Descriptive Functional Assessment of Problem Behavior: A Methodological Review

Transcription

1 Descriptive Functional Assessment 1 Descriptive Functional Assessment of Problem Behavior: A Methodological Review Ivy M. Chong, James E. Carr, & Tina M. Sidener Western Michigan University Abstract Descriptive methods of functional assessment have been used in the assessment of problem behavior of individuals with developmental disabilities for years. Due to the considerable variety of descriptive assessment methods that have been reported in the literature, we provide a narrative review that describes and organizes common methods for collecting and analyzing data during descriptive assessment. We also provide a quantitative review that summarizes the methodological features of 21 studies conducted between 1980 and The results are discussed in the context of the apparent discontinuity between the clinical needs and abilities of practitioners and the descriptive assessment methods being developed by researchers.

2 Descriptive Functional Assessment 2 Descriptive Functional Assessment of Problem Behavior: A Methodological Review Functional assessment has become the standard method of selecting treatments for problem behavior (e.g., self injury, aggression) of individuals with developmental disabilities (Repp & Horner, 1999). Functional assessment procedures are frequently classified into three categories: informant assessment, descriptive assessment 1 (aka, direct-observation assessment), and functional analysis (Iwata, Vollmer, & Zarcone, 1990; Lennox & Miltenberger, 1989). Informant assessments, which include interviews and rating scales, rely solely on the verbal report of caregivers and clients for information regarding potential determinants of problem behavior. Although informant assessments can efficiently produce information about a wide range of variables without undue effort, their psychometric properties have been routinely questioned (Sturmey, 1994). By contrast, functional analysis represents the most rigorous of the functional assessment methods. In a functional analysis, specific environmental events (e.g., putative discriminative stimuli and reinforcers) are experimentally manipulated to identify functional behavior-environment relations (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994). Although the functional analysis is the only functional assessment method capable of identifying causal relations, it cannot be readily applied to all problem behavior (e.g., lowfrequency behavior; Carr & LeBlanc, 2003). Further, concerns about the response effort, expertise, and cost associated with functional analysis administration have been raised (Desrochers, Hile, & Williams-Mosely, 1997; Sprague & Horner, 1995). The goal of descriptive assessment is to identify relations between environmental events and problem behavior through direct observation in the natural environment. Descriptiveassessment data are typically collected in a linear fashion as events unfold in time. Like all methods of functional assessment, descriptive assessment is primarily employed to generate hypotheses about the environmental function of problem behavior (Lalli & Goh, 1993). However, descriptive assessment has also been used to inform the development of subsequent functional analysis (Lalli, Browder, Mace, & Brown, 1993) and clarify ambiguous outcomes from functional analysis (Shirley, Iwata, & Kahng, 1999). The purported advantages and disadvantages of descriptive assessment fall somewhere between those of informant assessment and functional analysis. Descriptive assessment shares with informant assessment the ability to assess a wide range of variables such as distal antecedents, medications, and symptoms of illness. Descriptive assessment represents an improvement over informant assessment in that data are objectively collected in the natural environment. Further, unlike functional analyses, descriptive assessments do not produce elevated rates of problem behavior or involve the risk of individuals developing new reinforcement contingencies (Desrochers et al., 1997). However, the data produced via descriptive assessment are only correlational in nature and, thus, represent a weaker form of proof than that provided by functional analysis. Further, descriptive assessment data might be confounded by programmed environmental events (e.g., all problem behavior is redirected) that mask the detection of actual controlling variables (Thompson & Iwata, 2001). An additional 1 Although the descriptive approach is frequently referred to in the literature as descriptive analysis, we prefer descriptive assessment because the term analysis has historically denoted experimental manipulation in applied behavior analysis (Baer, Wolf, & Risley, 1968; Horner, 1994).

