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Record W4403260294 · doi:10.1017/ipm.2024.18

Addressing student mental health and suicide concerns: are we there yet?

2024· editorial· en· W4403260294 on OpenAlexaboutno aff
Jo Smith

Bibliographic record

VenueIrish Journal of Psychological Medicine · 2024
Typeeditorial
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPsychologyPsychiatry

Abstract

fetched live from OpenAlex

The mental health and suicide rates of further education (FE) and higher education (HE) students have been generating international concern in many countries, including the United States of America (USA), United Kingdom (UK), Canada, Australia, and Ireland. Several charters and national frameworks have emerged to support and inform whole institution provision. There is evidence of sector engagement and investment to support implementation in HE and to a lesser extent, FE, particularly from the USA and UK, although effectiveness evidence is currently lacking. Barriers affecting help seeking and early identification of difficulties, delays in accessing appropriate support, and lack of continuity of care from campus supports into specialist Mental Health services, remain key challenges. This editorial discusses the current position and the next stage of development in student mental health support and suicide prevention. Overall, the transformation of FE and HE provision to address student mental health and suicide concerns still has a considerable way to go.

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)0.007
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.014
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0090.005
Open science0.0030.002
Research integrity0.0140.020
Insufficient payload (model declined to judge)0.0100.007

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 head0.228
GPT teacher head0.573
Teacher spread0.345 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2024
Admission routes1
Has abstractyes

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