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Record W4407624683 · doi:10.1093/bjsw/bcaf028

Young people’s perspectives on barriers to accessing supports and services in Drayton Valley, Canada

2025· article· en· W4407624683 on OpenAlexafffundabout
Gianisa Adisaputri, Tonya Grant, Michael Ungar

Bibliographic record

VenueThe British Journal of Social Work · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchDalhousie University
KeywordsPsychosocialService providerAutonomyMental healthIndependence (probability theory)Public relationsBusinessMandateQualitative researchService (business)NursingPsychologyMedicineSociologyPolitical scienceMarketingPsychiatry

Abstract

fetched live from OpenAlex

Abstract As young people transition to adulthood, they are required to exercise more autonomy when accessing informal psychosocial support and formal health and social services. This qualitative study examines the lived experience of forty-nine young people aged thirteen to twenty-four in Drayton Valley, Canada, and their accounts of accessing support and services in response to mental and physical health needs. Drayton Valley is an economically volatile community dependent on the oil and gas industry. Using data from the Resilient Youth in Stressed Environment project, we investigated the experiences of young people when accessing healthcare, social, and community services. We used a general inductive analysis approach to develop a framework for how young people decide whether or not to engage with support and services. In general, youth reported needing positive knowledge about services, trust in both the organization and providers of services, the independence to seek supports and/or services that they valued, and the need to experience a fit with the mandate of their service provider. Our findings suggest that to increase the use of supports and services, policies need to better account for young people’s experiences when seeking help.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.358
Teacher spread0.329 · 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 teacher head, not a consensus.

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

Citations1
Published2025
Admission routes3
Has abstractyes

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