Streblo: the app prototype for managing stress in the construction industry

High levels of stress at work, great responsibilities, hazards and lack of balance between tasks and deadlines are common in the daily lives of many construction workers. Changing the patterns of thinking and behaviours is not an easy mission, and it requires constant support, learning and determination. E-health applications can contribute to this change through their ability to foster continuous interaction with the user. Mobile phone apps have shown promising results in the field of ‘e-health and wellbeing’. Accordingly, an App is being designed as a self-help system for stress management which will enable construction workers to 1) detect the onset of stress quite early, 2) track their stress status, 3) empower persons to cope with stressful and/or demanding situations in an adaptive way, 4) improve and streamline the operability of job tasks, and 5) optimise efficient solutions for the construction industry. The development of this innovative app, known as Streblo, is part of a wider research that is studying stress management in the construction industry. Streblo’s blueprint will match personality traits with coping strategies in real- life situations. Its inputs are being generated from a field study that has commenced, where 23 structured interviews have been used to collect data from construction workers on their 1) personality and 2) behaviours while experiencing stress. Results of the data collection and analysis are being used to develop Streblo (an App) with IT experts. The paper reports the detail development and performance of Streblo’s prototype. Ultimately, users will be able to engage Streblo on electronic devices (mobile phones, tablets, and computers) through both text and image-based communication obtain real-time solutions and feedbacks on their stress status. Streblo will enhance and support attitude and behavioural changes in people who suffer from stress symptoms in the construction industry.Streblo is being developed within a European Commission (EC) project H2020-MSCA- IF-2015/H2020-MSCA-IF-2015, Grant Agreement: 703236 - ‘Inhibiting Stress in the Construction Industry’ (INSTINCT). The authors are very grateful for this funding

Predictors of metabolic syndrome in community-dwelling older adults

OBJECTIVES: The metabolic syndrome has been associated with a variety of individual variables, including demographics, lifestyle, clinical measures and physical performance. We aimed to identify independent predictors of the prevalence and incidence of metabolic syndrome in a large cohort of older adults. METHODS: The Longitudinal Aging Study Amsterdam is a prospective cohort including community-dwelling adults aged 55-85 years. Metabolic syndrome was defined according to criteria of the National Cholesterol Education Program Adult Treatment Panel III. The incidence of metabolic syndrome was calculated over a period of three years. Stepwise backward logistic regression analyses were used to identify predictors, including variables for demographics, lifestyle, clinical measures and physical performance, both in a cross-sectional cohort (n = 1292) and a longitudinal sub-cohort (n = 218). RESULTS: Prevalence and incidence of metabolic syndrome were 37% (n = 479) and 30% (n = 66), respectively. Cross-sectionally, heart disease (OR: 1.91, 95% CI: 1.37-2.65), peripheral artery disease (OR: 2.13, 95% CI: 1.32-3.42), diabetes (OR: 4.74, 95% CI: 2.65-8.48), cerebrovascular accident (OR: 1.92, 95% CI: 1.09-3.37), and a higher Body Mass Index (OR: 1.32, 95% CI: 1.26-1.38) were significant independent predictors of metabolic syndrome. Longitudinally, Body Mass Index (OR: 1.16, 95% CI: 1.05-1.27) was an independent predictor of metabolic syndrome. CONCLUSION: Four age related diseases and a higher Body Mass Index were the only predictors of metabolic syndrome in the cross-sectional cohort, despite the large variety of variables included in the multivariable analysis. In the longitudinal sub-cohort, a higher Body Mass Index was predictive of developing metabolic syndrome

