session 4. The session was immediately terminated, and baseline (i.e., Lag 0) data collection for the treatment evaluation began.

Experimental Conditions

Lag 0 (Baseline) Allen was provided with free access to the playdoh for 30 s prior to the start of the first session each day, with the exception of the first session, which began immedi- ately after he met the exit criteria for pretreatment sign mand training. The experimenter initiated the session by

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removing access to the playdoh. Throughout the session, 20-s access to playdoh plus descriptive praise (e.g., “Playdoh! Nice job asking!”) was immediately provided on a Lag 0 schedule of positive reinforcement contingent on independent signs for “want.” Attempts to leave the table were blocked with the least amount of physical prompting possible by the experimenter.

Lag 1 Procedures in this condition were similar to Lag 0 with some exceptions. Access to playdoh was delivered for 20 s immediately contingent on the first independent sign mand topography emitted in each session. For the remainder of each session, 20-s access to playdoh plus descriptive praise was immediately provided contingent on prompted and indepen- dent variant sign mand topographies. Only the three target sign mand topographies (i.e., “want,” “toy,” “playdoh”) were eligible for reinforcement, and importantly, the participant had no exposure to sign mand training targeting the topographies for “toy” or “playdoh” prior to this phase. The lag schedule was combined with a progressive TD procedure to transfer control over the “toy” and “playdoh” sign mand topographies from model prompts to the EO and programmed reinforcer. If Allen did not emit a variant sign mand topography during the 2-s TD, the experimenter delivered a model prompt (some- times paired with a verbal prompt, “Do this,” to increase prompt effectiveness) for a target variant sign mand topogra- phy selected nonsystematically by the experimenter (i.e., best attempt at random choice of variant topography). Thus, Allen was permitted to sign repeatedly during the TD until a variant sign mand was emitted (i.e., within 2 s) or evoked (i.e., by a prompt). The experimenter continued to deliver the prompt at 2-s intervals until the prompt evoked the target variant sign mand topography. The length of the TD would have increased by 2 s every six consecutive trials that Allen failed to emit a variant sign mand topography, although this was not neces- sary for any sessions.

Results

All target sign mands were emitted during the treatment eval- uation. Data on specific topographies are not shown. Figure 1 displays the rates of independent variant, independent invari- ant, and prompted variant sign mand topographies. During baseline (i.e., Lag 0), moderate rates of independent variant manding were stable and rates of independent variant manding were low and steady. Coinciding with the introduc- tion of Lag 1 + TD, a moderate increase in prompted variant manding occurred along with a moderate decrease in the level of independent invariant manding and a moderate-to-large increase in the level of independent variant manding with a slightly ascending trend. The return to baseline resulted in an immediate decrease to a zero rate of prompted variant

manding (no prompts occurred), an increase in level and a shift to ascending trend in independent invariant manding, and a return to the baseline level of independent variant manding. Reintroduction of the Lag 1 + TD resulted in repli- cations of the changes in prompted variant, independent in- variant, and independent variant manding observed in the first Lag 1 + TD condition.

Table 1 provides a summary of cumulative different across- session sign mand topographies and mean independent differ- ent within-session sign mand topographies. Figure 2 provides session-by-session cumulative different mand topographies. The cumulative total increased from two in the first session to five by the end of the first Lag 1 + TD session, and the mean different within-session sign mand topographies increased from an overall mean of 1.67 in the Lag 0 conditions to an overall mean of 2.6 in the Lag 1 + TD conditions.

The first author assessed mand response class structure using procedures described in prior research (Richman, Wacker, Asmus, Casey, & Andelman, 1999; Silbaugh et al., 2017). First, he generated transcripts of within-session sign mand topographies, including independent and prompted

Fig. 1 Rates of independent variant (top panel), independent invariant (middle panel), and prompted variant (bottom panel) signing per session during conditions in which reinforcement was contingent on (a) any independent target sign mand topography (Lag 0) or (b) variant target sign mand topographies (Lag 1 + TD)

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target and nontarget sign mand topographies from session videos for all sessions. Next, he determined the relative laten- cies of each independent sign mand topography for each ses- sion on a trial-by-trial basis by assigning a ranking of 1 or 2 based on the order in which the two most frequent sign mand topographies occurred. Last, he calculated the percentage of trials in which a given independent sign mand topography was the first response within a session by dividing the number of trials in which a sign mand topography was given a rank of 1 by the number of trials (i.e., instances of the EO) for the session and converting the quotient to a percentage. For ex- ample, in a session in which an EO was presented 10 times, the sign mand topography “want” might be emitted first 8 times and the sign mand topography “toy” might be emitted first 2 times. Therefore, the percentage of trials in which the sign mand topography was ranked 1 for the session would be 80% for “want” and 20% for “toy.”

