Applying FRAME-IS to Characterize Provider-led Adaptations to a Cervical Cancer Prevention Intervention in Kenya

Applying FRAME-IS to Characterize Provider-led Adaptations to a Cervical Cancer Prevention Intervention in Kenya | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Applying FRAME-IS to Characterize Provider-led Adaptations to a Cervical Cancer Prevention Intervention in Kenya Harriet Fridah Adhiambo, Kathy Thomas, Megan Coe, Lynda Oluoch, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6933921/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Feb, 2026 Read the published version in Implementation Science Communications → Version 1 posted 5 You are reading this latest preprint version Abstract Background Implementation strategies that are contextually refined are essential for optimizing the delivery of evidence-based interventions (EBI) to prevent cervical cancer in low-resource settings. This paper reports the application of the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) to capture and disseminate strategy adaptations made to a single-visit, screen-and-treat approach with thermal ablation (SVSAT+ TA) strategy aimed at establishing sustainable cervical cancer prevention services in Kenya. Methods A FRAME-IS-based tracking spreadsheet was developed for data collection across 10 facilities during technical assistants' (TAs) site visits, phone calls, and monthly meetings with health providers between March 2023 and September 2024. Sources included tracking spreadsheets, TA narrative reports, and field notes from direct observations during the implementation phase. Descriptive statistics summarized site characteristics and adaptation trends. The exact Poisson test compared adaptation rates by facility level and period (early vs late). Results A total of 28 adaptations were identified. Most adaptations (70%, n=20) occurred in the early phase. Over half were planned (57%, n=16). We made modifications to module two (What was modified). Educational adaptations were most common (57%, n=16), primarily targeting providers delivering screening and treatment services. Resources-related adaptations accounted for 21% (n=6). Additionally, 43% (n=12) of the adaptations aimed to increase adoption by expanding the number of clinicians offering the SV-SAT+TA. Nearly half (46%, n=13) targeted the organization level. Over six months, Level five facilities had 2.67 adaptations per facility, compared to 2.85 in Level four facilities (rate ratio = 0.93 (95% CI = 0.39-2.08, p = 0.89), indicating no statistically significant difference in adaptation rates by facility levels. However, adaptation rates significantly declined, from 2.0 per facility in the early phase to 0.80 in the late phase (rate ratio = 2.50, 95% CI: 1.12–6.02, p = 0.02), suggesting a reduction in adaptations over time. Conclusion Education and resource-related adaptations were critical to improving SV-SAT+TA implementation. Future research should focus on evaluating the impact of these adaptations on implementation and clinical outcomes, refining the FRAME-IS framework, and supporting the establishment of an adaptome to guide scalable strategies in similar settings. Trial registration: NCT05472311. Cervical cancer adaptations implementation strategies FRAME-IS thermal ablation screen and treat. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Additional Declarations Table 1 to 3 are available in the Supplementary Files section. Supplementary Files Table1ParticipantCharacteristics.docx Table2AdaptationTypes.docx Table3ChangeinAdaptationRates.docx STROBEchecklistv4combined.docx Cite Share Download PDF Status: Published Journal Publication published 24 Feb, 2026 Read the published version in Implementation Science Communications → Version 1 posted Editorial decision: Major revision 09 Sep, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers invited by journal 13 Jul, 2025 Editor assigned by journal 24 Jun, 2025 First submitted to journal 23 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6933921","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484683576,"identity":"a2a39b95-b3a5-40cc-a302-6d6887f75541","order_by":0,"name":"Harriet Fridah 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This paper reports the application of the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) to capture and disseminate strategy adaptations made to a single-visit, screen-and-treat approach with thermal ablation (SVSAT+ TA) strategy aimed at establishing sustainable cervical cancer prevention services in Kenya.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA FRAME-IS-based tracking spreadsheet was developed for data collection across 10 facilities during technical assistants' (TAs) site visits, phone calls, and monthly meetings with health providers between March 2023 and September 2024. Sources included tracking spreadsheets, TA narrative reports, and field notes from direct observations during the implementation phase. Descriptive statistics summarized site characteristics and adaptation trends. The exact Poisson test compared adaptation rates by facility level and period (early vs late).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 28 adaptations were identified. Most adaptations (70%, n=20) occurred in the early phase. Over half were planned (57%, n=16). We made modifications to module two (What was modified). Educational adaptations were most common (57%, n=16), primarily targeting providers delivering screening and treatment services. Resources-related adaptations accounted for 21% (n=6). Additionally, 43% (n=12) of the adaptations aimed to increase adoption by expanding the number of clinicians offering the SV-SAT+TA. Nearly half (46%, n=13) targeted the organization level.\u003c/p\u003e\n\u003cp\u003eOver six months, Level five facilities had 2.67 adaptations per facility, compared to 2.85 in Level four facilities (rate ratio = 0.93 (95% CI = 0.39-2.08, p = 0.89), indicating no statistically significant difference in adaptation rates by facility levels. However, adaptation rates significantly declined, from 2.0 per facility in the early phase to 0.80 in the late phase (rate ratio = 2.50, 95% CI: 1.12–6.02, p = 0.02), suggesting a reduction in adaptations over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEducation and resource-related adaptations were critical to improving SV-SAT+TA implementation. 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