3 Descriptive Functional Assessment 3 limitation is that descriptive assessment can involve lengthy data collection and complicated data analysis. Descriptive assessment includes two distinct methods. The scatter plot is a graphicinspection technique in which response frequencies are visually depicted on a chart in which the x-axis is scaled to days of the week and the y-axis is scaled to times of the day (Kahng et al., 1998; Touchette, MacDonald, & Langer, 1985). As such, the scatter plot is structural in its analytic ability and is not designed to directly generate information regarding behavioral function. Instead, the scatter plot is used to identify temporal patterns of problem behavior, which could help better target subsequent functional assessment methods. The second distinct method of descriptive assessment is typically referred to as A-B-C (i.e., antecedent-behaviorconsequence) assessment or A-B-C recording (Lennox & Miltenberger, 1989). A-B-C assessment seeks to identify, among other things, antecedent and consequent events that are frequently contiguous with problem behavior. The term descriptive assessment will be used in the manuscript from this point forward to refer only to A-B-C assessments. Descriptive assessment is frequently traced to the seminal publication by Bijou, Peterson, and Ault (1968) who developed a methodology for observing and quantifying behavioral and environment events as they occurred in the natural environment. Although their method was originally designed for studying child-caregiver interactions and did not actually involve the detection of behavior-environment relations, it has since been routinely employed to identify the function of problem behavior. One of the main contributions of the Bijou et al. study was its proposed methodological framework for quantifying events from naturalistic observation: (a) operationalization of behavioral and environmental events, (b) assessment of interobserver agreement, (c) data collection, and (d) data analysis. This framework still guides descriptive assessments today (Asmus, Vollmer, & Borrero, 2002). Since the publication of the Bijou et al. study, descriptive assessment has changed over time such that it now encompasses multiple methods of data collection and analysis. Unfortunately, a consistent and appropriate vocabulary has not evolved to describe these variants. In an attempt to better organize the literature, we suggest that descriptive assessments be classified as either response-dependent records or scheduled observations. These distinctions are described below. Response-dependent Recording Data collection. Response-dependent recording is a form of descriptive assessment in which data are collected on the environmental events that are contiguous with problem behavior as it occurs. Common data collection categories include response topographies, antecedents, consequences (aka, subsequents; Mace, Lalli, & Pinter-Lalli, 1991), activities, locations, and the presence of specific individuals. We term this approach response-dependent recording because data collection is dependent on the occurrence of problem behavior. Thus, the probability of environmental events independent of problem behavior is unknown (Sprague & Horner, 1995). A common clinical use of response-dependent recording is to have paraprofessionals or caregivers collect functional assessment data on low-rate problem behavior. Two types of response-dependent data collection have been presented in the literature. The first variant employs a narrative approach (aka, the descriptive method; Miltenberger, 2004) in which written descriptions of environmental events are recorded when problem behavior occurs. The Detailed Behavioral Report (Groden, 1989) is an example of this approach. The main advantage of narrative recording is that, hypothetically, any unforeseen event could be recorded. However, important limitations of this tactic are that a) untrained observers might

4 Descriptive Functional Assessment 4 record inferences about the motivation of problem behavior (Crawford, Brockel, Schauss, & Miltenberger, 1992) and b) narrative records can be difficult to quantify (Iwata, Kahng, Wallace, & Lindberg, 2000). The second type of response-dependent data collection employs a structured approach (aka, the checklist method; Miltenberger) in which specific recording options are provided for major event categories. Data collectors can then simply check the relevant events that occur contiguous with problem behavior. The Inappropriate Behavior Record (Pyles & Bailey, 1990) and Functional Analysis Observation Form (O Neill et al., 1997) are examples of structured response-dependent records. This tactic alleviates some of the quantification and data-collection problems associated with narrative records. Data analysis. With few exceptions (e.g., Groden, 1989) systematic and empirically supported guidelines do not yet exist for the analysis of data from response-dependent recording. However, standard practice appears to be to collect A-B-C data on numerous (perhaps 10-15) problem behaviors and then sum the frequencies of specific antecedents and consequences that are contiguous with problem behavior. These data are then presented numerically (e.g., Groden) or on a bar graph (e.g., Pyles & Bailey, 1990) to assist with hypothesis development. Data collection. In contrast to response-dependent recording in which data are only collected when problem behavior occurs, scheduled observations (aka, continuous observation; Iwata et al., 2000; interval recording; Miltenberger, 2004) can be conducted to independently record problem behavior and