Dataset Information

Methods for capturing and analyzing adaptations: implications for implementation research.

ABSTRACT:

Background

Interventions are often adapted; some adaptations may provoke more favorable outcomes, whereas some may not. A better understanding of the adaptations and their intended goals may elucidate which adaptations produce better outcomes. Improved methods are needed to better capture and characterize the impact of intervention adaptations.

Methods

We used multiple data collection and analytic methods to characterize adaptations made by practices participating in a hybrid effectiveness-implementation study of a complex, multicomponent diabetes intervention. Data collection methods to identify adaptations included interviews, observations, and facilitator sessions resulting in transcripts, templated notes, and field notes. Adaptations gleaned from these sources were reduced and combined; then, their components were cataloged according to the framework for reporting adaptations and modifications to evidence-based interventions (FRAME). Analytic methods to characterize adaptations included a co-occurrence table, statistically based k-means clustering, and a taxonomic analysis.

Results

We found that (1) different data collection methods elicited more overall adaptations, (2) multiple data collection methods provided understanding of the components of and reasons for adaptation, and (3) analytic methods revealed ways that adaptation components cluster together in unique patterns producing adaptation "types." These types may be useful for understanding how the "who, what, how, and why" of adaptations may fit together and for analyzing with outcome data to determine if the adaptations produce more favorable outcomes rather than by adaptation components individually.

Conclusion

Adaptations were prevalent and discoverable through different methods. Enhancing methods to describe adaptations may better illuminate what works in providing improved intervention fit within context.

Trial registration

This trial is registered on clinicaltrials.gov under Trial number NCT03590041 , posted July 18, 2018.

SUBMITTER: Holtrop JS

PROVIDER: S-EPMC9335955 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Methods for capturing and analyzing adaptations: implications for implementation research.

Holtrop Jodi Summers JS Gurfinkel Dennis D Nederveld Andrea A Phimphasone-Brady Phoutdavone P Hosokawa Patrick P Rubinson Claude C Waxmonsky Jeanette A JA Kwan Bethany M BM

Implementation science : IS 20220729 1

<h4>Background</h4>Interventions are often adapted; some adaptations may provoke more favorable outcomes, whereas some may not. A better understanding of the adaptations and their intended goals may elucidate which adaptations produce better outcomes. Improved methods are needed to better capture and characterize the impact of intervention adaptations.<h4>Methods</h4>We used multiple data collection and analytic methods to characterize adaptations made by practices participating in a hybrid effe ...[more]

PMID: 35906602

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Project description:BackgroundDeveloping effective implementation strategies requires adequate tracking and reporting on their application. Guidelines exist for defining and reporting on implementation strategy characteristics, but not for describing how strategies are adapted and modified in practice. We built on existing implementation science methods to provide novel methods for tracking strategy modifications.MethodsThese methods were developed within a stepped-wedge trial of an implementation strategy package designed to help community clinics adopt social determinants of health-related activities: in brief, an 'Implementation Support Team' supports clinics through a multi-step process. These methods involve five components: 1) describe planned strategy; 2) track its use; 3) monitor barriers; 4) describe modifications; and 5) identify / describe new strategies. We used the Expert Recommendations for Implementing Change taxonomy to categorize strategies, Proctor et al.'s reporting framework to describe them, the Consolidated Framework for Implementation Research to code barriers / contextual factors necessitating modifications, and elements of the Framework for Reporting Adaptations and Modifications-Enhanced to describe strategy modifications.ResultsWe present three examples of the use of these methods: 1) modifications made to a facilitation-focused strategy (clinics reported that certain meetings were too frequent, so their frequency was reduced in subsequent wedges); 2) a clinic-level strategy addition which involved connecting one study clinic seeking help with community health worker-related workflows to another that already had such a workflow in place; 3) a study-level strategy addition which involved providing assistance in overcoming previously encountered (rather than de novo) challenges.ConclusionsThese methods for tracking modifications made to implementation strategies build on existing methods, frameworks, and guidelines; however, as none of these were a perfect fit, we made additions to several frameworks as indicated, and used certain frameworks' components selectively. While these methods are time-intensive, and more work is needed to streamline them, they are among the first such methods presented to implementation science. As such, they may be used in research on assessing effective strategy modifications and for replication and scale-up of effective strategies. We present these methods to guide others seeking to document implementation strategies and modifications to their studies.Trial registrationclinicaltrials.gov ID: NCT03607617 (first posted 31/07/2018).

Project description:BackgroundSelf-management is essential for good outcomes in type 2 diabetes and patients often benefit from self-management education. Shared medical appointments (SMAs) can increase self-efficacy for self management but are difficult for some primary care practices to implement. Understanding how practices adapt processes and delivery of SMAs for patients with type 2 diabetes may provide helpful strategies for other practices interested in implementing SMAs.MethodsThe Invested in Diabetes study was a pragmatic cluster-randomized, comparative effectiveness trial designed to compare two different models of diabetes SMAs delivered in primary care. We used a multi-method approach guided by the FRAME to assess practices' experience with implementation, including any planned and unplanned adaptations. Data sources included interviews, practice observations and field notes from practice facilitator check-ins.ResultsSeveral findings were identified from the data: 1) Modifications and adaptations are common in implementation of SMAs, 2) while most adaptations were fidelity-consistent supporting the core components of the intervention conditions as designed, some were not, 3) Adaptations were perceived to be necessary to help SMAs meet patient and practice needs and overcome implementation challenges, and 4) Content changes in the sessions were often planned and enacted to better address the contextual circumstances such as patient needs and culture.DiscussionImplementing SMAs in primary care can be challenging and adaptations of both implementation processes and content and delivery of SMAS for patients with type 2 diabetes were common in the Invested in Diabetes study. Recognizing the need for adaptations based on practice context prior to implementation may help improve fit and success with SMAs, but care needs to be given to ensure that adaptations do not weaken the impact of the intervention. Practices may be able to assess what might need to adapted for them to be successful prior to implementation but likely will continue to adapt after implementation.ConclusionAdaptations were common in the Invested in Diabetes study. Practices may benefit from understanding common challenges in implementing SMAs and adapting processes and delivery based on their own context.Trial registrationThis trial is registered on clinicaltrials.gov under Trial number NCT03590041, posted 18/07/2018.

Dataset Information

Methods for capturing and analyzing adaptations: implications for implementation research.

Background

Methods

Results

Conclusion

Trial registration

Publications

Methods for capturing and analyzing adaptations: implications for implementation research.

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