Effects of interventions implemented by occupational health professionals to prevent work-related stress complaints: a systematic review.

Work-related stress complaints are a growing societal problem. Occupational health professionals often play a key role in its prevention. However, studies providing an overview of preventive interventions and their effectiveness are lacking. Therefore, the aim of this systematic review was to summarise the evidence on the effectiveness of interventions delivered by occupational health professionals to prevent work-related stress complaints.A systematic search in PubMed, Embase, PsycInfo and Medline was performed in May 2023 based on PICO (population, intervention, control and outcomes) elements. Inclusion criteria were: peer-reviewed papers with a randomised controlled trial design, quasi-experimental design and pre-post evaluations with a control group; working populations not on sick leave; interventions delivered by occupational health professionals; and stress outcomes. Data were extracted using a predefined extraction form, risk of bias was assessed using the Cochrane risk of bias tool for randomised trials (RoB-2) and Risk of Bias in non-randomised Studies-of Interventions tool, and a narrative analysis was performed to summarise data.Nine studies were included in this review and encompassed a diverse range of populations, interventions and professionals involved, outcome measures, and effects observed. Five studies found either mixed effects on stress outcomes, short-term positive effects, or positive effects in a subgroup of participants demonstrating high adherence to the intervention.As the results show mixed findings, a high risk of bias, and a limited number of studies was available, more research is needed to the effectiveness of the interventions and the factors underlying this.

Electronic Nose Sensor Drift Affects Diagnostic Reliability and Accuracy of Disease-Specific Algorithms.

Sensor drift is a well-known disadvantage of electronic nose (eNose) technology and may affect the accuracy of diagnostic algorithms. Correction for this phenomenon is not routinely performed. The aim of this study was to investigate the influence of eNose sensor drift on the development of a disease-specific algorithm in a real-life cohort of inflammatory bowel disease patients (IBD). In this multi-center cohort, patients undergoing colonoscopy collected a fecal sample prior to bowel lavage. Mucosal disease activity was assessed based on endoscopy. Controls underwent colonoscopy for various reasons and had no endoscopic abnormalities. Fecal eNose profiles were measured using Cyranose 320®. Fecal samples of 63 IBD patients and 63 controls were measured on four subsequent days. Sensor data displayed associations with date of measurement, which was reproducible across all samples irrespective of disease state, disease activity state, disease localization and diet of participants. Based on logistic regression, corrections for sensor drift improved accuracy to differentiate between IBD patients and controls based on the significant differences of six sensors (p = 0.004; p < 0.001; p = 0.001; p = 0.028; p < 0.001 and p = 0.005) with an accuracy of 0.68. In this clinical study, short-term sensor drift affected fecal eNose profiles more profoundly than clinical features. These outcomes emphasize the importance of sensor drift correction to improve reliability and repeatability, both within and across eNose studies.