Role of Socio-Psychological Factors in Perceived Quality of Care Rendered by Traditional Medical Practitioners in Ibadan, Nigeria
Bibliographic record
Abstract
BACKGROUND: It was the aim of the current research to investigate perceived service quality rendered by traditional medical practitioners and the role of socio-psychological factors in the perception. METHODS: The first part, a quantitative cross-sectional survey utilized a 93-item questionnaire to examine the influence of quality of life, general health perception, socio-economic status and personality factors on perceived service quality. The second part, a qualitative study utilized 5 FGDs and 2 KIIs to explore consumers' evaluation of perceived service quality. Five research questions were raised. The 336 purposively-selected participants were attendees of traditional-health clinics/centers in Ibadan with a mean age of x(-)=30.60±9.97. FINDINGS: The FGD respondents opined that the scope of orthodox-medicine does not cover certain illnesses. 77.8% of the participants attested to the affordability and promptness of services in traditional hospitals; acknowledging that its perceived efficacy (i.e. 56.8%) motivate patronage of traditional-health service. The 2x2x3 ANOVA revealed significant main effect of quality of life (F[1,270]=41.05, p<.001) and socio-economic status (F[2,270]=36.34; p<.001); as well as interaction effect of quality of life, general health and socio-economic status (F[1,270]=9.624, p<.002); while the regression analysis showed independent influence of extraversion (B= 0.31; p<.001), agreeableness (B=0.303; p<.001) and openness to experience (B=0.166; p<.01). CONCLUSION: This sample acknowledged that traditional health care met quality standards. The role of socio-psychological factors in the quality appraisal was established. The need for better regulation and validation of traditional health care in assuring evidence based care was suggested.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".