1,721,032 research outputs found
Daily alcohol consumption among UK homeless people during COVID-19: a latent class and cross-sectional study
No full textBackground: alcohol consumption and related issues among the homeless population are key public health concerns. The COVID-19 pandemic may have altered drinking patterns among homeless people. We aimed to examine the drinking patterns of homeless people and their association with housing status.Methods: 1129 participants (82·5% female) from the COVID-19 Homeless Rapid Integrated Screening Protocol (CHRISP) study reported their drinking behaviours (i.e, daily drinking, drinking after waking up, alcohol-related injury, and getting help to stop drinking) and their past housing status (e.g, rough sleeping, with family/friends, and prison). Latent class analysis (LCA) was used to assess the daily drinking patterns and multinomial logistic regression was used to explore the relationship between housing status and daily drinking patterns.Findings: the prevalence of daily drinking was 14·3%. There were significant gender differences in alcohol-related injury and getting help to reduce/stop drinking (both p<0·05). The LCA identified an optimal three-class model: a high daily consumption group (Class 1, 7·6%), a low daily consumption group with alcohol-related injury (Class 2, 7·1%), and a low daily consumption group without negative consequences (Class 3, 85·3%). Using class 3 as the baseline, people who have lived in prison, as opposed to family/friends (reference group), were 8·6 times more likely to be classified into the high daily consumption group (Class 1). No significant drinking pattern differences were found between the reference group and other housing statuses.Interpretation: the prevalence of daily drinking among the UK homeless population during COVID-19 has been assessed for the first time. The findings suggest that different housing statuses are associated with different drinking patterns, and history of prison residence may reflect broader vulnerabilities or disadvantages. Authorities should enhance support for individuals leaving prison, including referrals and follow-up to alcohol and drug rehabilitation services.Funding: no funding was received in this study
Early environmental risks and the developmental dynamics of internalizing and externalizing problems from birth to adolescence
No full textInternalizing and externalizing problems often co-exist throughout an individual's development, shaped by a shared set of early environmental risks. However, most existing studies focused on discrete developmental periods, limiting understanding of how the negative impact of early-life adversity on mental health varies with age. Using data from 7,377 participants across seven waves of the UK Millennium Cohort Study (MCS), the current study investigated the bidirectional associations between internalizing and externalizing problems from ages 5 to 17, as well as the long-term impact of early environmental risks (i.e., prenatal influences, neonatal factors, maternal mental health, harsh parenting, and socioeconomic status) on the two symptom domains across time. Random-intercept cross-lagged panel analyses indicated that individuals with higher internalizing symptoms tended to report higher externalizing symptoms, with both symptom domains showing high stability over time. A significant positive bidirectional relationship between internalizing and externalizing problems was found from childhood to early adolescence. However, this pattern diverged in late adolescence: internalizing problems at age 14 no longer predict externalizing problems at age 17, whereas externalizing problems negatively predict subsequent internalizing symptoms. Early environmental risk factors significantly predicted both internalizing and externalizing problems from ages 5 to 14, with the effects generally decreasing with age, except for an increase at age 11. Gender differences were also observed in both the bidirectional relationships between the symptom domains and the long-term impact of early environmental risks. Findings underscore the enduring impact of early adversity on adolescent mental health and highlight the complex, evolving interaction between internalizing and externalizing problems. The study offers critical insights for early, sustained interventions that address multiple risks and adapt to adolescents' changing mental health needs over time.</p
Resource-constrained scheduling of a real project from the construction industry. A comparison of software packages for project management
No full textPsychometric network analysis of the Intuitive Eating Scale-2 in Chinese general adults
No full textThe Intuitive Eating Scale-2 (IES-2) is a measure of intuitive eating behaviors that has been extensively validated, with traditional latent variable modeling approaches, in youth and adults from many different populations, including college students in China. However, there is still a lack of research on the psychometric properties of the IES-2 in adults from the Chinese general population. Moreover, psychometric network analysis, as a complement to traditional latent variable modeling approaches, has not been used for examining the psychometric properties of the IES-2. Thus, the present study used a psychometric network approach to evaluate the psychometric properties of the IES-2 in Chinese adults from the general population. A sample of 700 Chinese general adults (50% women; Mage = 31.13 years, SD = 9.19) recruited online were included in the present study. Psychometric network analysis was performed. Exploratory graph analysis (EGA) identified four dimensions, which were well separated in the estimated network. The network structure showed excellent stability and metric measurement invariance (i.e., network loadings) across men and women. Furthermore, several items on the IES-2 were identified as key nodes in the network of the IES-2 that may be important for the development and maintenance of intuitive eating. For example, two items (i.e., “I trust my body to tell me when to eat,” and “I trust my body to tell me when to stop eating”) related to reliance on body cues were the most impactful nodes in the complete network. The findings of our study provide a greater understanding of the IES-2 from the perspective of network analysis and have implications for applications of intuitive eating interventions for general populations.</p
