Process evaluation frameworks in community mental health guide which implementation questions researchers ask and which data they collect, and the primary keyword for this post is process evaluation frameworks community mental health. A July 28, 2026 scoping review in PLOS One by Mere et al. mapped framework use in community mental health process evaluations published between 2006 and April 2025, finding clear temporal and geographic patterns. According to Mere et al. in PLOS One, the review included 83 studies and organized 54 distinct primary frameworks into a 14-category typology, revealing that implementation science frameworks became dominant while participatory frameworks declined as primary organizing approaches after 2015. Researchers and qualitative teams designing process evaluations need practical, reproducible ways to match evaluation questions to frameworks and to preserve community voice while using systematized tools.
Key Takeaways
According to the PLOS One scoping review, process evaluation in community mental health shifted from participatory frameworks toward implementation science between 2006 and April 2025; the review mapped 83 studies and 54 primary frameworks across 14 categories (PLOS One). "The field has undergone a paradigm shift from community-engaged to systematized evaluation approaches, " the authors write (Mere et al., 2026).
- Mere et al. identified 83 studies published between 2006 and April 2025 and extracted 54 distinct primary frameworks, reported in PLOS One on July 28, 2026.
- Implementation science frameworks accounted for 39.8% of primary frameworks overall, rising from 14.3% in 2006–2015 to 52.0% in 2016–2020, according to Mere et al. in PLOS One.
- Participatory frameworks were primary in 23.8% of studies in 2006–2015 but appeared as primary frameworks in zero studies after 2015, according to Mere et al. in PLOS One.
- Geographic concentration was pronounced: 54.2% of included studies originated in North America and 83.1% in high-income countries, reported by Mere et al. in PLOS One.
What happened and how the review measured it
The PLOS One scoping review found a measurable shift from participatory to implementation science frameworks in community mental health process evaluations between 2006 and April 2025.
According to Mere et al. in PLOS One, the authors searched PubMed, Web of Science, and EBSCOhost and screened 1, 143 records to arrive at 83 included studies; data extraction captured framework names, primary versus secondary use, geographic setting, study design, and publication year.
The review used an inductive typology-building process that organized 54 primary frameworks into 14 categories, with implementation science frameworks (determinant, evaluation, and process subtypes) dominating the landscape, as reported in PLOS One.
Findings Snapshot
| Date or period | Metric | Value (from PLOS One) | Implication |
|---|---|---|---|
| 2006–April 2025 | Studies included | 83 | Comprehensive mapping of framework use in community mental health process evaluations |
| 2006–2025 | Distinct primary frameworks identified | 54 | High fragmentation at the individual framework level despite category consolidation |
| 2006–2015 | Primary use of participatory frameworks | 23.8% | Participatory approaches were visible as organizing frameworks early in the period |
| 2016–2020 | Implementation science share | 52.0% | Implementation science became dominant in mid period |
| 2021–2025 | Studies published in recent period | 44.6% of all included studies | Rapid growth in process evaluation activity reported by Mere et al. |
| Overall | Top individual frameworks (counts) | RE-AIM (9), CFIR (8), MRC Framework (6) | No single framework exceeds ~11% of studies, indicating fragmentation |
| Geographic | North America share | 54.2% | Findings concentrated in high-income settings |
Implications for qualitative researchers and UX/implementation teams
Researchers should choose frameworks that match their primary evaluation questions rather than picking a framework for prestige, according to recommendations drawn from the PLOS One review.
According to Mere et al. in PLOS One, determinant frameworks like CFIR are best when the goal is to identify implementation barriers and facilitators, evaluation frameworks like RE-AIM suit questions about reach and sustainability, and process frameworks guide attention to stages and activities.
According to Mere et al. in PLOS One, the decline of participatory frameworks as primary organizing approaches after 2015 raises the risk that community voice is positioned as supplementary rather than central, so researchers designing qualitative components should explicitly document how community input shaped study questions, instruments, and interpretation.
How Evidano helps researchers bridge participation and systematization
Problem: Fragmented frameworks make qualitative synthesis slow
Solution: Evidano supports rapid ingestion and harmonization of heterogeneous qualitative data and framework constructs to accelerate synthesis.
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano can ingest interview transcripts and codebooks, map extracted themes to CFIR, RE-AIM, MRC, or user-defined frameworks, and quantify theme frequencies and cross-segment patterns to make fragmented frameworks comparable.
Problem: Preserving community voice while applying systematized frameworks
Solution: Evidano enables mixed analytic workflows that combine inductive coding with deductive framework mapping so participatory findings remain visible within implementation science structures.
Evidano supports thematic and cross-segment analysis plus AI chat over your documents to surface participant quotations tied to specific framework constructs, helping teams demonstrate where community input changed interpretations.
Learn more about relevant capabilities on the Evidano features page.
Problem: Secure, scalable processing of qualitative data
Solution: Evidano provides encrypted ingestion, transcription options, and PII redaction to support ethical qualitative analysis workflows.
Evidano offers transcription and PII redaction workflows and uses proprietary LLMs that are not used to train third-party models, addressing data security concerns for sensitive mental health data; see our data security page for details.
FAQ: process evaluation frameworks community mental health
Which framework should I pick for a community mental health process evaluation?
Answer: Match your primary evaluation question to framework function rather than adopting a framework by name.
According to Mere et al. in PLOS One, determinant frameworks like CFIR suit studies aiming to identify implementation barriers, evaluation frameworks like RE-AIM fit studies focused on reach and maintenance, and program theory approaches suit testing intervention logic.
If your goal is to preserve community partnership as central, consider embedding participatory methods even if you use an implementation science framework as the primary organizing tool, as Mere et al. noted that participatory approaches often appear as secondary frameworks after 2015.
Did participatory frameworks disappear after 2015?
Answer: Participatory frameworks stopped appearing as primary organizing frameworks after 2015 in the PLOS One sample, but they continued as secondary frameworks.
Mere et al. reported that 23.8% of studies in 2006–2015 used participatory approaches as primary frameworks, and none used them as primary frameworks after 2015, though CBPR and related approaches still appeared as secondary frameworks in later studies.
How many frameworks did the review identify and how fragmented is the field?
Answer: The review identified 54 distinct primary frameworks across 83 studies, indicating high fragmentation at the framework level.
Mere et al. reported 54 distinct primary frameworks organized into 14 categories, and only three frameworks (RE-AIM, CFIR, MRC) appeared in more than five studies, accounting for 27.7% of studies collectively.
How can AI tools preserve community voice while applying systematized frameworks?
Answer: Use AI-enabled workflows that combine inductive coding for emergent community themes with deductive mapping to established framework constructs.
Evidano and similar platforms can extract verbatim participant quotations, tag them to both inductive codes and framework constructs, and quantify their distribution, enabling transparent demonstration of how community input shaped conclusions.
Conclusion & Next Steps
The PLOS One scoping review by Mere et al. documents a measurable shift in community mental health process evaluation from participatory organizing frameworks toward implementation science between 2006 and April 2025, and it highlights both the benefits of systematization and the risk of sidelining community partnership.
Qualitative and implementation teams should document framework choice, preserve participatory data through mixed analytic workflows, and adopt tools that make emergent community themes auditable within systematized frameworks.
If you run process evaluations and want to accelerate thematic synthesis, preserve participant quotations mapped to multiple frameworks, and keep sensitive data secure, Try Evidano for free.