Mixed methods evaluation of implementation and outcomes in a community-based cancer prevention intervention

dc.contributor.authorKing, Emily S.en
dc.contributor.authorMoore, Carla J.en
dc.contributor.authorWilson, Hannah K.en
dc.contributor.authorHarden, Samantha M.en
dc.contributor.authorDavis, Marshaen
dc.contributor.authorBerg, Alison C.en
dc.contributor.departmentHuman Nutrition, Foods, and Exerciseen
dc.date.accessioned2019-08-12T14:13:06Zen
dc.date.available2019-08-12T14:13:06Zen
dc.date.issued2019-08-05en
dc.date.updated2019-08-11T03:21:08Zen
dc.description.abstractBackground Community-based educational programs can complement clinical strategies to increase cancer screenings and encourage healthier lifestyles to reduce cancer burden. However, implementation quality can influence program outcomes and is rarely formally evaluated in community settings. This mixed-methods study aimed to characterize implementation of a community-based cancer prevention program using the Consolidated Framework for Implementation Research (CFIR), determine if implementation was related to participant outcomes, and identify barriers and facilitators to implementation that could be addressed. Methods This study utilized quantitative participant evaluation data (n = 115) and quantitative and qualitative data from semi-structured interviews with program instructors (N = 13). At the participant level, demographic data (age, sex, insurance status) and behavior change intention were captured. Instructor data included implementation of program components and program attendance to create a 7-point implementation score of fidelity and reach variables. Degree of program implementation (high and low) was operationalized based on these variables (low: 0–4, high: 5–7). Relationships among degree of implementation, participant demographics, and participant outcomes (e.g., intent to be physically active or limit alcohol) were assessed using linear or ordinal logistic mixed effects models as appropriate. Interview data were transcribed and coded deductively for CFIR constructs, and constructs were then rated for magnitude and valence. Patterns between ratings of high and low implementation programs were used to determine constructs that manifested as barriers or facilitators. Results Program implementation varied with scores ranging from 4 to 7. High implementation was related to greater improvements in intention to be physically active (p <  0.05), achieve a healthy weight (p <  0.05), and limit alcohol (p <  0.01). Eight constructs distinguished between high and low implementation programs. Design quality and packaging, compatibility, external change agents, access to knowledge and information, and experience were facilitators of implementation and formally appointed internal implementation leaders was a barrier to implementation. Conclusions As higher implementation was related to improved participant outcomes, program administrators should emphasize the importance of fidelity in training for program instructors. The CFIR can be used to identify barriers and/or facilitators to implementation in community interventions, but results may be unique from clinical contexts.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationBMC Public Health. 2019 Aug 05;19(1):1051en
dc.identifier.doihttps://doi.org/10.1186/s12889-019-7315-yen
dc.identifier.urihttp://hdl.handle.net/10919/93025en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderThe Author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleMixed methods evaluation of implementation and outcomes in a community-based cancer prevention interventionen
dc.title.serialBMC Public Healthen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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