Integrating the tripartite influence, minority stress, and social comparison theories to explain body image and disordered eating in Chinese sexual minority men and women
No full textTheories of eating pathology explain body image and disordered eating in diverse populations, including sexual minority (SM) individuals. Yet, previous efforts to extend theories of eating pathology to SM individuals have mostly focused on Western populations. The present study integrated the tripartite influence, minority stress, and social comparison models to explain variance in body image and disordered eating in Chinese SM men and women. Chinese self-identified SM adults (N = 1051; n = 519 men, n = 532 women) completed an online, cross-sectional study that assessed sociocultural influences (e.g., tripartite influence), minority stress, social comparisons, drive for muscularity, and disordered eating. Two integrated models were tested for men and women using structural equation modeling. Across both populations, sociocultural influences exerted the largest direct positive effects on body image and disordered eating. In men, only downward body image comparisons were uniquely related to outcomes. In women, higher upward body image comparisons were uniquely associated with higher drive for muscularity and higher downward body image comparisons were uniquely associated with higher thinness-oriented disordered eating. Minority stressors (e.g., sexual orientation concealment, internalized homophobia) were uniquely related to outcomes in men, not women. Findings extend existing theories of body image and disordered eating to Chinese SM populations.</p
A general disease factor: evidence of a unifying dimension across mental and physical illness in children and adolescents
No full textBackground: understanding the relationship between mental and physical health conditions is crucial for developing comprehensive healthcare strategies. The putative existence of a general disease factor (d-factor) that underlies the vulnerability to both physical and mental conditions could have important implications to our approach to health assessment and treatment.Objective: to investigate the presence and characteristics of a general d-factor in children and adolescents.Methods: this Swedish registry-based cross-sectional study included children and adolescents born between 1996 and 2003 with follow up until 2013. We extracted data on 25 mental and physical health conditions according to the ICD-10 system. To determine the optimal dimensional structure of these conditions, several competing measurement models were tested, including correlated factors, one-factor, various bifactor specifications, and bifactor exploratory structural equation modelling (ESEM).Findings: the study cohort included 776,667 individuals (mean age 13.96 years, IQR=11.96-16.04; 51% male). The bifactor ESEM model, including a general d-factor and specific mental and physical health factors, provided the best fit to the data compared to alternative models (CFI=0.971, TLI=0.962, RMSEA=0.007 [0.007-0.007]). The d-factor accounted for substantial variance (ωh=0.582, ECV=0.498), while specific mental (ωhs=0.377, ECV=0.373) and physical (ωhs=0.423; ECV=0.130) factors also indicated additional significant unique contributions.Conclusions: this study provided evidence for a multidimensional structure of health in children and adolescents, characterised by a general d-factor underlying both mental and physical conditions, alongside distinct domain-specific factors. These findings have important implications for clinical practice, providing evidence that suggests the need for more integrated approaches to health assessment and treatment that consider the interconnectedness of mental and physical health.<br/
Large-scale evidence of a general disease (“ d” ) factor accounting for both mental and physical health disorders in different age groups
No full textBackground: it is unknown whether there is a general factor that accounts for the propensity for both physical and mental conditions in different age groups and how it is associated with lifestyle and well-being.Methods: we analyzed health conditions data from the Millennium Cohort Study (MCS) (age = 17; N = 19,239), the National Child Development Study (NCDS) (age = 44; N = 9293), and the English Longitudinal Study of Ageing (ELSA) (age ≥ 50; N = 7585). The fit of three Confirmatory Factor models was used to select the optimal solution by Comparative Fit Index, Tucker-Lewis Index, and Root Mean Square Error of Approximation. The relationship among d factor, lifestyles, and well-being was further explored.Results: supporting the existence of the d factor, the bi-factor model showed the best model fit in 17-year-olds (MCS:CFI = 0.97, TFI = 0.96, RMSEA = 0.01), 44-year-olds (NCDS:CFI = 0.96, TFI = 0.95, RMSEA = 0.02), and 50+ year-olds (ELSA:CFI = 0.97, TFI = 0.96, RMSEA = 0.02). The d factor scores significantly correlated with lifestyle and well-being, suggesting healthier lifestyles were associated with a reduced likelihood of physical and mental health comorbidities, which in turn improved well-being.Conclusions: contrary to the traditional dichotomy between mental and physical conditions, our study showed a general factor underlying the comorbidity across mental and physical diseases, related to lifestyle and well-being. Our results inform the conceptualization of mental and physical illness as well as future research assessing risk and pathways of disease transmission, intervention, and prevention. Our results also provide a strong rationale for a systematic screening for mental disorders in individuals with physical conditions and vice versa, and for integrated services addressing multimorbidity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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