Predicting trajectories of functional decline in 60- to 70-year-old people

Background: Early identification of people at risk of functional decline is essential for delivering targeted preventive interventions. Objective: The aim of this study is to identify and predict trajectories of functional decline over 9 years in males and females aged 60–70 years. Methods: We included 403 community-dwelling participants from the InCHIANTI study and 395 from the LASA study aged 60–70 years at baseline, of whom the majority reported no functional decline at baseline (median 0, interquartile range 0–1). Participants were included if they reported data on ≥ 2 measurements of functional ability during a 9-year follow-up. Functional ability was scored with 6 self-reported items on activities of daily living. We performed latent class growth analysis to identify trajectories of functional decline and applied multinomial regression models to develop prediction models of identified trajectories. Analyses were stratified for sex. Results: Three distinct trajectories were identified: no/little decline (219 males, 241 females), intermediate decline (114 males, 158 females), and severe decline (36 males, 30 females). Higher gait speed showed decreased risk of functional limitations in males (intermediate limitations, odds ratio [OR] 0.74, 95% CI 0.57–0.97; severe limitations, OR 0.42, 95% CI 0.26–0.66). The final model in males further included the predictors fear of falling and alcohol intake (no/little decline, area under the receiver operating curve [AUC] 0.68, 95% CI 0.62–0.73; intermediate decline, AUC 0.63, 95% CI 0.56–0.69; severe decline, AUC 0.79, 95% CI 0.71–0.87). In females, higher gait speed showed a decreased risk of intermediate limitations (OR 0.51, 95% CI 0.38–0.68) and severe limitations (OR 0.18, 95% CI 0.07–0.44). Other predictors in females were age, living alone, economic satisfaction, balance, physical activity, BMI, and cardiovascular disease (no/little decline, AUC 0.80, 95% CI 0.75–0.85; intermediate decline, AUC 0.74, 95% CI 0.69–0.79; severe decline, AUC 0.95, 95% CI 0.91–0.99). Conclusion: Already in people aged 60–70 years, 3 distinct trajectories of functional decline were identified in these cohorts over a 9-year follow-up. Predictors of trajectories differed between males and females, except for gait speed. Identification of people at risk is the basis for targeting interventions

Characteristics of effective self-management interventions in patients with COPD: individual patient data meta-analysis

It is unknown whether heterogeneity in effects of self-management interventions in patients with chronic obstructive pulmonary disease (COPD) can be explained by differences in programme characteristics. This study aimed to identify which characteristics of COPD self-management interventions are most effective. Systematic search in electronic databases identified randomised trials on self-management interventions conducted between 1985 and 2013. Individual patient data were requested for meta-analysis by generalised mixed effects models. 14 randomised trials were included (67% of eligible), representing 3282 patients (75% of eligible). Univariable analyses showed favourable effects on some outcomes for more planned contacts and longer duration of interventions, interventions with peer contact, without log keeping, without problem solving, and without support allocation. After adjusting for other programme characteristics in multivariable analyses, only the effects of duration on all-cause hospitalisation remained. Each month increase in intervention duration reduced risk of all-cause hospitalisation (time to event hazard ratios 0.98, 95% CI 0.97–0.99; risk ratio (RR) after 6 months follow-up 0.96, 95% CI 0.92–0.99; RR after 12 months follow-up 0.98, 95% CI 0.96–1.00). Our results showed that longer duration of self-management interventions conferred a reduction in all-cause hospitalisations in COPD patients. Other characteristics are not consistently associated with differential effects of self-management interventions across clinically relevant outcomes

The structural and convergent validity of three commonly used measures of self-management in persons with neurological conditions

Purpose Self-management ability is commonly assessed in chronic disease research and clinical practice. The purpose of this study was to assess the structural and convergent validity of three commonly used self-management outcome measures in a sample of persons with neurological conditions. Methods We used data from a Canadian survey of persons with neurological conditions, which included three commonly used self-management measures: the Partners in Health Scale (PIH), the Patient Activation Measure (PAM), and the Self-Efficacy for Managing a Chronic Disease Scale (SEMCD). Confirmatory factor analysis was used to assess the structural and convergent validity of the three measures. Results When treated as single-factor constructs, none of the measurement models provided a good fit to the data. A four-domain version of the PIH was the best fitting model. Confirmatory factor analysis suggests that the three tools measure different, but correlated constructs. Conclusions While the PAM, PIH and SEMCD scales are all used as measures of patient self-management, our study indicates that they measure different, but correlated latent variables. None, when treated as single, uni-dimensional construct, provides an acceptable fit to our data. This is probably because self-management is multi-dimensional, as is consistently shown by qualitative evidence. While these measures may provide reliable summative measures, multi-dimensional scales are needed for clinical use and more detailed research on self-management