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Record W4210363294 · doi:10.1089/jicm.2021.0180

The Effect of the Inner Engineering Online Program as a Positive Intervention on Subjective Well-Being and Positive Work Outcomes

2022· article· en· W4210363294 on OpenAlexaff
Tracy F. H. Chang, Triya Tessa Ramburn, Sheetal Pundir, Pradeep Purandare, Balachundhar Subramaniam

Bibliographic record

VenueJournal of Integrative and Complementary Medicine · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsVitalityWork (physics)PsychologyMindfulnessPsychological interventionApplied psychologyIntervention (counseling)Social psychologyClinical psychologyEngineering

Abstract

fetched live from OpenAlex

Objective: This study evaluates the effect of Inner Engineering Online (IEO) on subjective well-being and positive work outcomes. Design: The study uses a field quasi-experimental one group design with pre- and post-tests. Interventions: IEO is a multicomponent online self-paced program. The program consists of seven online sessions to be completed over a 4-week period. Results: The study finds that IEO has a positive effect on subjective well-being (mindfulness, joy, vitality, restfulness, and oneness) and positive work outcomes (meaningful work, psychological capital, and work engagement). Conclusion: The findings on IEO have important practical implications for improving subjective well-being and work experiences.

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 score0.407
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.336
Teacher spread0.326 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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