Qualitative researchers and program evaluators face a changing landscape of process evaluation frameworks in community mental health. The primary keyword for this guide is "process evaluation frameworks", and this post translates the findings of a comprehensive scoping review into practical, AI-enabled qualitative research workflows. The PLOS ONE scoping review by Mere et al. (published 28 July 2026) mapped 83 process evaluations published between 2006 and April 2025 and found a marked shift from participatory frameworks toward implementation science approaches. Read on for exact numbers, direct quotes from the study, a compact snapshot table, and step-by-step recommendations for using AI tools to preserve community voice while gaining systematized rigor.
Key Takeaways
According to the PLOS ONE scoping review by Mere et al. (published 28 July 2026), community mental health process evaluations shifted from participatory organizing frameworks toward implementation science frameworks across the 2006–2025 period. PLOS ONE
- 83 studies met inclusion criteria in the scoping review covering publications from 2006 through April 2025, as reported in Mere et al. (2026).
- The review identified 54 distinct primary frameworks used across those 83 studies, with implementation science frameworks comprising 39.8% (n = 33) of primary frameworks in the dataset (Mere et al., 2026).
- Participatory approaches appeared as the primary organizing framework in 23.8% of early publications (2006–2015) but were absent as primary frameworks after 2015, while implementation science frameworks rose to over 50% in 2016–2020, according to Mere et al. (2026).
- Geographic concentration was pronounced: 54.2% of included studies originated in North America and 83.1% were from high-income countries, per Mere et al. (2026).
- As the authors summarize, "The field has undergone a paradigm shift from community-engaged to systematized evaluation approaches, " and they note the research move toward "moving, perhaps, toward what might be called 'systematized participation'" (Mere et al., 2026).
What happened and how the review measured it
Answer: The PLOS ONE scoping review catalogued framework use in process evaluations of community mental health interventions and developed a typology to show trends and gaps.
According to Mere et al. (PLOS ONE, 28 July 2026), the authors searched PubMed, Web of Science, and EBSCOhost and screened 1, 143 records, ultimately including 83 studies published between January 2006 and April 2025.
The review extracted framework names, context, study design, and whether a framework was primary or secondary, then inductively organized 54 distinct primary frameworks into 14 categories based on theoretical orientation and stated function (Mere et al., 2026).
The authors measured temporal trends by dividing the period into 2006–2015, 2016–2020, and 2021–2025 and reported category-level percentages for each period to show the rise of implementation science frameworks and the decline of participatory primary frameworks (Mere et al., 2026).
Findings snapshot
| Date or period | Metric | Value (from Mere et al., 2026) | Implication for qualitative researchers |
|---|---|---|---|
| 2006–2025 | Records screened | 1, 143 records searched across 3 databases | Expect broad initial returns; plan deduplication and clear inclusion criteria |
| 2006–April 2025 | Studies included | 83 studies | Synthesis should compare frameworks across heterogeneous methods |
| 2006–2025 | Primary frameworks identified | 54 distinct frameworks organized into 14 categories | Prepare to document framework choice and rationale to aid comparability |
| As of April 2025 | Implementation science share | 39.8% of primary frameworks (n = 33) | Implementation science is now a common organizing lens; map its constructs to qualitative codes |
| 2006–2015 vs after 2015 | Participatory primary framework use | 23.8% in 2006–2015 (n = 5 early participatory studies); none as primary after 2015 | If community partnership is central, plan to embed participatory methods explicitly rather than assume they will appear |
| Geographic distribution | North America and high-income countries | North America 54.2%; High-income countries 83.1% | Guard against applying frameworks uncritically in low-resource or different cultural settings |
| Most-used individual frameworks | RE-AIM, CFIR, MRC | RE-AIM n = 9; CFIR n = 8; MRC n = 6 | These frameworks provide comparability but do not cover all community-engaged concerns |
Implications for qualitative researchers and evaluation teams
Answer: The PLOS ONE review implies that qualitative researchers must make explicit framework choices and protect community voice when implementation science frameworks dominate.
According to Mere et al. (2026), the shift toward implementation science increases methodological consistency but raises the risk that community participation is relegated from primary organizing logic to a secondary role.
Recommendation 1: State your evaluation question first, then pick a framework whose constructs match that question, as recommended by Mere et al. (PLOS ONE, 2026).
Recommendation 2: If your priority is community empowerment or partnership, plan participatory methods and name them as the primary organizing framework rather than treating participation as an add-on, because the review shows participatory approaches function differently than implementation science frameworks (Mere et al., 2026).