Figure 3 displays the percentage of trials per session in which each of the three most frequently independently emitted sign mand topographies were ranked first. “Want,” “clap,” and “playdoh” were emitted in a relatively predictable temporal order across trials, mostly during Lag 1 + TD sessions. “Want” was most likely to be emitted first during Lag 0 and Lag 1 + TD conditions (Lag 0: M = 95% of trials per session; Lag 1 + TD: M = 83% of trials per session). During the first Lag 1 + TD condition, “clap” (M = 8% of trials per session) or “playdoh” (M = 3% of trials per session), in that order, were the second most likely sign mand topographies to be emitted

first. During the second Lag 1 + TD condition, “playdoh” was the second most likely sign mand topography to be emitted first (M = 23% of trials per session).

Discussion

Much behavior-analytic research has demonstrated that mand training can increase the manding repertoires of individuals with language delays or deficits (e.g., Shafer, 1994; Sundberg & Partington, 1998; Wallace, 2007). For some, common mand training procedures may produce invariant patterns of manding insensitive to changes in contingencies mediated by a verbal audience. Procedures that reinforce mand variabil- ity may mitigate or replace repetitive manding, but unfortu- nately such procedures are lacking. Therefore, the current study aimed to extend prior research on the reinforcement of mand variability (i.e., Silbaugh et al., 2017) by evaluating the effects of a Lag 1 + TD procedure on the acquisition of new sign mand topographies and topographical sign mand vari- ability. Visual analysis of the results depicted in Fig. 1 sug- gests a largely nonvocal boy with autism acquired and varied multiple functionally equivalent sign mand topographies when variant and invariant manding contacted the contingen- cies that composed the Lag 1 + TD condition. This finding is consistent with prior research that suggested mand variability can be directly reinforced (Brodhead et al., 2016; Silbaugh et al., 2017) and provides additional support for the notion that lag schedules are a promising approach to establishing adap- tive mand variability.

New insight about mand variability training may be gained by comparing some differences between the current study and the procedures described by Silbaugh et al. (2017). First, Silbaugh et al. (2017) evaluated the effects of the procedures on topographical vocal mand variability in children with au- tism. However, the current study demonstrated the procedures can also increase nonvocal topographical mand variability

Fig. 3 Percentage of trials per session in which a given independent sign mand topography occurred first during Lag 0 and Lag 1 + TD conditions. Data are displayed for the three most frequent sign mand topographies

Table 1 Summary of cumulative different across-session sign mand topographies and mean independent different within-session sign mand topographies

First Session Final Session

Cumulative different across-session sign mand topographies

2 5

Lag 0 Lag 1 + TD

Mean independent different within-session sign mand topographies

1.67 2.6

Fig. 2 Cumulative different sign mand topographies exhibited across sessions and Lag 0 and Lag 1 + TD conditions

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(i.e., sign variability). Second, the current study targeted var- iability within a recently acquired mand with a very brief reinforcement history, whereas Silbaugh et al. (2017) targeted mands with a presumably much longer reinforcement history. This difference may explain why the participants in Silbaugh et al. (2017) did not emit all target alternative mand topogra- phies prompted during sessions, but Allen did. That is, when the outcomes of the two studies are compared, it may be in- ferred that a mand with a brief reinforcement history relative to a mand with a longer history may be more sensitive to procedures used to incorporate a variety of topographies into the response class, thereby establishing a new mand response class hierarchy. If so, mand variability training may have a more significant clinical impact when implemented early in intervention programming targeting manding. Third, the par- ticipants in Silbaugh et al. (2017) exhibited clear reduc- tions in levels of invariant manding when variant manding levels were elevated in Lag 1 + TD conditions, and al- though prompts were not technically eliminated from the treatment, prompts were not delivered in many sessions for both participants, suggesting that the Lag 1 schedule alone was sufficient to maintain mand variability. In the current study, Allen exhibited relatively similar levels of invariant manding across conditions, and prompts were used in most Lag 1 + TD sessions to evoke a variant response. Additional research is needed to identify vari- ables that determine levels of invariant manding when variant manding is reinforced.

