Systematized Participation: Process Evaluation Frameworks

Process evaluation frameworks are the conceptual tools researchers use to ask how and why community mental health interventions work in real settings. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to the PLOS One scoping review by Mere et al. published July 28, 2026, the literature on process evaluation frameworks in community mental health has shifted from participatory approaches toward implementation science between 2006 and 2025. Researchers and program leads need concrete guidance for framework selection and for preserving community voice while achieving methodological consistency. This post refracts the PLOS One findings through the lens of AI-enabled qualitative research, offering an evidence-based checklist and tools that qualitative teams can adopt immediately.

Key Takeaways

According to the July 28, 2026 PLOS One scoping review by Mere et al., community mental health process evaluations published between 2006 and 2025 show a major shift from participatory frameworks to implementation science frameworks; see the original article in PLOS One.

The review identified 83 studies published between 2006 and 2025 and 54 distinct primary frameworks, demonstrating both growth and fragmentation in the field.
Implementation science frameworks accounted for 39.8% of primary frameworks overall, rising from 14.3% in 2006–2015 to over 50% in 2016–2020, according to Mere et al. (PLOS One, July 28, 2026).
Participatory primary frameworks fell from 23.8% of studies in 2006–2015 to zero as a primary framework after 2015, though participatory elements persisted as secondary frameworks, Mere et al. reported in July 2026.
Geographic concentration was pronounced: 54.2% of included studies originated in North America and 83.1% in high-income countries, raising questions about global generalizability (Mere et al., PLOS One, 2026).
"From participation to systematization" captures the authors' framing of this trend, and they warn that systematization risks marginalizing community voice if participation is only treated as a secondary consideration (Mere et al., 2026).

What happened: who, when, and how the review measured change

The PLOS One scoping review by Mere et al. mapped framework use in process evaluations of community mental health interventions published between January 2006 and April 2025 and found 83 eligible studies.

Mere et al. searched PubMed, Web of Science, and EBSCOhost, screened 1, 143 records, and used an inductive coding process to group 54 named primary frameworks into 14 categories and to report temporal trends across three periods: 2006–2015, 2016–2020, and 2021–2025.

Mere et al. measured framework frequency, geographic distribution, and whether studies reported secondary frameworks; they recorded concrete counts such as RE-AIM appearing in 9 studies and CFIR in 8 studies.

Findings snapshot

Date / Period	Metric	Value (from Mere et al., PLOS One, July 28, 2026)	Implication
2006–2015	Participatory primary frameworks	23.8% of studies	Early literature prioritized community-engaged designs
2016–2020	Implementation science primary frameworks	52.0% of studies	Rapid adoption of systematized frameworks
2021–2025	Studies published	44.6% of the 83 studies	Recent surge in process evaluation reporting
2006–2025 (overall)	Distinct primary frameworks	54 frameworks across 83 studies	High fragmentation at the framework level
Geographic distribution (overall)	North America share	54.2% of studies	Potential bias toward high-income context assumptions

Implications for qualitative researchers and evaluation teams

How should I pick a framework for a community mental health process evaluation?

Choose a framework based on your primary evaluation question, not trendiness: determinant frameworks like CFIR suit questions about implementation barriers and facilitators, while evaluation frameworks like RE-AIM suit questions about reach and sustainability, as summarized by Mere et al. (PLOS One, July 28, 2026).

If community empowerment or partnership is a goal, explicitly select a participatory or hybrid approach and document how participation shapes methods rather than treating it as an afterthought.

What does the shift to implementation science mean for community voice?

The shift documented by Mere et al. (PLOS One, 2026) means many studies now adopt researcher-led frameworks; community engagement often appears as a secondary rather than primary framework.

Evaluation teams that want to maintain meaningful participation should embed participatory practices in study governance, instrument design, and analysis plans rather than only collecting stakeholder feedback.

How should low- and middle-income country teams adapt these findings?

Because Mere et al. found 83.1% of studies originated in high-income countries, teams in LMIC should treat dominant frameworks as starting points and prioritize contextual adaptation and co-design.

The World Health Organization mhGAP guidance provides implementation principles for low-resource settings that can be combined with local participatory practice; see the WHO mhGAP materials for practical adaptation strategies.

