multiple baseline design disadvantages

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. A coincidental event may contact a single unit of analysis (e.g., one of four participants) or multiple units (e.g., all participants). Carr, J. E. (2005). 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. Adding multiple tiers to the design allows for two types of additional comparisons to be used to evaluate, and perhaps rule out, these threats: (1) replications of baseline-treatment comparisons within subsequent tiers (i.e., horizontal analysis), and (2) comparisons across tiers (i.e., vertical analysis). Type I errors and power in multiple baseline designs. (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. The assumption that all tiers respond similarly to maturation may be somewhat more problematic. Remedial and Special Education, 34(1), 2638. A given period of maturation may affect various participants, various behaviors, or behaviors in various settings in different ways. The key characteristic that maturational processes share is that they may produce behavioral changes that would be expected to accumulate as a function of elapsed time in the absence of participation in research.Footnote 2 In order to control for maturation, we must attend to the passage of timetypically, calendar days. Therefore, researchers must exercise extreme caution in interpreting and generalizing the results from pre-experimental studies. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Craig H. Kennedy. In addition, arranging tiers that are isolated in other dimensions (e.g., location, behaviors, participants) confers overall strength, not weakness, for addressing coincidental events. 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. https://doi.org/10.1016/0005-7916(81)90055-0, Wolfe, K., Seaman, M. A., & Drasgow, E. (2016). WebAB design advantages - -simple to use AB design disadvantages - -cannot be used to make a confident assumption of a functional relation -vulnerable to confounding variables -does not provide for replication AB design - basic single subject design AB design has two phases of design - A: Baseline B: Intervention Reversal Design referred to as - Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Hersen and Barlows (1976) textbook appears to be the first complete description of the multiple baseline design with many of the ideas about experimental control that are current to this day. Nonconcurrent multiple baseline designs and the evaluation of educational systems. First, in the replicated within-tier comparison, each tier of the design is exposed to the treatment at a different point in time. 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. Basic Books. Single-case research designs: Methods for clinical and applied settings (3rd ed.). Recommendations for reporting multiple-baseline designs across participants. Thus, both of the articles introducing nonconcurrent multiple baselines made explicit arguments that replicated within-tier comparisons are sufficient to address the threat of coincidental events. 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. So, similar to maturation, the across-tier comparison is sometimes able to reveal effects of testing and session experience, but it may fail to do so in some circumstances. 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. 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. 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. An example of multiple baseline across behaviors might be to use feedback to develop a comprehensive exercise program that involves stretching, aerobic exercise, Threats to Internal Validity in Multiple-Baseline Design Variations. What are the benefits and problems of these designs? Concurrence is not necessary to detect and control for maturation. The tutorial begins with instructions for how to create a simple multiple condition/phase (e.g., withdrawal research design) line graph. Cooper et al. 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. Reasons for these specifications will become clear later in the article.) That is, session numbers do not necessarily correspond to the same periods of real time across tiers. We will explore these issues extensively after we sketch the historical development of multiple baseline designs and criticisms of nonconcurrent multiple baselines. Campbell, D. T., & Stanley, J. C. (1963). Perhaps a more general and powerful triad of processes that support demonstration of experimental control would be prediction, contradiction, and replication. For example, in a multiple baseline across participants, all the residents of a group home may contact peanut butter and jelly sandwiches for lunch but this change may disrupt the behavior of residents with a mild peanut allergy, but not other residents. As we mentioned above, across-tier comparisons require the assumptions that coincidental events will (1) contact and (2) have similar effects on all tiers of the design. 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. A potential treatment effect in any single tier could plausibly be explained as a result of a coincidental event. Correspondence to Such events might be said to contact all tiers, but affect only one of them. Type I Errors and Power in Multiple Baseline Designs, Assessing consistency of effects when applying multilevel models to single-case data. Behavior Therapy, 6(5), 601608. The author has no known conflicts of interest to disclose. https://doi.org/10.1007/s40614-022-00326-1, DOI: https://doi.org/10.1007/s40614-022-00326-1. In J. R. Ledford & D. L. Gast (Eds. On resolving ambiguities of the multiple-baseline design: Problems and recommendations. Smith, J. D. (2012). Under the proposed definition, such a study would not be considered a full-fledged multiple baseline. For example, physical growth and experiences with the environment can accumulate and result in relatively sudden behavioral changes when a toddler begins to walk. (pp. 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. The general steps for the development of the line graphs are as follows: 1. Harvey, M. T., May, M. E., & Kennedy, C. H. (2004). The multiple baseline family of designs includes multiple baseline and multiple probe designs. Applied behavior analysis (3rd ed.). 2023 Springer Nature Switzerland AG. Finally, practitioners whose work may be influenced by SCD research must understand these issues so they can give appropriate weight to research findings. Testing and session exposure may be particularly troublesome in a study that requires taking the participant to an unusual location and exposing them to unusual assessment situations in order to obtain baseline data. Advantages and Disadvantages of ABA Design. 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. When conditions are less ideal, additional tiers may be necessary. 