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Record W2937988831 · doi:10.1177/0008417419833402

Boredom and meaningful activity in adults experiencing homelessness: A mixed-methods study

2019· article· en· W2937988831 on OpenAlexvenueno aff
Carrie Anne Marshall, Lisa M. Davidson, Andrea Li, Rebecca Gewurtz, Laurence Roy, Skye Barbic, Bonnie Kirsh, Rosemary Lysaght

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsnot available
Fundersnot available
KeywordsBoredomPsychologySocial connectednessPsychological interventionQualitative researchClinical psychologyDevelopmental psychologySocial psychologySociologyPsychiatry

Abstract

fetched live from OpenAlex

Background. Boredom has been reported as a frequent problem experienced by homeless persons, with implications for mental and social well-being. Purpose. This study aimed to explore the nature and impact of boredom in the lives of homeless and formerly homeless persons. Method. A mixed-methods design was used to engage 13 participants in a structured 92-item quantitative interview using six standardized measures, followed by a semistructured qualitative interview. Correlational analyses were performed with the data compiled from the quantitative interviews, and grounded theory strategies were used to analyze our qualitative data. The two analyses were integrated at the stage of interpretation. Findings. Boredom was described as a profound and pervasive experience for homeless persons, imposing deleterious impacts on mental well-being and driving substance use. A strong positive correlation between meaningful activity and mental well-being ( r s = .767, p <. 01) and a strong negative correlation between boredom and belonging in one’s community ( r s = –.771, p < .01) were identified. Implications. Boredom is a critical topic of study for occupational therapy in the area of homelessness. Future research is needed to design and test interventions to optimize the mental well-being, participation, and social connectedness of this population.

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 score0.285
Threshold uncertainty score0.332

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 integrity0.0000.000
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 head0.081
GPT teacher head0.386
Teacher spread0.305 · 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

Citations62
Published2019
Admission routes1
Has abstractyes

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