A substantial proportion of chronic disease patients do not respond to self-management interventions, which suggests that one size interventions do not fit all, demanding more tailored interventions. To compose more individualized strategies, we aim to increase our understanding of characteristics associated with patient activation for self-management and to evaluate whether these are disease-transcending. A cross-sectional survey study was conducted in primary and secondary care in patients with type-2 Diabetes Mellitus (DM-II), Chronic Obstructive Pulmonary Disease (COPD), Chronic Heart Failure (CHF) and Chronic Renal Disease (CRD). Using multiple linear regression analysis, we analyzed associations between self-management activation (13-item Patient Activation Measure; PAM-13) and a wide range of socio-demographic, clinical, and psychosocial determinants. Furthermore, we assessed whether the associations between the determinants and the PAM were disease-transcending by testing whether disease was an effect modifier. In addition, we identified determinants associated with low activation for self-management using logistic regression analysis. We included 1154 patients (53% response rate); 422 DM-II patients, 290 COPD patients, 223 HF patients and 219 CRD patients. Mean age was 69.6±10.9. Multiple linear regression analysis revealed 9 explanatory determinants of activation for selfmanagement: age, BMI, educational level, financial distress, physical health status, depression, illness perception, social support and underlying disease, explaining a variance of 16.3%. All associations, except for social support, were disease transcending. This study explored factors associated with varying levels of activation for self-management. These results are a first step in supporting clinicians and researchers to identify subpopulations of chronic disease patients less likely to be engaged in self-management. Increased scientific efforts are needed to explain the greater part of the factors that contribute to the complex nature of patient activation for self-management.
Introduction: The association between obesity and outcome in critical illness is unclear. Since the amount of visceral adipose tissue(VAT) rather than BMI mediates the health effects of obesity we aimed to investigate the association between visceral obesity, BMI and 90-day mortality in critically ill patients. Method: In 555 critically ill patients (68% male), the VAT Index(VATI) was measured using Computed Tomography scans on the level of vertebra L3. The association between visceral obesity, BMI and 90-day mortality was investigated using univariable and multivariable analyses, correcting for age, sex, APACHE II score, sarcopenia and muscle quality. Results: Visceral obesity was present in 48.1% of the patients and its prevalence was similar in males and females. Mortality was similar amongst patients with and without visceral obesity (27.7% vs 24.0%, p = 0.31). The corrected odds ratio of 90-day mortality for visceral obesity was 0.667 (95%CI 0.424–1.049, p = 0.080). Using normal BMI as reference, the corrected odds ratio for overweight was 0.721 (95%CI 0.447–1.164 p = 0.181) and for obesity 0.462 (95%CI 0.208–1.027, p = 0.058). Conclusion: No significant association of visceral obesity and BMI with 90-day mortality was observed in critically ill patients, although obesity and visceral obesity tended to be associated with improved 90-day mortality.
BACKGROUND: Seclusion is a controversial intervention. Efficacy with regard to aggressive behaviour has not been demonstrated, and seclusion is only justified for preventing safety hazards. Previous studies indicate that nursing staff factors may be predictors for seclusion, although methodological issues may have led to equivocal results.OBJECTIVE: To perform a prospective cohort study to determine whether nursing staff characteristics are associated with seclusion of adult inpatients admitted to a closed psychiatric ward.METHOD: We studied the association between nurses' demographics and incidence of seclusion during every shift. Data were collected during five months in 2013. Multiple logistic regression was used for analysis.RESULTS: In univariable analysis, we found a non-significant association between seclusion and female gender, odds ratio (OR) = 5.27 (0.98-28.49) and a significant association between seclusion and nurses' large physical stature, OR = 0.21 (0.06-0.72). We found that physical stature is the most substantial factor, although not significant: ORadjusted = 0.27 (0.07-1.04).CONCLUSION: Nurses' gender may be a predictor for seclusion, but it seems to be mediated by the effect of physical stature. We used a rigorous, census-based, prospective design to collect data on a highly detailed level and found a large effect of physical stature of nurses on seclusion. We found nurses' physical stature to be the most substantial predictor for seclusion. These and other factors need to be explored in further research with larger sample size.
