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Beyond case reports
Published in Margaret Walshe, Maggie-Lee Huckabee, Clinical Cases in Dysphagia, 2018
In contrast to the case report, single-subject research is considered to be either semi-experimental or experimental, and attempts to influence an independent variable in order to examine its effects on a dependent variable in a clinical condition. The clinician will consider the question at hand and consider the strength of the theoretical proposition. Is there a body of evidence suggesting that the question is grounded in the existing science? During the search for evidence the clinician should consider how the questions were asked in the supporting literature. Elaboration may be necessary to construct a novel question related to existing science and to allow for a design that is explanatory. The search may also yield conventions for the appropriate units of measurement, as well as established summary statistical methods. Perhaps most importantly there should be a clinical question that motivates the effort. Ideally the clinician has experienced a clinical conundrum that is not sufficiently addressed in the available scientific literature, which affords an opening to further understand the problem at hand.
How to Think about Cause-Effect Relationships: Multiple and Single Observations 1
Published in Milos Jenicek, How to Think in Medicine, 2018
A single-subject research design is devised to draw cause-effect phenomena from observations in a single individual, whatever its limitations might be. In observational research, at least one situation before, and one after some intervention, is compared. In experimental research of repetitive episodic clinical events, interventions instead of individuals may be randomized yielding an “N-of-1” clinical trial as proposed by Guyatt et al.50,51
Study Designs and Measures of Effect Size
Published in Mohamed M. Shoukri, Analysis of Correlated Data with SAS and R, 2018
Single-subject research is experimental rather than descriptive, and its purpose is to establish a causal relationship between independent and dependent variables. Single-subject research employs within- and between-subjects comparisons to control for major threats to internal validity and requires systematic replication to enhance external validity (Martella, Nelson, and Marchand-Martella, 1999). We shall now outline some of the basic features of single-subject design (SSD).
Robot-mediated interventions for teaching children with ASD: A new intraverbal skill
Published in Assistive Technology, 2022
Jessica Korneder, Wing-Yue Geoffrey Louie, Cristyn M. Pawluk, Ibrahim Abbas, Molly Brys, Faith Rooney
In this study, we utilized a single-subject research design with a small sample size which may limit the generalizability of the results when considered independently. However, it is currently well established that in order to form an evidenced-based practice and generalize an ABA-based intervention for individuals with ASD it is necessary to replicate at minimum five single-subject studies by three different research groups across three geographical locations (Horner et al., 2005). The results of this study demonstrated that SARs could teach a skill to children with ASD with the same efficiency and efficacy as human delivered therapies. Hence, we hope this study can serve as a starting point toward building a replicable body of literature to support the use of SAR technology as an evidenced-based approach for delivering ABA-based therapies to children with ASD. Namely, for interventions to be included as an evidence-based practice, future studies should extend upon and replicate SARs research, especially in clinically based settings (Dickstein-Fischer et al., 2018; National Autism Center, 2009).
Peer-led, transformative learning approaches increase classroom engagement in care self-management classes during inpatient rehabilitation of individuals with spinal cord injury
Published in The Journal of Spinal Cord Medicine, 2019
Julie Gassaway, Michael L. Jones, W. Mark Sweatman, Tamara Young
Study Design. We used a multiple-baseline design, wherein the revised classes were introduced across three subject areas in step-wise fashion over successive weeks.22, 23 Commonly used in single-subject research, characteristics of this design include repeated baseline measurements and staggered introduction of the intervention across at least three behaviors (of a single participant), settings, or individuals. The multiple-baseline design can also be applied to groups of individuals or settings (such as classes) assuming the groups are independent, that is change in one group following introduction of an intervention does not carry over to other groups.24 The design controls for the effect of extraneous events (history) by showing that changes occur after and only after introduction of the intervention to each group.25 Data analysis of the design involves examining – visually and statistically – changes in the slope or level of the repeated measures taken before and after introduction of the intervention across each group. In this case, the classes for three subject areas – skin care, bladder management, and special concerns – were treated as groups. Over a 15-week period, the conventional classes for each of these subject areas were replaced with revised, peer-led classes. The order in which the revised classes were introduced across subject areas was determined randomly.
Evaluation of hand orthoses in Duchenne muscular dystrophy
Published in Disability and Rehabilitation, 2018
Johanna Weichbrodt, Britt-Marie Eriksson, Anna-Karin Kroksmark
The results from studies of a progressive disease such as DMD must be interpreted in light of knowledge about the disease. Single-subject research design was considered to be the most suitable design for this study. It also became apparent that a composite analysis of the various components was necessary in order to give a fair presentation of the results. If significant findings had only been calculated based on changes in relation to the mean of phase A, positive changes in trend and level would not have emerged from the results. For example, the mean value could be the same in both phase A and phase B, or even show negative significance, and still represent a positive change in trend and level, provided that the change decreased or did not progress as quickly as in phase A. This outcome may also represent a large positive change for the individual.