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Remote delivery of a mindfulness-based intervention to decrease stress levels and promote coping among health-care workers during the COVID-19 pandemic.

2023· article· en· W4379282883 on OpenAlexaff
Joelle Helou, Aisling Barry, Xiang Y. Ye, Fei‐Fei Liu, Anet Julius, D. Létourneau, Philip Wong, Laura A. Dawson, Mary Elliott

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkWestern University
Fundersnot available
KeywordsMindfulnessMedicinePsychological interventionBurnoutCoping (psychology)Intervention (counseling)Health careClinical psychologyFamily medicinePhysical therapyNursing

Abstract

fetched live from OpenAlex

11007 Background: The COVID-19 pandemic has caused significant stress amongst everyone around the world. Healthcare workers (HCW) in particular, experience substantial stress in these challenging environments. In an effort to find supportive interventions for radiation oncology providers, while respecting the requirements of physical distancing, we proposed the remote delivery of a mindfulness-based intervention (MBI). The primary aim of this study is to determine the association of this intervention with a reduction of perceived stress. Secondary aims are to evaluate the impact on coping and burnout amongst HCW in the Radiation Program (RP). Methods: This is a single-centre, single-arm, pilot study. All HCW associated with the RP were eligible. This was a voluntary effort. The intervention - manualized, mindfulness-based group for HCW, entitled Mindfulness-Based Resilience and Well-Being Training, consisted of four 1-hour sessions per week for 4 weeks. From Nov 2020 to Dec 2021, 6 consecutive closed groups MBI were delivered remotely using Zoom. Each group consisted of 5-12 participants and one professional with a background in mindfulness facilitation. The Perceived Stress Scale (PSS), The Maslach Burnout Inventory and the BriefCOPE questionnaire were collected pre-intervention, and at 1, 4 and 12 weeks post-intervention. Linear mixed effect models with a random intercept to account for the repeated measures were used to assess the change of outcomes over time. Results: Amongst 43 HCWs who expressed initial interest, 33 completed the study. At 1-, 4- and 12-weeks post-intervention 25, 24 and 21 participants provided completed questionnaires respectively. Time constraint was the main reason for withdrawal and missing data. There was a significant decrease in perceived stress at week 1, 4 and 12 when compared to baseline [mean baseline PSS score: 22.5 (SD = 4.6), week 1: 18.4 (4.9), p= 0.002, week 4: 16.8 (6.5), p< 0.001, week 12: 16.3 (6.8), p< 0.001]. Overall, 7 (21%) participants reported high PSS (27-40) at baseline while none reported high levels at 1 and 12 weeks. Problem focused coping( p= 0.02), and active coping ( p= 0.009) were significantly higher at 1 week but not at 4 and 12 weeks. Conclusions: The remote delivery of a MBI is feasible and effective to reduce perceived stress levels and to promote coping across HCWs. These findings need to be validated in a larger cohort. Time was a major constraint preventing the participation of interested HCWs. It would be extremely valuable for departments to support such interventions and programs to help HCWs cultivate skills to meet the demands related to working in healthcare environments throughout and beyond this crisis.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.296
GPT teacher head0.564
Teacher spread0.268 · 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 designNon-randomized trial
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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