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Record W7117514358 · doi:10.1007/s44192-025-00325-z

Validation of a reduced version of the child and youth resilience measure (CYRM-28) for public health use in Aotearoa New Zealand

2025· article· en· W7117514358 on OpenAlexaff
Linda Liebenberg, Jackie Sanders, Jayne Mercier

Bibliographic record

VenueDiscover Mental Health · 2025
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
FundersMinistry of Business, Innovation and Employment
KeywordsAotearoaMental healthPsychological interventionPsychological resiliencePopulationPublic healthService providerResilience (materials science)Resource (disambiguation)

Abstract

fetched live from OpenAlex

Globally, there is increasing need to address the burden of mental illness on populations, including youth, and increasing recognition of the role of social determinants on mental health. The study of resilience, as an ecological process of individual and community resource mobilisation in the face of adversity, is a promising lens through which to understand culturally and contextually relevant factors that enhance or inhibit mental wellbeing. This paper reports on a validation of a reduced, 2-factor, 17-item form of the child and youth resilience measure (CYRM-28) on a population of youth in Aotearoa (New Zealand) who were involved in multiple service systems, including child and adolescent mental health services. It builds on previous work which validated the full 28-item scale. It responds to needs articulated by researchers and service providers for a shortened version of the CYRM-28 that reduces assessment burdens on youth and clinicians. The reduced form may be helpful in mental health settings to quickly understand the resilience resources around vulnerable youth and support interventions that build on strengths and directly address areas where resources are missing.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.990

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.369
Teacher spread0.323 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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