Developing a prognostic model for stress reduction in patients with prolonged work-related stress.
Stress Health
; 2023 Oct 18.
Article
in En
| MEDLINE
| ID: mdl-37853852
ABSTRACT
Mindfulness-based stress reduction (MBSR) is a 9-session group-treatment programme for managing stress. Research suggests variability in the outcomes of MBSR among participants. This prognostic (not causal) study develops a multivariable model that may support clinicians in forecasting expected MBSR outcomes. We used data of 763 patients collected from MBSR programs conducted between October 2015 and March 2022. Candidate prognostic factors at baseline included psychosocial work environment, sociodemographic, and clinical information. Multiple imputation was used to handle missing data (imputations = 200). Important prognostic factors were backward selected in ≥5% of the imputed datasets. The final prediction model including the selected prognostic factors was evaluated using linear regression with a four-fold internal cross-validation procedure. Reductions in perceived stress from baseline to end of the MBSR programme were predicted by a lower General Severity Index (ß = 2.00, p < 0.01), higher baseline levels of stress (ß = -0.88, p < 0.01), and somewhat by having managerial responsibility in the latest job (vs. no; ß = -2.53, p = 0.07). The remaining prognostic factors were weaker predictors, for example, gender and income. Internal validity of the final model was indicated by consistent results from four randomly folded subsamples. This study developed a prognostic model predicting changes in stress levels in relation to the MBSR programme. A reduction in stress level was particularly predicted by milder psychological symptoms and higher baseline levels of perceived stress. These predictions cannot be taken as evidence of causal associations. Forecasting of the illness course should be cautiously practiced using clinical judgement regarding individual patients.
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1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Stress Health
Year:
2023
Document type:
Article
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