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Record W4376617814 · doi:10.1097/nna.0000000000001293

Thinking, Feeling, Behaving

2023· article· en· W4376617814 on OpenAlexaff
Deborah Price, Nicole Figueroa, Linda Macera-DiClemente, Sue Wintermeyer-Pingel, Penny Riley, Dana Tschannen

Bibliographic record

VenueJONA The Journal of Nursing Administration · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsFeelingPsychologyCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study examined the impact of the MINDBODYSTRONG ® program on mental health and lifestyle behaviors among a sample of staff nurses, clinical nurse leaders, and faculty, when offered after the onset of the COVID-19 pandemic. BACKGROUND: Previous studies have demonstrated the MINDBODYSTRONG program decreased anxiety and depressive symptoms, improved job satisfaction, and sustained healthy lifestyle behaviors in newly licensed RNs. This program has not been studied with experienced nurses. In addition, the use of a virtual format is unique. METHODS: A pre-post design was used for this pilot study. Subjects were recruited from a large Midwestern medical center and affiliated school of nursing. Registered participants of the MINDBODYSTRONG program attended 7 weekly sessions virtually. RESULTS: The MINDBODYSTRONG intervention suggests sustained improvement in perceived stress, anxiety, depression, and use of healthy behaviors. CONCLUSION: This pilot study supports that the MINDBODYSTRONG program may be effective in addressing mental health and healthy lifestyle beliefs for staff nurses, clinical nurse leaders, and nursing faculty.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.142
GPT teacher head0.484
Teacher spread0.342 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2023
Admission routes1
Has abstractyes

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Same venueJONA The Journal of Nursing AdministrationSame topicCOVID-19 and Mental HealthFrench-language works237,207