Basic variability research (Odum, Ward, Barnes, & Burke, 2006; Stahlman & Blaisdell, 2011; Wagner & Neuringer, 2006) suggests operant variability may be increased by intro- ducing delays to reinforcement following relatively repetitive baseline responding. In the current study, during Lag 0, the first instance of sign manding emitted in each trial was imme- diately reinforced. However, because Allen was permitted to emit multiple responses in each trial during Lag 1 + TD ses- sions until the contingency was met, reinforcer delivery was contingent on variant sign mand topographies but also delayed in relation to early invariant responses in the trial. Thus, it is possible that differences in mand variability between phases in the current study may have been determined by delays to reinforcement in relation to the first response emitted on trials rather than the lag schedule. Future research could further clarify the relative effects of lag schedules and delays to rein- forcement on manding by using multiple schedules to com- pare rates of mand variability across conditions in which (a) reinforcement is delivered according to the lag schedule de- scribed in the current study and (b) reinforcement is delivered independent of variant responding but following a brief delay yoked to the average delay to reinforcement under the lag schedule. Relatively elevated rates under the lag schedule would provide additional support for the hypothesis that in- creased variant manding under a lag schedule is attributable to

a dependency between reinforcement and the variant dimen- sion of manding.

Inspection of the data in Table 1 suggests that Allen only emitted approximately the level of sign mand variability re- quired to produce the reinforcer in Lag 1 + TD phases. This finding is largely consistent with the results of prior research (Brodhead et al., 2016; Silbaugh et al., 2017). The cumulative different across-session sign mand topographies summarized in Table 1 demonstrate that Allen acquired five new function- ally equivalent sign mand topographies across only 19 (i.e., 3 sessions of pretreatment sign mand training and 16 sessions of sign mand training) 5-min sessions, including the arbitrary sign acquired during pretreatment assessment (i.e., clapping). This finding may be considered particularly striking consider- ing that Allen’s team had reported great difficulty with iden- tifying reinforcers that consistently maintained independent manding and that mand training in other modalities (i.e., vo- cal, electronic devices, card exchange) had largely been unsuccessful.

The relative latencies of the three most frequent sign mand topographies were compared to assess mand response class structure. The data depicted in Fig. 2 show that although Allen emitted high rates of independent variant sign manding during the Lag 1 condition, for the majority of sessions, “want” was the first sign mand topography emitted, which suggests that new sign mand topographies were incorporated into the mand during treatment in a manner that resulted in the formation of a response class hierarchy. In the first Lag 1 + TD condition, the second most frequent sign mand form emitted was the arbitrary clap response established during the pretreat- ment assessment. By the end of the second Lag 1 + TD con- dition, the second most frequent sign mand topography emit- ted was “playdoh,” and differences in relative response strength (as assessed by indirect measurement using relative response latencies) between “want” and “playdoh” largely diminished in the last two sessions. Future studies could focus more on variables (e.g., lag schedule value, number of mand topographies targeted, parameters of reinforcement, length of contact with the lag schedule) that may influence the effects of mand variability training on the relative response strength of new members integrated into the response class. That is, such studies might shed some light on how mands, and perhaps by analogy socially mediated challenging behavior, come to be organized probabilistically as new members enter the func- tional response class.

The current findings may also have theoretical implications related to the emergence of more complex verbal behavior. When Allen varied sign mand topographies within a trial un- der the lag schedule, he typically emitted the response se- quence “want” followed by “playdoh,” or “want” followed by “toy.” Structurally, these response patterns are equivalent to two-word sentences, suggesting that schedules selective for verbal operant variability and their associated contexts may

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play an important role in the development of novel word com- binations from the members of an existing repertoire and the transition to use of longer-mean-length utterances. In natural environments, the early emergence of mands in the form of sentences may reflect naturally occurring contingencies of re- inforcement selective for topographical variability and the for- mation of mand response class hierarchies consisting of new and existing response forms. Any underlying principle may apply to other verbal operants as well. In some cases, when individuals with language delays or deficits fail to demon- strate an increased mean length of utterance despite intensive high-quality behavioral intervention, the outcome may reflect in part a failure of the program to systematically provide a verbal environment selective for verbal variability, and future avenues of research could investigate these possibilities.

