The use of social media in a physical activity campaign: A case study of MoveU
Bibliographic record
Abstract
Background:Little is currently known about how social media should be integrated into physical activity (PA) promotion, and how it can be exploited to enhance social marketing campaigns. MoveU is a PA campaign with a social media component at the University of Toronto that aims to increase active healthy living particularly among first year female students. Purpose:This research aims to explore the role of Facebook in enhancing the effectiveness of a PA intervention (MoveU) from the perspective of the health promoters involved in the development of the campaign, and the students exposed to the campaign. Methodology:A mixed methods evaluation was conducted which comprised nine interviews with key partners involved in various aspects of the campaign; focus groups with students (n=45), and analytic data capturing Facebook usage from one academic year. Results:All partners and most students believed that social media can be an effective tool within health promotion because of the volume of young people who use it. By the end of the academic year (April, 2014), the MoveU Facebook page had 2250 followers, representing a modest growth of 968 followers since August, 2013. 84% of followers were female and 83% were between 18-24 years old suggesting social media was being used by the target audience. Although partners saw social media as a platform to facilitate engagement through discussions, students tended to focus on its role in event announcement. This was also reflected in the modest engagement of, on average, 35 clicks, “likes” shares, and comments per post. Conclusion:There is a role for social media in PA promotion but within MoveU there were unrealistic expectations about how it would assist campaign goals. The optimal use of social media like Facebook for PA campaigns is in its ability to efficiently communicate tailored messages to a specific target audience. Acknowledgments: Ontario Trillium Foundation and Canadian Institutes of Health Research Population Intervention for Chronic Disease Prevention Training Program
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".