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Record W4317568443 · doi:10.1016/j.crbeha.2023.100096

The links between fear of missing out, status-seeking, intrasexual competition, sociosexuality, and social support

2023· article· en· W4317568443 on OpenAlexaff
Adam C. Davis, Graham Albert, Steven Arnocky

Bibliographic record

VenueCurrent Research in Behavioral Sciences · 2023
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsNipissing University
Fundersnot available
KeywordsPsychologySocial psychologyFeelingWorryPerspective (graphical)Sexual selectionEvolutionary psychologyApprehensionDevelopmental psychologyCognitive psychologyAnxietyEcologyBiology

Abstract

fetched live from OpenAlex

With the surge of social media use in contemporary society, scholars have focused on how feelings of apprehension that one is missing out on important social activities (i.e., fear of missing out [FoMO]) might influence mental health. However, worry surrounding social inclusion is not a contemporary problem, and successfully participating in social events is an important aspect of human evolutionary history. To our knowledge, researchers have yet to frame the phenomenon of FoMO in an evolutionary perspective. In a sample of N = 327 heterosexual American adults (Mage = 36.94, SD = 10.24), we found that FoMO correlated positively with status-striving and intrasexual competitiveness, as well as unrestricted sociosexual behavior and desires. Among females, but not males, FoMO was negatively linked to received social support. Results highlight how adults higher in FoMO express a greater inclination to compete for evolutionarily salient social and reproductive resources and devote more effort toward short-term mating. FoMO may also alert females to the absence of desired social support. Findings provide insight into the utility of an evolutionary approach to studying individual differences in the experience of FoMO, which can aid in gathering a more comprehensive understanding of the construct.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.006
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 head0.483
GPT teacher head0.579
Teacher spread0.096 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
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

Citations7
Published2023
Admission routes1
Has abstractyes

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