Determinants of preventive behavior against Covid-19 in secondary school students based on Health Belief Model (HBM): a structural equations modeling (SEM).

Measures such as education, improving knowledge, attitude and taking preventive action to protect against COVID-19 are vital strategies for prevention. The aim of this study was to determine the predictability of Health Belief Model (HBM) constructs in performing preventive behaviors against COVID-19 among secondary school students in Chabahar, Iran. In this cross-sectional-analytical study, 400 secondary school students of Chabahar city were investigated by simple random sampling. The data collection tool was a questionnaire including demographic characteristics, knowledge, behavior, and Health Belief Model constructs' questions. Exploratory Factor Analysis (EFA) was used to evaluate the validity of HBM constructs, and the structural equation modeling (SEM) method was used to evaluate the direct and indirect effects of the relationship between knowledge, HBM constructs, and preventive behavior against COVID-19 based on the conceptual model. Based on the results of the structural modeling, the direct effect of knowledge on the constructs of the health belief model was positive and significant (ß = 0.34, P-value < 0.001), and on the preventive behavior of students was insignificant (ß = 0.12, P-value = 0.07) while the indirect effect of knowledge through increasing the constructs of the HBM on student behavior was positive and significant (ß = 0.30, P < 0.001). The relationship between the constructs of the HBM constructs and student behavior was also positive and significant (ß = 0.89, P-value < 0.001).Due to the fact that knowledge and HBM structures played a role in predicting the adoption of preventive behavior from COVID-19, it is possible to design appropriate interventions to increase knowledge, sensitivity, perceived severity, and self-efficacy, in order to recover from COVID-19 by adopting preventive behaviors.

Mental health and quality of life in patients with chronic liver disease: a single-center structural equation model.

BACKGROUND: Chronic liver disease (CLD) is one of the leading disease burdens in Pakistan. Until now, there has only been limited focus in the country on providing health services through tertiary services in urban cities, whereas there is almost no research in Pakistan on the mental health and quality of life of CLD patients. This study aimed to understand which predictors influence the mental health and quality of life of CLD patients in order to advise better policy protection. METHODS: Data was collected from CLD patients at the Pakistan Kidney and Liver Institute and Research Centre, Lahore, Pakistan. A total of 850 respondents were part of the final sample. The age of respondents ranged from 18 to 79 years and included the following diagnosis: (i) Chronic Viral Hepatitis (n = 271), (ii) Cirrhosis (n = 259), (iii) Hepatocellular Carcinoma (n = 193), and (iv) Non-viral Liver Disease (n = 127). RESULTS: Mean results reveal that females as well as illiterate patients need more support for mental health and communication with their physician; whereas men need more support to develop coping strategies. Structural equation modelling results reveal that the severity of symptoms (ß = 0.24, p < 0.001), coping strategies (ß=-0.51, p < 0.001), and doctor communication (ß=-0.35, p < 0.001) predict mental health. Quality of life is associated with the severity of symptoms (ß=-0.36, p < 0.001), coping strategies (ß = 0.26, p < 0.05), and doctor communication (ß = 0.09, p < 0.05). CONCLUSIONS: A 'bio-psycho-social-spiritual' model is recommended for Pakistan's CLD patients which includes the integration of social officers to provide support in four key areas to secure mental health and quality of life of patients.

Simultaneous alleviation of verification and reference standard biases in a community-based tuberculosis screening study using Bayesian latent class analysis.

