Sense of community and willingness to support malaria intervention programme in urban poor Accra, Ghana
Bibliographic record
Abstract
BACKGROUND: The extensive research on community members' willingness to support malaria interventions ignores the role of psychosocial determinants. This study assesses the impact of individuals' sense of community (perceptions of community cohesion, altruism, seeking help from neighbours and migrant status) on their willingness to participate in a mosquito control programme using data on 768 individuals from the 2013 RIPS Urban Health and Poverty Survey in poor coastal communities in Accra, Ghana. A contingent valuation experiment was employed to elicit individuals' willingness to support the programme by contributing nothing, labour time/money only or both. RESULTS: Findings show that different dimensions of sense of community related differently with willingness to support the programme. Perceived community cohesion was associated with lower odds while help-seeking from neighbours and being a migrant were associated with higher odds of supporting the programme. Altruism was the only dimension not linked to willingness to participate. CONCLUSIONS: Different dimensions of sense of community are associated with community members' willingness to provide labour, time or both to support the malaria eradication programme. The findings of this study have implications for targeting social relational aspects, in addition to geographical aspects, of communities with malaria-resilient policy and intervention. They also warrant further research on psychosocial factors that predict willingness to support health programmes in urban poor settings.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".