relevant environmental events (i.e., putative S D s, reinforcers, establishing operations) during specified time periods. The original publication by Bijou et al. (1968) illustrated this approach using a two-stage method. First, observations were conducted in which caregiver and child behaviors were narratively 2 recorded in a sequential manner (see also Repp & Karsh, 1994). Based on this record, an observational code was developed for more structured data collection during future observations. A critical difference between scheduled observations and response-dependent recording is that with the former data are typically collected on all relevant environmental events and response topographies as they occur using real-time or interval recording. Events are then classified as antecedents or consequences based on their temporal contiguity to problem behavior. Data analysis. Data from scheduled observations are typically analyzed sequentially with the conditional probability index, which represents the probability of one event given another. The conditional probability index is calculated as follows: p(a B) = p(ab) p(a) In the most common use of the conditional probability in descriptive assessment, A represents an instance of the problem behavior and B represents an environmental event. For example, in the assessment of the functional determinants of self-injurious behavior (SIB), the conditional probability of attention as a consequence for problem behavior is determined by dividing the number of occurrences of SIB followed by attention (p[ab]) by the total number of occurrences of SIB (p[a]). 2 Although Bijou et al. (1968) presented data in a narrative format, data were actually collected on a continuous basis during scheduled observations. Thus, this approach should not be confused with response-dependent narrative recording.

5 Descriptive Functional Assessment 5 A number of conditional probability calculations have been employed to quantify behavior-environment relations from scheduled observations. Descriptions of three of these follow. First, the simple conditional probability of an environmental event given problem behavior can be computed as described above. For example, Crawford et al. (1992) showed that the stereotypic behavior of four adults with mental retardation occurred in the absence of social interaction for 85% to 100% of time samples, suggesting an automatic reinforcement function. Some authors have improved upon this method by also calculating the conditional probability of problem behavior given an event (p[b A]) to account for the potential inflationary effects of variable base rates of behavior and environmental events (for an extended discussion of this problem, see Yoder & Fuerer, 2000). For example, Lerman and Iwata (1993) reported both the conditional probabilities of problem behavior given environmental events (antecedents, consequences) and environmental events given problem behavior in their descriptive assessment of SIB exhibited by six adults with mental retardation. As an alternative solution to this variable base-rate problem, some authors have advocated the use of Yule s Q, which is a measure of association that takes into account chance association (Oliver, Hall, & Nixon, 1999; Yoder & Fuerer). Third, Vollmer, Borerro, Wright, Van Camp, and Lalli (2001) recently illustrated a third arrangement in which the conditional probability of a consequent event given an occurrence of problem behavior is compared with the conditional probability of the event independent of behavior (i.e., background probability). Borrero, Vollmer, and Wright (2002) experimentally demonstrated that a reinforcement effect was achieved only when the former exceeded the latter (see also Hammond, 1980). Including environmental events that occur at different points (e.g., 5 s after, 10 s after) in time relative to the target behavior can also extend the aforementioned conditional probability analyses. This approach is commonly referred to as lag-sequential analysis (e.g., Forman, Hall, & Oliver, 2002). probability values obtained from scheduled observations are typically analyzed in one of two ways. Data analysis is sometimes based on an aggregate of all observations, in which case data are typically depicted on a bar graph for visual inspection (e.g., Crawford et al., 1992; Pyles, Riordan, & Bailey, 1997; Vollmer et al., 2001). Another common method is the repeated-measures approach in which conditional probability values from each scheduled observation are plotted on a line graph for visual inspection (e.g., Lalli et al., 1993; Lerman & Iwata, 1993). Rationale The purpose of the present paper is to systematically review the methodology 3 of published studies on the descriptive assessment of problem behavior of individuals with developmental disabilities. We believe such a review is warranted for at least four reasons. First, although the methodological features of informant assessment (Sturmey, 1994) and experimental analysis (Hanley, Iwata, & McCord, 2003) have been critically reviewed, no such analysis exists yet for descriptive assessment. Second, as illustrated earlier, reports of 3 It should be noted that the present review is methodological rather than quantitative in nature. In other words, epidemiological summaries will not be presented on behavioral functions or effect sizes of subsequent treatments. Although such information has its relevance, we believe it premature and potentially problematic to quantitatively summarize such data given the variability of descriptive assessment data collection and assessment methods and correlational nature of the data.

