Kinesiology student attitudes and mental health
Bibliographic record
Abstract
In recent years there has been an effort to normalize mental health and to encourage individuals to seek support for mental health issues. This effort has been particularly evident on university campuses. Participants in this study were 239 male and 290 female students enrolled in kinesiology courses. Students completed the Questionnaire of Student Attitudes toward Schizophrenia. The questionnaire is comprised of two topics: stereotypes of schizophrenia and social distance, i.e. the students' readiness to enter different types of social relationships with someone who has schizophrenia. In the stigma process undesirable characteristics are stereotypically linked to a condition and serve to justify negative social reactions, i.e. stereotypes form the basis of behavioural intentions. There were significant differences between female (4.77 ± 3.42) and male (6.24 ± 4.18) students in total stigma toward schizophrenia. Males reported more stereotyped beliefs (2.51 ± 1.66) and sought to maintain greater social distance to people with schizophrenia (3.73 ± 3.06) compared to females (1.90 ± 1.46 for stereotype; 2.86 ± 2.51 for social distance). Overall stigma scores were relatively low, however gender differences do exist and these differences should be addressed in attempts at increasing awareness and acceptance of mental health issues. Many kinesiology graduates will be employed in health and physical activity related fields and this will inevitably result in contact with individuals with mental health issues, students should be made aware of their own biases and seek to address them.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".