Improving the delivery of care for patients with diabetes through understanding optimised team work and organisation in primary care

Peer reviewedPublisher PD

Interactional justice at work is related to sickness absence: a study using repeated measures in the Swedish working population

Background: Research has shown that perceived unfairness contributes to higher rates of sickness absence. While shorter, but more frequent periods of sickness absence might be a possibility for the individual to get relief from high strain, long-term sickness absence might be a sign of more serious health problems. The Uncertainty Management Model suggests that justice is particularly important in times of uncertainty, e.g. perceived job insecurity. The present study investigated the association between interpersonal and informational justice at work with long and frequent sickness absence respectively, under conditions of job insecurity. Methods: Data were derived from the 2010, 2012, and 2014 biennial waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH). The final analytic sample consisted of 19,493 individuals. We applied repeated measures regression analyses through generalized estimating equations (GEE), a method for longitudinal data that simultaneously analyses variables at different time points. We calculated risk of long and frequent sickness absence, respectively in relation to interpersonal and informational justice taking perceptions of job insecurity into account. Results: We found informational and interpersonal justice to be associated with risk of long and frequent sickness absence independently of job insecurity and demographic variables. Results from autoregressive GEE provided some support for a causal relationship between justice perceptions and sickness absence. Contrary to expectations, we found no interaction between justice and job insecurity. Conclusions: Our results underline the need for fair and just treatment of employees irrespective of perceived job insecurity in order to keep the workforce healthy and to minimize lost work days due to sickness absence

Instrument development, data collection, and characteristics of practices, staff, and measures in the Improving Quality of Care in Diabetes (iQuaD) Study

Peer reviewedPublisher PD

Statistical analysis plan for the LAKANA trial: a cluster-randomized, placebo-controlled, double-blinded, parallel group, three-arm clinical trial testing the effects of mass drug administration of azithromycin on mortality and other outcomes among 1–11-month-old infants in Mali

BACKGROUND:The Large-scale Assessment of the Key health-promoting Activities of two New mass drug administration regimens with Azithromycin (LAKANA) trial in Mali aims to evaluate the efficacy and safety of azithromycin (AZI) mass drug administration (MDA) to 1–11-month-old infants as well as the impact of the intervention on antimicrobial resistance (AMR) and mechanisms of action of azithromycin. To improve the transparency and quality of this clinical trial, we prepared this statistical analysis plan (SAP). METHODS/DESIGN: LAKANA is a cluster randomized trial that aims to address the mortality and health impacts of biannual and quarterly AZI MDA. AZI is given to 1–11-month-old infants in a high-mortality setting where a seasonal malaria chemoprevention (SMC) program is in place. The participating villages are randomly assigned to placebo (control), two-dose AZI (biannual azithromycin-MDA), and four-dose AZI (quarterly azithromycin-MDA) in a 3:4:2 ratio. The primary outcome of the study is mortality among the intention-to-treat population of 1–11-month-old infants. We will evaluate relative risk reduction between the study arms using a mixed-effects Poisson model with random intercepts for villages, using log link function with person-years as an offset variable. We will model outcomes related to secondary objectives of the study using generalized linear models with considerations on clustering. CONCLUSION: The SAP written prior to data collection completion will help avoid reporting bias and data-driven analysis for the primary and secondary aims of the trial. If there are deviations from the analysis methods described here, they will be described and justified in the publications of the trial results. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT04424511. Registered on 11 June 2020

Pandemic dreams: network analysis of dream content during the COVID-19 lockdown

We used crowdsourcing (CS) to examine how COVID-19 lockdown affects the content of dreams and nightmares. The CS took place on the 6th week of the lockdown. Over the course of one week, 4275 respondents (mean age 43, SD=14 years) assessed their sleep and 811 reported their dream content. Overall, respondents slept substantially more (54.2%) but reported an average increase of awakenings (28.6%) and nightmares (26%) from the pre-pandemic situation. We transcribed the content of the dreams into word lists and performed unsupervised computational network and cluster analysis of word associations, which suggested 33 dream clusters including 20 bad dream clusters, of which 55% were pandemic specific (e.g. Disease Management, Disregard of Distancing, Elderly in Trouble). The dream association networks were more accentuated for those who reported an increase in perceived stress. This CS survey on dream-association networks and pandemic stress introduces novel, collectively shared COVID-19 bad dream contents. </p

