Determinants of intention to use social media for health purposes among Jewish women in Israel: A cross-sectional study
Bibliographic record
Abstract
Women use the Internet more for health purposes than men, probably due to their gender socialization as caregivers. Indeed, women’s use of social media for health is not a one-time occurrence but is expected to continue for a long time to come. Hence, it is important to understand women’s future intention to use social media for health purposes. This study integrated health empowerment, health beliefs and digital inequality perspectives to explain this intention among Jewish female social media users (N = 94). The data were collected through a telephone survey. The results indicated that searching for health information on social media and cues to action are consistent predictors of women’s intention to use social media for health purposes. With the exception of marital status, no effect of socio-demographic variables was found. Health empowerment approach and health belief model are, therefore, the best predictors of future intention to use social media for health. Women should be encouraged by their communities to expand their experience with social media, since it may serve as a source of health empowerment. In addition, they must be encouraged to be more attentive to internal or external stimuli in maintaining or changing their health behavior.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".