The lack of data on maintenance and social validity is a limitation that should be addressed in future research. In ad- dition, the current study did not evaluate the effects of the Lag 1 condition in the absence of prompts, so additional research in which prompts are eliminated from the current proce- dures is necessary to evaluate the effects of a Lag 1 schedule alone. Future research could also examine the effects of mand variability training targeting topographi- cal variability during the treatment of challenging behav- ior using FCT (Carr & Durand, 1985) to assess potential clinical advantages over the traditional approach, which does not use schedules selective for variability. Last, the generality of the current findings is unknown pending replication with additional participants.

Implications for Practice

& Demonstrates how practitioners might combine prompts with lag schedules to teach and reinforce mand variability in children with autism;

& Demonstrates increased topographical sign mand variabil- ity attributable to a lag schedule with prompting;

& Provides evidence for the development of a new sign mand response class hierarchy using a lag schedule with prompting.

Acknowledgements We thank the families for participating in our re- search, and Samantha Swinnea for her assistance with data collection. We also thank Allen Neuringer for his helpful insights and comments on an earlier version of the manuscript.

Compliance with Ethical Standards

Conflict of interest We report no conflicts of interest.

Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institu- tional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent Informed consent was obtained from all individual participants included in the study.

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ELEMENTARY READING. INTERVENTION USE CASE SCENARIO: Information about the school where this scenario is taking place: Applewood Elementary is a K-8 school located in an Urban district in the state of Minnesota. In the last 2 years they have

implemented an RtI process in order to ensure that all students make progress toward proficiency in Reading, Math,

Writing and Behavior. As part of that RtI process, the school participates in Universal Screening, Benchmark Testing,

Data review meetings and Parent informational sessions. The student selected for this case study is a second-grade

student who was identified in 1st grade with attendance and reading difficulties.

Information about the student who is the focus for this scenario:

John is an 8-year-old second grade student at Applewood Elementary. He is personable and likes to be the teacher’s

helper. He is motivated to work hard but is easily distracted and needs assistance to re-engage once he is off task. His

attendance was in the at – risk range in the previous year when he was a 1st grade student. Any student below the 90%

for attendance receives a Tier 2 intervention at Applewood Elementary. John received a Tier 2 intervention for

Attendance in 1st grade which was successful. He was exited from that intervention and is on a “watch – list” this year

to ensure he continues to meet the attendance requirements of Applewood Elementary. He also struggled with Reading

fluency and comprehension and was provided a Tier 2 intervention but this was unsuccessful which team members felt

was related to his poor attendance. John’s 1st grade teacher met with his current teacher in the beginning of the year to

share information about John’s attendance and reading progress from the previous year.

How is a student who might need an intervention identified?

John was assessed in the areas of Literacy and Numeracy in the fall of 2012. He was also tested using the Measure of

Academic Progress (MAP). Results of those assessments indicated that he was not meeting the standard in Oral Reading

Fluency and struggled with comprehension of what he read. MAP scores were below the proficiency level < 168. John

appeared to be proficient in Numeracy or Math operations according to MAP scores, quarter assessments and

classroom formative assessments.

John was reading approximately 25 WRC and at a level E, which would indicate that, he was at risk for failing to attain

grade-level proficiency. Both F&P and CBM provide benchmark goals for fall, winter and spring. Using those fall

benchmark scores for second grade, John would need to read about 44 WRC to be on his way to meeting the end-of-

year level of 85 WRC. He would also have to be at a level J in order to be at a level M by the end of the second grade.

John’s grade level team met after benchmarking assessments and decided that John was a good candidate for a Tier 2

intervention in Reading.

What additional data is gathered to more completely understand student’s needs?

Following the initial benchmark assessments John’s teacher completed a diagnostic assessment in Reading to further

identify current reading level, word recognition, fluency, comprehension and vocabulary skills.

2

What does the data tell you about the student?