BACKGROUND: Estimation of prevalence and diagnostic test accuracy in tuberculosis (TB) prevalence surveys suffer from reference standard and verification biases. The former is attributed to the imperfect reference test used to bacteriologically confirm TB disease. The latter occurs when only the participants screening positive for any TB-compatible symptom or chest X-ray abnormality are selected for bacteriological testing (verification). Bayesian latent class analysis (LCA) alleviates the reference standard bias but suffers verification bias in TB prevalence surveys. This work aims to identify best-practice approaches to simultaneously alleviate the reference standard and verification biases in the estimates of pulmonary TB prevalence and diagnostic test performance in TB prevalence surveys. METHODS: We performed a secondary analysis of 9869 participants aged ≥15 years from a community-based multimorbidity screening study in a rural district of KwaZulu-Natal, South Africa (Vukuzazi study). Participants were eligible for bacteriological testing using Xpert Ultra and culture if they reported any cardinal TB symptom or had an abnormal chest X-ray finding. We conducted Bayesian LCA in five ways to handle the unverified individuals: (i) complete-case analysis, (ii) analysis assuming the unverified individuals would be negative if bacteriologically tested, (iii) analysis of multiply-imputed datasets with imputation of the missing bacteriological test results for the unverified individuals using multivariate imputation via chained equations (MICE), and simultaneous imputation of the missing bacteriological test results in the analysis model assuming the missing bacteriological test results were (iv) missing at random (MAR), and (v) missing not at random (MNAR). We compared the results of (i)-(iii) to the analysis based on a composite reference standard (CRS) of Xpert Ultra and culture. Through simulation with an overall true prevalence of 2.0%, we evaluated the ability of the models to alleviate both biases simultaneously. RESULTS: Based on simulation, Bayesian LCA with simultaneous imputation of the missing bacteriological test results under the assumption that the missing data are MAR and MNAR alleviate the reference standard and verification biases. CRS-based analysis and Bayesian LCA assuming the unverified are negative for TB alleviate the biases only when the true overall prevalence is <3.0%. Complete-case analysis produced biased estimates. In the Vukuzazi study, Bayesian LCA with simultaneous imputation of the missing bacteriological test results under the MAR and MNAR assumptions produced overall PTB prevalence of 0.9% (95% Credible Interval (CrI): 0.6-1.9) and 0.7% (95% CrI: 0.5-1.1) respectively alongside realistic estimates of overall diagnostic test sensitivity and specificity with substantially overlapping 95% CrI. The CRS-based analysis and Bayesian LCA assuming the unverified were negative for TB produced 0.7% (95% CrI: 0.5-0.9) and 0.7% (95% CrI: 0.5-1.2) overall PTB prevalence respectively with realistic estimates of overall diagnostic test sensitivity and specificity. Unlike CRS-based analysis, Bayesian LCA of multiply-imputed data using MICE mitigates both biases. CONCLUSION: The findings demonstrate the efficacy of these advanced techniques in alleviating the reference standard and verification biases, enhancing the robustness of community-based screening programs. Imputing missing values as negative for bacteriological tests is plausible under realistic assumptions.

The Effect of Cigarette Content Marketing on Students' Smoking Behavior and Decisions: A PLS-SEM Approach.

OBJECTIVE: This research aims to analyze the influence of cigarette content marketing on student behavior, and on cigarette purchasing decisions, as well as the influence of behavior on cigarette purchasing decisions. METHODS: This research is quantitative, using a sample of 500 smoking students from twelve universities in the city of Medan, Indonesia, who were selected using a simple random sampling technique. Data collection was carried out by distributing questionnaires that had been tested for convergent validity with an Outer Loading value > 0.7 and an AVE value > 0.5, and for discriminant validity with an HTMT value < 0.9. The data was analyzed using a multivariate analysis technique which combines factor analysis and regression analysis. RESULTS: The research results show that the t-statistical value for the behavioral variable (BHV) is 4.128 (> 1.98) and the p-value is 0.000 (< 0.05), which means that the BHV variable has a significant effect on the cigarette purchasing decision variable (PD). The t-statistical value for the content marketing (CM) variable is 27.57 (> 1.98) and the p-value is 0.000 (< 0.05), which means that the CM variable has a significant effect on the BHV variable. The t-statistical value for the CM variable is 18,542 (> 1.98) and the p-value is 0.000 (< 0.05), which means that the CM variable has a significant effect on the PD variable.  93.2% of respondents admitted that they had seen cigarette marketing content on social media, many of them (43%) believed that smoking was detrimental to their health, but the most influential factor was their perception regarding the activity of smoking. CONCLUSION: Cigarette marketing content has been proven to influence students' behavior towards cigarettes, as well as directly influencing their decision to purchase cigarettes. Students' behavior towards cigarettes also influences their decisions in purchasing cigarettes.

A latent class analysis of international change and continuity in adolescent health and wellbeing: A repeat cross-sectional study.

