multiple baseline design disadvantages
On the other hand, if we observe that one tier shows a change whereas other tiers that have been observed for similar amounts of time do not show similar changes, this may reduce the plausibility of the maturation threat. (Our specification of phase change offset in terms of real time, days in baseline, and sessions in baseline is unusual. Concurrence is not necessary to detect and control for maturation. However, this kind of support is not necessary: lagged replications of baseline predictions being contradicted by data in the treatment phase provide strong control for all of these threats to internal validity. Using Single-Case Designs in Practical Settings: Is Within-Subject Replication Always Necessary? These coincidental events would contact all tiers of a multiple baseline that include this individual participant, but not tiers that do not involve this participant. If a potential treatment effect is seen in one tier, the researcher cannot refer to data from the same day in an untreated tier because the tiers are not synchronized in real time and may not even overlap in real time. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. They never raise the question of whether replicated within-tier comparisons are sufficient to rule out threats to internal validity and establish experimental control. In addition, functionally isolating tiers (e.g., across settings) such that they are highly unlikely to be subjected to the same instances of a threat can also contribute to this goal. Single-case experimental designs: Strategies for studying behavior change. WebLike RCTs, the multiple baseline design can demonstrate that a change in behavior has occurred, the change is a result of the intervention, and the change is significant. If A changes after B is put into practice, a researcher can draw the Conclusion that B caused A to change. Third, patterns of results influence the number of tiers needed to yield definitive conclusions. A study may be at heightened risk of coincidental events if the target behavior is particularly sensitive to events in the environment that are uncontrolled by the experimenter. Further, if the potential treatment effect is more gradual (as one might expect from an educational intervention on a complex skill), maturational changes may be impossible to distinguish from treatment effects. For example, two rooms in the same treatment center would share more coincidental events than a room in a treatment center and another room at home. If these assumptions are not valid, then it would be possible to observe stable baselines in untreated tiers even though the change in the treated tier was a result of an extraneous variable. This insensitivity is not due to poor experimental design or implementation, it is built in to the nature of multiple baseline designs across participants. When conditions are less ideal, additional tiers may be necessary. Features of the target behaviors, participants, measurement, and so forth can make threats to internal validity more or less likely. The present article is focused on the second questionwhether systematic changes in data can be attributed to the treatment. This controversy began soon after the first formal description of nonconcurrent multiple baseline designs by Hayes (1981) and Watson and Workman (1981). Campbell, D. T., & Stanley, J. C. (1963). Instead, the idea that lag across phase changes includes three important dimensions and that these lags are critical for establishing experimental control and justifying strong causal conclusions should be elevated in importance. It is interesting that this emphasis on across-tier comparisons is the opposite of that evident in Baer et al. They do not elaborate on the importance of this type of comparison. Alternating Treatment Designs Watch on What are the disadvantages of alternating treatments? 2023 Springer Nature Switzerland AG. https://doi.org/10.1901/jaba.1968.1-91, Article As we argued above, the observation of no change in an untreated tier is not strong evidence against a coincidental event affecting the treated tier. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Coincidental events might be expected to be more variable in their effect than interventions that are designed to have consistent effects. A potential treatment effect in any single tier could plausibly be explained as a result of a coincidental event. Journal of Applied Behavior Analysis, 30(3), 533544. Experimental and quasi-experimental designs for research. Any alternative explanation of this pattern of results would have to posit an alternative set of causes that could plausibly result in changes in the dependent variable in this specific pattern across the multiple tiers. The across-tier analysis can provide an additional set of comparisons that may reveal a maturation effect, but it is not a conclusive test. Three phonological patterns were targeted for each child. There is ample empirical evidence of differential impact of variables across tiers. For example, a baseline might be Hayes, S. C. (1981). Hersen, M., & Barlow, D. H. (1976). Second, in a remarkably understated reference to the across-tier comparison, Baer et al. So, for example, session 10 in tier 2 must take place at some time between tier 1s session 9 and 11. If it changes at that point, evidence is accruing that the experimental variable is indeed effective, and that the prior change was not simply a matter of coincidence (p. 94). WebWhat are some disadvantages of alternating treatment design? Thus, for any multiple baseline design to address the threat of maturation, it must show changes in multiple tiers after substantially differing numbers of days in baseline. We can strongly argue that all tiers contact testing and session experience during baseline because we schedule and conduct these sessions. Nonconcurrent designs are said to be substantially compromised with respect to internal validity and in general this limitation is ascribed to their supposed weakness in addressing threats of coincidental events (i.e., history). Independent from