ArticleAdministration and policy in mental health2024
The Promise and Challenges of Practice-Oriented Research: A Commentary on the Special Issue.
Article in Administration and policy in mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
At the centre of POR is the concept of collaboration between patients, therapists, agencies, and third-party payers. For this commentary, I review the articles of the special issue with attention to both the opportunities and challenges offered by practice-oriented research (POR). I also reviewed some previous research on practice-research networks and how that research might inform POR. The use of routine outcome monitoring (ROM), artificial intelligence (AI), and program evaluation (PE) models show promise for advancing POR. However, each comes with its challenges. The use of ROM to improve patient outcomes has research support. However, researchers have identified problems with implementing ROM because of low uptake by clinicians and because clinicians may see ROM as a potential intrusion. AI shows promise to improve patient outcomes by potentially providing therapists with immediate and nuanced data to inform interventions and interpersonal stances specific to each patient. However, the scaling up of AI runs the risk of dehumanizing psychological interventions. PE may provide a context for allowing therapists to engage in POR to address real-world processes and outcomes of mental health interventions. However, like ROM PE faces the challenge of trust among clinicians and patients who may be reluctant to participate. Despite these challenges, and because of efforts to nurture and maintain respectful collaborations, articles in this special issue highlight how POR can play a pivotal role in bridging the gap between theory and practice.
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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.