BACKGROUND: Since the early 2000s, there have been marked trends in adolescent health and wellbeing indicators across Europe, North America and Australia. In particular, there have been substantial declines in youth drinking. We know little about how these trends are underpinned by co-occurring indicators within individuals. This paper aims to analyse change over time in how indicators cluster within individuals and differences in these patterns between five countries with different trends in youth drinking. METHODS: We analysed four waves of repeat cross-sectional survey data from 15-year-olds in England (n = 5942), Italy (n = 5234), the Netherlands (n = 5408), Hungary (n = 5274), and Finland (n = 7446), which were included in the Health Behaviours in School-aged Children (HBSC) study between 2001/02 and 2013/14. We defined clusters of individuals using multigroup latent class analyses which accounts for change over time. The class indicators included health behaviours, attitudes, wellbeing and relationships. We modelled associations between class membership, sex, and family affluence over time. RESULTS: We identified four classes in all countries: Overall unhealthy, Overall healthy, Moderately healthy and Substance abstainers with behaviour risk indicators. The proportion of adolescents in the Overall unhealthy class declined between 2001/02 and 2013/14 by between 22.8 percentage points (pp) in England and 3.2pp in Italy. The extent to which indicators of health and wellbeing changed as linked clusters differed across countries, but changes in alcohol consumption, smoking, drug use and sexual activity were typically concurrent. Adolescents with low family affluence were more likely to be in the Overall unhealthy class in all years. CONCLUSIONS: Improvements in indicators of adolescent health and well-being are due mainly to concurrent declines in drinking, smoking, sexual activity, and cannabis use, but these declines are not consistently associated with improvements in other domains. They have also not led to reductions in inequalities in indicators of health and well-being.

Clustering of health behaviors and their associations with cardiometabolic risk factors among adults at high risk for type 2 diabetes in India: A latent class analysis.

BACKGROUND: We aimed to identify clusters of health behaviors and study their associations with cardiometabolic risk factors in adults at high risk for type 2 diabetes in India. METHODS: Baseline data from the Kerala Diabetes Prevention Program (n = 1000; age 30-60 years) were used for this study. Information on physical activity (PA), sedentary behavior, fruit and vegetable intake, sleep, and alcohol and tobacco use was collected using questionnaires. Blood pressure, waist circumference, 2-h plasma glucose, high-density lipoprotein and low-density lipoprotein cholesterol, and triglycerides were measured using standardized protocols. Latent class analysis was used to identify clusters of health behaviors, and multilevel mixed-effects linear regression was employed to examine their associations with cardiometabolic risk factors. RESULTS: Two classes were identified, with 87.4% of participants in class 1 and 12.6% in class 2. Participants in both classes had a high probability of not engaging in leisure-time PA (0.80 for class 1; 0.73 for class 2) and consuming <5 servings of fruit and vegetables per day (0.70 for class 1; 0.63 for class 2). However, participants in class 1 had a lower probability of sitting for >=3 h per day (0.26 vs 0.42), tobacco use (0.10 vs 0.75), and alcohol use (0.08 vs 1.00) compared to those in class 2. Class 1 had a significantly lower mean systolic blood pressure (ß = -3.70 mm Hg, 95% confidence interval [CI] -7.05, -0.36), diastolic blood pressure (ß = -2.45 mm Hg, 95% CI -4.74, -0.16), and triglycerides (ß = -0.81 mg/dL, 95% CI -0.75, -0.89). CONCLUSION: Implementing intervention strategies, tailored to cluster-specific health behaviors, is required for the effective prevention of cardiometabolic disorders among high-risk adults for type 2 diabetes.

Assessing pain severity and treatment outcomes in patients with low back pain: A Structural equation modeling approach at the center for the rehabilitation of the Paralysed, Bangladesh.

OBJECTIVES: This study aims to observe the associated risk factors of lower back pain and the factors that increase the pain severity. So, the main objective of this research is to identify the factors which may cause the lower back pain and the causal effect on the pain severity and respective treatment. This study also tries to determine the demographical characteristics of the low back pain patients and determine the inter relationship of psychological health, work stress and treatment effect with the pain disability index. STUDY DESIGN: In this cross-sectional study, 200 patients with lower back pain were interviewed who were taking treatments from the physiotherapy department at the Center for the Rehabilitation of the Paralysed, Savar, Dhaka, Bangladesh. METHODS: A quantitative research model has been performed to observe the relationship between different causes of low back pain effects on the patients. Different statistical analysis including structural equation modeling have been performed to observe their pain severity and treatment effect. RESULTS: The study found 64% (128) of the total participants as male and 36% (72) as female among 200 patients of low back pain. The study also observed the highest portion of the patients belong to the age group 39 to 45 years (21.5%). On the basis of BMI, obese weight respondents were 26.5% (53), overweight respondents were 37% (74), normal weight respondents were 33% (66), and underweight respondents were only 3.5% (7). Here, sex, body mass index (BMI), living place and educational status have significant association with pain disability index (PDI). On the other hand, smoking tendency of patients has insignificant relationship (p>0.05) with pain disability index (PDI). The path coefficients of the structural equation model identified that all the null hypotheses of no significant relationship have been rejected for 5% level of significance. The hypothesis of psychological health is positively related to pain severity of a patient has an acceptable strength (ß = 0.745, p<0.001) and a positive direction. Another hypothesis (Psychological health is positively related to the treatment of a patient) shows an acceptable strength (ß = 0.401, p <0.001) and a positive direction. Work stress is also found to be positively related to pain severity of a patient with an acceptable strength (ß = 0.544, p < 0.001) and a positive direction. The hypothesis (Work stress is positively related to the treatment of a patient) has an acceptable strength (ß = 0.322, p< 0.05) and a positive direction. The hypothesis (pain severity is positively related to the treatment of patients) shows an acceptable strength (ß = 0.801, p < 0.001) and a positive direction. CONCLUSION: The research found out the psychological health situation and work stress of patients are significantly related with pain severity with acceptable strength. Also, Pain severity is significantly associated with treatment scheme intensity.

