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Record W4281928257 · doi:10.2196/37583

Proximal Risk for Suicide: Protocol for an Ecological Momentary Assessment Study

2022· article· en· W4281928257 on OpenAlexvenueno aff
Pravesh Sharma, Robert Peck, Anthony R Sinicrope, Thomas Pavey, Jennifer J. Muehlenkamp

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
FundersMayo Clinic
KeywordsSuicidal ideationPsychologySuicide preventionProtocol (science)Poison controlHuman factors and ergonomicsInjury preventionRisk assessmentClinical psychologyMedicineMedical emergencyComputer securityAlternative medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Suicide is a prevalent public health concern in the United States across all age groups. Research has emphasized the need to identify risk markers that prevent suicide along shorter timeframes, such as days to weeks. Furthermore, little has been done to explore the relative significance of factors that can predict short-term suicide risk or to evaluate how daily variability in these factors impacts suicidal ideation or behavior. This proposed project aims to identify risk factors that best predict near-time changes in suicidal ideation and examine potential interactions between these factors to predict transitions into suicidal thinking or behaviors. OBJECTIVE: The aim of this proposed study is threefold: (1) To identify which psychological risk factors are most strongly associated with proximal changes in suicide risk across days and weeks. (2) To evaluate theoretical assumptions of the Integrative-Motivational-Volitional Theory of Suicide. (3) To determine how disruptions in physiological arousal interact with theoretical mechanisms of risk to predict concurrent and short-term prospective increase in suicidal thoughts and behaviors. METHODS: A daily diary or ecological momentary assessment design will be utilized with 200 participants. Participants will complete 2 in-person visits separated by 3 weeks during which they will complete 3 brief daily assessments within their natural environments using the ilumivu research app on a smart device. Research will occur at the Mayo Clinic Health System (MCHS) Eau Claire site. Participants will be recruited through chart review and standard care delivery assessment. RESULTS: This manuscript outlines the protocol that will guide the conduct of the forthcoming study. CONCLUSIONS: The proposed project aims to lead efforts using technological advances to capture microchanges in suicidal thinking/behavior over shorter timeframes and thereby guide future clinical assessment and management of suicidal patients. Results of this study will generate robust evidence to evaluate which risk factors predict proximal changes in suicidal ideation and behaviors. They will also provide the ability to examine potential interactions with multiple theoretically derived risk factors to predict proximal transitions into worsening suicidal thinking or behaviors. Such information will provide new targets for intervention that could ultimately reduce suicide-related morbidity and mortality. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37583.

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)0.028
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.069
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.025
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.003
Science and technology studies0.0060.002
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0690.015

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 head0.507
GPT teacher head0.649
Teacher spread0.142 · 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 designObservational
Domainnot available
GenreProtocol

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

Citations3
Published2022
Admission routes1
Has abstractyes

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