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Record W4404200005 · doi:10.2196/63132

Ecological Momentary Assessment of Self-Harm Thoughts and Behaviors: Systematic Review of Constructs From the Integrated Motivational-Volitional Model

2024· review· en· W4404200005 on OpenAlexvenueno aff
Lizzy Winstone, Jon Heron, Ann John, Olivia J Kirtley, Paul Moran, Jennifer J. Muehlenkamp, Rory C. O’Connor, Becky Mars

Bibliographic record

VenueJMIR Mental Health · 2024
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintPsychologyEcologyHarmSocial psychologyComputer scienceBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The integrated motivational-volitional model (IMV) is one of the leading theoretical models of suicidal thoughts and behavior. There has been a recent proliferation in the assessment of suicidal and nonsuicidal self-harm thoughts and behaviors (SHTBs) in daily life. OBJECTIVE: This systematic review synthesized evidence from ecological momentary assessment (EMA) studies in the SHTB literature to address the following questions: (1) Which constructs in the IMV model have been assessed using EMA, and how have they been assessed? (2) Do different constructs from the IMV model fluctuate in daily life? (3) What is the relationship between the different IMV constructs and SHTBs in daily life? METHODS: Consistent with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted systematic searches of 5 databases-Web of Science, Embase, MEDLINE, PsycINFO, and Europe PMC Preprints-from inception to March 26, 2024. RESULTS: Our searches resulted in the inclusion and narrative synthesis of 53 studies across 58 papers. A total of 15 IMV constructs were measured using EMA across the included papers. The most frequently measured constructs were thwarted belongingness (24/58, 41% of the papers), future thinking (20/58, 34% of the papers), and perceived burdensomeness (16/58, 28% of the papers). The least frequently measured constructs were humiliation, social problem-solving, mental imagery, and perceived capability for suicide. None of the included papers measured memory biases, goals, norms, or resilience using EMA. Comparison of intraclass correlation coefficients (45/58, 78% of the papers) revealed moderate but inconsistent within-person variance across all the examined constructs. We found evidence (39/58, 67% of the papers) of concurrent associations between almost all constructs and SHTBs in daily life, with some evidence that entrapment, shame, rumination, thwarted belongingness, hopelessness, social support, and impulsivity are additionally associated with SHTBs in lagged (ie, longitudinal) relationships. CONCLUSIONS: Comparisons were hindered by variation in methodology, including the populations studied, EMA sampling scheme, operationalization of IMV constructs and SHTBs, and statistical approach used. Our findings suggest that EMA studies are a useful methodology for examining risk factors for SHTBs; however, more research is needed for some IMV constructs. Quality assessment suggested several areas for improvement in the reporting of EMA studies in this field. TRIAL REGISTRATION: PROSPERO CRD42022349514; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=349514.

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)0.036
metaresearch head score (Gemma)0.143
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.143
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0090.013
Bibliometrics0.0170.015
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.072
GPT teacher head0.445
Teacher spread0.373 · 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 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

Citations12
Published2024
Admission routes1
Has abstractyes

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