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Record W2755735949 · doi:10.1080/02615479.2017.1388776

Exploring the impact of mindfulnesss on mental wellbeing, stress and resilience of undergraduate social work students

2017· article· en· W2755735949 on OpenAlexfundno aff
Audrey Roulston, Lorna Montgomery, Anne Campbell, Gavin Davidson

Bibliographic record

VenueSocial Work Education · 2017
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsMindfulnessPsychologyThematic analysisPsychological resilienceMental healthClinical psychologyScale (ratio)AnxietyIntervention (counseling)Qualitative researchSocial psychologyPsychotherapistPsychiatrySociology

Abstract

fetched live from OpenAlex

Mindfulness is becoming more popular as emerging research demonstrates its benefits for self-care, by cultivating calmness and decreasing stress or anxiety. This pilot study aimed to measure the impact of a six-week Mindfulness course, modelled on the manualised treatment programme developed by Kabat-Zinn on the mental well-being, stress and resilience of undergraduate social work students in Northern Ireland. This was a mixed methods study involving two groups: (1) intervention group participants who attended a six-week Mindfulness course (April–May 2016) and (2) control group participants. Basic socio-demographic data were collected from all participants and all were invited to complete the Warwick-Edinburgh Mental Well-being Scale, the Perceived Stress Scale and the Resilience Scale during weeks 1 and 6. Statistical tests were used to compare mean scores from the scales, and qualitative data were manually analysed using thematic content analysis. Findings indicated significant changes in the scores for well-being, stress and resilience for the intervention group, but not for the control group. Mindfulness may not appeal to all students so it should not be a mandatory component of training, but may be offered as one of the wider approaches to self-care for undergraduate social work degree students.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.072
GPT teacher head0.411
Teacher spread0.339 · 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

Citations60
Published2017
Admission routes1
Has abstractyes

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