The impact of social determinants on health outcomes in a region in the North of England: a structural equation modelling analysis.

OBJECTIVES: The aim of this study was to identify the impact of social determinants of health on physical and mental health outcomes in a UK population. STUDY DESIGN: Structural equation modelling was used to hypothesise a model of relationships between health determinants and outcomes within a region in the North of England using large-scale population survey data (6208 responses). METHODS: We analysed responses from a population survey to assess the influence of a deprivation-based index at the environmental level, education and income on a behaviour index (smoking, alcohol consumption, physical activity, and dietary habits) and the influence of all these factors on self-reported physical health and the influence of the behaviour index and income on mental wellbeing. RESULTS: The proposed model was well supported by the data. Goodness-of-fit statistics, most notably a low value of the root mean square error of approximation (RMSEA), supported the validity of the proposed relationships (RMSEA = 0.054). The model revealed all examined paths to be statistically significant. Income and education were influential in determining an individual's behaviour index score, which, with income was the most important predictor of both the correlated outcomes of physical health and mental wellbeing (P < 0.001 in all cases). CONCLUSIONS: Findings challenge the traditional view of singular causal pathways, emphasising that interventions should consider the underlying influencing socio-economic conditions, which would influence behaviour and therefore physical and mental wellbeing. The extent to which the model is supported by the data, and the statistical significance of individual relationships accentuates the imperative for comprehensive public health strategies that integrate multiple socio-economic factors.

Investigating the role of the built environment, socio-economic status, and lifestyle factors in the prevalence of chronic diseases in Mashhad: PLS-SEM model.

Background: Chronic diseases remain a significant contributor to both mortality and disability in our modern world. Physical inactivity and an unhealthy diet are recognized as significant behavioral risk factors for chronic diseases, which can be influenced by the built environment and socio-economic status (SES). This study aims to investigate the relationship between the built environment, SES, and lifestyle factors with chronic diseases. Methods: The current study was conducted in Mashhad's Persian cohort, which included employees from Mashhad University of Medical Sciences (MUMS). In the study, 5,357 participants from the cohort were included. To assess the state of the built environment in Mashhad, a Geographic Information System (GIS) map was created for the city and participants in the Persian Mashhad study. Food intake and physical exercise were used to assess lifestyle. A food frequency questionnaire (FFQ) was used to assess food intake. To assess food intake, the diet quality index was computed. To assess the link between variables, the structural model was created in accordance with the study's objectives, and partial least square structural equation modeling (PLS-SEM) was utilized. Results: The chronic diseases were positively associated with male sex (p < 0.001), married (p < 0.001), and higher age (p < 0.001). The chronic diseases were negatively associated with larger family size (p < 0.05), higher SES (p < 0.001), and higher diet quality index (DQI) (p < 0.001). No significant relationship was found between chronic disease and physical activity. Conclusion: Food intake and socioeconomic status have a direct impact on the prevalence of chronic diseases. It seems that in order to reduce the prevalence of chronic diseases, increasing economic access, reducing the class gap and increasing literacy and awareness should be emphasized, and in the next step, emphasis should be placed on the built environment.

Treatment confidence and patient participation in multidisciplinary tumor conferences: A structural equation modeling approach.

