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Record W4392463242 · doi:10.1080/19371918.2024.2325564

Exploring Social Work professionals’ Experiences of the Mindfulness-Based Social Work and Self-Care Programme: A Focus Group Study

2024· article· en· W4392463242 on OpenAlexaff
Alan Maddock, Karen McGuigan, Pearse McCusker

Bibliographic record

VenueSocial Work in Public Health · 2024
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsQueen's University
FundersDepartment of Health, Northern Ireland
KeywordsSocial workPsychologyMindfulnessThematic analysisSuperordinate goalsFocus groupCoping (psychology)Social supportSocial psychologyApplied psychologyQualitative researchClinical psychologySociology

Abstract

fetched live from OpenAlex

The evidence for the potential of mindfulness-based programmes to support improved social work practice and self-care is growing. The aim of this focus group study was to explore social workers’ (n = 13) experiences of the Mindfulness-based Social Work and Self-care programme (MBSWSC). Thematic analysis highlighted two superordinate themes: benefits to direct social work practice and coping with the social work role. Four subordinate themes highlighted the different social work practice components that were enhanced through MBSWSC participation: social work assessment, service user engagement and team working, working to social work values, and social work skills. Three subordinate themes identified improvements in individual processes which supported enhanced stress coping: moving from avoidant to approach coping, improved boundaries, increased emotional awareness and reduced negative thinking. Our findings indicate that the MBSWSC programme can have a multi-faceted positive effect on social work practice, and on social work professional’s capacity to cope with their role.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.005
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.135
GPT teacher head0.395
Teacher spread0.260 · 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 designQualitative
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

Citations5
Published2024
Admission routes1
Has abstractyes

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