Exploring the Role of Social Media in Promoting Healthy Consumption
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Social media communication positively impacts relationship quality and as a result, influences healthy consumption value co-creation. • Relationship quality mediates the relationship between social media communication and value co-creation to enhance healthy consumption. • COVID-19 positively moderates the relationship between relationship quality and value co-creation. • The SOR model has been applied for the exploration of the relationships among social media communication, healthy consumption value co-creation and relationship quality. • A new model is proposed for the examination of the relationship between social media communication, relationship quality and value co-creation considering the impact of the mediating effect of COVID-19 on the relationship between relationship quality and value co-creation. This research seeks to investigate how interactions on social media influence the collaborative creation of value in promoting healthy consumption. To gain a more profound understanding of the process of social media communication and its impact on generating shared value, we employed the Stimuli-Organism-Response (SOR) model to formulate our hypotheses. Our study drew upon a survey conducted across five countries and regions (Canada, Malaysia, Taiwan, the United Kingdom, and the United States). By utilising Structural Equation Modelling (SEM), we tested these hypotheses. The results of our research indicate that social media communication significantly enhances the quality of relationships within online communities, subsequently influencing the creation of value in the context of healthy consumption. The findings show individuals who maintain good relationships within their social media networks and believe they can obtain not only important information but also are more likely to share information about their own experiences regarding healthy consumption. We conclude the paper by discussing the theoretical and practical implications of our findings.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it