6 Descriptive Functional Assessment 6 descriptive assessment indicate numerous variations of data collection and analysis methods. We believe such variability warrants a summary of the literature to document common practices. Third, despite several notable limitations, there are times when descriptive assessment is preferred over informant assessment or functional analysis, such as when direct observation data are needed on low-rate, high-intensity problem behavior (Radford & Ervin, 2002). Finally, in a recent survey of practitioners in the field of mental retardation, Desrochers et al. (1997) reported that 78.4 % of practitioners reported frequent use of ABC analysis, which was also reported as the most useful of functional assessment methods. Thus, despite significant procedural variability and apparent paucity of empirically supported guidelines for descriptive-assessment data collection and analysis, the methods have been widely disseminated. Method Article Selection and Inclusion Criteria The goal of our literature search was to identify peer-reviewed, empirical articles that employed descriptive assessments to identify the function of problem behavior of individuals with developmental disabilities. Articles were selected for the review using a two-tier process. First, a computerized search of the PsycINFO TM database was conducted to identify journal articles that were published between 1980 and 2002 and contained variants of descriptive assessment, descriptive analysis, functional assessment, and functional analysis. Only those articles that were deemed relevant to the present paper based on a review of their abstracts were retained. A second PsycINFO TM search was then conducted using only the terms functional assessment and functional analysis to identify journals that contained 10 or more articles on the topics between The following journals were identified using this search: Journal of Applied Behavior Analysis, Research in Developmental Disabilities, Journal of Behavior Therapy and Experimental Psychiatry, Behavioral Interventions, and Behavior Modification. The abstracts of every empirical article published in these journals between were reviewed to identify additional articles. The abstract and method section of each article identified by the two aforementioned searches were reviewed to determine their inclusion in the present review. Articles were included in the review if the following five criteria were met: a) the focus of the article was the assessment and/or treatment of problem behavior (e.g., SIB); b) the descriptive assessment method was A-B-C in nature rather than a scatter plot; c) the descriptive assessment data collection procedures were adequately described; d) quantitative data from the descriptive assessment were reported in the article; and e) participants were diagnosed with a developmental disability (e.g., mental retardation, autism). Twenty-one articles were identified for the present review. Coding Categories Each of the 21 articles that was included in the sample (see Table 1) was evaluated for the information in the following categories. Participants. The number of participants exposed to descriptive assessment in each article was recorded. Setting. The setting in which each descriptive assessment was conducted was coded as either naturalistic or analogue in nature. Settings were classified as analogue if they were employed only during the course of the study (e.g., outpatient clinic, research room). Settings

7 Descriptive Functional Assessment 7 were classified as naturalistic if the participant spent significant time there outside of the study s purview (e.g., home, school, day program). Target behaviors. Data were collected on the specific topographies of problem behavior exposed to descriptive assessment. Because some studies did not report response topographies for every participant, we were unable to determine the exact distribution of topographies in our sample. Instead, we recorded whether any of the following common problem-behavior classes was reported in each study: SIB, aggression, stereotypy, and disruptive behavior (e.g., tantrums, bizarre speech, destruction). Other response topographies that did not easily fit into these categories were also recorded.. The number and duration (in min) of each observation session was recorded. Data collection format. Each descriptive assessment method was coded as either response-dependent or a scheduled observation depending on how data were collected. Response-dependent procedures were coded as narrative or structured depending on how data were collected. Data analysis. Each study was coded along three dimensions of data analysis. First, we determined the format of data analysis by recording whether data were analyzed using a the distribution of percentages of frequencies (most commonly associated with response-dependent recording) or conditional probability (most commonly associated with scheduled observations). Second, we recorded whether data were presented graphically (e.g., in a bar or line graph) or numerically. Third, we recorded whether assessment data were aggregated before data analysis or separated into smaller units for a repeated measures analysis. Interobserver agreement. Each