OBJECTIVE: Multidisciplinary tumor conference (MTC) is a key instrument in multidisciplinary cancer care. In recent years, if and how patient participation in MTC can contribute to a more patient-centered care have been scientifically discussed. This study aimed to identify determinants of treatment confidence in the context of patient participation in MTC. Therefore, the association among health literacy-sensitive communication, trust in health-care providers (HCP), and treatment confidence is examined. METHODS: This study used data from the multicenter, observational study "PINTU" on patient participation in MTC. Data were collected from November 2018 to February 2020. Validated scales for treatment confidence, health literacy-sensitive communication, and trust in providers were included in the structural equation modeling (SEM) analysis. RESULTS: A total of 95 patients participated in MTC. The sample compromised n = 80 completed datasets. The SEM fit measures indicated good fit of the proposed model. The analysis showed a positive association between health literacy-sensitive communication and treatment confidence when adding the mediating effect of trust in providers. CONCLUSION: Patient-centered communication during MTC in combination with a trustful relationship between participating patients and health-care providers is positively associated with treatment confidence. The results indicated the relevance of a trustful doctor-patient communication and relationship. Trainings for physicians targeting patient-centered communication could be a promising approach to strengthen patient participation.

Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis.

PURPOSE: Research on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin's lymphoma, breast, uterine, cervical, and colorectal cancer). METHODS: This study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used. RESULTS: Subjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin's lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types. CONCLUSION: Identifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.

Inflammation as a mediator between adverse childhood experiences and adult depression: A meta-analytic structural equation model.

Exposure to adverse childhood experiences (ACEs) confers a higher risk of developing depression in adulthood, yet the mediation of inflammation remains under debate. To test this model, we conducted a systematic review and two-stage structural equation modelling meta-analysis of studies reporting correlations between ACEs before age 18, inflammatory markers and depression severity in adulthood. Scopus, Pubmed, Medline, PsycInfo, and CINAHL were searched up to 2 October 2023. Twenty-two studies reporting data on C-reactive protein (CRP, n = 12,935), interleukin-6 (IL-6, n = 4108), tumour necrosis factor-α (TNF-α, n = 2256) and composite measures of inflammation (n = 1674) were included. Unadjusted models revealed that CRP (ß = 0.003, 95 % LBCI 0.0002 to 0.0068), IL-6 (ß = 0.003, 95 % LBCI 0.001 to 0.006), and composite inflammation (ß = 0.009, 95 % LBCI 0.004 to 0.018) significantly mediated the association between ACEs and adult depression. The mediation effects no longer survived after adjusting for BMI; however, a serial mediation model revealed that BMI and IL-6 sequentially mediated the association between ACEs and depression (ß = 0.002, 95 % LBCI 0.0005 to 0.0046), accounting for 14.59 % and 9.94 % of the variance of IL-6 and depressive symptoms, respectively. Due to the cross-sectional nature of assessment of inflammation and depression findings should be approached with caution; however, results suggest that complex interactions of psychoneuroimmunological and metabolic factors underlie the association between ACEs and adulthood depression.

The impact of social support on benefit finding among patients with advanced lung cancer and their caregivers: based on actor-partner interdependence mediation model.

PURPOSE: Advanced lung cancer and its treatment serve as a sudden stressful event that profoundly impacts the psychological experience of both the patients and their primary caregiver. This study used dyadic analyses to explore the dyadic effects of social support on benefit finding and whether hope level mediates the patient-caregiver dyads in advanced lung cancer. METHODS: Two hundred ninety-five pairs of patients with advanced lung cancer and primary caregivers completed the Social Support Rating Scale (SSRS), the Herth Hope Index (HHI), and the Benefit Finding Scale (BFS). Dyadic analyses were conducted using structural equation modelling based on the actor-partner interdependence mediation model. RESULTS: The results indicated that for both patients (B = 0.259, 95% CI = 0.135-0.423, P < 0.001) and their primary caregivers (B = 0.596, 95% CI = 0.403-0.838, P < 0.001), hope level mediated the actor effect of social support on benefit finding; social support was positively associated with hope level and further enhanced benefit finding. Regarding partner effects (B = 0.242, 95% CI = 0.119-0.404, P < 0.001), primary caregivers' social support significantly indirectly affected patients' benefit finding through patients' hope level. CONCLUSION: There is an interaction between social support, hope level, and benefit finding in patients with advanced lung cancer and their primary caregivers. Healthcare professionals ought to be vigilant in recognizing patients and caregivers who are vulnerable, have limited social support, and possess diminished hope levels. At the same time, nurses should provide timely psychological support and counseling to patients and their caregivers, encourage them to actively participate in social activities, and inspire their confidence and hope in life, thus improving their benefit findings.