Ms Reeder identified that John was not using context when he read and that he rarely self-corrected his errors. In

addition, unfamiliar vocabulary words appeared to slow down his fluency. Ms Reeder knew that weekly gains of 1.5 –

2.0 WRC were feasible if the reading instruction was rich enough (Fuchs, Fuchs, Hamlett, Walz & Germann, 1993). This

rate of growth should be attainable during the 13 weeks available for intervention and would result in John reading

about 75 WRC not at grade level proficiency but would move him out of the at-risk range.

INDIVIDUAL LEARNING PLAN

When was the ILP recorded in CFS?

Yes the teacher recorded this information in the ILP and the team entered the data when it became apparent that the

student needed an intervention. This information was shared with the parent at Parent – Teacher conferences.

What is the recorded in the students ILP?

What are the student’s strengths?

John is an 8-year-old second grade student at Applewood Elementary. He is personable and likes to be the teacher’s

helper. He is motivated to work hard but is easily distracted and needs assistance to re-engage once he is off task. He

struggles with reading fluency, comprehension and word recognition. The teacher has identified small group instruction,

pre-teaching of material and close proximity to her as three strategies that help John be successful.

What are the student’s academic goals?

Increase Reading Fluency and Improve Comprehension so that John will improve ability to read meaningful, rich

literature and expository texts.

Specify school & home actions to support goals

Weekly progress monitoring gains will be sent home

Independent readings will be sent home.

Specify work or home goals

John will read books sent home with a parent or older sibling.

He will also share his progress monitoring sheets with his parent explaining them to the parent.

State health results of health screening

No health concerns at this time

INTERVENTION PLANNING (Tier 2)

What steps are taken to plan the intervention?

Planning Team: Data Coach, Literacy Specialist, Classroom Teacher, & Interventionist if different from Classroom

Teacher.

During Professional Learning Community Meetings and/or Grade level team meetings.

Following the formalized plan the classroom teacher is responsible for recording the intervention plan into Classroom

for Success.

3

Should any information in the student’s background question answers be modified/expanded?

If yes, what?

No.

What is the intervention plan?

● Area of need: Word Recognition Fluency, Reading Fluency and Comprehension

● Intervention: LLI in small group of 3 students. Pre-Teaching Vocabulary words using the University of

Minnesota PRESS vocabulary intervention during his Core guided reading.

● Start Date: September 20, 2012

● Days per week: 5 days per week

● Minutes per day: 30 minutes a day

● Initial group size: 4

● Baseline level: WRC = 25, 26, 25. Comprehension skills less than 25% of material comprehended

following reading.

● Goal performance level: 1.5 – 2.0 WRC weekly

● Follow up date: 7 weeks

● Interventionist: Teacher

● Intervention notes description: Ms Reeder met with John and 3 other students for 30 minutes during

skills time. Leveled Literacy Intervention is a small group program for phonics, comprehension, fluency

and writing. Objectives for lessons included:

● Specific work on sounds, letters, and words in activities

● Close reading to deepen and expand comprehension.

● Explicit teaching of effective and efficient strategies for expanding vocabulary.

● Explicit teaching for fluent and phrased reading.

● Use of writing about reading for the purpose of communicating and learning how to express

ideas for a particular purpose and audience using a variety of writing strategies.

Differentiation during Core Tier 1:

John was also provided guided reading instruction within a small group, the goal was to improve John’s comprehension

skills in order to move him from a level E reader to a Level J by the Spring of his 2nd grade year. For the first 15 minutes

Ms Reeder pre-taught vocabulary words. Vocabulary was introduced by having John act-out words, or have them draw

the words. This vocabulary strategy is from the PRESS interventions at University of Minnesota. Each week the goal was

to learn 3 – 5 new vocabulary words and read them fluently within the context of their leveled readers. The last two days

of the week were also spent talking about the stories and answering comprehension questions, doing story retells,

clarifying main ideas and summarizing stories.

What is the progress monitoring plan?

 Weekly gains of 1.5 – 2.0 Words Read Correct per minute in reading fluency.

 Improved comprehension of material read from 25% to 50% using comprehension workbook activities.

4

THE INTERVENTION HAS BEEN DELIVERED

Was the intervention delivered with fidelity?

Teacher fidelity checklist completed after 1st week of intervention by Literacy Coach. Intervention was

delivered with 98% accuracy. If a new intervention was implemented a fidelity checklist would be

implemented by the Literacy Coach.

What is the progress monitoring data?