study was coded to determine whether interobserver agreement (IOA) was assessed for the descriptive assessment data collection procedure. Intercoder Agreement Point-by-point agreement (# of agreements [# of agreements + disagreements]) was calculated to assess agreement between coders. An agreement was defined as both coders recording the same feature (e.g., data collection format) for an article. Agreement was assessed for 6 (28.6%) of the 21 articles and was 95%. All discrepancies were examined and resolved before final codes were applied. Results Of the 21 studies that comprised our sample, 123 participants with developmental disabilities were exposed to some form of descriptive assessment. Given the criteria with which articles were sampled, it is not surprising that the modal participant diagnosis was mental retardation. Nineteen (90.5%) of the studies were conducted in naturalistic settings, thus reaffirming one of the commonly reported uses of descriptive assessment (i.e., data collection in the natural environment). The distribution of target behaviors across studies is as follows. Eleven (52.4%) studies reported aggression, 10 (47.6%) reported SIB, 8 (38.1%) reported disruptive behavior, 7 (33.3%) reported stereotypy, 1 (4.7%) reported self-restraint, and 1 (4.7%) reported noncompliance. This distribution of aberrant response topographies is similar to that reported by Hanley et al. (2003) in a review of the functional analysis literature. Nineteen (90.5%) of the 21 studies employed the schedule-observation approach. Only 2 (9.5%) studies employed response-dependent recording. The mean number of observations

8 Descriptive Functional Assessment 8 reported across the studies was 29.7 (range, 3 to 115). However, this figure should be interpreted with some caution as 2 studies did not report their observation frequency and 5 studies only reported central-tendency measures, which were included in our calculation. The mean length of observations was 48.4 min (range, 1-300), with the exception of two studies that reported 16.5 continuous hours of data collection (Forman et al., 2002) and 3, 10.5-hr observations (Brusca, Nieminen, Carter, & Repp, 1989). Eighteen (85.7%) of the studies used conditional probability 4 methods for data analysis, while the other 3 (14.3%) studies reported percentage or frequency distributions. Two of the studies that reported percentage or frequency distribution data employed response-dependent data collection. Sixteen (76.2%) of the studies provided graphic depictions of their data and 10 (47.6%) studies employed a repeated-measures technique for data analysis. All of the studies in our sample reported IOA assessment, which satisfies the reported conventions of the descriptive assessment approach (Asmus et al., 2002; Bijou et al., 1968). Discussion Our review of the descriptive assessment literature indicates that the vast majority of studies have focused on the functional assessment of severe problem behavior (e.g., SIB, aggression) in the natural environment. The most common method of descriptive assessment was the scheduled-observation approach and the most common data-analytic technique was the conditional probability index. The length and frequency of these observations varied considerably. Further, the modal study in the sample employed the graphic display of data from multiple sessions, which is consistent with methodological conventions in applied behavior analysis. Although it is not uncommon for reviews of the functional assessment literature (e.g., Hanley et al., 2003; Kurtz et al., 2003) to report the distribution of behavioral functions within the sample, we did not code articles for behavioral function or the outcomes of subsequent treatment for several reasons. First, we were primarily interested in the methodology of descriptive assessment. Second, authors did not consistently provide a clear synthesis regarding behavioral function from their descriptive assessment data. When distinct behavioral functions were proposed, the process by which this happened was often unclear (e.g., Arndorfer, Miltenberger, Woster, Rortvedt, & Gaffaney, 1994). Furthermore, some studies recorded only antecedents (Brusca et al., 1989) and some only consequences (Thompson & Iwata, 2001), rendering it difficult to make certain statements about behavioral function. Finally, as mentioned earlier, the correlational nature of descriptive assessment data combined with the considerable variability in data collection and assessment methods diminished our confidence in the utility of a summary of behavioral functions. Similarly, the outcomes of treatments prescribed by descriptive assessment were not recorded because not all of the studies included treatment data and when they did it was not always clear exactly how treatments were matched to descriptive assessment results. 4 Although not every study that we coded as using the conditional probability index reported values from 0-1.0, their reporting metric conveyed the same information. For example, Brusca et al. (1989) reported percentage measures and Emerson, Hatton, Robertson, Henderson, and Cooper (1999) reported an odds ratio. However, both of these measures were based on conditional probabilities.