Latent profiles of fatigue in inflammatory bowel disease.

INTRODUCTION: Fatigue is prevalent in people with inflammatory bowel disease (IBD) and has been associated with IBD activity, sleep quality, depression, and anxiety. This study aimed to identify fatigue profiles or clusters through latent profile analysis. METHODS: An online questionnaire was administered through three tertiary IBD centres, social media and through Crohn's Colitis Australia. Fatigue was assessed via the Functional assessment of chronic illness measurement system fatigue subscale (FACIT-F), a validated assessment of fatigue and its severity. Validated measures of anxiety, depression, IBD activity and sleep quality were also included. Latent profile analysis was performed including fatigue, sleep quality, active IBD, and depression and anxiety. The relationships between profiles and IBD and demographic data were investigated. RESULTS: In a cohort of 535 respondents, 77% were female, the median age was 41 years (range 32-52 years), and the majority had Crohn's disease (62%). Severe fatigue was seen in 62%. Latent profile analysis identified four distinct profiles differing by fatigue score - low fatigue, at-risk profile, active IBD, and a poor mental health profile. Female gender, obesity and opioid usage were associated with higher risk of being in the active IBD and poor mental health profile. Age over 40 was associated with lower risk of being in the poor mental health profile. CONCLUSION: Latent profile analysis identifies four classes of fatigue in an IBD cohort with associations with specific risk factors for fatigue along with specific IBD and demographic attributes. This has implications for the classification of fatigue in IBD and treatment algorithms.

Sex Differences in Clustering Unhealthy Lifestyles Among Survivors of COVID-19: Latent Class Analysis.

BACKGROUND: The COVID-19 pandemic has underscored the significance of adopting healthy lifestyles to mitigate the risk of severe outcomes and long-term consequences. OBJECTIVE: This study focuses on assessing the prevalence and clustering of 5 unhealthy lifestyle behaviors among Vietnamese adults after recovering from COVID-19, with a specific emphasis on sex differences. METHODS: The cross-sectional data of 5890 survivors of COVID-19 in Vietnam were analyzed from December 2021 to October 2022. To examine the sex differences in 5 unhealthy lifestyle behaviors (smoking, drinking, unhealthy diet, physical inactivity, and sedentary behavior), the percentages were plotted along with their corresponding 95% CI for each behavior. Latent class analysis was used to identify 2 distinct classes of individuals based on the clustering of these behaviors: the "less unhealthy" group and the "more unhealthy" group. We examined the sociodemographic characteristics associated with each identified class and used logistic regression to investigate the factors related to the "more unhealthy" group. RESULTS: The majority of individuals (male participants: 2432/2447, 99.4% and female participants: 3411/3443, 99.1%) exhibited at least 1 unhealthy behavior, with male participants being more susceptible to multiple unhealthy behaviors. The male-to-female ratio for having a single behavior was 1.003, but it escalated to 25 for individuals displaying all 5 behaviors. Male participants demonstrated a higher prevalence of combining alcohol intake with sedentary behavior (949/2447, 38.8%) or an unhealthy diet (861/2447, 35.2%), whereas female participants tended to exhibit physical inactivity combined with sedentary behavior (1305/3443, 37.9%) or an unhealthy diet (1260/3443, 36.6%). Married male participants had increased odds of falling into the "more unhealthy" group compared to their single counterparts (odds ratio [OR] 1.45, 95% CI 1.14-1.85), while female participants exhibited lower odds (OR 0.65, 95% CI 0.51-0.83). Female participants who are underweight showed a higher likelihood of belonging to the "more unhealthy" group (OR 1.11, 95% CI 0.89-1.39), but this was not observed among male participants (OR 0.6, 95% CI 0.41-0.89). In both sexes, older age, dependent employment, high education, and obesity were associated with higher odds of being in the "more unhealthy" group. CONCLUSIONS: The study identified notable sex differences in unhealthy lifestyle behaviors among survivors of COVID-19. Male survivors are more likely to engage in unhealthy behaviors compared to female survivors. These findings emphasize the importance of tailored public health interventions targeting sex-specific unhealthy behaviors. Specifically, addressing unhealthy habits is crucial for promoting post-COVID-19 health and well-being.

Profiles of disordered eating behaviour in type 1 diabetes using the DEPS-R and behaviour and glycaemic outcomes in a real-life setting.

