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Registration: Determinants of undergraduate student well-being: A scoping review protocol

2025· other· en· W6977449612 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typeother
Languageen
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyConstruct (python library)Mental healthRelevance (law)PopulationPsychological interventionAnxietyIntervention (counseling)

Abstract

fetched live from OpenAlex

Objective: This scoping review aims to examine the extent and type of evidence related to the determinants of undergraduate student well-being in Canada and the United States. This review focuses on understanding the theoretical frameworks, measurement approaches, and predictors of well-being, with the goal of identifying factors that can inform the development of predictive models and screening tools to identify students at risk.Research Questions: This review will be guided by the following research questions: What theoretical frameworks are most frequently applied to define and measure well-being among college and university students in the most recent literature?Hedonic or EudaimonicSubjective vs. Psychological vs. Affective Global or single dimensionTo what extent do studies on student well-being differentiate between mental health symptoms, such as anxiety and depression, and broader, non-clinical measures of well-being?Outcome measures used - clinical vs universal vs combinationWhat factors are identified as predictors of subjective and psychological well-being among post secondary students?What are the determinants of well-being in the recent literatureWhat are the correlation coefficients associated with each factorInclusion criteria: This review includes studies that focus on undergraduate students in post-secondary programs in Canada or the United States, with well-being defined as a global construct encompassing subjective, affective, or psychological dimensions. Quantitative, correlational or observational designs published in English between 2019, and the present are included. Studies that focus on graduate students or intervention evaluations are excluded to ensure relevance to the target population and research objectives.Methods: Key databases include ProQuest, PsycArticles, and SCOPUS. The search is focused on studies published from 2019 onward. Study selection, data extraction, and analysis are guided by the JBI framework for scoping reviews. The results will synthesize participant demographics, theoretical frameworks, measurement approaches, and predictors of well-being to address the stated objectives.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.070
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.168
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0700.102
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0150.017
Science and technology studies0.0050.003
Scholarly communication0.0070.008
Open science0.0050.007
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.1680.032

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 head0.024
GPT teacher head0.323
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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 routes1
Has abstractyes

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