9 Descriptive Functional Assessment 9 A number of studies have compared descriptive assessment with functional analysis (e.g., Lerman & Iwata, 1993; Sasso et al., 1992). The results of these comparisons have been inconsistent, which seemingly argues against the use of descriptive assessment. One of the problems with this admittedly small body of research is that different studies have used different descriptive assessment data collection and analysis methods and none of them employed the more contemporary probability analyses proposed by Vollmer et al. (2001). It would be interesting to replicate some of these earlier studies with more contemporary data-analytic techniques. However, the ultimate purpose of such studies needs to be revisited. If the purpose of comparing descriptive and experimental methods is to develop a valid descriptive assessment for situations in which the functional analysis cannot be used, the scheduled-observation approach, which requires relatively high response rates, does not appear to adequately address this purpose. In other words, the clinical need for a non-experimental functional assessment method for moderate- to high-frequency problem behavior is unknown. If such comparison research is conducted in the future, a cost-benefit analysis of each method in terms of assessment duration, cost, and complexity would be quite beneficial. The remainder of our discussion is organized around the primary descriptive assessment methods of response-dependent recording and scheduled observations. Response-dependent Recording The most surprising finding in our review was that only 2 empirical studies (Crawford et al., 1992; Sasso et al, 1992) employed response-dependent recording. This is rather troublesome for several reasons. First, response-dependent recording is arguably the more common of the descriptive assessment methods used by clinicians and it is clearly the method that requires a lesser amount of effort to implement. Second, behavioral textbooks (e.g., Kazdin, 2001) and clinical manuals (e.g., O Neill et al., 1997) routinely describe response-dependent recording as if its methods were already well understood (i.e., empirically supported). Third, one of the main benefits of descriptive assessment is the ability to assess low-rate problem behavior. This benefit is primarily associated with response-dependent recording because scheduled observations require higher response rates to permit in vivo data collection. Although the scheduledobservation approach has been rather well developed over the last two decades, these procedures involve sophisticated data collection (e.g., real-time computerized data collection) and analyses (e.g., multiple conditional probability analyses) and do not appear relatively well suited for most clinicians. Although there are relatively few empirical studies devoted to response-dependent recording, we believe additional research is warranted given the procedure s widespread use, relatively low effort, and purported ability to assess low-rate problem behavior. We offer the following research topics as possible contributions to the existing literature. First, although Groden and Lantz s (2001) efforts in staff training and reliability assessment are commendable, additional studies need to be conducted to evaluate the predictive validity of response-dependent recording in comparison to a functional analysis or treatment evaluation. Although Sasso et al. (1992) demonstrated correspondence between response-dependent recording and functional analysis, their descriptive assessment data were collected during contexts identified via prior experimental analysis; thus, it is unknown how useful the descriptive assessment would have been had it been conducted independently. Crawford et al. (1992) demonstrated similar correspondence between response-dependent recording and functional analysis. However, it is unknown how their descriptive assessment data were summarized. Furthermore, both of these

10 Descriptive Functional Assessment 10 studies evaluated relatively high-rate problem behavior; thus, the generality of their findings to lower-rate problem behavior is unknown. Given the paucity of existing research in the area, we believe a well-documented case series clearly documenting response-dependent recording procedures and results and successful function-based treatment would be a useful contribution. An additional research topic is the comparison of structured (e.g., Pyles & Bailey, 1990) and narrative (e.g., Groden, 1989) data collection procedures. Although the use of the structured data collection format appears to offer clear practical benefits over the narrative approach, there are currently no empirical data to inform the issue. A third area for future research is the examination of data analysis for responsedependent recording. Although there are currently no empirically derived guidelines for analyzing data from multiple records, the method of analyzing the distribution of frequencies of specific environmental events appears to be standard (Groden, 1989; Sasso & Reimers, 1988). However, there is a potential problem with this method. By evaluating consequent and antecedent events independent of each other, the resultant data might evoke judgments about behavioral function that would be quite different had the events been assessed within putative contingencies. For example, the antecedent instruction provided might suggest an escape function when evaluated by itself and an attention function when evaluated with the consequence delivered a mild reprimand. It might be beneficial to evaluate the frequency of antecedentconsequence groupings rather than independent environmental events. Desrochers et al. (1997) found that clinicians reported the ABC analysis to be the most useful of functional assessment methods. Although it is possible that clinicians were referring to both response-dependent and scheduled-observation methods, we suspect they were primarily referring to the former given the