Transitions to Belonging: Evaluating the Impacts of a Community-Based Physical Activity Program Through the Lens of Newcomer Youths’ Definitions of Mental Health
Bibliographic record
Abstract
The immigrant population in Canada is rapidly increasing and projected to rise exponentially in the coming years. The immigrant population faces complex and diverse challenges when transitioning into a new country, and this occurrence may be uniquely experienced by youth, who are also navigating transitions in child development, most notably into adolescence. Embedded in a broader mixed-methods pilot project, the aim of this thesis was to qualitatively investigate the impact of the Immigrant-based Physical Literacy for Youth (IPLAY) program on mental health and well-being. Twenty-one Afghan youth were interviewed, eleven who participated in the fall offering of the program (Mage = 15 ± 3; nmales=7), and ten who participated in the winter offering (Mage = 15.8 ± 1.8; nmales=5). Results indicated that youth held a holistic conceptualization of mental health, contrasting what is common practice in the field and literature. This holistic conceptualization had youth perceiving mental health as a dichotomy, recognizing the connection between physical and mental health, and sometimes including descriptions of soul. Mental health was also often connected to the youth’s own experience as a newcomer, discussing newfound feelings of safety, the life left behind, the role of adjustment, and new opportunities and future-oriented thinking. Participation in the IPLAY program seemed to affect mental health and well-being outcomes for the youth, including the opportunity to reconnect, expand social connections, experience a general source of enjoyment, and retreat from home and usual responsibilities. Beyond individual well-being outcomes, the program also seemed to serve as a vehicle for broader integration, by encouraging gender interactions, creating a multicultural environment, and bolstering the youths’ motivation and confidence to engage in new activities. Such findings provide a rich tapestry of understanding into how newcomer youth define, understand, and experience mental health, and may have important policy implications to shift understanding of transition stress from migration beyond just the initial arrival. The results also indicate that programs such as IPLAY can have important and positive impacts on youth participants, and how future programming may be able to adapt to further support the growing demographic of newcomer youth.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".