Recommendation 3: When working in low- and middle-income contexts, critically evaluate framework transferability: Mere et al. (2026) report only 14.4% of studies came from LMICs, signaling a gap in contextual validation.
How Evidano helps bridge participation and systematization
Definition: Evidano and its role
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano can ingest transcripts, coded notes, and framework checklists to produce thematic, frequency, and cross-segment analyses that make framework application transparent and auditable.
Problem: Framework fragmentation and opaque selection
Researchers face 54 distinct frameworks across 83 studies (Mere et al., 2026), making selection ad hoc and synthesis difficult.
Solution: Rapid mapping from data to framework constructs
Evidano can import transcripts and code them against CFIR, RE-AIM, MRC, or custom participatory constructs, then produce crosswalks that show which data support which framework domains.
Use the Evidano features for thematic coding, cross-segmentation, and co-occurrence networks to compare how implementation science and participatory lenses illuminate the same dataset.
Problem: Losing community voice in systematized evaluations
Mere et al. (2026) observed participatory frameworks being displaced as primary organizing structures after 2015, even when community input remained present as secondary data.
Solution: Preserve participatory interpretation with AI-assisted workflows
Evidano supports analyst-defined codebooks and stakeholder-accessible reports so community co-analysts can review AI-generated themes and correct misclassifications, preserving partnership while achieving reproducible structure.
For participatory coding cycles, Evidano’s transcription and PII redaction options let teams safely share de-identified materials for community co-analysis and for audit trails required by funders.
Problem: Synthesizing multi-framework evidence
Mere et al. (2026) show most studies reference secondary frameworks (73% of studies), producing multi-theoretical datasets that are hard to compare.
Solution: Cross-framework synthesis and visualization
Evidano can run parallel code schemas (for example CFIR and CBPR constructs) and generate frequency tables and co-occurrence networks that show where frameworks overlap or diverge, helping teams answer the question: which framework best captures our evaluation questions?
FAQ: process evaluation frameworks
What are the dominant process evaluation frameworks used in community mental health?
Answer: Implementation science frameworks (CFIR, RE-AIM, process frameworks) are dominant according to Mere et al. (PLOS ONE, 28 July 2026).
Mere et al. (2026) report implementation science frameworks accounted for 39.8% (n = 33) of primary frameworks in the 83 included studies, with CFIR and RE-AIM among the most cited individual frameworks.
Did participatory approaches disappear after 2015?
Answer: Participatory approaches stopped appearing as primary frameworks after 2015 in the review, but they continued to appear as secondary frameworks in later studies.
Mere et al. (2026) found that participatory frameworks were primary in 23.8% of studies in 2006–2015 (five studies) and none as primary after 2015; however CBPR and related approaches appeared as secondary frameworks in eight later studies, indicating repositioning rather than total disappearance.
How should I choose a framework for a community mental health process evaluation?
Answer: Choose a framework that aligns explicitly with your primary evaluation questions and document that choice, the PLOS ONE review recommends.
Mere et al. (2026) advise matching questions to framework function: determinant frameworks for identifying implementation barriers, evaluation frameworks for reach and adoption, and participatory frameworks when partnership, empowerment, or community-defined outcomes are central.
How can AI tools like Evidano reduce the risk of losing community voice?
Answer: AI can automate coding and visualization while keeping community reviewers in the loop to validate and reinterpret analytic outputs.
Mere et al. (2026) highlight the shift toward systematization; Evidano’s workflow lets teams run structured, implementation-focused analyses and then openly compare results with participatory codes that community members co-develop, preserving partnership while producing reproducible results.
Are the review findings generalizable globally?
Answer: Generalizability is limited because the review’s literature is concentrated in high-income countries, as the authors note.
Mere et al. (2026) report 83.1% of studies came from high-income countries and only 14.4% were from low- and middle-income countries, so researchers should treat framework transferability across contexts cautiously and prioritize local validation.
Conclusion & Next Steps
The PLOS ONE scoping review by Mere et al. (published 28 July 2026) documents a clear movement from participatory organizing frameworks toward implementation science frameworks across 2006–2025, and it recommends deliberate framework choice and attention to equity and participation.
Qualitative researchers should make framework selection explicit, justify trade-offs, and consider dual workflows that privilege community co-analysis alongside systematized constructs, as suggested by Mere et al. (2026).
Evidano can help operationalize that dual workflow by importing transcripts, running parallel codebooks, and producing auditable crosswalks between implementation science constructs and participatory codes; see Evidano features for capabilities.
Next step: pilot a dual analysis on a small dataset to compare what implementation science and participatory lenses reveal, then scale with reproducible codebooks and stakeholder review.
Get started now: Try Evidano for free.