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Record W2802651311 · doi:10.1080/22423982.2018.1466604

Exploring coping strategies and mental health support systems among female youth in the Northwest Territories using body mapping

2018· article· en· W2802651311 on OpenAlexafffundabout
Candice Lys

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersIndspireCanadian Institutes of Health ResearchPublic Health Agency of Canada
KeywordsMental healthCoping (psychology)PsychologyGeographyGerontologyMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

The mental health of young women in the Northwest Territories (NWT), Canada, is a critical public health concern; however, there is a dearth of research that examines how this population manages mental health challenges. This study explores the self-identified strategies that female youth in the NWT use to cope with mental health issues. The arts-based qualitative method of body mapping and a trauma-informed, strengths-based approach grounded in social ecological theory was used to collect data during in-depth semi-structured interviews. Forty-one participants (aged 13-17 years) attended FOXY body mapping workshops in six NWT communities in 2013 then completed interviews regarding the content of their body maps. Thematic analysis was used to identify five themes related to coping strategies: grounding via nature, strength through Indigenous cultures, connection with God and Christian beliefs, expression using the arts, and relationships with social supports. These results can be used to develop culturally relevant, strengths-based, trauma informed interventions that improve coping and resiliency among Northern youth.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
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 head0.162
GPT teacher head0.407
Teacher spread0.244 · 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 designQualitative
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

Citations56
Published2018
Admission routes3
Has abstractyes

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