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Record W4399141550 · doi:10.1080/07448481.2024.2355162

Longitudinal associations between sense of belonging, imposter syndrome, and first-year college students’ mental health

2024· article· en· W4399141550 on OpenAlexaff
Anh Dao, Samantha Pegg, Sydney Okland, Haley Green, Autumn Kujawa

Bibliographic record

VenueJournal of American College Health · 2024
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsWestern University
FundersNational Center for Advancing Translational SciencesNational Institute of Mental HealthNational Institutes of Health
KeywordsMental healthDepression (economics)PsychologyClinical psychologyLongitudinal studyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Objective: The first year of college is a time of major changes in social dynamics, raising questions about ways to promote students’ mental health. We examined longitudinal associations between students’ sense of belonging, imposter syndrome, depressive symptoms, and well-being. Participants: Fifty-eight first-year college students at a university in the United States participated in the study. Methods: Students completed questionnaires during the first 6 months of college (T1) and at the end of the academic year (T2). Results: Greater sense of social and academic belonging was correlated with lower imposter syndrome, depression, and greater well-being at T1. Accounting for T1 measures, lower imposter syndrome predicted greater well-being but not depression at T2. Accounting for T1 mental health, belonging was not a significant predictor of depression or well-being at T2. Conclusion: Increasing sense of belonging and addressing imposter syndrome early in the transition to college may be critical in promoting mental health.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.361
Teacher spread0.339 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2024
Admission routes1
Has abstractyes

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