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Record W7131751953

Self-harm in the community : staff and parent perspectives

2025· other· en· W7131751953 on OpenAlexaboutno aff
Georgina Edwards

Bibliographic record

VenueWarwick Research Archive Portal (University of Warwick) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLCritical appraisalThematic analysisMental healthChecklistQualitative researchInclusion (mineral)Quality (philosophy)Distress
DOInot available

Abstract

fetched live from OpenAlex

Research indicates that mental health staff experience shock, distress and powerlessness when supporting people who self-harm. Existing studies have focused on inpatient staff, neglecting the voices of those working in community settings. AIM: The aim of the current systematic review and thematic synthesis was to explore community staff experiences of supporting people who self-harm. METHODS: PsycINFO, MEDLINE, CINAHL and Web of Science were searched from inception to 4th February 2025. Searches found 3,035 records, of which twelve reporting on 82 participants were identified as meeting the inclusion criteria and included in the synthesis. The Critical Appraisal Skills Programme Qualitative Checklist was used to assess the quality of included studies. RESULTS: Studies took place in the UK, USA, Ireland and Canada. All studies were qualitative recruiting Counsellors, Community Mental Health Nurses, Psychotherapists and a Social Care Support Worker. Studies obtained an average quality rating score of 17.9 out of 20, with most studies being highly rated. Thematic synthesis yielded five themes; 1) Staff experience an all-consuming, long-lasting emotional whirlwind, 2) Staff feel stuck between a rock and a hard place, 3) Staff see systemic challenges as impacting their support of people who self-harm, 4) Staff carry the weight of many different responsibilities, 5) It is necessary for staff to have ways of coping. CONCLUSION: A lack of consensus in the conceptualisation of self-harm highlights a need for researchers’ transparency regarding their theoretical position. The findings highlight the challenging experience staff have when supporting people who self-harm, warranting a need for further support and training.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.317
Teacher spread0.272 · 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 designNot applicable
Domainnot available
GenreOther

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

Explore more

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