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Record W2982694013 · doi:10.11575/prism/37219

Coping with Distal and Proximal Stressors: A Transactional Model of Stress Among First-Year Undergraduate Students

2019· dissertation· en· W2982694013 on OpenAlexfundno aff
Julia C. Poole

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
FundersAlberta InnovatesKillam Trusts
KeywordsStressorCoping (psychology)PsychologyTransactional analysisTransactional leadershipClinical psychologyApplied psychologySocial psychology

Abstract

fetched live from OpenAlex

The transition to post-secondary education has been cited as a period of high stress, and increased rates of mental health concerns among undergraduate samples suggest that many students are poorly equipped to cope with this transition. The current study utilized the transactional model of stress (Folkman & Lazarus, 1984) to address the need for a comprehensive model of stress and coping among undergraduate students. A sample of first-year undergraduate students completed self-report questionnaires within the initial months of their first term (Time 1; n= 788) and again within the final months of their second term (Time 2; n= 621). Structural equation modeling was used to analyze the associations among stress and coping variables at the start of the year, including distal stressors, proximal stressors, appraisal of stressors, coping strategies, and emotion regulation strategies, with mental health outcomes at the end of the year, including depression, anxiety, and life satisfaction. Results indicated that stress and coping variables at the start of the year explained almost half (45.3%) of the variability in mental health outcomes at the end of the year. Taken together, the structural model provides a useful framework for the conceptualization, assessment, and treatment of stress-related mental health concerns among first-year undergraduate students. Clinical implications and directions for future research and theory development are discussed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.047
GPT teacher head0.366
Teacher spread0.319 · 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
Published2019
Admission routes1
Has abstractyes

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