ArticleAnnals of behavioral medicine : a publication of the Society of Behavioral Medicine2025
Improving the design and analytic methods used in NIH-funded clinical trials involving behavioral interventions.
Article in Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
2 authors.
Funding
Abstract
Behavioral interventions are widely used in clinical trials supported by the National Institutes of Health (NIH). When behavioral interventions involve group-formatted components and/or shared interventionists, they require special design and analytic methods not needed in trials that do not involve these features. The NIH Office of Disease Prevention (ODP) and the NIH Office of Behavioral and Social Sciences Research (OBSSR) offer resources to make it easier for investigators to use appropriate methods to evaluate these interventions. This commentary draws attention to these issues and highlights the ODP and OBSSR resources available to investigators. We urge investigators to take advantage of these resources to learn about and adopt appropriate sample size and analytic methods for trials to evaluate behavioral interventions so that their results will be reliable and reproducible. That is the best way to advance the science of behavioral interventions to improve health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.