Health Promotion Education in India: Present Landscape and Future Vistas
Bibliographic record
Abstract
'Health promotion is the process of enabling people to increase control over and to improve their health'. This stream of public health is emerging as a critical domain within the realm of disease prevention. Over the last two decades, the curative model of health care has begun a subtle shift towards a participatory model of health promotion emphasizing upon practice of healthy lifestyles and creating healthy communities. Health promotion encompasses five key strategies with health communication and education as its cornerstones. Present study is an attempt to explore the current situation of health promotion education in India with an aim to provide a background for capacity building in health promotion. A systematic predefined method was adopted to collect and compile information on existing academic programs pertaining to health promotion and health education/communication. Results of the study reveal that currently health promotion education in India is fragmented and not uniform across institutes. It is yet to be recognized as a critical domain of public health education. Mostly teaching of health promotion is limited to health education and communication. There is a need for designing programmes for short-term and long-term capacity building, with focus on innovative methods and approaches. Public health institutes and associations could play a proactive role in designing and imparting academic programs on health promotion. Enhancing alliances with various institutes involved in health promotion activities and networking among public health and medical institutes as well as health services delivery systems would be more productive.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".