relative complexity of the latter. Thus, it is possible that clinicians have already developed an effective response-dependent recording technology independent of the research literature. However, it is perhaps more likely that such procedures are implemented with great variability and without clear guidelines. Ultimately, the poor correspondence between the more rigorous scheduled-observation approach and the functional analysis does not bode well for research on the predictive validity of response-dependent recording. Given the practicality and ubiquity of response-dependent recording, we believe that such research is nonetheless warranted. From our review, it is evident that research resources have consistently been allocated to the evaluation of the scheduled-observation approach to descriptive assessment. We believe this is potentially problematic for several reasons. First, this approach requires problem behaviors that are likely to occur during the observation. Although the rate requirement for a scheduled observation might not be as high as that for a brief (e.g., 10 min) experimental analysis session, this approach clearly is impractical for the evaluation of low-rate problem behavior. Second, this approach requires relatively sophisticated operational definitions (including judgments about the presence/absence of putative establishing operations), complicated data collection procedures including interval and real-time recording, and sophisticated data-analytic techniques. We doubt that many clinicians have the expertise to properly conduct such assessments. Further, despite frequent claims that functional analyses require the most time, effort, and expertise to implement (Sprague & Horner, 1995), our review indicates that functional analyses fair better with respect to these concerns than do scheduled observations. However, this approach does have its merits.

11 Descriptive Functional Assessment 11 When functional analyses cannot be conducted (perhaps due to ethical or political concerns), the scheduled-observation approach appears to be a reasonable alternative. One of the most interesting outcomes of the literature s near-exclusive focus on scheduled observations has been the evolution of conditional probability methods for data analysis. As mentioned earlier, Vollmer et al. (2001) have applied the contingency analyses introduced by Hammond (1980) to quantify results from scheduled observations. This research shows that when the conditional probability of an environmental event given problem behavior is greater than the probability of the event independent of behavior (background probability), a reinforcement effect is likely to be achieved. Hammond termed this pattern a positive contingency. This approach holds much promise because it seemingly eliminates much of the ambiguity in data analysis and interpretation from scheduled observations. In other words, if a positive contingency pattern is detected in the conditional probability evaluation (i.e., conditional vs. background probability) of an environmental event and problem behavior, existing research suggests this event could be functionally related to the behavior. This conditional probability approach also overcomes, to some extent, the confounding influence of intermittent reinforcement in the detection of relevant variables. For example, even if a problem behavior were reinforced on a variable-ratio 10 schedule (cp =.10), as long as the background probability was lower than.10, a positive contingency would be in effect. The conditional probability approach proposed by Vollmer et al. (2001) is not without its limitations. The first problem concerns the size of the discrepancy between the conditional and background probabilities. There are currently no empirically derived guidelines to determine the significance (i.e., predictive validity) of the size of the discrepancy between the two values. Through multiple analyses it might be possible to eventually determine the critical size of the difference that is predictive of an actual reinforcement contingency. Another problem is that Vollmer et al. evaluated only those behavior-environment relations that occurred during putative establishing operations. We understand the logic behind this practice and believe that it likely enhances the analysis; however, the practice requires a considerably sophisticated data collector. If future research could demonstrate whether this step is critical to the approach, then the expertise required to conduct such conditional probability analyses will be better delineated. Furthermore, as Hackenberg and Vollmer (2001) mentioned, it is practically difficult to quantify the nonoccurrence of behavior (i.e., response independence) for the background probability calculation. In order to calculate the background probability, an interval of time must be arbitrarily selected between environmental events and problem behavior. If the event falls outside of that interval, it is considered to be independent of behavior, otherwise it is considered related. Several possibilities exist for addressing this problem. It might be possible to compare the conditional probability with the overall (unconditional) probability of the event (Watson, 1997). Although they did not present their actual data, Vollmer et al. mentioned that their conditional probability analyses that employed overall probability were not particularly informative. Despite this finding and the fact that the overall probability is an admittedly liberal index for comparison purposes, its sheer practicality warrants future investigation to fully determine its value. Another possibility for calculating the background probability would be to divide each interresponse time (IRT) into first and second halves. Environmental events occurring during the first half of the IRT would figure into the conditional probability calculation, whereas events occurring during the second half would figure into the background probability calculation (Hall & Oliver, 2000).

