Leadership behavior has a significant impact on employee behavior, performance and well-being. Extant theory and research on leadership behavior, however, has predominantly focused on employee performance, treating employee well-being (typically measured as job satisfaction) as a secondary outcome variable related to performance, rather than as an important outcome in and of itself. This qualitative state of the science review examines the process by which leadership behavior (i.e., change, relational, task, passive) affects employee well-being. We identify five mediator groupings (social-cognitive, motivational, affective, relational, identification), extend the criterion space for conceptualizing employee well-being (i.e., psychological: hedonic, eudaimonic, negative; and physical), examine the limited evidence for differential processes that underlie the leader behavior-employee well-being relationship and discuss theoretical and methodological problems inherent to the literature.We conclude by proposing a theoretical framework to guide a future research agenda on how, why and when leadership behavior impacts employee well-being.

Aim COVID-19 clinical presentation is heterogeneous, ranging from asymptomatic to severe cases. While there are a number of early publications relating to risk factors for COVID-19 infection, low sample size and heterogeneity in study design impacted consolidation of early findings. There is a pressing need to identify the factors which predispose patients to severe cases of COVID-19. For rapid and widespread risk stratification, these factors should be easily obtainable, inexpensive, and avoid invasive clinical procedures. The aim of our study is to fill this knowledge gap by systematically mapping all the available evidence on the association of various clinical, demographic, and lifestyle variables with the risk of specific adverse outcomes in patients with COVID-19. Methods The systematic review was conducted using standardized methodology, searching two electronic databases (PubMed and SCOPUS) for relevant literature published between 1st January 2020 and 9th July 2020. Included studies reported characteristics of patients with COVID-19 while reporting outcomes relating to disease severity. In the case of sufficient comparable data, meta-analyses were conducted to estimate risk of each variable. Results Seventy-six studies were identified, with a total of 17,860,001 patients across 14 countries. The studies were highly heterogeneous in terms of the sample under study, outcomes, and risk measures reported. A large number of risk factors were presented for COVID-19. Commonly reported variables for adverse outcome from COVID-19 comprised patient characteristics, including age >75 (OR: 2.65, 95% CI: 1.81–3.90), male sex (OR: 2.05, 95% CI: 1.39–3.04) and severe obesity (OR: 2.57, 95% CI: 1.31–5.05). Active cancer (OR: 1.46, 95% CI: 1.04–2.04) was associated with increased risk of severe outcome. A number of common symptoms and vital measures (respiratory rate and SpO2) also suggested elevated risk profiles. Conclusions Based on the findings of this study, a range of easily assessed parameters are valuable to predict elevated risk of severe illness and mortality as a result of COVID-19, including patient characteristics and detailed comorbidities, alongside the novel inclusion of real-time symptoms and vital measurements.

It has recently been proposed that measures of the perception of the state of one’s own body (“interoception”) can be categorised as one of several types depending on both how an assessment is obtained (objective measurement vs. self-report) and what is assessed (degree of interoceptive attention vs. accuracy of interoceptive perception). Under this model, a distinction is made between beliefs regarding the degree to which interoceptive signals are the object of attention and beliefs regarding one’s ability to perceive accurately interoceptive signals. This distinction is difficult to test, however, because of the paucity of measures designed to assess self-reported perception of one’s own interoceptive accuracy. This article therefore reports on the development of such a measure, the Interoceptive Accuracy Scale (IAS). Use of this measure enables assessment of the proposed distinction between beliefs regarding attention to, and accuracy in perceiving, interoceptive signals. Across six studies, we report on the development of the IAS and, importantly, its relationship with measures of trait self-reported interoceptive attention, objective interoceptive accuracy, confidence in the accuracy of specific interoceptive percepts, and metacognition with respect to interoceptive accuracy. Results support the distinction between individual differences in perceived attention towards interoceptive information and the accuracy of interoceptive perception.

Background University students in the United Kingdom are experiencing increasing levels of anxiety. A program designed to increase awareness of one’s present levels of well-being and suggest personalized health behaviors may reduce anxiety and improve mental well-being in students. The efficacy of a digital version of such a program, providing biofeedback and therapeutic content based on personalized well-being metrics, is reported here. Objective The aim of this study was to test the efficacy and sustained effects of using a mobile app (BioBase) and paired wearable device (BioBeam), compared with a waitlist control group, on anxiety and well-being in university students with elevated levels of anxiety and stress. Methods The study employed a randomized, waitlist-controlled trial with assessments at baseline, 2 weeks, postintervention (4 weeks), and follow-up (6 weeks). Participants were eligible if they were current full-time undergraduate students and (1) at least 18 years of age, (2) scored >14 points on the Depression, Anxiety, and Stress Scale-21 items (DASS-21) stress subscale or >7 points on the DASS-21 anxiety subscale, (3) owned an iOS mobile phone, (4) did not have any previous psychiatric or neurological conditions, (6) were not pregnant at the time of testing, and (7) were able to read and understand English. Participants were encouraged to use BioBase daily and complete at least one course of therapeutic content. A P value ≤.05 was considered statistically significant. Results We found that a 4-week intervention with the BioBase program significantly reduced anxiety and increased perceived well-being, with sustained effects at a 2-week follow-up. Furthermore, a significant reduction in depression levels was found following the 4-week usage of BioBase. Conclusions This study shows the efficacy of a biofeedback digital intervention in reducing self-reported anxiety and increasing perceived well-being in UK university students. Results suggest that digital mental health interventions could constitute a novel approach to treat stress and anxiety in students, which could be combined or integrated with existing therapeutic pathways. Trial Registration Open Science Framework (OSF.io) 2zd45; https://osf.io/2zd45/