Watson and Workman (1981), Hayes (1981) published a lengthy article introducing SCDs to clinical psychologists and made the point that these designs are well-suited to conducting research in clinical practice. In this section, we examine how within- and across-tier comparisons may support (or fail to support), internal validity in concurrent and nonconcurrent multiple baseline designs. The vast majority of contemporary published multiple baseline designs describe the timing of phases in terms of sessions rather than days or dates. By synchronized we mean that session 1 in all tiers takes place before session 2 in any tier, and this ordinal invariance of session number across tiers is true for all sessions. Any one tier may, at best, demonstrate a potential treatment effect; however, a set of three or more tiers may strongly address the threat of coincidental events and clearly demonstrate experimental control. We will explore these issues extensively after we sketch the historical development of multiple baseline designs and criticisms of nonconcurrent multiple baselines. Concurrent and nonconcurrent multiple baseline designs address maturation in virtually identical ways through both within- and across-tier comparisons. The multiple baseline design is useful for interventions that are irreversible due to learning effects, and when treatment cant be withdrawn. Only through repeated measurement across all tiers from the start of a study can you be confident that maturation and history threats are not influencing observed outcomes. By nature, undetected events are unknown. Journal of Consulting & Clinical Psychology, 49(2), 193211. For example, for a child who is on the cusp of walking, a month of exposure to maturational variables may result in a significant improvement in walking, but much less change in fine motor skills. Timothy A. Slocum, P. Raymond Joslyn, Sarah E. Pinkelman, Thomas R. Kratochwill, Joel R. Levin, Esther R. Lindstrm, Marc J. Lanovaz, Stphanie Turgeon, Tara L. Wheatley, Jonathan Rush, Philippe Rast & Scott M. Hofer, Perspectives on Behavior Science However, an across-tier comparison is not definitive because testing or session experience could affect the tiers differently. When determining whether a multiple baseline study demonstrates experimental control, researchers examine the data within and across tiers and also consider the extent to which alternative explanations (e.g., extraneous variables or confounds) could plausibly account for the obtained data patterns. Three children (ages 4;3 to 5;3) with moderate-severe to severe SSDs participated in two cycles of therapy. This is a preview of subscription content, access via your institution. To understand the ability of concurrent designs to meet these assumptions we must distinguish different types of coincidental events based on the scope of their effects. If an extraneous variable were to have a tier-specific effect, it would be falsely interpreted as a treatment effect. One is that if a Advantages and Disadvantages of ABA Design. In the end, judgments about the plausibility of threats and number of tiers needed must be made by researchers, editors, and critical readers of research. Although publication dates would suggest that Kazdin and Kopel (1975) was published before Hersen and Barlow (1976), Kazdin and Kopel cite Hersen and Barlow, and not the other way around. Multiple baseline designs are the workhorses of single-case design (SCD) research and are the predominant design used in modern applied behavior analytic research (Coon & Rapp, 2018; Cooper et al., 2020). For example, physical growth and experiences with the environment can accumulate and result in relatively sudden behavioral changes when a toddler begins to walk. The assumption that maturation contacted all tiers is strongparticipants were all exposed to maturational variables (i.e., unidentified biological events and environmental interactions) for the same amount of time. the effects of the treatment variable are inferred from the untreated behaviors (p. 227). Elapsed time does not directly cause maturational changes in behavior. Reasons for these specifications will become clear later in the article.) Instead, a detailed understanding of how specific threats to internal validity are addressed in multiple baseline designs and specific design features that strengthen or weaken control for these threats are needed. Behavioral Interventions, 33(2), 160172. In a concurrent multiple baseline that involves a single participant across settings, behaviors, antecedent stimuli etc., this kind of event would be expected to contact all tiers. (2018) state: Confidence that maturation and history [coincidental events] threats are under control is based on observing (a) an immediate change in the dependent variable upon introduction of the independent variable, and (b) baseline (or probe) condition levels remaining stable while other tiers are exposed to the intervention. For example, instrumentation is addressed primarily through observer training, calibration, and IOA. They do not mention the across-tier comparison, presumably because they believe that this analysis is not necessary to establish experimental control. The concurrent multiple baseline design opened up many new opportunities to conduct applied research in contexts that were not amenable to other SCDs. Controlling for coincidental events requires attention to the specific dates on which events occur. This pattern seriously weakens the argument that the independent variable was responsible for the change in the treated tier. 288335). Every multiple baseline design in which potential treatment effects are observed in some but not all tiers demonstrates that tiers are not always equally sensitive to interventions. The details of situations in which this across-tier comparison is valid for ruling out threats to internal validity are more complex than they may appear. Textbooks commonly describe and characterize the design without clearly defining it. Johnston, J. M., Pennypacker, H. S., & Green, G. (2010). Wacker, D., Berg, W., Harding, J., & Cooper-Brown, L. (2004). Routledge. How many tiers do we need? This raises the question of how many replications are necessary to establish internal validity. Kazdin, A. E. (2021). Timothy A. Slocum. As a result, concurrent and nonconcurrent designs are virtually identical in their control for maturation threats. In J. R. Ledford & D. L. Gast (Eds. https://doi.org/10.3758/s13428-011-0111-y, Article In such an instance, there may be a disruption to experimental control in only one-tier of the design and not others, thus influencing the degree of internal Experimental and quasi-experimental designs of research. Therefore, concurrent and nonconcurrent designs are virtually identical in control for testing and session experience. Rather, the passage of time allows for more opportunities for participants to interact with their environmentleading to maturational changes. Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). WebDisadvantage: Covariance among subjects may emerge if individuals learn vicariously through the experiences of other subjects Also, identifying multiple subjects in the same If the baseline phase provides sufficiently stable data to support a strong prediction of the subsequent data path and the data path prediction is contradicted by the actual data after the introduction of the independent variable, this provides some suggestion that the independent variable may have been the cause of the changea potential treatment effect. WebMultiple Baseline Description Multiple measures are used to obtain data over two or more baselines The end result appears visually as a series of A-B designs on top of one another The DV may consist of 2 or more different behaviors Versatile and relatively easy to understand Perhaps the most common design in use today Multiple Baseline Design If Likewise, setting-level coincidental events are those that contact a single setting. With stable data, the range within which future data points will fall is If a potential treatment effect is observed in the treated tier but a change in the dependent variable is also observed in corresponding sessions in a tier that is still in baseline, this provides evidence that an extraneous variable may have caused both changes. However, it does not rule out maturation as an alternative explanation of the change in behavior. This assumption was initially identified by Kazdin and Kopel in 1975, but its implications for the rigor of the across-tier comparison have rarely been discussed since that time. All three of these dimensions of lag are necessary to rigorously control for commonly recognized threats to internal validity and establish experimental control. Table 1 summarizes these threats to internal validity and the dimension of lag necessary to control for each. However, if this within-tier pattern is replicated in multiple tiers after differing numbers of baseline sessions, this threat becomes increasingly implausible. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. For the purposes of this article, we define a multiple baseline design as a single-case experimental design that evaluates causal relations through the use of multiple baseline-treatment comparisons with phase changes that are offset in (1) real time (e.g., calendar date), (2) number of days in baseline, and (3) number of sessions in baseline. However, researchers in clinical, educational, and other applied settings recognized that they could expand research much further if the tiers of a multiple baseline could be conducted as they became available sequentially rather than simultaneously. WebMULTIPLE BASELINE DESIGN Most widely used for evaluating treatment effects in ABA Highly flexible Do not have to withdraw treatment variable Is an alternative to reversal Pergamon. WebNew Mexico's Flagship University | The University of New Mexico The across-tier analysis of coincidental events is the main way that concurrent and nonconcurrent multiple baselines differ. Thus, the additional temporal separation that is possible in a nonconcurrent design is a strength rather than a weakness in controlling for coincidental events. Any of these types of circumstances may require additional tiers in order to clearly address threats to internal validity. Further, it is impossible to know how many events, which events, or the severity of the events that are missed by an across-tier comparison. . For both types of comparisons, addressing maturation begins with an AB contrast in a single tier. https://doi.org/10.1177/0145445516644699, Department of Special Education & Rehabilitation Counseling, Utah State University, 2865 Old Main Hill, Logan, UT, 84322, USA, Timothy A. Slocum,Sarah E. Pinkelman,P. Raymond Joslyn&Beverly Nichols, You can also search for this author in The lag between phase changes must be long enough that maturation over any single amount of time cannot explain the results in multiple tiers. Google Scholar, Coon, J. C., & Rapp, J. T. (2018). WebOften creates lots of problems BAB Reversal Design Doesnt enable assessment of effects prior to the intervention May get sequence effects May be appropriate with dangerous behaviors Addresses ethics of withholding effective treatment Need to be careful when using NCR Reversal Technique Noncontingent reversal That is, session numbers do not necessarily correspond to the same periods of real time across tiers. The first is the reversal design and the authors describe the important applied limitation with this designsituations in which reversals are not possible or feasible in applied settings. (Similar arguments can be made for comparisons across settings, persons, and other variables that might define tiers.) Single case experimental design and empirical clinical practice. The across-tier comparison provides another possible source of control for maturation. In general, a longer lag is better because it reduces the chance that an event could impact multiple tiers. We are not pointing to flaws in execution of the design; we are pointing to inherent weaknesses. Webmultiple baseline (3 forms) 1. across bx 2. across settings, 3. across subjects or groups using 