A comprehensive model of health education barriers of health-care system in Iran
Bibliographic record
Abstract
BACKGROUND: According to the importance of health education (HE) in disease control and prevention and inadequacy of HE in the Iran's health-care system, clarifying the HE barriers is necessary. OBJECTIVES: This study aimed to clarifying the comprehensive model of HE barriers of health-care system in Iran. METHODS: This qualitative study was conducted in 2019. Twenty-one health experts and physicians at different levels of the health system, a former health deputy of the Ministry of Health, and 26 community health workers (CHWs) were selected through purposive sampling. Data were collected through semi-structured individual interviews and group discussions and analyzed simultaneously by conventional content analysis. RESULTS: Five themes were extracted including individual barriers (most important categories: inadequate ability of CHWs in HE, poor motivational factors at individual level, and educator's wrong beliefs), interpersonal (most important categories: weakness of other health-care providers in the education of CHWs, lack of proper understanding by health authorities of scientific and correct HE, inappropriate communication, unrealistic expectations from CHWs, problems with monitoring and supervision, poor work commitment, and client-related problems), organizational (most important categories: high workload of CHWs, problems related to educational resources, inappropriate attitude of managers and officials, and inappropriate evaluation and monitoring), community (most important categories: not believing CHWs by people, people's disinterest and lack of motivation in education, cultural problems, problems with the Internet and virtual social networks, and weak cross-sectoral cooperation), and contextual barriers (most important categories: barriers related to universities, broadcasting, the nature of HE science, as well as gap between practical education and theory). CONCLUSION: Considering the multidimensional barriers such as individual, interpersonal, organizational, community, and contextual barriers, compiling and executing a comprehensive document with the participation of authorities, specialists, and service providers is recommended to remove barriers. This is in line with the Ottawa Charters' "reorienting health services."
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".