How did general practices organize care during the COVID-19 pandemic: the protocol of the cross-sectional PRICOV-19 study in 38 countries

Background General practitioners (GPs) play a crucial role in the fight against the COVID-19 pandemic as the first point of contact for possibly infected patients and are responsible for short and long-term follow-up care of the majority of COVID-19 patients. Nonetheless, they experience many barriers to fulfilling this role. The PRICOV-19 study investigates how GP practices in 38 countries are organized during the COVID-19 pandemic to guarantee safe, effective, patient-centered, and equitable care. Also, the shift in roles and tasks and the wellbeing of staff members is researched. Finally, PRICOV-19 aims to study the association with practice- and health care system characteristics. It is expected that both characteristics of the GP practice and health care system features are associated with how GP practices can cope with these challenges. This paper describes the protocol of the study. Methods Using a cross-sectional design, data are collected through an online questionnaire sent to GP practices in 37 European countries and Israel. The questionnaire is developed in multiple phases, including a pilot study in Belgium. The final version includes 53 items divided into six sections: patient flow (including appointments, triage, and management for routine care); infection prevention; information processing; communication; collaboration and self-care; and practice and participant characteristics. In the countries where data collection is already finished, between 13 and 636 GP practices per country participated in the study. Questionnaire data are linked with OECD and HSMR data regarding national policy responses to the pandemic and analyzed using multilevel models considering the system- and practice-level. Discussion To the best of our knowledge, the PRICOV-19 study is the largest and most comprehensive study that examines how GP practices function during the COVID-19 pandemic. Its results can significantly contribute to better preparedness of primary health care systems across Europe for future major outbreaks of infectious diseases.

Mental health and loneliness in Scottish schools: A multilevel analysis of data from the Health Behaviour in School-aged Children study

Adolescent loneliness and poor mental health represent dual public health concerns. Yet, associations between loneliness and mental health, and critically, how these unfold in school settings are less understood. Framed by social ecological theory, this study aimed to identify key predictors of adolescent mental health, and examine school-level variation in the relationship between loneliness and mental health.Cross-sectional data on adolescents from the 2018 wave of the Health Behaviour in School-aged Children study (HBSC) in Scotland were used (N = 5,286). Mental health was measured as a composite variable containing items assessing: nervousness, irritability, sleep difficulties and feeling low. Loneliness was measured via a single item assessing how often adolescents felt ‘left out’. Multilevel models were used to identify key social ecological predictors of mental health, associations with loneliness, and between-school variation.Loneliness, as well as demographic, social, and school factors, were found to be associated with mental health. Schools accounted for around 8% of the variation in adolescents’ mental health, and the between-school difference in mental health was greater among adolescents with high levels of loneliness. Additionally, the negative effect of loneliness on mental health was stronger in schools with lower average mental health scores.The findings suggest that schools can play an important role in shaping adolescent mental health. Our study uniquely identifies that school-based interventions targeting mental health may be especially necessary among lonely adolescents, and programmes aimed at tackling loneliness may be more beneficial in schools with poorer mental health.

Temporal relationships between device-derived sedentary behavior, physical activity, and sleep in early childhood

Study Objectives Understanding the ideal composition of a child’s day requires a better understanding of the relations between wake behaviors (sedentary behavior [SB], physical activity [PA]) and sleep. Here we examine between- and within-person temporal associations between daytime wake behaviors and overnight sleep in early childhood, an important age when healthy behaviors are initiated and 24-hour behaviors are largely determined by caregivers. Methods Daily, repeated measures of wake behavior and overnight sleep were assessed via wrist-worn actigraphy (mean=9 days/nights) in 240 children (50.8±9.8 months). Multilevel models with lagged effects were used to examine the temporal associations between wake and overnight sleep measures and adjusted for daily nap duration, age, sex, and socioeconomic status. Results Between-person associations for sleep outcomes were negative between MVPA and total activity for sleep efficiency (SE). Between-person associations for wake outcomes were positive between sleep duration and light PA, and negative between SE and both MVPA and total PA. When children obtained higher SE relative to their individual average, they were more likely to engage in less SB and greater MVPA and total PA the next day. Conclusions Generally, days with greater activity or sleep were not associated with greater subsequent sleep or PA. Most subsequent behaviors were not influenced by children achieving higher activity or sleep relative to their individual average levels, although higher sleep efficiency was beneficially associated with next day wake behaviors. Future analyses with young children should consider within-person associations and could investigate lagged effects beyond one day.

