Local HIV/AIDS NGOs and Client Satisfaction: Dimensions and Explanatory Factors through a Multilevel Regression Analysis
Bibliographic record
Abstract
Background: HIV/AIDS Non-governmental organizations (NGOs) in Benin can use evaluations (including client satisfaction surveys) as tools to improve the effectiveness of their interventions. Objective: It is to identify the dimensions of NGO clients’ satisfaction and their associated factors. Methods: We conducted a cross-sectional survey of 2413 clients receiving both preventive and curative services from 31 NGOs working in HIV/AIDS prevention-screening and providing care to persons living with HIV. Results: We identified four dimensions of satisfaction relevant to our setting: reception and humane attitude, accessibility of care and resources, staff availability and competence and continuity of care. Individual factors [(age positively and gender (men negatively)] statistically significantly influenced global satisfaction and three of its four dimensions but the strength of these associations was too weak. Concerning organizational factors, involvement in evaluation had a negative effect on reception and humane attitude. A local source as principal source of funding was associated with greater satisfaction with accessibility of care and resources, while foreign partners as the principal source of funding were associated with greater satisfaction in terms of both global satisfaction and its dimensions, except for continuity of care. Organizational factors explain from 12.5% to 15.6% of the variance of global satisfaction and its dimensions (except for continuity of care). Conclusion: These information on the global satisfaction and its dimensions as well as the influencing factors are important for NGOs and their partners as these can help them to plan and implement actions to improve performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".