Volvamos Juntos: evaluation of the implementation of a Social Health Intervention to mitigate the impact of Covid-19 in businesses in Antofagasta, Chile
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has had an impact not only on healthcare but also on labor and socioeconomic sectors worldwide, leading to the development of strategies to mitigate the crisis' widespread repercussions. In Antofagasta, Chile, an innovation project entitled Volvamos Juntos ("Let's Return Together") was developed to support a diverse group of micro and small businesses. The project consisted of accompanying companies in the process of reopening safely and included interventions ranging from educating and testing employees for COVID-19 to developing protocols to avoid contagion and other preventive measures. The evaluation of the project's implementation is presented here. METHODS: A mixed-methods, collaborative study was conducted, adhering to the Consolidated Framework for Implementation Research (CFIR) and Proctor's Implementation Outcomes, with an online survey, interviews, and focus groups with businesses' representatives, the implementation team, and program stakeholders. Quantitative analyses were descriptive: frequencies and means were calculated, along with dispersion measures as appropriate, and in some cases, ANOVA tests were performed to assess differences. Qualitative information was processed with content analysis. Finally, an integrated hybrid analysis was conducted, guided by the study's objectives and theoretical framework. RESULTS: A total of 156 leaders from 203 participating businesses answered the online survey (response rate: 76.8%), and 46 people participated in the qualitative component (31 in interviews, 15 in focus groups). Overall, the program's implementation according to different CFIR dimensions and certain outcomes was evaluated satisfactorily. In the survey, 96.7% participants rated the program's suitability as satisfactory to maximum (grades 5 to 7 out of 7), 92.3% rated the feasibility with an average of 6.0, 97.4% rated the sustainability with an average of 5.9, and 94.3% indicated that they would favorably recommend (grades 6 or 7) the program to other institutions. Strengths and weaknesses were identified, and lessons learned include the need to plan for changing contexts, the relevance of collaborative and interdisciplinary work, and the importance of flexible support processes that promote autonomy and sustainability. CONCLUSIONS: Volvamos Juntos met its proposed implementation objectives, despite several challenges. Reflections from this innovative social health program are relevant for the development of other interventions in times of crisis. TRIAL REGISTRATION: N/A.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".