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. Houghton Mifflin. The lag between phase changes must be long enough that maturation over any single amount of time cannot explain the results in multiple tiers. For example, there is less room for participant-level coincidental events if all participants reside in a single group home than if they reside in different group homes in different states. For example, knowing the date of session 10 in tier 1 tells us nothing about the date of session 10 in tier 2. Part of Springer Nature. In this case, the effects of this kind of event could be revealed through the across-tier comparison of participants or behaviors that have not been exposed to the independent variable. 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. 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. Single-case designs for educational research. Johnston, J. M., Pennypacker, H. S., & Green, G. (2010). Single case experimental designs: Strategies for studying behavior change (3rd ed.). However, in a concurrent multiple baseline across participants, participant-level events contact only a single tier (participant)the coincidental event would not contact other tiers (participants)we might say that the across-tier analysis is inherently insensitive to detecting this kind of event. Perspect Behav Sci 45, 647650 (2022). Concurrent and nonconcurrent multiple baseline designs address maturation in virtually identical ways through both within- and across-tier comparisons. Predi Abab Design Essay et al. 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. Characteristics of single-case designs used to assess intervention effects in 2008. First, studies differ with respect to the experimental challenges imposed by the phenomena under study. This comparison may reveal a likely maturation effect. It is surprising that there is no single consensus definition of multiple baseline designs. In the past, there was significant controversy regarding the relative rigor of concurrent and nonconcurrent multiple baseline designs. For example, a baseline might be The concurrent multiple baseline design opened up many new opportunities to conduct applied research in contexts that were not amenable to other SCDs. Therefore, we believe that these features should be explicitly included in the definition of multiple baseline designs. 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. The across-tier comparison is an additional basis for evaluating alternative explanations. Natural multiple baselines across persons: A reply to Harris and Jenson. This skepticism of nonconcurrent designs stems from an emphasis on the importance of across-tier comparisons and relatively low importance placed on replicated within-tier comparisons for addressing threats to internal validity and establishing experimental control. 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. Second, the across-tier comparison assumes that extraneous variables will affect multiple tiers similarly. 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. Thus, a multiple baseline with phase changes sufficiently lagged (in terms of number of sessions) provides rigorous control for this threat. Single case experimental design and empirical clinical practice. In both within- and across-tier comparisons, the dates on which the sessions took place are not relevant to the effects of testing and session experience. Google Scholar. However, an across-tier comparison is not definitive because testing or session experience could affect the tiers differently. The Nonconcurrent Multiple-Baseline Design: It is What it is and Not Something Else. Given that multiple baseline designs make up such a large proportion of the existing SCD literature and current research activity, it is critical that SCD researchers thoroughly understand the specific ways that multiple baseline designs address potential threats to internal validity so that they can make experimental design decisions that optimize internal validity and accurately evaluate, discuss, and interpret the results of their research. 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 Estimating reliabilities and correcting for sampling error in indices of within-person dynamics derived from intensive longitudinal data, Optimizing Detection of True Within-Person Effects for Intensive Measurement Designs: A Comparison of Multilevel SEM and Unit-Weighted Scale Scores, https://doi.org/10.1023/B:JOBE.0000044735.51022.5d, https://doi.org/10.1037/0022-006X.49.2.193, https://doi.org/10.1177/001440290507100203, https://doi.org/10.1016/S0005-7894(75)80181-X, https://doi.org/10.1007/s40614-020-00263-x, https://doi.org/10.3758/s13428-011-0111-y, https://doi.org/10.1016/0005-7916(81)90055-0, http://creativecommons.org/licenses/by/4.0/, SI: Commentary on Slocum et al, Threats to Internal Validity. Kazdin, A. E. (2021). Create the graph from the data in Sheets; 3. WebNew Mexico's Flagship University | The University of New Mexico limitation of alternating treatment designs: o it is susceptible to multiple treatment interference, o rapid back-and-forth switching of treatments does not reflect the typical manner in which interventions are applied and may be viewed as artificial and undesirable. Child Development, 44, 547554. (1981). The process begins with a simple baseline-treatment (AB) comparisona change from baseline to treatment within a single tier. The present article is focused on the second questionwhether systematic changes in data can be attributed to the treatment. and (2) Was any change the result of the independent variable? In this article, we first define multiple baseline designs, describe common threats to internal validity, and delineate the two bases for controlling these threats. Nonconcurrent multiple baseline designs, however, do not afford this comparison. 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. Single-case research designs: Methods for clinical and applied settings (3rd ed.). For example, in a multiple baseline across settings, the settings could present somewhat different demands. Third, patterns of results influence the number of tiers needed to yield definitive conclusions. 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). Events that contact a single participant may be termed participant-level. In a review of the SCD literature, Shadish and Sullivan (2011) found multiple baseline designs making up 79% of the SCD literature (54% multiple baseline alone, 25% mixed/combined designs). Pearson Education. The bottom line is that the experimenter can never know whether a coincidental event has contacted only a single tier of a concurrent multiple baseline and, therefore, whether it is possible for the across-tier comparison to detect this threat. This paper describes procedures for using these designs, So, for example, session 10 in tier 2 must take place at some time between tier 1s session 9 and 11. Create the data table in Sheets; 2. Journal of Consulting & Clinical Psychology, 49(2), 193211. Behavior Research Methods, 43(4), 971980. A broad and general impression such as these designs are relatively strong is not sufficient to guide experimental design decisions or to evaluate particular variations of multiple baseline designs.

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