MétaCan
Menu
Back to cohort
Record W2169753958 · doi:10.1080/14733145.2012.761717

A systematic review of the literature on counselling and psychotherapy for the prevention of suicide: 1. Quantitative outcome and process studies

2013· review· en· W2169753958 on OpenAlexaboutno aff
David A. Winter, Siobhan Bradshaw, Frances Bunn, David Wellsted

Bibliographic record

VenueCounselling and Psychotherapy Research · 2013
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychotherapistSystematic reviewPsychological interventionPsychologyOutcome (game theory)CognitionMeta-analysisScope (computer science)Clinical psychologyMEDLINEMedicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Scope of review: The paper reports a meta‐review of 15 previous systematic reviews and meta‐analyses of the literature concerning the outcome of counselling and psychotherapy with people at risk of suicide; a meta‐analysis of 67 outcome studies in this area; and a narrative review of 17 studies of the therapeutic process. Publication time span: The literature reviewed was published between 1981 and 2008. Publication origin: The majority of the literature reviewed was by authors from the USA or the UK, but there were also authors from other European countries, Australia, Canada, India, and Sri Lanka. Findings: There is evidence of the effectiveness of dialectical behaviour therapy, cognitive‐behavioural therapy, and problem solving therapy, but also for other forms of therapy. Therapist and client variables, as well as the therapeutic relationship, appear to be related to treatment outcome. Conclusions: People at risk of suicide should have access to psychological interventions, including, but not necessarily limited to, those within the cognitive‐behavioural spectrum. Therapies for which there have been promising findings, but which are under‐researched, should be a research priority.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.351
GPT teacher head0.564
Teacher spread0.213 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations21
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCounselling and Psychotherapy ResearchSame topicSuicide and Self-Harm StudiesFrench-language works237,207