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Record W6921870992 · doi:10.7939/r3-gynm-5x85

Children and Youth Mental Health: The Role of a Collaborative, School-Based Wraparound Support Intervention in Fostering Mental Health

2023· dissertation· en· W6921870992 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2023
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPsychological interventionIntervention (counseling)Focus groupLeverage (statistics)Mental illness

Abstract

fetched live from OpenAlex

There is an increased recognition that early mental health interventions are needed in response to a growing mental health crisis among children and youth. Schools are promising sites for early intervention because they have existing infrastructure for accessing and engaging with students. Specifically, collaborative initiatives involving community partnerships allow schools to leverage shared resources to deliver mental health support. However, more research is needed to guide the development and implementation of early interventions so that they effectively address the mental health needs of children and youth. Therefore, the present study explored the role of collaborative, school-based mental health services in fostering children and youth’s mental health, through All in for Youth, a wraparound model of support in Edmonton, Canada. Three research questions were addressed: (1) What mental health concerns do children and youth experience? (2) What are the factors that impact the use of collaborative school-based mental health services? (3) Does a collaborative school-based approach to mental health services lead to perceived mental health impacts among children and youth (i.e., emotionally, psychologically, and/or behaviourally)? A multiple methods secondary analysis was conducted to address this research inquiry. Interview and focus group data generated with students (n = 51 students; grades 2 – 9) and parents/caregivers (n = 18) across seven AIFY elementary and junior high schools were analyzed to understand participants’ experiences with collaborative, school-based mental health services. Additionally, school cohort data (n = 7 schools; n = 2,073 students) were analyzed with information on students’ socio-demographic characteristics and use of services across schools. The quantitative findings indicated that overall, n = 885 students (42.7%) accessed any type of mental health service across the seven schools, with close to equivalent service use by gender (50.2% male, 49.5% female, 0.3% genderqueer) and grade level (kindergarten – grade 9; M = 10%, SD = 1.9%, range = 6.3–13%). There was also high service use across diverse student statuses (Indigenous , 24.5%; Refugee, 9.5%; English language learner, 30.1%; specialized learning needs, 18.7%). Participants accessed mental health services in primarily individual or combined individual and group settings (72.9%) and as an informal, short-term client (75.1%). Furthermore, many service users went on to use two or more mental health services (42.2%). The interview and focus group findings revealed high mental health needs among students, which were further exacerbated by the COVID-19 pandemic. In response to these needs, a supportive school culture, adequate school communication, and a stable and well-resourced mental health workforce promoted access to collaborative, school-based mental health services. Finally, mental health services were described to support children and youth through the experience of having a supportive relationship with a safe and caring adult, developing an improved capacity to cope with school and life, and improved overall family functioning. The findings underscore the importance of developing school-based mental health services that recruit school-community partnerships on the delivery of services and take an ecological, wraparound approach to addressing students’ multi-faceted mental health needs. Study implications and future directions for research are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.203
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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