The effects of opportunity motivation and environmental contingencies on market growth strategies of African early-stage entrepreneurs

PurposeThe purpose of this paper is to examine how early-stage entrepreneurs' opportunity motivation impacts their choice of market growth strategies as well as the contingent roles of institutional environments and product market conditions in Africa.Design/methodology/approachThe study employs hierarchical linear modeling to test multilevel models with nested data empirically.FindingsThe findings show that African early-stage entrepreneurs who are opportunity-driven and from countries with strong institutional environments have a higher tendency to adopt market exploration strategies. African early-stage entrepreneurs from countries with strong product market conditions have a higher tendency to adopt market penetration strategies. Further interaction tests show that both contingency conditions, namely institutional environments and product market conditions, moderate the effects of opportunity motivation on market growth strategies of African early-stage entrepreneurs.Practical implicationsThe study shows that policymakers in Africa need to develop flexible, supportive market-related policies based on entrepreneurs' growth paths, institutional environments and product market conditions.Originality/valueThe study is the first to explore multilevel influences on early-stage entrepreneurs' market growth strategies in Africa. It sheds new insights on the entrepreneurial marketing process of early-stage entrepreneurs in Africa.

Adaptive MR-Guided Stereotactic Radiotherapy is Beneficial for Ablative Treatment of Lung Tumors in High-Risk Locations

PurposeTo explore the benefit of adaptive magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) for treatment of lung tumors in different locations with a focus on ultracentral lung tumors (ULT).Patients & MethodsA prospective cohort of 21 patients with 23 primary and secondary lung tumors was analyzed. Tumors were located peripherally (N = 10), centrally (N = 2) and ultracentrally (N = 11, planning target volume (PTV) overlap with proximal bronchi, esophagus and/or pulmonary artery). All patients received MRgSBRT with gated dose delivery and risk-adapted fractionation. Before each fraction, the baseline plan was recalculated on the anatomy of the day (predicted plan). Plan adaptation was performed in 154/165 fractions (93.3%). Comparison of dose characteristics between predicted and adapted plans employed descriptive statistics and Bayesian linear multilevel models. The posterior distributions resulting from the Bayesian models are presented by the mean together with the corresponding 95% compatibility interval (CI).ResultsPlan adaptation decreased the proportion of fractions with violated planning objectives from 94% (predicted plans) to 17% (adapted plans). In most cases, inadequate PTV coverage was remedied (predicted: 86%, adapted: 13%), corresponding to a moderate increase of PTV coverage (mean +6.3%, 95% CI: [5.3–7.4%]) and biologically effective PTV doses (BED10) (BEDmin: +9.0 Gy [6.7–11.3 Gy], BEDmean: +1.4 Gy [0.8–2.1 Gy]). This benefit was smaller in larger tumors (−0.1%/10 cm³ PTV [−0.2 to −0.02%/10 cm³ PTV]) and ULT (−2.0% [−3.1 to −0.9%]). Occurrence of exceeded maximum doses inside the PTV (predicted: 21%, adapted: 4%) and violations of OAR constraints (predicted: 12%, adapted: 1%, OR: 0.14 [0.04–0.44]) was effectively reduced. OAR constraint violations almost exclusively occurred if the PTV had touched the corresponding OAR in the baseline plan (18/19, 95%).ConclusionAdaptive MRgSBRT is highly recommendable for ablative treatment of lung tumors whose PTV initially contacts a sensitive OAR, such as ULT. Here, plan adaptation protects the OAR while maintaining best-possible PTV coverage.

