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Record W7118160174 · doi:10.17605/osf.io/qrpyw

Exploring Gender Differences in Psychological Need Satisfaction and University Student Well-Being

2025· other· W7118160174 on OpenAlexaboutno aff
Ben Thomas, Nicholas Cholmsky, Richard Koestner

Bibliographic record

VenueOpen Science Framework · 2025
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyMultilevel modelSelf-determination theoryNeed theoryUniversality (dynamical systems)Psychological researchBasic needs

Abstract

fetched live from OpenAlex

Basic psychological needs (competence, relatedness, and autonomy) play a central role in human flourishing. Self-Determination Theory research consistently shows that the satisfaction of these needs predicts well-being, while frustration predicts ill-being (Ryan & Deci, 2000). Understanding whether these effects operate similarly across social groups is critical for developing policies that effectively support healthy psychological functioning. Although basic psychological need effects have shown to be universal across gender, very little work has tested whether this universality holds when each basic psychological need is tested individually (Ryan & Deci, 2000). Additionally, cross-cultural Self-Determination Theory research has demonstrated significant cultural differences in the strength of well-being outcomes in response to changes in basic psychological need satisfaction (Nalipay et al., 2020). Gender, a cultural construct of its own, may demonstrate similar differences when each basic psychological need is separated during analysis (Andermann, 2010). The proposed study asks whether changes in competence, relatedness, and autonomy predict well-being similarly for men and women over the course of a school year. We predict that increases in satisfaction of any single need will correlate positively with subjective well-being and negatively with controlled motivation, extrinsic aspirations, and ill-being. However, we expect gender to moderate the strength of these associations, challenging the assumption of full universality within Self-Determination Theory. The objectives are to compile a balanced archival dataset using archival longitudinal data from the McGill Human Motivation Lab (2014–2019). Male participants in each study will be matched with female participants, and change in scores for each need will be calculated across the academic year. Hierarchical linear regressions in SPSSX will then test the predictive effects of each need and the moderating role of gender. This study will contribute to the understanding of basic psychological needs, gender, and university student well-being. Additionally, as students are often required to sacrifice satisfaction in one need for the growth of another, this research can guide university institutions to create policies and initiatives that promote the basic psychological needs most central to student well-being (Holding et al., 2020).

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.009
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0060.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.124
GPT teacher head0.369
Teacher spread0.245 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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