Causal inference under interference with prognostic scores for dynamic group therapy studies Article Swipe
Bing Han
,
Susan M. Paddock
,
Lane F. Burgette
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1515/ijb-2019-0126
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1515/ijb-2019-0126
Group therapy is a common treatment modality for behavioral health conditions. Patients often enter and exit groups on an ongoing basis, leading to dynamic therapy groups. Examining the effect of high versus low session attendance on patient outcomes is a research question of interest. However, there are several challenges to identifying causal effects in this setting, including the lack of randomization, interference among patients, and the interrelatedness of patient participation. Dynamic therapy groups motivate a unique causal inference scenario, as the treatment statuses are completely defined by the patient attendance record for the therapy session, which is also the structure inducing interference. We adopt the Rubin causal model framework to define the causal effect of high versus low session attendance of group therapy at both the individual patient and peer levels. We propose a strategy to identify individual, peer, and total effects of high attendance versus low attendance on patient outcomes by the prognostic score stratification. We examine performance of our approach via simulation and apply it to data from a group cognitive behavioral therapy trial for treating depression among patients in a substance use disorders treatment setting.
Related Topics
Concepts
Attendance
Causal inference
Treatment and control groups
Randomized controlled trial
Inference
Propensity score matching
Randomization
Medicine
Session (web analytics)
Cognition
Clinical trial
Cognitive behavioral therapy
Psychology
Clinical psychology
Psychiatry
Computer science
Internal medicine
Artificial intelligence
World Wide Web
Economic growth
Economics
Pathology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1515/ijb-2019-0126
- OA Status
- green
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3195008426
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3195008426Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1515/ijb-2019-0126Digital Object Identifier
- Title
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Causal inference under interference with prognostic scores for dynamic group therapy studiesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-08-13Full publication date if available
- Authors
-
Bing Han, Susan M. Paddock, Lane F. BurgetteList of authors in order
- Landing page
-
https://doi.org/10.1515/ijb-2019-0126Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.ncbi.nlm.nih.gov/pmc/articles/9973534Direct OA link when available
- Concepts
-
Attendance, Causal inference, Treatment and control groups, Randomized controlled trial, Inference, Propensity score matching, Randomization, Medicine, Session (web analytics), Cognition, Clinical trial, Cognitive behavioral therapy, Psychology, Clinical psychology, Psychiatry, Computer science, Internal medicine, Artificial intelligence, World Wide Web, Economic growth, Economics, PathologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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33Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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