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BACKGROUND: Depression is prevalent among lung cancer patients undergoing chemotherapy, and the symptom cluster of fatigue-pain-insomnia may influence their depression. Identifying characteristics of patients with different depression trajectories can aid in developing more targeted interventions. This study aimed to identify the trajectories of depression and the fatigue-pain-insomnia symptom cluster, and to explore the predictive factors associated with the categories of depression trajectories. METHODS: In this longitudinal study, 187 lung cancer patients who were undergoing chemotherapy were recruited and assessed at the first (T1), second(T2), and fourth(T3) months using the Patient Health Questionnaire-9 (PHQ-9), the Brief Pain Inventory (BPI), the Brief Fatigue Inventory (BFI), and the Athens Insomnia Scale (AIS). Growth Mixture Model (GMM) and Latent Class Analysis (LCA) were used to identify the different trajectories of the fatigue-pain-insomnia symptom cluster and depression. Binary logistic regression was utilized to analyze the predictive factors of different depressive trajectories. RESULTS: GMM identified two depressive trajectories: a high decreasing depression trajectory (40.64%) and a low increasing depression trajectory (59.36%). LCA showed that 48.66% of patients were likely members of the high symptom cluster trajectory. Binary logistic regression analysis indicated that having a history of alcohol consumption, a higher symptom cluster burden, unemployed, and a lower monthly income predicted a high decreasing depression trajectory. CONCLUSIONS: Depression and fatigue-pain-insomnia symptom cluster in lung cancer chemotherapy patients exhibited two distinct trajectories. When managing depression in these patients, it is recommended to strengthen symptom management and pay particular attention to individuals with a history of alcohol consumption, unemployed, and a lower monthly income.

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Objective: To construct a model for predicting recidivism in violence in community-based schizophrenia spectrum disorder patients (SSDP) by adopting a joint modeling method. Methods: Based on the basic data on severe mental illness in Southwest China between January 2017 and June 2018, 4565 community-based SSDP with baseline violent behaviors were selected as the research subjects. We used a growth mixture model (GMM) to identify patterns of medication adherence and social functioning. We then fitted the joint model using a zero-inflated negative binomial regression model and compared it with traditional static models. Finally, we used a 10-fold training-test cross validation framework to evaluate the models' fitting and predictive performance. Results: A total of 157 patients (3.44%) experienced recidivism in violence. Medication compliance and social functioning were fitted into four patterns. In the counting model, age, marital status, educational attainment, economic status, historical types of violence, and medication compliance patterns were predictive factors for the frequency of recidivism of violence (P<0.05). In the zero-inflated model, age, adverse drug reactions, historical types of violence, medication compliance patterns, and social functioning patterns were predictive factors for the recidivism in violence (P<0.05). For the joint model, the average value of Akaike information criterion (AIC) for the train set was 776.5±9.4, the average value of root mean squared error (RMSE) for the testing set was 0.168±0.013, and the average value of mean absolute error (MAE) for the testing set was 0.131±0.018, which were all lower than those of the traditional static models. Conclusion: Joint modeling is an effective statistical strategy for identifying and processing dynamic variables, exhibiting better predictive performance than that of the traditional static models. It can provide new ideas for promoting the construction of comprehensive intervention systems.

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Body Mass Index (BMI) trajectories are important for understanding how BMI develops over time. Missing data is often stated as a limitation in studies that analyse BMI over time and there is limited research exploring how missing data influences BMI trajectories. This study explores the influence missing data has in estimating BMI trajectories and the impact on subsequent analysis. This study uses data from the English Longitudinal Study of Ageing. Distinct BMI trajectories are estimated for adults aged 50 years and over. Next, multiple methods accounting for missing data are implemented and compared. Estimated trajectories are then used to predict the risk of developing type 2 diabetes mellitus (T2DM). Four distinct trajectories are identified using each of the missing data methods: stable overweight, elevated BMI, increasing BMI, and decreasing BMI. However, the likelihoods of individuals following the different trajectories differ between the different methods. The influence of BMI trajectory on T2DM is reduced after accounting for missing data. More work is needed to understand which methods for missing data are most reliable. When estimating BMI trajectories, missing data should be considered. The extent to which accounting for missing data influences cost-effectiveness analyses should be investigated.