The Role of Conditional Likelihoods in Latent Variable Modeling

In psychometrics, the canonical use of conditional likelihoods is for the Rasch model in measurement. Whilst not disputing the utility of conditional likelihoods in measurement, we examine a broader class of problems in psychometrics that can be addressed via conditional likelihoods. Specifically, we consider cluster-level endogeneity where the standard assumption that observed explanatory variables are independent from latent variables is violated. Here, “cluster” refers to the entity characterized by latent variables or random effects, such as individuals in measurement models or schools in multilevel models and “unit” refers to the elementary entity such as an item in measurement. Cluster-level endogeneity problems can arise in a number of settings, including unobserved confounding of causal effects, measurement error, retrospective sampling, informative cluster sizes, missing data, and heteroskedasticity. Severely inconsistent estimation can result if these challenges are ignored.

Catching Up on Multilevel Modeling

This review focuses on the use of multilevel models in psychology and other social sciences. We target readers who are catching up on current best practices and sources of controversy in the specification of multilevel models. We first describe common use cases for clustered, longitudinal, and cross-classified designs, as well as their combinations. Using examples from both clustered and longitudinal designs, we then address issues of centering for observed predictor variables: its use in creating interpretable fixed and random effects of predictors, its relationship to endogeneity problems (correlations between predictors and model error terms), and its translation into multivariate multilevel models (using latent-centering within multilevel structural equation models). Finally, we describe novel extensions—mixed-effects location–scale models—designed for predicting differential amounts of variability.

Suicidal Ideation and Risk Reduction Associated with Participation in a Therapist-Supported Digital Mental Health Intervention

Background Suicide is a significant public health concern with increasing prevalence. Novel interventions that reduce stigma and increase accessibility, such as therapist-supported digital mental health interventions, are urgently needed. Methods This preregistered retrospective cohort, single-arm, and intent-to-treat study with 778 patients examined suicidal ideation (SI) trajectories using multilevel models during and up to 6-months after an 12-week therapist-supported digital mental health intervention (Meru Health Program [MHP]) as assessed by the ninth item of the Patient Health Questionnaire-9 (PHQ-9). Estimates of associated suicide attempts and deaths by suicide were calculated using published data linking PHQ-9-assessed SI to records of suicide attempts and deaths by suicide. Results MHP participants reporting SI “not at all” significantly increased between baseline and end-of-treatment (78.02–91.00%). Effect sizes of SI changes between baseline and end-of-treatment, 3-month, and 6-month follow-ups were 0.33 (95%CI=0.27-0.38), 0.32 (95%CI=0.27-0.38), and 0.32 (95%CI=0.27-0.438), respectively. Results also indicated an estimated 30.49% reduction (95%CI=25.15%-35.13%) in suicide attempts and death by suicide across treatment. Conclusion This real-world study provides preliminary evidence that participants of the MHP show significant reductions in SI and estimated suicide attempts and deaths by suicide across treatment that are maintained 6-months following treatment. The next steps are to conduct a randomized control trial to confirm these results.

The association between binge eating and health behaviors during times of high and low stress among first-year university students

The current study examined binge eating behaviors among first-year undergraduate students over the academic year (September 2019, November 2019, January 2020, March 2020), and if between and within person effects of physical activity and sleep impact binge eating behaviours during times of higher-and lower-stress (n=394, Mage=18.6). Participants completed online surveys of moderate and vigorous exercise, hours and quality of sleep, and binge eating behaviours four times over the academic year. Results of multilevel models revealed relatively stable binge eating scores across the academic year. We did not find evidence of robust associations between exercise and sleep and binge eating behaviors during times of high and low stress over the academic year. Large increases in vigorous physical activity may be effective in reducing binge eating behaviors among women. These findings suggest that the effect of exercise on binge eating behaviours may be smaller than previous research suggests and that targeted exercise intervention is needed to see meaningful changes in binge eating behaviors.