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Record W3136580386 · doi:10.3390/ijerph18062897

Meaning in Life Mediates the Association between Environmental Engagement and Loneliness

2021· article· en· W3136580386 on OpenAlexafffundabout
Fanli Jia, Kendall Soucie, Kyle Matsuba, Michael W. Pratt

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsWilfrid Laurier UniversityKwantlen Polytechnic UniversityUniversity of Windsor
FundersWilfrid Laurier University
KeywordsLonelinessMeaning (existential)PsychologyAssociation (psychology)Thematic analysisEnvironmentalismSocial psychologyPerspective (graphical)Qualitative researchDevelopmental psychologySociologyPsychotherapistPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Although the positive outcomes of human-environment interactions have been established, research examining the motivation between engagement in pro-environmental activities and psychological well-being is limited. In this mixed-methods study, the relationship between pro-environmental engagement, meaning in life, and well-being, including loneliness and depression, were investigated in a sample of 112 young adults in Canada. It was found that engaging in pro-environmental activities was negatively associated with loneliness. This association was mediated by meaning in life (e.g., an intrinsic motive of caring for future generations). In addition, qualitative analyses explored how engaging in pro-environmental activities has a meaningful impact on meaning in life, and on well-being. A thematic analysis generated three unique themes: (1) responsibility to teach the next generation about the environment, (2) deep appreciation for and connection to nature, and (3) renewed agency through self-directed learning. Overall, findings suggest that meaning in life is a core motive that underlies the association between environmental engagement and loneliness. The present study enriched the relationship between pro-environmentalism and well-being with a mixed-methods perspective.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 science0.0000.001
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 head0.065
GPT teacher head0.376
Teacher spread0.311 · 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.

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

Citations16
Published2021
Admission routes3
Has abstractyes

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