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Record W4416975222 · doi:10.1080/10615806.2025.2597764

Coping profiles across adulthood: findings from a 3-wave longitudinal study using latent profile transition analysis

2025· article· en· W4416975222 on OpenAlexafffund
Colin T. Henning, Amy Van Elswyk, Laura J. Summerfeldt, James D. A. Parker

Bibliographic record

VenueAnxiety Stress & Coping · 2025
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsTrent University
FundersGambling Research Exchange Ontario
KeywordsCoping (psychology)Longitudinal studyLongitudinal dataCoping behaviorLatent class modelYoung adult

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The use of various coping strategies has important impacts on individuals' health and well-being. However, most of the coping literature continues to use variable-centred approaches that ignore unique within-person interactions among coping strategies, as well as change in these interactions over time. The present study sought to address these gaps by identifying coping profiles representing distinct interactions between a set of coping strategies and examining the stability of these profiles over time. DESIGN AND METHODS: The study used data from a large community sample of Canadians (N = 1,372) who completed the short form for the Coping Inventory for Stressful Situations (CISS-SF) scale at three time-points or waves over 5 years. Latent profile transition analysis (LPTA) was used to identify latent profiles and then examine the stability of the profiles over time. RESULTS: LPTA revealed three distinct coping profiles: Engaged, Avoidance-Oriented, and Disengaged. All coping profiles showed relatively strong stability across the three waves, with Engaged coping being the most stable over time. CONCLUSIONS: These findings have important implications for future coping research using a person-centred approach, including for the identification of individuals at risk for poor life outcomes due to reliance on these coping profiles.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.363
Teacher spread0.313 · 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.

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

Citations0
Published2025
Admission routes2
Has abstractyes

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