In network theory depression is conceptualized as a complex network of individual symptoms that influence each other, and central symptoms in the network have the greatest impact on other symptoms. Clinical features of depression are largely determined by sociocultural context. No previous study examined the network structure of depressive symptoms in Hong Kong residents. The aim of this study was to characterize the depressive symptom network structure in a community adult sample in Hong Kong during the COVID-19 pandemic. A total of 11,072 participants were recruited between 24 March and 20 April 2020. Depressive symptoms were measured using the Patient Health Questionnaire-9. The network structure of depressive symptoms was characterized, and indices of “strength”, “betweenness”, and “closeness” were used to identify symptoms central to the network. Network stability was examined using a case-dropping bootstrap procedure. Guilt, Sad Mood, and Energy symptoms had the highest centrality values. In contrast, Concentration, Suicide, and Sleep had lower centrality values. There were no significant differences in network global strength (p = 0.259), distribution of edge weights (p = 0.73) and individual edge weights (all p values > 0.05 after Holm–Bonferroni corrections) between males and females. Guilt, Sad Mood, and Energy symptoms were central in the depressive symptom network. These central symptoms may be targets for focused treatments and future psychological and neurobiological research to gain novel insight into depression.

The purposes of this review are to describe the existing research on frailty measurement of older people and to understand their characteristics, with a focus on conceptual definitions, psychometric properties, and diagnostic accuracies. We reviewed the published literature to explore if cross‐cultural studies of different types of frailty measurements have been conducted and to determine their applicability in the community setting. Narrative review with limited electronic database search and cross reference searching of included studies was performed. Studies published after year 2001 were searched for using MEDLINE and CINAHL Plus databases with keywords. A total of 5144 search results were obtained, but only 42 frailty measurements were identified in 68 studies. For the type, three different measurements were indicated, namely, self‐report instrument (n = 17), clinical observation assessment (n = 19), and mixed frailty assessment instrument (n = 6). Only 12 (29%) measurements examined reliability and validity. Nevertheless, over 35% did not perform any psychometric testing before applying. For diagnosis accuracies, 35 (83%) frailty measurements reported the cut‐off value(s) for determining level of the frailty. However, the sensitivity (56%‐89.5%) and specificity (52%‐91.3%) varied. The applicability was also diverse and some frailty instruments should be only used in some specific population and mode of administration. This review provides an overview of three major types of frailty measurements used in different settings with different purposes. For estimating the prevalence of frailty of older people in a community, the self‐report type may be appropriate. The psychometric properties of many reviewed instruments are reported insufficiently. The cut‐off value(s) are usually suggested with diverse sensitivity and specificity. Self‐report instruments, such as Groningen Frailty Indicator (GFI) and Tilburg Frailty Indicator (TFI), are the most extensively examined in terms of satisfactory psychometric properties. Thus, GFI and TFI, with the current evidence, are recommended to be used in the community setting for frailty screening tools.

Background The early identification of pre-frailty and frailty among older people is a global priority because of the increasing incidence of frailty and associated adverse health outcomes. This study aimed to validate the Groningen Frailty Indicator-Chinese (GFI-C), a widely used screening instrument, and determine the optimal cut-off value in Chinese communities to facilitate pre-frailty and frailty screening. Methods This methodological study employed a cross-sectional and correlational design to examine the psychometric properties of GFI-C, namely, internal consistency, stability, and concurrent and construct validities. The appropriate cut-off values for pre-frailty and frailty screening in the receiver-operating characteristic (ROC) curve were determined through sensitivity and specificity analysis. Results A total of 350 community older people had been assessed and interviewed by a nurse. The GFI-C showed satisfactory internal consistency (Cronbach’s α = 0.87) and two-week test-retest reliability (intra-class correlation coefficient = 0.87). Concurrent validity (r = 0.76, p < 0.001) showed a moderate correlation with Fried’s frailty phenotype. The known-groups method, hypothesis testing and confirmatory factory analysis (three-factor model; χ2/df = 2.87, TLI = 0.92, CFI = 0.93, GFI = 0.92, RMR = 0.014; RMSEA = 0.073) were suitable for the establishment of construct validity. Based on the ROC and Youden’s index, the optimal cut-off GFI-C values were 2 (sensitivity, 71.5%; specificity, 84.7%) for pre-frailty and 3 for frailty (sensitivity, 88.2%; specificity, 79.6%). Conclusions The result indicated that GFI-C is a reliable and valid instrument for pre-frailty and frailty screening among older Chinese people in communities. For optimal diagnostic accuracy, the cut-off values of 3 for frailty and 2 for pre-frailty are recommended.

Objective: The aim of this study is to extrapolate the clinical features of children with severe neurologic impairment (SNI) based on the functional characteristics and comorbidities described in published studies.Methods: Four databases were searched. We included studies that describe clinical features of a group of children with SNI (≥20 subjects <19 years of age with >1 neurologic diagnosis and severe functional limitation) using data from caregivers, medical charts, or prospective collection. Studies that were not written in English were excluded. We extracted data about functional characteristics, comorbidities, and study topics. Results:We included 102 studies, spanning 5 continents over 43 years, using 41 distinct terms for SNI. The terms SNI and neurologic impairment (NI) were used in 59 studies (58%). Most studies (n = 81, 79%) described ≥3 types of functional