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IntroductionGeographical accessibility is important against health equity, particularly for less developed countries as Nepal. It is important to identify the disparities in geographical accessibility to the three levels of public health facilities across Nepal, which has not been available.MethodsBased on the up-to-date dataset of Nepal formal public health facilities in 2021, we measured the geographical accessibility by calculating the travel time to the nearest public health facility of three levels (ie, primary, secondary and tertiary) across Nepal at 1×1 km2 resolution under two travel modes: walking and motorised. Gini and Theil L index were used to assess the inequality. Potential locations of new facilities were identified for best improvement of geographical efficiency or equality.ResultsBoth geographical accessibility and its equality were better under the motorised mode compared with the walking mode. If motorised transportation is available to everyone, the population coverage within 5 min to any public health facilities would be improved by 62.13%. The population-weighted average travel time was 17.91 min, 39.88 min and 69.23 min and the Gini coefficients 0.03, 0.18 and 0.42 to the nearest primary, secondary and tertiary facilities, respectively, under motorised mode. For primary facilities, low accessibility was found in the northern mountain belt; for secondary facilities, the accessibility decreased with increased distance from the district centres; and for tertiary facilities, low accessibility was found in most areas except the developed areas like zonal centres. The potential locations of new facilities differed for the three levels of facilities. Besides, the majority of inequalities of geographical accessibility were from within-province.ConclusionThe high-resolution geographical accessibility maps and the assessment of inequality provide valuable information for health resource allocation and health-related planning in Nepal.

Objective: This paper provides a systematic review and meta-analysis on the prevalence rate of mental health issues of the major population, including general population, general healthcare workers (HCWs), and frontline healthcare workers (HCWs), in China over one year of the COVID-19 crisis. Design: A systematic review and meta-analysis. Data sources: articles in PubMed, Embase, Web of Science, and medRxiv up to November 16, 2020, one year after the first publicly known confirmed COVID-19 case. Eligibility criteria and data analysis: any COVID-19 and mental disorders relevant English studies with frontline/general healthcare workers, general adult population sample, using validated scales. We pooled data using random-effects meta-analyses to estimate the prevalence rates of anxiety, depression, distress, general psychological symptoms (GPS), insomnia, and PTSD and ran meta-regression to tease out the heterogeneity. Results: The meta-analysis includes 131 studies and 171 independent samples. The overall prevalence of anxiety, depression, distress, GPS, insomnia, and PTSD are 11%, 13%, 20%, 13%, 19%, and 20%, respectively. The meta-regression results uncovered several predictors of the prevalence rates, including severity (e.g., above severe vs. above moderate, p<0.01; above moderate vs. above mild, p<0.01) and type of mental issues (e.g., depression vs. anxiety, p=0.04; insomnia vs. anxiety p=0.04), population (frontline HCWs vs. general HCWs, p<0.01), sampling location (Wuhan vs. non-Wuhan, p=0.04), and study quality (p=0.04). Limitations: First, we only focus on China population, which may limit the generalizability of the results. Second, 96.2% studies included in this meta-analysis were cross-sectional. Last, since we only included studies published in English, we expect to have a language bias. Conclusion: Our pooled prevalence rates are significantly different from, yet largely between, the findings of previous meta-analyses, suggesting the results of our larger study are consistent with, yet fine-tune, the findings of the smaller, previous meta-analyses. Hence, this meta-analysis not only provides a significant update on the mental health prevalence rates in COVID-19 but also suggests the need to update meta-analyses continuously to provide more accurate estimates of the prevalence of mental illness during this ongoing health crisis. While prior meta-analyses focused on the prevalence rates of mental health disorders based on one level of severity (i.e., above mild), our findings also suggest a need to examine the prevalence rates at varying levels of severity. The one-year cumulative evidence on sampling locations (Wuhan vs. non-Wuhan) corroborates the typhoon eye effect theory. Our finding that the prevalence rates of distress and insomnia and those of frontline healthcare workers are higher suggest future research and interventions should pay more attention to those mental outcomes and populations. Keywords: systematic review; meta-analysis; COVID-19; mental health; epidemic; general population; healthcare workers; frontline healthcare workers

Although the topic of forgiveness has received abundant attention in research on close relationships, little is known about the benefits of forgiveness in work relationships. This is unfortunate because research suggests that forgiveness is associated with numerous beneficial outcomes, such as improved social relationships and psychological well-being. The present research addresses the question whether and when forgiveness is associated with enhanced work outcomes. It was expected that forgiveness is associated with better work outcomes, especially when perceived work relationship quality between victim and offender is strong rather than weak. Study 1 (n = 472 MTurk participants) revealed that trait forgiveness was strongly associated with a broad range of work outcomes. Study 2 (n = 216 Dutch working employees) showed that state forgiveness was negatively associated with burnout. Study 3 (n = 370 Prolific participants) replicated the positive association between forgiveness (both trait and state) and work outcomes (especially well-beingrelated work outcomes, that is, job satisfaction, work engagement, and less burnout). Moreover, the associations between state forgiveness and work outcomes were stronger when the quality of work relationships (i.e., exchange quality) was high rather than low. Furthermore, only in cases of high exchange quality, the positive association between trait forgiveness and work outcomes could be explained by higher levels of state forgiveness. These findings suggest that levels of work relationship quality are of great importance to better understand forgiveness in the work context. Implications of these findings for the role of interpersonal forgiveness in the work context are discussed.

ObjectiveThis paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis.MethodWe systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity.ResultsThe meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p &lt; 0.01; above moderate vs. above mild, p &lt; 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p &lt; 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04).ConclusionThe meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.