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Record W1167501672 · doi:10.1177/070674371506000603

A Youth Suicide Prevention Plan for Canada: A Systematic Review of Reviews

2015· review· en· W1167501672 on OpenAlexafffundvenueabout
Kathryn Bennett, Anne E. Rhodes, Stephanie Duda, Amy Cheung, Katharina Manassis, Paul S. Links, Christopher J. Mushquash, Peter Braunberger, Amanda S. Newton, Stan Kutcher, Jeffrey A. Bridge, Robert Santos, Ian Manion, John D. McLennan, Alexa Bagnell, Ellen L. Lipman, Maureen Rice, Péter Szatmári

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2015
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsCentre for Addiction and Mental HealthUniversity of CalgaryChildren's Hospital of Eastern OntarioUniversity of OttawaUniversity of ManitobaGovernment of ManitobaIzaak Walton Killam Health CentreDalhousie UniversityUniversity of AlbertaMcMaster UniversitySt. Joseph's Care GroupNOSM UniversityHospital for Sick ChildrenHealth Sciences CentreSt. Michael's HospitalSunnybrook Health Science CentreLakehead UniversityAlberta Health ServicesSickKids FoundationUniversity of TorontoMcMaster Children's HospitalLondon Health Sciences Centre
FundersCanadian Institutes of Health Research
KeywordsMedicineSystematic reviewPsychosocialPoison controlSuicidal ideationPsychological interventionSuicide preventionPopulationRandomized controlled trialPsychiatryObservational studyFamily medicineMEDLINEMedical emergencyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: We conducted an expedited knowledge synthesis (EKS) to facilitate evidence-informed decision making concerning youth suicide prevention, specifically school-based strategies and nonschool-based interventions designed to prevent repeat attempts. METHODS: Systematic review of review methods were applied. Inclusion criteria were as follows: systematic review or meta-analysis; prevention in youth 0 to 24 years; peer-reviewed English literature. Review quality was determined with AMSTAR (a measurement tool to assess systematic reviews). Nominal group methods quantified consensus on recommendations derived from the findings. RESULTS: No included review addressing school-based prevention (n = 7) reported decreased suicide death rates based on randomized controlled trials (RCTs) or controlled cohort studies (CCSs), but reduced suicide attempts, suicidal ideation, and proxy measures of suicide risk were reported (based on RCTs and CCSs). Included reviews addressing prevention of repeat suicide attempts (n = 14) found the following: emergency department transition programs may reduce suicide deaths, hospitalizations, and treatment nonadherence (based on RCTs and CCSs); training primary care providers in depression treatment may reduce repeated attempts (based on one RCT); antidepressants may increase short-term suicide risk in some patients (based on RCTs and meta-analyses); this increase is offset by overall population-based reductions in suicide associated with antidepressant treatment of youth depression (based on observational studies); and prevention with psychosocial interventions requires further evaluation. No review addressed sex or gender differences systematically, Aboriginal youth as a special population, harm, or cost-effectiveness. Consensus on 6 recommendations ranged from 73% to 100%. CONCLUSIONS: Our EKS facilitates decision maker access to what is known about effective youth suicide prevention interventions. A national research-to-practice network that links researchers and decision makers is recommended to implement and evaluate promising interventions; to eliminate the use of ineffective or harmful interventions; and to clarify prevention intervention effects on death by suicide, suicide attempts, and suicidal ideation. Such a network could position Canada as a leader in youth suicide prevention.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.141
GPT teacher head0.374
Teacher spread0.233 · 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

Citations90
Published2015
Admission routes4
Has abstractyes

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