Is Twitter social support related to likelihood of using Twitter for behavior change strategies
Bibliographic record
Abstract
Background: Twitter is a popular internet-based social media designed for interpersonal communication via micro-blogging, representing an online virtual community. In previous work we found that perceptions about using Twitter-delivered Cognitive behavioural strategies (CBS) were related to readiness to use Twitter for health behaviour change (Locke and Brawley, 2014). Our question is whether Twitter provides social support (SS) to its users and if this is associated with indicants of likelihood of its use for change. Cutrona and Russell (1990) suggest that different types of SS (i.e., social provisions; SPs) are perceived and needed in different situations. Understanding the SPs people perceive as available through Twitter might provide evidence for its tailored utilization for use of CBS. Purpose: To examine whether the SPs subscales of Guidance and Reliable Alliance are related to perceptions of using Twitter-based cognitive behavioural strategies (CBS) for diet and exercise change. These two subscales conceptually relate to use of CBS and are based on Cutrona and Russell’s idea that specific SPs may be particularly useful in specific contexts. Method: 88 adults ( M age = 26, 65% Female), recruited via social media and internet bulletin boards, completed: demographic information, the social provisions scale, and perceptions about using Twitter-delivered CBS (i.e., goal-setting, monitoring, feedback) for diet and exercise change. Results: Each of Guidance, Reliable Alliance, and a third subscale, Attachment, were correlated with CBS perceptions ( ps <.05). Subsequent multiple regression analyses predicted relationships between these 3 subscales and likelihood of using Twitter-delivered CBS ( R 2 range .06-.11, p <05). A similar pattern was evident for diet change. Conclusion: Specific SPs were related to the likelihood of using Twitter-delivered CBS for behaviour change. It appears that Twitter provides some sort of SS to its users and its association with the likelihood of change may offer an advantage for those perceiving greater support. Acknowledgments: Canada Research Chair Training Funds
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".