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OBJECTIVES: Due to statistical challenges in disentangling the mobility effect (i.e., intergenerational educational mobility) from the position effect (i.e., parental and person's own education), the impact of intergenerational educational mobility on cognitive function remains unclear. We employed a novel approach to identify the mobility effect and investigate the net impact of intergenerational educational mobility on heterogeneous patterns of cognition among middle-aged and older adults in China. METHODS: Participants aged 45 and older were recruited from the China Health and Retirement Longitudinal Study, a population-based prospective cohort study between 2011 and 2018. We identified cognitive trajectories using the growth mixture model (GMM) and subsequently employed the mobility contrast model (MCM) to examine the effects of intergenerational educational mobility on cognitive patterns stratified by gender. RESULTS: Almost two thirds of respondents experienced intergenerational educational mobility, and 55% experienced upward mobility. Men had a higher rate of upward mobility than women. Three population-based cognitive patterns were identified: the low cognitive function with decline group (28%), the moderate cognitive function group (47%), and the high cognitive function group (26%). MCM analysis revealed that both upward and downward intergenerational educational mobility negatively affected cognitive trajectory patterns, extending beyond the influence of individuals' current and parental education. DISCUSSION: In future research, the impact of mobility can be studied in longitudinal data sets by combining the GMM and MCM approaches. The net negative effect of intergenerational educational mobility on cognitive trajectory patterns indicates that it should be recognized as an independent predictor of cognitive decline.

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Positive youth development (PYD) frameworks suggest that a critical response to investigating the challenges young Black men living in resource poor communities experience involves identifying contextual resources in young men's lives and personal assets that promote success. The following study examines heterogeneity in proactive coping assets trajectories, parental practices as predictors of developmental trajectories, and associated outcomes of each trajectory. The study sample consisted of Black emerging adult men living in rural Georgia (N = 504). At baseline, men were between the ages of 19 and 22 (Mage = 20.29; SD = 1.10). At wave four, the participants' mean age was 27.67 (SD = 1.39). Results of growth mixture modeling from waves 1 to 3 discerned three developmental trajectory classes of emerging adults' proactive coping assets: a high and increasing class (n = 247, 49%), a low and stable class (n = 212, 42%), and a moderate and decreasing class (n = 45, 9%). Trajectory classes were linked to baseline levels of parental support, coaching, and expectations. Analysis revealed that parental support and parental coaching predicted proactive coping asset trajectory class identification. Links were then investigated between emerging adults' proactive coping asset trajectory classes and wave four physical health, depression, and alcohol use. Results revealed significant associations between class identification, alcohol use, and physical health. Study findings provide evidence supporting the impact of parenting on emerging adult Black men, underscoring the need to expand resources that support parenting and emerging adult relationships.

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AIM: To investigate the trajectory patterns and influencing factors of supportive care needs in stroke patients. DESIGN: A longitudinal study. METHODS: In total, 207 stroke patients who received treatment at the Department of Neurology in a hospital in Xuzhou between July 2022 and July 2023 were recruited using convenience sampling. Questionnaires including supportive care needs, hospital anxiety and depression scale, and the Barthel index were investigated at baseline and at 1, 3, and 6 months. A latent class growth model was applied to identify the supportive care needs trajectories. Multiple logistic regression was used to determine the predictors for membership. This study adheres to STROBE reporting guidelines. RESULTS: Three patterns of supportive care needs trajectories were identified: A high needs slow decline group (20.8%), a medium needs stable group (56.5%) and a medium needs rapid decline group (22.7%). Based on further analysis, the findings indicated that age, education level, monthly income, comorbidity, activities of daily living, anxiety and depression were associated with the trajectory categories of supportive care needs with stroke patients. CONCLUSION: This study demonstrates heterogeneity in changes in supportive care needs among stroke patients. Healthcare providers need to consider these different categories of needs and develop individualized care measures based on the characteristics of different patients. IMPACT: Healthcare providers should be aware of the fluctuations in care needs of stroke patients at various stages. Additionally, the study aimed to identify patients' specific needs based on their circumstances, monitor the rehabilitation process and establish a more personalized and optimized care plan through multidisciplinary collaboration. The ultimate goal was to alleviate symptomatic distress and address the long-term care needs of patients. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

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BACKGROUND: Social anxiety among postoperative breast cancer patients is a prevalent concern, with its intensity fluctuating throughout the course of treatment. The study aims to describe the trajectory of social anxiety in postoperative breast cancer patients, explore the influencing factors, and provide theoretical support for the construction of future intervention programs. METHODS: This study was conducted from June 2022 to January 2023, encompassing 213 breast cancer patients from three first-class hospitals in China. Data collection occurred at four distinct time points. A growth mixture model was employed to identify latent categories representing the trajectories of social anxiety changes among patients. A multiple regression analysis was utilized to explore predictive factors associated with different latent trajectory categories. RESULTS: The trajectory of social anxiety changes in postoperative breast cancer patients includes five potential categories: maintaining mild social anxiety group, changing from mild to moderate social anxiety group, maintaining moderate social anxiety group, changing from moderate to severe social anxiety group, and maintaining severe social anxiety group. Cluster analysis results indicated three types: positive, negative, and low. Logistic regression analysis revealed that younger age, spouses concerned about postoperative appearance, chemotherapy with taxol-based drugs, opting for modified radical surgery or radical mastectomy surgical approaches, and breast cancer patients with negative rumination were factors that influenced patients' social anxiety (P < 0.05). CONCLUSION: The trajectory of social anxiety in postoperative breast cancer patients comprises five potential categories. In clinical practice, it is essential to strengthen the management of high-risk populations susceptible to experiencing social anxiety emotions, including younger age, spouses concerned about postoperative appearance, chemotherapy with taxol-based drugs, opting for modified radical surgery or radical mastectomy surgical approaches, and breast cancer patients with negative rumination.

