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Record W2106854666 · doi:10.5539/gjhs.v4n4p159

Health Promotion Education in India: Present Landscape and Future Vistas

2012· article· en· W2106854666 on OpenAlexvenueno aff
Sanghamitra Pati, Kavya Sharma, Sanjay Zodpey, Kavita Chauhan, Madhumita Dobe

Bibliographic record

VenueGlobal Journal of Health Science · 2012
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionHealth educationPublic healthPublic relationsHealth policyCitizen journalismHealth carePromotion (chess)HRHISMedicineInternational healthPolitical scienceNursingEnvironmental health

Abstract

fetched live from OpenAlex

'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.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.477
Teacher spread0.438 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2012
Admission routes1
Has abstractyes

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