AIMS: The Diabetes Eating Problems Survey - Revised (DEPS-R) is commonly used to assess disordered eating behaviour (DEB) in individuals with type 1 diabetes and has advantages compared to other measures not specifically tailored to diabetes. A score ≥20 on the DEPS-R is used to indicate clinically significant DEB; however, it does not distinguish between eating disorder (ED) phenotypes necessary to guide treatment decisions, limiting clinical utility. METHODS: The current study used latent class analysis to identify distinct person-centred profiles of DEB in adults with type 1 diabetes using the DEPS-R. Analysis of Variance with Games Howell post-hoc comparisons was then conducted to examine the correspondence between the profiles and binge eating, insulin restriction and glycaemic control (HbA1c, mean blood glucose, and percent time spent in hyperglycaemia) during 3 days of assessment in a real-life setting. RESULTS: Latent class analysis indicated a 4-class solution, with patterns of item endorsement suggesting the following profiles: Bulimia, Binge Eating, Overeating and Low Pathology. Differences in binge eating, insulin restriction and glycaemic control were observed between profiles during 3 days of at-home assessment. The Bulimia profile was associated with highest HbA1c and 3-day mean blood glucose. CONCLUSIONS: There are common patterns of responses on the DEPS-R that appear to reflect different ED phenotypes. Profiles based on the DEPS-R corresponded with behaviour in the real-life setting as expected and were associated with different glycaemic outcomes. Results may have implications for the use of the DEPS-R in research and clinical settings.

Factors associated with return to play following conservative treatment for lumbar spondylolysis among young athletes: A retrospective case series using structural equation modeling.

INTRODUCTION: Lumbar spondylolysis is the most common underlying cause of lower back pain (LBP) in young athletes. Conservative treatment methods are often used to reduce pain and promote healing. Several parameters may affect the duration of conservative treatment, such as the time to return to play (RTP), patient behavior, and physical parameters; however, no study has comprehensively assessed the factors that affect the time to RTP. OBJECTIVES: This study aimed to determine the factors associated with the time required for RTP among young athletes with early-stage spondylolysis receiving conservative treatment using structural equation modeling (SEM). METHODS: In this retrospective case series, 137 young athletes (128 males and 9 females, aged 9-18 years) with early-stage lumbar spondylolysis were enrolled. All patients were examined using plain radiography and magnetic resonance imaging and treated conservatively (sports cessation, wearing a corset, therapeutic exercises, and low-intensity pulsed ultrasound radiation). SEM was used to investigate the factors affecting the time to RTP in these patients. RESULTS: The final model included the following factors: spondylolysis laterality, symptom duration, lower-extremity flexibility, treatment interval, patient adherence, and residual LBP. SEM revealed that patient adherence to physician orders (p < 0.01), treatment interval (p < 0.001), and spondylolysis laterality (p < 0.001) contributed directly to shortened RTP. CONCLUSION: Patient adherence is essential for reducing the time to RTP among young athletes receiving conservative treatment for early-stage spondylolysis.

Latent class analysis of chest CT abnormalities to define subphenotypes in patients with MPO-ANCA-positive microscopic polyangiitis.

BACKGROUND: Patients with microscopic polyangiitis (MPA) and positive myeloperoxidase antineutrophil cytoplasmic antibody (MPO-ANCA) may present with various abnormalities in chest computed tomography (CT). This study aimed to identify subphenotypes using latent class analysis (LCA) and to explore the relationship between the subphenotypes and clinical patterns, as well as compare the clinical characteristics of these subphenotypes in patients with MPO-ANCA-positive MPA (MPO-MPA). METHODS: The study identified subphenotypes using LCA based on chest CT findings in 178 patients with MPO-MPA and pulmonary involvement from June 2014 to August 2022. RESULTS: LCA identified 27 participants (15.2%) in class 1, 43 (24.1%) in class 2, 35 (19.7%) in class 3, and 73 (41.0%) in class 4. Class 1 was characterized by prominent inflammatory exudation, class 2 by fibrosis and architectural distortion, class 3 by predominantly bronchiectasis, and class 4 by lesions mixed with inflammation and fibrosis. Class 1 had the highest level of extrapulmonary disease activity, with 77.8% of patients experiencing diffuse alveolar hemorrhage. Class 2 had the lowest level of extrapulmonary disease activity, with 41.9% of patients showing usual interstitial pneumonia. Class 3 patients were more likely to have complications involving the ear, nose, and throat, as well as pulmonary infections before treatment, and they exhibited the best outcomes. The characteristics and outcomes of class 4 were intermediate among the four classes. CONCLUSIONS: These findings suggest that bronchiectasis may represent a unique pattern of pulmonary involvement in MPO-MPA, highlighting the importance of screening for bronchiectasis in MPO-MPA and identifying optimal management strategies.

