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Record W3014997179 · doi:10.1002/pits.22366

Feasibility trial of the school‐based STRONG intervention to promote resilience among newcomer youth

2020· article· en· W3014997179 on OpenAlexafffundabout
Claire V. Crooks, Sharon Hoover, Alexandra Smith

Bibliographic record

VenuePsychology in the Schools · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsLondon Health Sciences CentreWestern University
FundersMinistère de l’Éducation, Gouvernement de l’OntarioStrong
KeywordsPsychologyOptimismDistressIntervention (counseling)Psychological resilienceCoping (psychology)Focus groupProgram evaluationMedical educationStress managementClinical psychologyPsychotherapistMedicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract There are thousands of refugee students in Canadian schools and many struggle with distress and trauma symptoms. Even those not demonstrating overt distress may face adjustment challenges. This paper describes the pilot of the Supporting Transition Resilience of Newcomer Groups (STRONG) program in ten schools. STRONG is a 10‐session, manualized program focused on building skills and helping students process their migration journey. This pilot used a pragmatic mixed‐methods approach to evaluate the feasibility of STRONG, with a focus on acceptability, implementation, and perceived utility of the intervention. Clinicians ( n = 16) provided data at the training, throughout the intervention and at the end through clinician surveys and focus groups. Clinicians reported high levels of acceptability for the training and program. Implementation challenges included time constraints, external influences, and some challenges with language. Overall STRONG was seen to provide significant positive benefits for students in increasing connectedness, stress management, and coping strategies. Clinicians felt that students developed more positive self‐image and had improved optimism. This feasibility trial of the STRONG program indicated the potential utility for promoting resilience and reducing distress among refugee students through a structured, school‐based group intervention.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.413
Teacher spread0.313 · 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.

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

Citations26
Published2020
Admission routes3
Has abstractyes

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