multiple baseline design disadvantages

(Our specification of phase change offset in terms of real time, days in baseline, and sessions in baseline is unusual. The multiple baseline design is useful for interventions that are irreversible due to learning effects, and when treatment cant be withdrawn. Although the across-tier comparison may detect some coincidental events; it cannot be assumed to detect them all. Journal of Behavior Therapy & Experimental Psychiatry, 12(3), 257259. As a result, concurrent and nonconcurrent designs are virtually identical in their control for maturation threats. While the fact that the researcher does not use a large number of participants has its advantages, it also has a downside: Because the experimental trials are run on only one subject, it is difficult to empirically show with the experiment's data that the findings will generalize out to larger populations. 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. Maturational changes may be smooth and gradual, or they may be sudden and uneven. WebDisadvantage: Covariance among subjects may emerge if individuals learn vicariously through the experiences of other subjects Also, identifying multiple subjects in the same He acknowledged that earlier authors had stated that multiple baselines must be concurrent and he noted that in a nonconcurrent multiple baseline the across-tier comparison could not reveal coincidental events. They describe the control afforded by the design: The experimenter is assured that his treatment variable is effective when a change in rate appears after its application while the rate of concurrent (untreated) behaviors remains relatively constant (p. 226). (pp. For example, in a study of language skills in typically developing 3-year-old children, maturation would be a particular concern. In order to demonstrate experimental control, the researcher makes two paradoxical assumptions. 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. Control for testing and session experience requires attention to the number of sessions that participants experience. Still, for a given study, the results influence the number to tiers required in a rigorous multiple baseline design. If an extraneous variable were to have a tier-specific effect, it would be falsely interpreted as a treatment effect. Hayes, S. C. (1981). Behavioral Assessment, 7(2), 129132. Second, we briefly summarize historical methodological writing and current textbook treatment of these designs. Thus, the additional temporal separation that is possible in a nonconcurrent design is a strength rather than a weakness in controlling for coincidental events. Data from the treatment phase in one tier can be compared to corresponding baseline data in another tier. Journal of Applied Behavior Analysis, 1(1), 9197. Using Single-Case Designs in Practical Settings: Is Within-Subject Replication Always Necessary? 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. The point is that although the across-tier comparison may reveal a maturation effect, there are also circumstances in which it may fail to do so. PubMed Central 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. This provides clear information about the number of sessions that precede the phase change in each tier, and therefore constitutes a strong basis for controlling the threat of testing and session experience. Or in a multiple baseline across settings that are assessed at different times of the day, a socially challenging event such as an increase in daily bullying on a morning bus ride could disrupt the target behavior of a participant for the first hour of the day, but have reduced effects thereafter. With control for coincidental events in multiple baseline designs resting squarely on replicated within-tier comparisons, there is no basis for claiming that, in general, concurrent designs are methodologically stronger than nonconcurrent designs. For example, instrumentation is addressed primarily through observer training, calibration, and IOA. To summarize, the replicated within-tier analysis with sufficient lag can rigorously control for the threat of maturation. https://doi.org/10.1002/bin.191, Article It is interesting that this emphasis on across-tier comparisons is the opposite of that evident in Baer et al. Pergamon. https://doi.org/10.1023/B:JOBE.0000044735.51022.5d, Hayes, S. C. (1981). Second, as we have discussed above, the amount of lag between phase changes (in terms of sessions in baseline, days in baseline, and elapsed days) is the primary design feature that reduces the plausibility of any single threat accounting for changes in multiple tiers, and thereby threatening the internal validity of the design as a whole. 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. The multiple baseline design was initially described by Baer et al. If factors other than the experimenters manipulation of the independent variable could plausibly account for the obtained data patterns, experimental control has not been demonstrated and functional relations cannot be inferred. The across-tier analysis of coincidental events is the main way that concurrent and nonconcurrent multiple baselines differ. Learn more about Institutional subscriptions. Finally, we make recommendations for more rigorous use, reporting, and evaluation of multiple baseline designs. https://doi.org/10.1037/0022-006X.49.2.193. This has been the topic of important recent methodological research, including studies of the interobserver reliability of expert judgements of changes seen in published multiple baseline designs (Wolfe et al., 2016) and use of simulated data to test Type I and II error rates when judgements of experimental control are made based on different numbers of tiers (Lanovaz & Turgeon, 2020). In this article, we first define multiple baseline designs, describe common threats to internal validity, and delineate the two bases for controlling these threats. The assumption that all tiers respond similarly to maturation may be somewhat more problematic. Department of Educational Psychology, Neag School of Education, University of Connecticut, Storrs, CT, 06269, USA, You can also search for this author in Without the latter you cannot conclude, with confidence, that the intervention alone is responsible for observed behavior changes since baseline (or probe) data are not concurrently collected on all tiers from the start of the investigation. volume45,pages 647650 (2022)Cite this article. Oxford University Press. Neither the within-tier comparison, nor the across-tier comparison depends on the tiers being conducted simultaneously; both types of comparisons only require that phase changes occur after substantially different amounts of time since the beginning of baselinethat is, each tier is exposed to different amounts of maturation (i.e., days) prior to the phase change. 