12 Descriptive Functional Assessment 12 In addition to the recommendations regarding conditional probability analysis, a number of research questions remain in the area of scheduled observations. From a data collection standpoint, given the considerable variation evident in our sample, it is important to determine the optimal number and length of observational sessions. With respect to data analysis, the Borrero et al. (2002) investigation that validated the positive contingency predictions of the aforementioned probability analyses needs to be replicated with additional participants. Such validation could be achieved via comparisons with the outcomes of functional analysis or treatment evaluation. Furthermore, although these probability analyses hold much promise, clinical guidelines need to eventually be developed to guide their use. As mentioned earlier, the effort required to collect and analyze data from scheduled observations could be prohibitive for many clinicians. The development of clear guidelines and job aids (e.g., software for calculating probabilities) would enable this technology to be used outside of the research arena. Conclusion The present review demonstrated that the descriptive assessment has received relatively little research attention over the last two decades. In a recent literature review of the functional analysis literature, Hanley et al. (2003) identified 253 studies in which individuals with developmental disabilities were exposed to experimental functional analysis. By contrast, only 21 studies were identified in the present review during a comparable time frame. Of the descriptive assessment methods, the response-dependent recording approach has rarely been investigated, despite its potential applied benefits and its popularity in clinical manuals (Grodin, Stevenson, & Groden, 1996; O Neill et al., 1997) and behavioral texts (e.g., Kazdin, 2001; Miltenberger, 2004). Conversely, the scheduled-observation approach has received considerably more research attention, but its methods of data collection and analysis are quite complicated, perhaps too much so for many clinicians. Future research is warranted on both approaches to better clarify and systematize their methods of data collection and analysis, determine their utility in selecting function-based treatments, and determine the relative costs and benefits associated with each approach.

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17 Table 1. Summary of studies employing descriptive functional assessment methods. Authors Year n Setting Target Behaviors # of Observation Duration (min) Belfiore et al natural self-injury 5 45 Brusca et al natural self-injury, stereotypy 3 3, 10.5-hr observations Data Collection Format Crawford et al natural stereotypy 4 15 Event Dependent Emerson et al analogue self-injury, aggression Emerson et al natural self-injury, aggression, disruption 8-16 (total = 8 hrs) 8-16 (total = 8 hrs) Emerson et al natural stereotypy Forman et al natural self-injury, self-restraint unknown total = 16.5 hrs Freeman et al natural self-injury, aggression Hall et al natural aggression, disruption 8 45 Harding et al natural aggression, disruption, noncompliance 4, 6, (M = 8 min) Lalli et al natural self-injury, aggression 5 60 Lerman & Iwata natural self-injury 24, 24, 24, 24, 24, 48 Mace & Lalli natural disruption Mueller et al natural stereotypy unknown 15 Oliver et al natural aggression 8 60 Pyles et al natural stereotypy Repp & Karsh natural aggression, stereotypy, disruption 74, 83, 84, 82, Sasso et al natural aggression, disruption Event Dependent Tang et al natural stereotypy Thompson & Iwata natural Vollmer et al analogue self-injury, aggression, disruption self-injury, aggression, disruption 4-17 (M = 7.1) Data Format Percentage Distribution Frequency Distribution Frequency Distribution Data Analysis Graphic Inspection Repeated Measures IOA Yes No Yes Yes No Yes No No Yes Yes No Yes No No Yes No No Yes Yes No Yes No No Yes Yes No Yes No No Yes Yes No Yes