PDF Alternating treatments design: one strategy for comparing the effects of two treatments in a single subject

Table Of Content

• Sequential contrast effects with human subjects.
• Analysis of Effects in SSEDs
• Andy LeCompte Salon
• Alternating Treatments and Adapted Alternating Treatments Designs

2Given the absence of phases, immediacy and variability are likely to have a different meaning in the ATD context, as compared to multiple-baseline and ABAB designs. Regarding immediacy, an effect should be immediately visible, if it is to be detected, as each condition lasts for only one or two consecutive measurement occasions. Regarding data variability in each condition, it refers to measurements that are not adjacent.

Sequential contrast effects with human subjects.

The most basic single-subject research design is the reversal design, also called the ABA design. This is the level of responding before any treatment is introduced, and therefore the baseline phase is a kind of control condition. When steady state responding is reached, phase B begins as the researcher introduces the treatment.

Analysis of Effects in SSEDs

These designs provide strong internal validity evidence regarding the effectiveness of the interventions. External validity, however, may be compromised by the threat of multiple-treatment interference. Additionally, the same advantages and disadvantages of ABAB designs apply, including issues related to the reversibility of the target behavior. Despite their limitations, these designs can provide strong empirical data upon which to base decisions regarding the selection of treatments for an individual client.

Andy LeCompte Salon

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Examples of their use are provided in the section entitled “Illustrations and Comparison of the Results,” including a graphical representation of most of these techniques. In Table ​Table1,1, we also refer to the particular figure that represents an application of a technique. Arguably one of the prettiest hair salons in Los Angeles—and one of the highest reviewed on Yelp—Atelier by Tiffany is where you go to get pampered. There are a variety of services, ranging from haircuts and custom color to wedding hairstyles and treatments, making it a one-stop shop for any special events you may have coming up. The duration of an Alternating Treatment Design study can vary depending on the specific goals and needs of the child, but it often extends over several weeks to gather sufficient data for meaningful analysis. Yes, Alternating Treatment Design can be used to evaluate a wide range of interventions, such as communication methods, behavior management techniques, or social skills training programs.

Alternating Treatments and Adapted Alternating Treatments Designs

Then a treatment such as positive attention might be introduced first at school and later at home. Again, if the dependent variable changes after the treatment is introduced in each setting, then this gives the researcher confidence that the treatment is, in fact, responsible for the change. The percentage of time he spent studying (the dependent variable) was low during the first baseline phase, increased during the first treatment phase until it leveled off, decreased during the second baseline phase, and again increased during the second treatment phase.

In addition to visual comparison, a quantification using only the obtained (observed) measurements may be preferable to a quantification using the interpolated values from the ALIV. A possible quantification using only observed values is the “average difference between successive observations” (ADISO; Manolov & Onghena, 2018). As suggested by Ledford et al. (2019), measurements from one condition are compared to adjacent measurements of the other condition. The calculations focus on level, whereas potential distinct trends are quantified via increasing or decreasing differences between adjacent values. For an ATD with block randomization of condition ordering, it is straightforward to perform the comparisons within blocks.

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The study was approved by the Institutional Review Board of the City University of New York (CUNY). The plotting of individual participants’ data, examining the data, and making judgements about whether and to what extent the independent variable had an effect on the dependent variable. The issue of when, if ever, the data generated from SSEDs should be statistically analyzed has a long and, at times, contentious history (Iwata, Neef, Wacker, Mace, & Vollmer, 2000).

In this phase, the interventionist identified target responses to be used in the subsequent phases of the study. Ten new one-step directions were selected from Teaching language to children with autism or other developmental disorders (Sundberg & Partington 1998). The interventionists chose targets that were not part of the participant’s current or past preschool intervention. Additionally, no one-step directions that specifically stated an object manipulation (e.g., “Touch ball!”) or explicit body part manipulation (e.g., “Touch nose!”) were tested. During a trial, the interventionist provided one of the 10 one-step directions and waited 5 s for the participant to respond. After 5 s, regardless of the participant’s responses, the interventionist initiated a new trial.

Why is the reversal—the removal of the treatment—considered to be necessary in this type of design? Notice that an AB design is essentially an interrupted time-series design applied to an individual participant. Recall that one problem with that design is that if the dependent variable changes after the treatment is introduced, it is not always clear that the treatment was responsible for the change. It is possible that something else changed at around the same time and that this extraneous variable is responsible for the change in the dependent variable.

The interested reader is referred to regression-based procedures for model-based inference (Onghena, 2020). In particular, these techniques allow modeling the average level of the measurements in each condition and, if desired, the trends. The readings suggested for regression-based options in the SCED context are Moeyaert et al. (2014), Shadish et al. (2013), and Solmi et al. (2014), whereas for options in the context of N-of-1 trials Krone et al. (2020) and Zucker et al. (2010) can be consulted. Among the possibilities for a random determination for condition ordering, a completely randomized design (Onghena & Edgington, 2005) entails that the conditions are randomly alternated without any restriction, but this could lead to problematic sequences such as AAAAABBBBB or AAABBBBBAA.