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]. 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. A : true B : false. 288335). The non-concurrent multiple baseline across-individuals design: An extension of the traditional multiple baseline design. After implementing the treatment for the first tier, they say, rather than reversing the just produced change, he instead applies the experimental variable to one of the other as yet unchanged responses. 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. Web14 : A multiple-baseline design requires that the targeted behavior return to baseline levels when the treatment is removed. This consensus is that nonconcurrent multiple baseline designs are substantially weaker than concurrent designs (e.g., Cooper et al., 2020; Johnston et al., 2020; Kazdin, 2021). Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). However, an across-tier comparison is not definitive because testing or session experience could affect the tiers differently. Describe the retrospective and prospective research designs. Examples could include family events, illness, changed social interactions (e.g., breaking up with a partner), losing or gaining access to a social service program, etc. The Nonconcurrent Multiple-Baseline Design: It is What it is and Not Something Else. Behavior Therapy, 6(5), 601608. This would draw attention to the relationship between the prediction from baseline and the (possible) contradiction of that prediction by the obtained treatment-phase data, and the replication of this prediction-contradiction pair in subsequent tiers. Rand McNally. The issue of concurrence of tiers should be considered along with many other design variations that can be manipulated to create a design that fits the particular experimental challenges of a particular study. And researchers generally design and implement interventions, select tiers, and employ measures that will likely show consistent treatment effects. Other design features that contribute to the isolation of tiers such that any single extraneous variable is unlikely to contact multiple tiers can also strengthen the independence of tiers. Second, in a remarkably understated reference to the across-tier comparison, Baer et al. When conditions are less ideal, additional tiers may be necessary. The tutorial begins with instructions for how to create a simple multiple condition/phase (e.g., withdrawal research design) line graph. Concurrent multiple baseline designs are multiple baseline designs in which the tiers are synchronized in real time. https://doi.org/10.1177/001440290507100203, Johnston, J. M., Pennypacker, H. S., & Green, G. (2020). Journal of Behavioral Education, 13(4), 267276. Finally, practitioners whose work may be influenced by SCD research must understand these issues so they can give appropriate weight to research findings. https://doi.org/10.1016/S0005-7894(75)80181-X, Kratochwill, T. R., Hitchcock, J., Horner, R. H., Levin, J. R., Odom, S. L., Rindskopf, D. M., & Shadish, W. R. (2013). WebIdentify the limitations of multiple baseline design 1.Does not demonstrate experimental control directly 2Provides more information about effectiveness of treatment Further, for both types of multiple baselines, the threat of coincidental events should be evaluated primarily based on replicated within-tier comparisons. Create the graph from the data in Sheets; 3. Concurrence is not necessary to detect and control for maturation. Pearson Education. Although it is plausible that an extraneous variables influence could coincide with one phase change, it is less plausible that such a coincidence would occur twice, and even less plausible that it would occur three times. In particular, within-tier comparisons may be strengthened by isolating tiers from one another in ways that reduce the chance that any single coincidental event could coincide with a phase change in more than one tier (e.g., temporal separation). Experimental and quasi-experimental designs for research. in their classic 1968 article that defined applied behavior analysis. 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. In this highly influential early textbook on SCD, Hersen and Barlow describe only the across-tier analysis and fail to mention replicated within-tier comparisons. This has been the sharpest point of criticism of nonconcurrent multiple baselines. 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. Coincidental events might be expected to be more variable in their effect than interventions that are designed to have consistent effects. If session experience exerted a small degree of influence on the DV, an effect might be observed in settings where the behavior is more likely, but not in settings where the behavior is less likely. 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. Routledge. Experimental and quasi-experimental designs for generalized causal inference. To offer some guidance, we believe that under ideal conditionsadequate lags between phase changes, circumstances that do not suggest that threats are particularly likely, and clear results across tiersthree tiers in a multiple baseline can provide strong control against threats to internal validity. 