Single-Subject Research Designs Research Methods in Psychology 2nd Canadian Edition

Table Of Content

• Multiple baseline
• Data Analysis in Single-Subject Research
• Expanded Treatment
• UCLA transit pass programs improved accessibility and reduced emissions in 2023
• Historic gift to UCLA School of Law advances Latino legal scholarship
• V. Chapter 5: Experimental Research
• The Family of Single-Case Experimental Designs

As an example, consider a study by Scott Ross and Robert Horner (Ross & Horner, 2009).Ross, S. They were interested in how a school-wide bullying prevention program affected the bullying behavior of particular problem students. At each of three different schools, the researchers studied two students who had regularly engaged in bullying. During the baseline phase, they observed the students for 10-minute periods each day during lunch recess and counted the number of aggressive behaviors they exhibited toward their peers.

Multiple baseline

The beginning phase of an ABA design which acts as a kind of control condition in which the level of responding before any treatment is introduced. When the researcher waits until the participant’s behavior in one condition becomes fairly consistent from observation to observation before changing conditions. This means plotting individual participants’ data, looking carefully at those plots, and making judgments about whether and to what extent the independent variable had an effect on the dependent variable. In this design the baseline phase is followed by separate phases in which different treatments are introduced.

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Data Analysis in Single-Subject Research

The most basic single-subject research design is the reversal design, also called the ABA design. In visually inspecting their data, single-subject researchers take several factors into account. One of them is changes in the levelOne factor that is considered in the visual inspection of single-subject data.

Expanded Treatment

Figure 10.4 "An Approximation of the Results for Hall and Colleagues’ Participant Robbie in Their ABAB Reversal Design" approximates the data for Robbie. Figure 10.4 “An Approximation of the Results for Hall and Colleagues’ Participant Robbie in Their ABAB Reversal Design” approximates the data for Robbie. Finally, while the emphasis in personalized medicine is the identification of an optimal treatment plan for an individual person, situations in which multiple baselines across people prove relevant for precision medicine may arise. In a similar vein, differential response to a common treatment in a multiple-baseline-across-people design can help to identify individual differences that can compromise the response to a treatment. In an alternating treatments designA single-subject research design in which multiple treatments are alternated rapidly on a regular schedule., two or more treatments are alternated relatively quickly on a regular schedule. For example, positive attention for studying could be used one day and mild punishment for not studying the next, and so on.

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It is common for inverted floor plans to feature elevated outdoor spaces with the use of decks and balconies. Bredesen said the program’s downsides are its complexity and that the burden falls on patients and caregivers to follow it. Their most common complaints were the diet and lifestyle changes, and having to take multiple pills each day. The study was conducted Dr. Dale Bredesen of the UCLA Mary S. Easton Center for Alzheimer’s Disease Research and the Buck Institute for Research on Aging. An AB design is a two-part or phase design composed of a baseline ("A" phase) with no changes and a treatment or intervention ("B") phase.[4][5] If there is a change then the treatment may be said to have had an effect.

Historic gift to UCLA School of Law advances Latino legal scholarship

Research on HTE has shown variability in outcomes in RCTs, and in some studies very few people actually exhibit the benefits of that treatment (Williams, 2010). One approach in RCTs is to assess moderators of treatment response to identify individual differences that may predict response to a treatment. This approach may not limit variability in response, and substantial reduction in variability of treatment for subgroups in comparison to the group as a whole is far from assured. Even if variability is reduced, the average effect for that subgroup may not be representative of individual members of the subgroup. In an alternating treatments design, two or more treatments are alternated relatively quickly on a regular schedule. In an alternating treatments design, two or more treatments are alternated relatively quickly on a regular schedule.

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The number of participants needed for a fully powered RCT may be substantially different from the number projected from a small-sample RCT. These small, underpowered, early phase translational studies may provide too large an estimate of an effect size, leading to an underpowered RCT. Likewise, a small-sample RCT can lead to a small effect size that can, in turn, lead to a failure to implement a potentially effective intervention (Kraemer et al., 2006).

Figure 10.4 Results of a Generic Single-Subject Study Illustrating Level, Trend, and Latency. The male infertility patients that Dr. Werthman sees have frequently been told by other fertility doctors that they could not be helped, yet most respond quite well to the correct surgical procedure administered by Dr. Werthman. Sensitive to the needs of his patients, Dr. Werthman has worked tirelessly to expand the options available to treat male infertility. He uses the techniques that have been proven to consistently get the best results for patients, with the least amount of discomfort. Before the surgery begins, Dr. Werthman conducts a test to see if sperm are located within the vas deferens at the original vasectomy site.

A reversal design graph is used to visualize data from a within-subject A-B-A experimental design. Next, the researcher presents the independent variable—usually some type of treatment or intervention—and records any changes in behavior (phase B). Lastly, the independent variable is removed and behavior is measured at the baseline again (phase A).

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 level of responding before any treatment is introduced and therefore acts as a kind of control condition. The researcher waits until the participant’s behaviour in one condition becomes fairly consistent from observation to observation before changing conditions. The dependent variable ranges between 10 and 15 units during the baseline, then has a sharp decrease to 7 units when treatment is introduced. However, the dependent variable increases to 12 units soon after the drop and ranges between 8 and 10 units until the end of the study.