Week WRC Errors Aimline 1.5 – 2.0

Week 1 Baseline 25 2 Baseline

Week 2 Baseline 26 3 Baseline

Week 3 Baseline 25 3 Baseline

Week 4 26 5 Did not meet Aimline

Week 5 26 4 Did not meet

Week 6 27 3 Did not meet

Week 7 27 2 Did not meet

Week 8 28 1 Did not meet

Week 9 25 0 Did not meet

Week 10 26 0 Did not meet

Did the student meet the intervention goal?

● An aimline was created with a goal of 2.0 words per week increase

● Progress monitoring was completed weekly

● The decision rule was decided on by the team: Decision rule = after the collection of 6 – 8 data points if 4 points

or more are below the aimline a change in intervention is necessary.

John did not meet the Progress Monitoring goal for WRC or comprehension of material read. The team met and

decided that John should be provided 45 minutes two times a day.

Was the intervention successful?

● Was the intervention successful? NO

● Was the students area of need assessed correctly? YES

● Was the planned timeline followed? YES

● Was the frequency followed? YES

● Was the grouping followed? YES

5

● Selected outcome for intervention: unsuccessful remain at tier 2

● Additional notes:

What tier is the student now at?

Tier 2

What are the next steps for this student?

The student will receive another tier 2 intervention.

INTERVENTION PLANNING (second Tier 2)

What data/evidence is used to identify the student’s needs? What does the data tell you about

the student’s current needs?

 Progress monitoring data

What steps are taken to plan the intervention?

During last intervention, the team met and decided that John should be provided 45 minutes two times a day.

What is the intervention plan?

● Area of need: Word Recognition Fluency, Reading Fluency and Comprehension

● Intervention: LLI in small group of 3 students. Pre-Teaching Vocabulary words using the University of

Minnesota PRESS vocabulary intervention during his Core guided reading.

● Start Date: September 20, 2012

● Days per week: 5 days per week

● Minutes per day: 45 minutes, 2xs a day

● Initial group size: 4

● Baseline level: WRC = 25, 26, 25. Comprehension skills less than 25% of material comprehended

following reading.

● Goal performance level: 1.5 – 2.0 WRC weekly

● Follow up date: 7 weeks

● Interventionist: Teacher

● Intervention notes description: Ms Reeder met with John and 3 other students for 30 minutes during

skills time. Leveled Literacy Intervention is a small group program for phonics, comprehension, fluency

and writing. Objectives for lessons included:

● Specific work on sounds, letters, and words in activities

● Close reading to deepen and expand comprehension.

● Explicit teaching of effective and efficient strategies for expanding vocabulary.

● Explicit teaching for fluent and phrased reading.

● Use of writing about reading for the purpose of communicating and learning how to express

ideas for a particular purpose and audience using a variety of writing strategies.

6

● 15 minutes of duet reading/repeated reading and comprehension questions with Reading Corp

Teacher (new in this intervention)

What is the progress monitoring plan?

 Weekly gains of 1.5 – 2.0 Words Read Correct per minute in reading fluency.

 Improved comprehension of material read from 25% to 50% using comprehension workbook activities.

THE INTERVENTION HAS BEEN DELIVERED

Was the intervention delivered with fidelity?

Yes

What is the progress monitoring data?

Week GOM – WRC Errors Meets Goal

Week 11 28 4 Did not meet Goal

Week 12 28 5 Did not meet Goal

Week 13 29 3 Did not meet Goal

Week 14 30 1 Did not meet Goal

Week 15 32 1 Did meet Goal

Week 16 33 4 Did not meet Goal

Did the student meet the intervention goal?

No, The Tier 2 intervention was not successful. The student did not meet the goal.

Was the intervention successful?

● Was the intervention successful? NO

● Was the student’s area of need assessed correctly? YES

● Was the planned timeline followed? YES

● Was the frequency followed? YES

● Was the grouping followed? YES

● Selected outcome for intervention: Unsuccessful escalate to tier 3

● Additional notes:

● A new Tier 2 intervention was implemented and 6 more weeks of data was collected.

● John was not meeting the weekly goal for WRC. In addition, his comprehension continued to be at

the 30% for leveled text.

7

● John’s ability to read fluently and recognize new words automatically continued to lag far behind

students in his Tier 2 group and his class.