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. Timothy A. Slocum. Campbell, D. T., & Stanley, J. C. (1963). Nonconcurrent multiple baseline designs and the evaluation of educational systems. For example, knowing the date of session 10 in tier 1 tells us nothing about the date of session 10 in tier 2. As Kazdin and Kopel point out, it is clearly possible for treatments to have broad effects on multiple tiers and for extraneous variables to have narrow effects on a specific tier. The concurrent multiple baseline design opened up many new opportunities to conduct applied research in contexts that were not amenable to other SCDs. As Kazdin and Kopel (1975) pointed out, multiple baseline designs require that the effects of the independent variable must have tier-specific effects, yet the across-tier analysis requires that extraneous variables must not have tier-specific effects. The within-tier comparison may be further strengthened by increasing independence of the tier in other dimensions. The consensus in recent textbooks and methodological papers is that nonconcurrent designs are less rigorous than concurrent designs because of their presumed limited ability to address the threat of coincidental events (i.e., history). An alternative explanation would have to suggest, for example, that in one tier, experience with 5 baseline sessions produced an effect coincident with the phase change; in a second tier, 10 baseline sessions had this effect, again coinciding with the phase change; and in a third tier, 15 baseline sessions produced this kind of change and happened to correlate with the phase change. Thus, although the across-tier analysis does provide a test of the maturation threat, a lack of change in untreated tiers cannot definitively rule it out. Applied behavior analysis (3rd ed.). This certainty is increased by isolation of tiers in time and other dimensions. Kazdin, A. E. (2021). We challenge this assertion. We use function of elapsed time descriptively rather than causally. must have stable baseline and tx in first bx Additional replications further reduce the plausibility of extraneous variables causing change at approximately the same time that the independent variable is applied to each tier. The across-tier comparison provides another possible source of control for maturation. The problem of tier-specific coincidental events can be reduced by selecting tiers that differ on only a single factor (e.g., participants, settings, behaviors) and are as similar as possible on that factor. 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 authors argue that like the concurrent multiple baseline design, the nonconcurrent form can rule out coincidental events (i.e., history) as a threat to internal validity and that experimental control can be established by the replication of the within-tier comparison with phase changes offset relative to the beginning of baseline. Therefore, we believe that these features should be explicitly included in the definition of multiple baseline designs. 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. Type I errors and power in multiple baseline designs. In this case, the across-tier comparison would give the false appearance of strong internal validity. If the pattern of change shortly after implementation of the treatment is replicated in the other tiers after differing lengths of time in baseline (i.e., different amounts of maturation), maturation becomes increasingly implausible as an alternative explanation. Interrater agreement on the visual analysis of individual tiers and functional relations in multiple baseline designs. So, for example, session 10 in tier 2 must take place at some time between tier 1s session 9 and 11. 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). Behavior Research Methods, 43(4), 971980. If this patterna clear prediction from baseline being contradicted when and only when the independent variable is introducedcan be replicated across additional tiers of the multiple baseline, then the evidence of a treatment effect is incrementally strengthened. When changes in data occur immediately after the phase change, are large in magnitude, and are consistent across tiers, threats to internal validity tend to be less plausible explanations of the data patterns, and fewer tiers would be required to rule them out. Second, the across-tier comparison assumes that extraneous variables will affect multiple tiers similarly. Alternating Treatment Designs Watch on What are the disadvantages of alternating treatments? volume45,pages 619638 (2022)Cite this article. In general, in a concurrent multiple baseline design across any factor, the across-tier analysis is inherently insensitive to coincidental events that are limited to a single tier of that factor. Further, for the across-tier comparison to detect the influence of a coincidental event, that event must not only contact multiple tiers, it must cause similar changes in the dependent measure across multiple tiers. 234235). Concurrent and nonconcurrent multiple baseline designs address maturation in virtually identical ways through both within- and across-tier comparisons. However, each replication of the possible treatment effect that takes place at a substantially distinct calendar date reduces the plausibility of this threat. The present article is focused on the second questionwhether systematic changes in data can be attributed to the treatment. Taplin, P. S., & Reid, J. Potential setting-level events include staffing changes in classroom, redecoration or renovation of the physical environment, and changes in the composition of the peer group in a classroom, group home, or worksite. It is possible that a coincidental event may be present for all tiers but have different effects on different tiers. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Two articles published in 1981 described and advocated the use of nonconcurrent multiple baseline designs (Hayes, 1981; Watson & Workman, 1981). We examine how these comparisons address maturation, testing and session experience, and coincidental events. This would align the definition with the critical features required to demonstrate experimental control and thereby allow strong causal statements based on multiple baseline designs. Nonconcurrent multiple baseline designs, however, do not afford this comparison. If each tier of a multiple baseline represents a different participant in a different environment (e.g., school versus clinic) located in a different city, this would further reduce the chance that any single event or pattern of events could have contacted the participants coincident with the phase changes.

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