3-5 tiers. Thus, to demonstrate experimental control, the effects of the independent variable must not generalize; and to detect an extraneous variable through the across-tier comparison, the effects of that extraneous variable must generalize. Peer reviewers and editors who serve as gatekeepers for the scientific literature must also have a deep understanding of these issues so that they can distinguish between stronger and weaker research, ensure that information critical to evaluating internal validity is included in research reports, and assess the appropriateness of discussion and interpretation of results. In this design, behavior is measured across either multiple individuals, behaviors, or settings. Watson and Workman (1981) noted that the requirement that observations be taken concurrently clearly poses problems for researchers in applied settings (e.g., schools, mental health centers), since clients with the same target behavior may only infrequently be referred at the same point in time (p. 257). Sometimes, the multiple baseline design may be more appropriate to use in interventions with small sample - 216.238.99.111. Harvey, M. T., May, M. E., & Kennedy, C. H. (2004). (p. 365), Of course, the major problem with this [nonconcurrent multiple baseline] strategy is that the control for history (i.e., the ability to assess subjects concurrently) is greatly diminished. Coincidental events (i.e., history) are specific events that occur at a particular time (or across a particular period) and could cause changes in behavior. The general steps for the development of the line graphs are as follows: 1. 66 : Discuss the advantages and disadvantages of using visual inspection of graphs rather than statistics to evaluate the significance of the results. a potential treatment effect in the first tier would be vulnerable to the threat that the changes in data could be a result of Hayes argued that fortunately the logic of the strategy does not really require (p. 206) an across-tier comparison because the within-tier comparison rules out these threats. Although the claims that nonconcurrent multiple baseline designs are weaker than concurrent multiple baselines, especially with respect to threats of coincidental events, are nearly universal in the current literature, none of these authors acknowledge or address, the arguments made by Watson and Workman (1981) and Hayes (1981) in support of these designs. . The logic of replicated within-tier analysis applies equally to concurrent and nonconcurrent designs. (1968) who emphasized the replicated within-tier comparison. Although the design entails two of the three elements of baseline logicprediction and replicationthe absence of concurrent baseline measures precludes the verification of [the prediction]. Smith (2012) found that SCD was reported in 143 different journals that span a variety of fields such as behavior analysis, psychology, education, speech, and pain management; across these fields, multiple baselines account for 69% of SCDs. Therefore, we view this approach as less desirable than the standard multiple baseline design across subjects and suggest that it should be employed only when the standard approach is not feasible. Multiple baseline designs are intended to evaluate whether there is a functional (causal) relation between the introduction of the independent variable and changes in the dependent variable. ), Single case research methodology: Applications in special education and behavioral sciences (pp. Although the across-tier comparison may detect some coincidental events; it cannot be assumed to detect them all. Application of multiple baseline designs in behavior analytic research: Evidence for the influence of new guidelines. Threats to Internal Validity in Multiple-Baseline Design Variations. Additionally, the Perspect Behav Sci 45, 619638 (2022). A functional relation can be inferred if the pattern of data demonstrates experimental controlthe experimenters ability to produce a change in the dependent variable in a precise and reliable fashion (Sidman, 1960). In this case, the across-tier comparison would give the false appearance of strong internal validity. et al. Oxford University Press. The nature of control for coincidental events (i.e., history) provided by the within-tier comparison in both concurrent and nonconcurrent multiple baseline designs is relatively straightforward. Maturational changes may be smooth and gradual, or they may be sudden and uneven. In the case of multiple baseline designs, a stable baseline supports a strong prediction that the data path would continue on the same trajectory in the absence of an effective treatment; these predictions are said to be verified by observing no change in trajectories of data in other tiers that are not subjected to treatment; and replication is demonstrated when a treatment effect is seen in multiple tiers. Google Scholar. This control assumes that the replications are sufficiently offset in real time (e.g., calendar days) to ensure that a single coincidental event could not plausibly cause the effects observed in multiple tiers. This is consistent with the judgements made by numerous existing standards and recommendations (e.g., Gast et al., 2018; Horner et al., 2005; Kazdin, 2021; Kratochwill et al., 2013). Each replication requires an assumption of a separate event coinciding with a distinct phase change. Routledge/Taylor & Francis Group. The tutorial begins with instructions for how to create a simple multiple condition/phase (e.g., withdrawal research design) line graph. It is clear that we cannot claim that these assumptions are always valid for multiple baseline designs. The purposes of this article are to (1) thoroughly examine the impact that threats to internal validity can have on concurrent and nonconcurrent multiple baseline designs; (2) describe the critical features of each design type that control for threats to internal validity; and (3) offer recommendations for use and reporting of concurrent and nonconcurrent multiple baseline designs.
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