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Record W2975558299 · doi:10.1136/bmjopen-2019-030728

Qualitative case study investigating PAX-good behaviour game in first nations communities: insight into school personnel’s perspectives in implementing a whole school approach to promote youth mental health

2019· article· en· W2975558299 on OpenAlexafffundabout
Wu Yu, Mariette Chartier, Gia Ly, Ari Phanlouvong, Shelby Thomas, Jonathon Weenusk, Nora Murdock, Garry Munro, Jitender Sareen

Bibliographic record

VenueBMJ Open · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsFirst Nations Health and Social Secretariat of ManitobaManitoba HealthUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMedicineMental healthQualitative researchPublic healthMedical educationPublic relationsNursingPsychiatrySocial scienceSociology

Abstract

fetched live from OpenAlex

OBJECTIVES: PAX-Good Behaviour Game (PAX-GBG) is associated with improved mental health among youth. First Nations community members decided on a whole school approach to facilitate PAX-GBG implementation, by offering intervention training to all staff members in their schools. Our objective is to gain a greater understanding of how this approach was viewed by school personnel, in order to improve implementation in remote and northern First Nations communities. DESIGN: We conducted a qualitative case study using semi-structured interviews. SETTING: Interviews were conducted in First Nations schools located in northern Manitoba, Canada, in February 2018. PARTICIPANTS: We used purposive sampling in selecting the 23 school staff from First Nations communities. INTERVENTION: PAX-GBG is a mental health promotion intervention that teachers deliver in the classroom alongside normal instructional activities. It was implemented school-wide over 4 months from October 2017 to February 2018. OUTCOME MEASURES: We inquired about the participants' perception of PAX-GBG and the whole school approach. We applied an iterative coding system, identified recurring ideas and classified the ideas into major categories. RESULTS: Implementing the PAX-GBG whole school approach improved students' behaviour and created a positive school environment. Students were learning self-regulation, had quieter voices and demonstrated awareness of the PAX-GBG strategies. All teachers interviewed had used the programme. Support from school administrators and having all school personnel use the programme consistently were facilitators to successful implementation. Challenges included the timing of training, lack of clarity in how to implement and implementing among students in older grades and those with special needs. CONCLUSIONS: The whole school approach to implementing PAX-GBG was viewed as an acceptable and feasible way to extend the reach of PAX-GBG in order to promote the mental health of First Nations youth. Recommendations included ensuring school leadership support, changes to the training and cultural and literacy adaptations.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.008
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.148
GPT teacher head0.473
Teacher spread0.325 · 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 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

Citations20
Published2019
Admission routes3
Has abstractyes

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