Is organizational justice climate at the workplace associated with individual-level quality of care and organizational affective commitment?:A multi-level, cross-sectional study on dentistry in Sweden

Purpose The aim of this study is to investigate whether organizational justice climate at the workplace level is associated with individual staff members’ perceptions of carequality and affective commitment to the workplace.Methods The study adopts a cross-sectional multi-level design. Data were collected using an electronic survey and a response rate of 75% was obtained. Organizational justice climate and affective commitment to the workplace were measured by items from Copenhagen Psychosocial Questionnaire and quality of care by three self-developed items. Non-managerial staff working at dental clinics with at least five respondents (n = 900 from 68 units) was included in analyses. A set of Level-2 random intercept models were built to predict individual-level organizational affective commitment and perceived quality of care from unit-level organizational justice climate, controlling for potential confoundingby group size, gender, age, and occupation.Results The results of the empty model showed substantial between-unit variation for both affective commitment (ICC-1 = 0.17) and quality of care (ICC-1 = 0.12). The overall results showed that the shared perception of organizational justice climate at the clinical unit level was significantly associated with perceived quality of care and affective commitment to the organization (p < 0.001).Conclusions Organizational justice climate at work unit level explained all variation in affective commitment among dental clinics and was associated with both the individualstaff members’ affective commitment and perceived quality of care. These findings suggest a potential for that addressing organizational justice climate may be a way to promote quality of care and enhancing affective commitment. However, longitudinal studies are needed to support causality in the examined relationships. Intervention research is also recommended to probe the effectiveness of actions increasingunit-level organizational justice climate and test their impact on quality of care and affective commitment

The Network Structure of Childhood Psychopathology in International Adoptees

International adoptees are at an increased risk of emotional and behavioral problems, especially those who are adopted at an older age. We took a new approach in our study of the network structure and predictability of emotional and behavioral problems in internationally adopted children in Finland. Our sample was from the on-going adoption study and comprised 778 internationally adopted children (387 boys and 391 girls, mean age 10.5 (SD 3.4) years). Networks were estimated using Gaussian graphical models and lasso regularization for all the children, and separately for those who were adopted at different ages. The results showed that anxiety/depressive symptoms, social problems, and aggressiveness were the most central symptom domains. Somatic symptoms were the least central and had the weakest effect on the other domains. Similarly, aggressiveness, social problems, and attention problems were high in terms of predictability (73-65%), whereas internalizing problems were relatively low (28-56%). There were clear but local age-group differences in network structure, symptom centrality, and predictability. According to our findings, network models provide important additional information about the centrality and predictability of specific symptom domains, and thus may facilitate targeted interventions among international adoptees.Peer reviewe

Team climate, intention to leave and turnover among hospital employees: Prospective cohort study

<p>Abstract</p> <p>Background</p> <p>In hospitals, the costs of employee turnover are substantial and intentions to leave among staff may manifest as lowered performance. We examined whether team climate, as indicated by clear and shared goals, participation, task orientation and support for innovation, predicts intention to leave the job and actual turnover among hospital employees.</p> <p>Methods</p> <p>Prospective study with baseline and follow-up surveys (2–4 years apart). The participants were 6,441 (785 men, 5,656 women) hospital employees under the age of 55 at the time of follow-up survey. Logistic regression with generalized estimating equations was used as an analysis method to include both individual and work unit level predictors in the models.</p> <p>Results</p> <p>Among stayers with no intention to leave at baseline, lower self-reported team climate predicted higher likelihood of having intentions to leave at follow-up (odds ratio per 1 standard deviation decrease in team climate was 1.6, 95% confidence interval 1.4–1.8). Lower co-worker assessed team climate at follow-up was also association with such intentions (odds ratio 1.8, 95% confidence interval 1.4–2.4). Among all participants, the likelihood of actually quitting the job was higher for those with poor self-reported team climate at baseline. This association disappeared after adjustment for intention to leave at baseline suggesting that such intentions may explain the greater turnover rate among employees with low team climate.</p> <p>Conclusion</p> <p>Improving team climate may reduce intentions to leave and turnover among hospital employees.</p