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Record W3199643928 · doi:10.1101/2021.09.15.21263562

Concurrent validity and reliability of suicide risk assessment instruments: A meta analysis of 20 instruments across 27 international cohorts

2021· preprint· en· W3199643928 on OpenAlexaff
Adrián I. Campos, Laura S. van Velzen, Dick J. Veltman, Elena Pozzi, Sonia Ambrogi, Elizabeth D. Ballard, Nerisa Banaj, Zeynep Başgöze, Sophie Bellow, Francesco Benedetti, Irene Bollettini, Katharina Brosch, Erick J. Canales‐Rodríguez, Emily K. Clarke‐Rubright, Lejla Čolić, Colm G. Connolly, Philippe Courtet, Kathryn R. Cullen, Udo Dannlowski, Maria R. Dauvermann, Christopher G. Davey, Jérémy Deverdun, Katharina Dohm, Tracy Erwin-Grabner, Negar Fani, Lydia Fortea, Paola Fuentes‐Claramonte, Ali Saffet Gönül, Ian H. Gotlib, Dominik Grotegerd, Mathew A. Harris, Ben J. Harrison, Courtney C. Haswell, Emma L. Hawkins, Dawson Hill, Yoshiyuki Hirano, Tiffany C. Ho, Fabrice Jollant, Tanja Jovanović, Tilo Kircher, Bonnie Klimes‐Dougan, Emmanuelle Le Bars, Christine Löchner, Andrew M. McIntosh, Susanne Meinert, Yara Mekawi, Elisa Melloni, Philip B. Mitchell, Rajendra A. Morey, Akiko Nakagawa, Igor Nenadić, Émilie Olié, Fabrício Pereira, Rachel Phillips, Fabrizio Piras, Sara Poletti, Edith Pomarol‐Clotet, Joaquim Raduà, Kerry J. Ressler, Gloria Roberts, Elena Rodríguez‐Cano, Matthew D. Sacchet, Raymond Salvador, Anca‐Larisa Sandu, Eiji Shimizu, Aditya Singh, Gianfranco Spalletta, J. Douglas Steele, Dan J. Stein, Frederike Stein, Jennifer S. Stevens, Giana I. Teresi, Aslihan Uyar-Demir, Nic J. van der Wee, Steven J. van der Werff, Sanne J.H. van Rooij, Daniela Vecchio, Norma Verdolini, Eduard Vieta, Gordon D. Waiter, Heather C. Whalley, Sarah Whittle, Tony T. Yang, Carlos Alfonso Tovilla‐Zárate, Paul M. Thompson, Neda Jahanshad, Anne‐Laura van Harmelen, Hilary P. Blumberg, Lianne Schmaal, Miguel E. Rentería

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMcGill University
FundersCilagEuropean Social FundEuropean Regional Development FundInstituto de Salud Carlos IIINational Health and Medical Research CouncilNational Institutes of HealthRappaport FoundationAd Astra Chandaria FoundationCentres de Recerca de CatalunyaH. Lundbeck A/SServierFundação BialUniversiteit LeidenMinistero della SaluteNational Institute of Mental HealthInternational Bipolar FoundationMinisterio de Ciencia e InnovaciónAmerican Foundation for Suicide PreventionEuropean CommissionIndiviorCentro de Investigación Biomédica en Red de Salud MentalNational Alliance for Research on Schizophrenia and DepressionMcLean HospitalBrainsWayBiogenUniversity of MinnesotaYale UniversityGeneralitat de CatalunyaMedical Research CouncilVerily Life Sciences
KeywordsSuicidal ideationPsychologyConcurrent validityClinical psychologyPoolingRating scaleScale (ratio)Reliability (semiconductor)Beck Hopelessness ScalePoison controlMajor depressive disorderSuicide preventionBeck Depression InventoryPsychiatryPsychometricsMedicineDevelopmental psychologyMedical emergencyComputer sciencePower (physics)Anxiety

Abstract

fetched live from OpenAlex

Abstract Objective A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behaviour. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. Method Here, we examine this issue through two approaches: (i) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments; and (ii) by pooling data (N∼6,000 participants) from cohorts from the ENIGMA-Major Depressive Disorder (ENIGMA-MDD) and ENIGMA-Suicidal Thoughts and Behaviour (ENIGMA-STB) working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behaviour. Results Our results suggested a pattern of moderate-to-high correlations between instruments, consistent with the wide range of correlations, r=0.22-0.97, reported in the literature. Two common complex instruments, the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Scale for Suicidal Ideation (SSI), were highly correlated with each other (r=0.83), as were suicidal ideation items from common depression severity questionnaires. Conclusions Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behaviour, but share a core factor with single suicidal ideation items found in depression severity questionnaires. Multi-site collaborations including cohorts that used distinct instruments for suicide risk assessment should be feasible provided that they harmonise across instruments or focus on specific constructs of suicidal thoughts or behaviours. Key points Question: To inform future suicide research in multi-site international consortia, it is important to examine how different suicide measures relate to each other and whether they can be used interchangeably. Findings: Findings suggest detailed instruments (such as the Columbia Suicide Severity Rating Scale and Beck Scale for Suicidal Ideation) provide valuable information on suicidal thoughts and behaviour, and share a core factor with items on suicidal ideation from depression severity rating scale (such as the Hamilton Depression Rating Scale or the Beck Depression Inventory). Importance: Results from international collaborations can mitigate biases by harmonising distinct suicide risk assessment instruments. Next steps: Pooling data within international suicide research consortia may reveal novel clinical, biological and cognitive correlates of suicidal thoughts and/or behaviour.

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)0.096
metaresearch head score (Gemma)0.139
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0960.139
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.030
Bibliometrics0.0070.009
Science and technology studies0.0010.002
Scholarly communication0.0060.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.403
Teacher spread0.320 · 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.

Study designMeta-analysis
DomainMethods
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

Citations4
Published2021
Admission routes1
Has abstractyes

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