The associations of social networking site use and self-reported general health, mental health, and well-being among Canadians
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
Objectives To investigate social networking site (SNS) use and frequency, and their potential associations with self-reported general health, mental health, and well-being among the Canadian population using the nationally representative 2013 General Social Survey (GSS). Methods Data were collected via Statistics Canada GSS 2013 (cycle 27). Six separate one-way analysis of covariances (ANCOVAs) were conducted to determine differences in general health, mental health, and well-being for both SNS use and frequency, controlling for age, gender, number of children at home, household location, education, and income. Results SNS users were younger (with nearly 96% being 15–24 years old vs. 27% ≥ 75 years; p < .001), female ( p < .001), have three or fewer children at home ( p < .001), live in urban/Prince Edward Island locations, were at the lower or higher ends of household income ( p < .001), and were less educated ( p < .001). Among all Internet users, better general health ( p = .03) was associated with using SNSs, yet better mental health ( p = .001) and well-being ( p = .001) were associated with not using SNSs. Among SNS account-holders, those who never accessed their accounts had significantly lower general health ( p = .007), mental health ( p < .001), and well-being ( p < .001) compared with those who accessed their accounts, regardless of frequency. Conclusion Differences exist for SNS use and frequency and health outcomes. However, investigations into the possible differences that may exist between individuals who do not have a SNS account and those who do, but do not use it, are needed in the future.
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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 | 0.001 | 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 | 0.004 | 0.001 |
| 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