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Record W2115034421 · doi:10.1037/a0014605

Linking goal progress to subjective well-being at work: The moderating role of goal-related self-efficacy and attainability.

2009· article· en· W2115034421 on OpenAlexafffund
Georgia Pomaki, Paul Karoly, Stan Maes

Bibliographic record

VenueJournal of Occupational Health Psychology · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of British Columbia
FundersMichael Smith Health Research BC
KeywordsPsychologyGoal settingCognitionGoal orientationGoal pursuitWell-beingSelf-efficacyNeed for cognitionCognitive psychologyWork motivationSubjective well-beingSocial psychologyWork (physics)PsychotherapistHappiness

Abstract

fetched live from OpenAlex

Although goal progress is often hypothesized to be positively linked to well-being, existing research points to an inconsistent relationship and suggests that potential moderators need to be examined. This longitudinal study investigated whether 2 aspects of goal cognition-goal attainability and self-efficacy-influence the relationship between goal progress and well-being (viz., job satisfaction and emotional exhaustion) in a sample of 172 nurses. Work goal progress was not directly associated with well-being. Rather, the link between goal progress and well-being was moderated by goal cognition. Individuals who started off with unfavorable goal cognitions but who managed to achieve goal progress reported an increase in well-being, compared with those who had favorable goal cognitions and similar rates of progress. Progress appears to have compensated for low initial goal cognition in the prediction of well-being, and high initial goal cognition appears to have undermined this predictive relationship. Also, goal progress was associated with an increase in self-efficacy and goal attainability from Time 1 to Time 2. Results are discussed in relation to goal theories and the concept of self-correcting goal cycles.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.346
Teacher spread0.329 · 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.

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

Citations63
Published2009
Admission routes2
Has abstractyes

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