How Evidano helps in framework-driven qualitative process evaluation

Problem: Fragmented frameworks slow synthesis → Solution: Rapid, comparable coding

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

Evidano supports thematic, content, frequency, and cross-segment analyses so teams can apply a chosen framework (for example CFIR or RE-AIM) across interviews and documents and produce standardized codebooks and cross-site comparisons; learn more on our features page.

Problem: Participation gets sidelined → Solution: document and surface community input

Evidano can ingest transcripts, community advisory notes, and meeting minutes and then generate a stakeholder-coded dataset that preserves who said what, enabling transparent tracing of community contributions back to analytic claims.

Evidano supports AI chat over your documents so teams can query where community voices appear in the data and produce reports that explicitly show how participatory input influenced decisions; see AI chat over your documents.

Problem: Multisite synthesis is slow → Solution: harmonize codes and frequency summaries

Evidano produces hierarchical code trees, frequency tables, and cross-segment comparisons automatically, which speeds synthesis across sites using different frameworks while preserving local nuance.

Teams can use Evidano to export standardized summary tables that align with framework constructs (for example mapping CFIR constructs to site-level implementation barriers).

FAQ: process evaluation frameworks

What is the single best framework for community mental health process evaluation?

There is no single best framework; the answer depends on your evaluation question and context.

Mere et al. (PLOS One, July 28, 2026) found that implementation science categories dominate but no single framework covers more than about 11% of studies, so select frameworks by function (determinant, evaluation, process) and consider hybridization.

Did participatory frameworks disappear after 2015?

Participatory frameworks ceased to appear as primary organizing frameworks after 2015 but continued as secondary frameworks in later studies, according to Mere et al. (PLOS One, 2026).

The disappearance as primary frameworks suggests a repositioning rather than a wholesale rejection, so teams seeking participation should declare participatory methods as primary and describe how they shape design and analysis.

How can I preserve community voice while using an implementation science framework?

You can preserve community voice by making participation a core design decision: co-create the evaluation questions, co-develop instruments, code jointly with community partners, and report partnership processes alongside implementation outcomes.

Evidano can operationalize this by tagging speaker roles in transcripts and producing reports that separate community-derived codes from researcher-derived codes.

Will using implementation frameworks improve comparability across studies?

Yes, using shared implementation frameworks increases comparability, but Mere et al. (PLOS One, 2026) caution that framework-level fragmentation still limits synthesis unless teams align specific constructs and measures.

Practical steps include publishing codebooks, mapping measures to framework constructs, and sharing data extracts for meta-synthesis.

Conclusion & Next Steps

The PLOS One scoping review by Mere et al. (published July 28, 2026) documents a clear shift from participatory to implementation science frameworks in community mental health process evaluations, with 83 studies and 54 primary frameworks identified between 2006 and 2025.

Researchers should choose frameworks according to evaluation purpose, document participatory processes when used, and consider hybrid designs that embed community partnership within systematized frameworks.

Evidano can accelerate transparent, participatory-aligned analysis by standardizing coding, preserving speaker roles, and producing cross-site summaries that map directly to framework constructs; learn more on our features page.

If you want to pilot these approaches on your transcripts, survey text, or meeting notes, Try Evidano for free.

Topics

process evaluation frameworks
community mental health process evaluation
participatory evaluation frameworks
implementation science frameworks

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Systematized Participation: Process Evaluation Frameworks

Key Takeaways

What happened: who, when, and how the review measured change

Findings snapshot

Implications for qualitative researchers and evaluation teams

How should I pick a framework for a community mental health process evaluation?

What does the shift to implementation science mean for community voice?

How should low- and middle-income country teams adapt these findings?

How Evidano helps in framework-driven qualitative process evaluation

Problem: Fragmented frameworks slow synthesis → Solution: Rapid, comparable coding

Problem: Participation gets sidelined → Solution: document and surface community input

Problem: Multisite synthesis is slow → Solution: harmonize codes and frequency summaries

FAQ: process evaluation frameworks

What is the single best framework for community mental health process evaluation?

Did participatory frameworks disappear after 2015?

How can I preserve community voice while using an implementation science framework?

Will using implementation frameworks improve comparability across studies?

Conclusion & Next Steps

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