What tier is the student now at?

John is in a Tier 3 intervention.

What are the next steps for this student?

● The school problem solving team met to identify a Tier 3 intervention and decide who would be

implementing this intervention.

● School Problem Solving Team = Grade level teachers, interventionists, school psychologist, social

worker and reading specialist.

INTERVENTION PLANNING (Tier 3)

What data/evidence is used to identify the student’s needs? What does the data tell you about

the student’s current needs?

● Progress Monitoring data

● School Attendance

● Behavior referrals

● Home and school interview was completed by the School Social Worker to identify if there were home

issues

● Phone conference with parent.

What steps are taken to plan the intervention?

Planning Team for Tier 3 Intervention: Classroom teacher, psychologist, school social worker, special

education SERT and Principal.

Team will input the new plan after the Professional Learning Community data meeting. New Intervention

planned because of a lack of adequate progress in the second Tier 2 interventions.

What is the intervention plan?

● Area of need: Reading Fluency and Comprehension. Word Recognition Fluency (Decoding)

● Intervention: Reading Mastery II – Fast Cycle start lesson 80 out of 160 lessons.

● Start Date: Week 18

● Days per week: 5 Days per week

● Minutes per day: 45 minutes per day – 30 minutes in the morning during skills time Reading Mastery

and 15 minutes in the guided reading group 1 – 1 with Reading Teacher

● Initial group size: 3

● Baseline level: WRC = 34,36,38 – Comprehension of Material Read 40%

● Goal performance level: Student will be reading 44 WRC Winter Benchmark and at Level J

8

● Follow up date: February 28, 2014

● Interventionist: Literacy Teacher

● Intervention notes description: John will work with 2 other students every day on Reading Mastery

Fast Cycle with 2 students who are at a similar level. Literacy program to improve his Word Decoding,

Comprehension and Reading Fluency. The Professional Learning Community and data team will

reconvene in 8 weeks and make a decision a progress.

What is the progress monitoring plan?

● Weekly Progress monitoring – 2.0 Words Read Correct

● F&P Level J

● 90% passing of 4 Mastery Test from Reading Mastery Fast Cycle

THE INTERVENTION HAS BEEN DELIVERED

Was the intervention delivered with fidelity?

Yes

What is the progress monitoring data?

Weeks WRC Error Aimline Goal

Week 18 30 4 Baseline

Week 19 31 5 Baseline

Week 20 31 3 Baseline

Week 21 32 5 Did not meet Goal

Week 22 33 2 Did not meet Goal

Week 23 33 1 Did not meet Goal

Week 24 34 2 Did not meet Goal

Week 25 35 1 Did not meet Goal

Week 26 34 2 Did not meet Goal

Week 27 35 1 Did not meet Goal

Mastery Test Reading Mastery FC Pass with 90% Accuracy

Mastery Test Lesson 90 85% – redid week later 90%

Mastery Test Lesson 100 89% – redid week later 90%

Mastery Test Lesson 110 85% – redid week later 89% – redid 90%

9

Mastery Test Lesson 120 90%

Did the student meet the intervention goal?

 John did not meet Aimline goal or Fluency Goal.

 John did not meet Mastery Test Goal

 John continues to comprehend less than 50% of what he reads

Was the intervention successful?

 Was the intervention successful? NO

 Was the student’s area of need assessed correctly? YES

 Was the planned timeline followed? Yes

 Was the frequency followed? Yes

 Was the grouping followed? Yes

 Selected outcome for intervention: unsuccessful refer to intervention evaluation team

 Additional notes:

What tier is the student now at?

Referral to Intervention Review

What are the next steps for this student?

Tier 3 team will reconvene and create an assessment document.

INTERVENTION REVIEW

The Intervention Evaluation team reviews the student information.

School Psychologist, Classroom Teacher, Social Worker, Special Education Teacher, Parent and Principal

Is it decided the student should be evaluated for SpEd?

● Was the student are of need assessed correctly? Yes

● Was the student’s area of need addressed by the implemented interventions? Yes

● Did the progress monitoring tool align to the implemented interventions? Yes

● Were the interventions implemented as planned? Yes

● Is there sufficient data to make a determination? Yes

● Has parental consent for evaluation been received? Yes

● Select Outcome for Evaluation Review: Continue to Special Ed Evaluation