ArticleJournal of personality and social psychology2019
Implicit interpersonal evaluations as a risk factor for suicidality: Automatic spousal attitudes predict changes in the probability of suicidal thoughts.
Article in Journal of personality and social psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 25 citations in OpenAlex.
- Development and validation of the risk score for estimating suicide attempt in patients with major depressive disorder.Social psychiatry and psychiatric epidemiology · 2024Article
- The threat sensitivity scale: A brief self-report measure of dispositional sensitivity toward perceiving threats to physical harm.Scientific reports · 2024Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Thwarted social connection is a critical risk factor for suicidality, and several theoretical perspectives highlight the importance of interpersonal affect to social connection. Given that marriage is an increasingly important source of social connection, we examined the role of automatic spousal attitudes-conceptualized as spontaneously activated affective associations involving one's spouse-in predicting suicidal thoughts in 3 longitudinal studies of married couples. Studies 1a (
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.