Low diagnostic performance of thick blood smears of 50 µl in comparison with direct examination of 10 µl blood and the leukoconcentration technique of 5ml blood among loiasis-suspected patients with low microfilaremia in Gabon, Central Africa, using the STARD-BLCM guidelines.

BACKGROUND: The aim of this study was to determine performance indicators of thick blood smears of 50 µl (TBS-50), following the Standards for the Reporting of Diagnostic Accuracy Studies-Bayesian Latent Class Model (STARD-BLCM) guidelines. TBS-50 was compared with two common parasitological techniques-direct examination of 10 µl blood and a leukoconcentration of 5 ml-for the diagnosis of microfilaremic loiasis. METHODS: The study population was recruited among patients of the Department of Parasitology-Mycology-Tropical Medicine over a period of 1 year. Age, sex, symptoms, and eosinophilia variables were recorded from laboratory registers and medical files. Direct examination of 10 µl of blood, TBS-50, and the leukoconcentration technique with 5 ml of blood were performed for each patient. The classical formula and BLCM were used to determine the diagnostic accuracy of the three techniques as well as the prevalence of microfilaremic loiasis. Three models were built within the framework of BLCM-the BLCM model I and alternative models II and III-for sensitivity analysis. RESULTS: In total, 191 patients consented to be included. The direct blood examination and TBS-50 yielded comparable qualitative and quantitative results. Hence, they are reported together. The prevalence of Loa loa microfilaremia was 9.4% (95% CI 5.7-14.5; n = 18/191) with direct blood examination/TBS-50 and 12.6% [8.2-18.1] (n = 24/191) for leukoconcentration. Comparing TBS-50 with the leukoconcentration method using the classical formula, the sensitivity was 75.0% [53.3-90.2], specificity was 100.0% [97.8-100.0], the positive predictive value was 100.0% [81.5-100.0], and the negative predictive value was 96.5% [92.6-98.7]. The prevalence of microfilaremic loiasis was estimated at 9.7% [6.2-13.7] using BLCM model I. The outputs of BLCM model I showed sensitivity of 78.9% [65.3-90.3], specificity of 100.0% [99.3-100.0], a positive predictive value of 99.1% [87.2-100.0], and a negative predictive value of 93.0% [87.3-97.7] for direct blood examination/TBS-50. CONCLUSIONS: TBS-50 demonstrates low sensitivity relative to two other techniques. In one in five cases, the result will be falsely declared negative using these methods. However, this method can be deployed with limited funds.

A latent class analysis of family resilience and its relationship with fear of recurrence in lung cancer patients: a cross-sectional study.

PURPOSE: Family resilience helps cancer-affected families overcome challenges and may influence an individual's fear of cancer recurrence (FCR). Identifying distinct classes of family resilience among lung cancer patients is crucial for tailored interventions. This study aimed to identify latent classes of family resilience in lung cancer patients and explore their relationships with FCR. METHODS: Three hundred ten lung cancer patients from three hospitals in Fujian were recruited from June to September 2021. Clinical data were extracted from medical records, while sociodemographic details, family resilience, and FCR were self-reported. A latent class analysis was performed to identify family resilience classes. RESULTS: A 4-class solution showed the best fit. Compared to Class 1, the patients who had no comorbidities (ORs = 3.480-16.005) had an increased likelihood of belonging to Class 2 and 3, while those who were not family breadwinners (ORs = 0.118-0.176) had a decreased likelihood. Further, the patients who (1) did not lack interest/pleasure in doing things during the past 2-week period (OR = 7.057), (2) were never smokers (OR = 6.230), and (3) were urban residents (OR = 8.985) had an increased likelihood of belonging to Class 4, while those who were (1) male (OR = 0.167), (2) not the family breadwinner (OR = 0.152), and (3) had none or only one child (OR = 0.203) had a decreased likelihood of belonging to Class 4. The FCR level differed significantly among these four classes. CONCLUSION: Our study identified four distinct classes of family resilience among Chinese lung cancer patients. FCR severity decreased with increasing levels of family resilience.