Accepted for/Published in: JMIR Mental Health
Date Submitted: Jul 21, 2020
Date Accepted: Dec 13, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Characteristics, Outcomes, and Statistical Solutions of Missing Cases in Web-Based Psychotherapy - replication and elaboration [Methods paper]
ABSTRACT
Background:
Missing cases present a challenge to our ability to evaluate the effects of web-based psychotherapy trials. Because they are often lost to follow up, less is known about the characteristics of missing cases or their likely clinical outcomes, or the likely effect of the treatment being trialled.
Objective:
To explore the characteristics of cases missing, their likely treatment outcomes, and the ability of different statistical models to approximate missing post-treatment data.
Methods:
A sample of internet-delivered cognitive behavioural therapy participants in routine care (n=6701) was used to identify predictors of dropping out of treatment, and predictors that moderated clinical outcomes, such as psychological distress, anxiety and depressive symptoms. These variables were then incorporated into statistical models that approximated replacement outcomes for missing cases, with the results compared through sensitivity and cross-validation analyses.
Results:
Lower treatment completion and higher symptom scores at pre-treatment were identified as the dominant predictors of missing cases, as well as the rate of symptom change. Statistical replacement methods that overlooked these features underestimated missing case outcomes by as much as 40%.
Conclusions:
The treatment outcomes of the cases that were missing at follow up were distinct from the remaining observed sample. Overlooking the features of missing cases is likely to result in an inaccurate estimate of the effect of treatment.
Citation
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