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Record W6996508944

A Self-Determination Theory Perspective on Wellbeing in the Transition from University: 
\nTrait Autonomy and Basic Psychological Need Satisfaction through Graduates’ Goal Pursuits, Past and Present

2021· dissertation· en· W6996508944 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2021
Typedissertation
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyTraitPerspective (graphical)Life satisfactionTransition (genetics)Self-determination theoryWell-being
DOInot available

Abstract

fetched live from OpenAlex

This research aims to identify determinants of wellbeing in the transition from university, a challenging lifespan transition with long-term implications for adult development. We applied self-determination theory, a theory of motivation, wellbeing, and optimal development, to propose an integrative model of wellbeing during this transition. This model predicts that trajectories of wellbeing should reflect the extent to which social environments encountered during the transition support vs. thwart graduates’ basic psychological needs, the extent to which graduates’ dispositional tendencies catalyze processes that facilitate vs. undermine need satisfaction, and the extent to which need-relevant qualities of social environments and graduates’ need-relevant dispositional tendencies influence one another across the transition. We tested this model by investigating whether trait autonomy, a dispositional factor associated with need satisfaction and wellbeing within SDT, promotes graduates’ wellbeing by facilitating need satisfaction though goal pursuits, past and present. We examined this overarching hypothesis across two analyses of longitudinal data collected from graduates transitioning from a large, public university in Québec. Study 1 investigated whether trait autonomy promotes wellbeing by catalyzing need-satisfying processes of striving for post-graduation goals. Results confirmed that higher levels of trait autonomy predicted more self-concordant striving processes and, through them, increases in graduates’ life satisfaction across the transition from university. Study 2 investigated whether trait autonomy might also promote wellbeing by providing graduates with need-satisfying memories of past striving. We tested this hypothesis in relation to a single memory – that of facing an unattainable goal while in university – and two distinct, but conceptually related memory pathways – (i) need satisfaction associated with unconscious activation of episodic memories and (ii) need-satisfying themes of growth in narratives consciously constructed from these memories. The results confirmed our hypothesis, but mainly through the first memory pathway, raising theoretical and methodological issues for future research. Together, findings constitute the first empirical evidence for an integrative, SDT-based model of wellbeing in the transition from university, make theoretical contributions to SDT and other frameworks (i.e., the self-concordance model, the theory of episodic memory need satisfaction, and the theory of narrative identity), raise intriguing questions for future research, and identify promising approaches to intervention to support the wellbeing of graduates during this key transition.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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 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
Published2021
Admission routes1
Has abstractyes

Explore more

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