Assessing fidelity of cognitive behavioral therapy in rural VA clinics: design of a randomized implementation effectiveness (hybrid type III) trial

Cucciare, Michael A.; Curran, Geoffrey M.; Craske, Michelle G.; Abraham, Traci H.; McCarthur, Michael B.; Marchant-Miros, Kathy; Lindsay, Jan A.; Kauth, Michael R.; Landes, Sara J.; Sullivan, Greer

doi:10.1186/s13012-016-0432-4

Cited by 15 publications

(14 citation statements)

References 41 publications

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“…A large number of documents on computerized cognitive behavioral therapy (37 documents) were excluded because underlying methods were often unclear and reviews on these systems already exist. [39][40][41][42][43]…”

Section: Study Selection Title and Abstract Screeningmentioning

confidence: 99%

Artificial Intelligence and Primary Care Research: A Scoping Review

et al. 2020

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PURPOSE Rapid increases in technology and data motivate the application of artificial intelligence (AI) to primary care, but no comprehensive review exists to guide these efforts. Our objective was to assess the nature and extent of the body of research on AI for primary care. METHODSWe performed a scoping review, searching 11 published or gray literature databases with terms pertaining to AI (eg, machine learning, bayes* network) and primary care (eg, general pract*, nurse). We performed title and abstract and then full-text screening using Covidence. Studies had to involve research, include both AI and primary care, and be published in English. We extracted data and summarized studies by 7 attributes: purpose(s); author appointment(s); primary care function(s); intended end user(s); health condition(s); geographic location of data source; and AI subfield(s). RESULTSOf 5,515 unique documents, 405 met eligibility criteria. The body of research focused on developing or modifying AI methods (66.7%) to support physician diagnostic or treatment recommendations (36.5% and 13.8%), for chronic conditions, using data from higher-income countries. Few studies (14.1%) had even a single author with a primary care appointment. The predominant AI subfields were supervised machine learning (40.0%) and expert systems (22.2%).CONCLUSIONS Research on AI for primary care is at an early stage of maturity. For the field to progress, more interdisciplinary research teams with end-user engagement and evaluation studies are needed. Ann Fam Med 2020;18:250-258. https://doi.

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Section: Study Selection Title and Abstract Screeningmentioning

confidence: 99%

Artificial Intelligence and Primary Care Research: A Scoping Review

et al. 2020

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“…Our findings suggest that the likelihood of clinical uptake after training is also heavily influenced by implementation climate; leadership at call centers wishing to implement SPI will need to address center constraints that conflict with successful utilization of SPI (e.g., short call times, emphasis on current crisis). While studies examining both implementation and effectiveness during dissemination trials are becoming more common in other disciplines (Cucciare et al., ; Damschroder et al., ; Zatzick et al., ), this approach has only begun to be applied to suicide prevention (Stanley, ; Labouliere et al., ). Future studies should further investigate what differentiates settings that are and are not conducive to SPI, and how these obstacles to effective implementation can best be overcome.…”

Section: Discussionmentioning

confidence: 99%

Safety Planning on Crisis Lines: Feasibility, Acceptability, and Perceived Helpfulness of a Brief Intervention to Mitigate Future Suicide Risk

Labouliere

Stanley

Lake

et al. 2019

Suicide & Life Threat Behav

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Background The role of crisis hotlines traditionally was limited to de‐escalation and service linkage. However, hotlines are increasingly recruited to provide outreach and follow‐up to suicidal individuals. Hotlines have the opportunity to not just defuse current crises but also provide brief interventions to mitigate future risk. The Safety Planning Intervention (SPI) is a brief intervention designed to help manage suicidal crises, but its feasibility and effectiveness on hotlines are not established. Aims This study examined feasibility and perceived effectiveness of SPI, as reported by 271 crisis counselors at five centers in the National Suicide Prevention Lifeline network. Method Counselors were trained to use SPI. Self‐report surveys were completed immediately after training (time 1) and at the end of the study, approximately 9 months later (time 2). Results Counselors reported that SPI was feasible and helpful, and was used on both incoming and follow‐up calls. Utilization and perceived effectiveness at time 2 were predicted by self‐efficacy, feasibility, and helpfulness at time 1. Limitations Results are preliminary and limited to counselors’ perceptions. Future RCTs should establish efficacy of SPI for crisis callers. Conclusion The Safety Planning Intervention is a promising approach to reduce crisis callers’ future suicide risk that hotline counselors report is both feasible and helpful.

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“…39 Using the frameworks and study designs of implementation science, researchers have discovered the key barriers and facilitators to clinician and organizational use of CBT treatments, as well as the strategies critical to its implementation across diverse settings. [40][41][42][43][44] This success story can exist within obstetrics.…”

Section: The Methodologies Of Implementation Science: a Brief Overviewmentioning

confidence: 99%

Implementation Science is Imperative to the Optimization of Obstetric Care

2020

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In an effort aimed at improving outcomes, obstetric teams have enacted comprehensive care bundles and other clinical tools. Yet, these practices have had limited degrees of success on a national scale. Implementation science aims to bridge the divide between the development of evidence-based interventions and their real-world utilization. This emerging field takes into account key stakeholders at the clinician, institution, and health policy levels. Implementation science evaluates how well an intervention is or can be delivered, to whom, in which context, and how it may be up-scaled and sustained. Other medical disciplines have embraced these concepts with success. The frameworks and theories of implementation science can and should be incorporated into both obstetric research and practice. By doing so, we can increase widespread and timely adoption of evidence and further our common goal of decreasing maternal morbidity and mortality. Key Points

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Assessing fidelity of cognitive behavioral therapy in rural VA clinics: design of a randomized implementation effectiveness (hybrid type III) trial

Cited by 15 publications

References 41 publications

Artificial Intelligence and Primary Care Research: A Scoping Review

Artificial Intelligence and Primary Care Research: A Scoping Review

Safety Planning on Crisis Lines: Feasibility, Acceptability, and Perceived Helpfulness of a Brief Intervention to Mitigate Future Suicide Risk

Implementation Science is Imperative to the Optimization of Obstetric Care

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