Unknown

Dataset Information

0

Model and approach for assessing implementation context and fidelity in the HEALing Communities Study.


ABSTRACT:

Background

In response to the U.S. opioid epidemic, the HEALing (Helping to End Addiction Long-termSM) Communities Study (HCS) is a multisite, wait-listed, community-level cluster-randomized trial that aims to test the novel Communities That HEAL (CTH) intervention, in 67 communities. CTH will expand an integrated set of evidence-based practices (EBPs) across health care, behavioral health, justice, and other community-based settings to reduce opioid overdose deaths. We present the rationale for and adaptation of the RE-AIM/PRISM framework and methodological approach used to capture the CTH implementation context and to evaluate implementation fidelity.

Methods

HCS measures key domains of the internal and external CTH implementation context with repeated annual surveys and qualitative interviews with community coalition members and key stakeholders. Core constructs of fidelity include dosage, adherence, quality, and program differentiation-the adaptation of the CTH intervention to fit each community's needs. Fidelity measures include a monthly CTH checklist, collation of artifacts produced during CTH activities, coalition and workgroup attendance, and coalition meeting minutes. Training and technical assistance delivered by the research sites to the communities are tracked monthly.

Discussion

To help attenuate the nation's opioid epidemic, the adoption of EBPs must be increased in communities. The HCS represents one of the largest and most complex implementation research experiments yet conducted. Our systematic examination of implementation context and fidelity will significantly advance understanding of how to best evaluate community-level implementation of EBPs and assess relations among implementation context, fidelity, and intervention impact.

SUBMITTER: Knudsen HK 

PROVIDER: S-EPMC7531282 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC8710122 | biostudies-literature
| S-EPMC7774649 | biostudies-literature
| S-EPMC7322847 | biostudies-literature
| S-EPMC7533113 | biostudies-literature
| S-EPMC7394176 | biostudies-literature
| S-EPMC7238406 | biostudies-literature
| S-EPMC7029500 | biostudies-literature
| S-EPMC6212575 | biostudies-literature
| S-EPMC7531340 | biostudies-literature
| S-EPMC7528891 | biostudies-literature