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Background: This study focuses on the heterogeneity, interaction, and imbalance in the concurrent development of physical and mental health trajectories among Chinese elderly. Methods: The data used in this study are from four waves of the China Health and Retirement Longitudinal Study (CHRLS) conducted between 2011 and 2018. A multidimensional growth mixture model (MGMM) was employed to analyze the patterns and characteristics of co-occurring physical and mental health development. Additionally, multinomial logistic regression analysis was conducted to systematically investigate the factors that predict the conjoint trajectories of physical and mental health. Results: The study findings reveal the presence of four distinct latent classes of conjoint trajectories for physical and mental health. These classes are categorized as follows: 'physical and mental health deteriorating', 'physical disease increasing & low mental vulnerability maintaining', 'low physical & mental vulnerability maintaining', and 'high physical disease increased & mental health moderate-stable'. Furthermore, demographic characteristics, socioeconomic status, family-society relations, health behaviors, and institutional factors were found to significantly predict these latent classes. Conclusion: The study emphasizes the diversity and complexity of physical and mental co-occurring developmental health issues in the elderly population in China. These findings have significant implications for the development of targeted intervention strategies that take into account the unique health changes experienced by older adults. Additionally, they can serve as evidence for the establishment of a comprehensive long-term care system.

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Background: Oppositional Defiant Disorder (ODD) is a disruptive behavioral disorder; however, increasing evidence emphasizes irritable mood as a primary symptom of ODD. Objectives: This study investigated whether heterogeneous groups (classes) of individuals can be differentiated based on ODD sub-dimensions (irritability and defiance) or on overall ODD symptoms longitudinally. We also examine associations between ODD trajectory class and comorbid substance use (heavy episodic drinking, cannabis use), mental health (depression and anxiety) and behavioral symptoms (ADHD, aggression and substance use) in both adolescence and young adulthood (controlling for adolescent levels of each of these concerns). Method: Data were from a randomly recruited community sample of 662 Canadian youth (T1 ages 12-18) followed biennially for 10 years (T6 ages 22-29). Results: Growth mixture models revealed trajectories classes of ODD based on severity of symptoms. A three-class solution provided the best fit with Low (n = 119; 18%), Moderate (n = 473; 71.5%), and High (n = 70; 10.6%) ODD classes. Class trajectory differences were similarity based on symptoms severity (rather than type) for symptom sub-dimensions (irritability defiance). Adolescent and young adult substance use, mental health symptoms, and behavioral problems were significantly higher for the High ODD trajectory class compared to both other classes. Youth in the Moderate ODD trajectory class also showed higher comorbid symptoms in adolescence and young adulthood, compared to the Low ODD trajectory class. Conclusion: Early identification of children and adolescents with high or moderate ODD symptoms and interventions that simultaneously address defiance and irritability are supported by the findings.

Contexte: Le trouble oppositionnel avec provocation (TOP) est un trouble du comportement perturbateur; toutefois, des données probantes croissantes soulignent que l'humeur irritable est un symptôme primaire du TOP. Objectifs: La présente étude a investigué si les groupes (classes) hétérogènes de personnes qui peuvent être différentiées au mieux selon les sous-dimensions (irritabilité et défi) ou selon les symptômes généraux du TOP longitudinalement. Nous examinons également les associations entre la classe de trajectoire du TOP et l'utilisation de substances comorbide (lourde consommation d'alcool épisodique, utilisation de cannabis), la santé mentale (dépression et anxiété) et symptômes comportementaux (TDAH, agression et utilisation de substances) tant chez les adolescents que chez les jeunes adultes (contrôler les niveaux adolescents de chacun de ces problèmes). Méthode: Les données provenaient d'un échantillon communautaire recruté au hasard de 662 jeunes Canadiens (âges T1 2­18) suivis tous les deux ans pendant 10 ans (T6 âges 22­29). Résultats: Des modèles de mélange de croissance ont révélé des classes de trajectoire du TOP basées sur la gravité des symptômes. Une solution en trois classes a fourni le meilleur ajustement avec des classes de TOP faible (n = 119; 18 %), modérée (n = 473; 71,5 %), et élevée (n = 70; 10,6 %). Les différences de classes de trajectoire étaient également basées sur la gravité des symptômes (plutôt que sur le type) des sous-dimensions des symptômes (irritabilité, défi). L'utilisation de substances chez les adolescents et les jeunes adultes, les symptômes de santé mentale et les problèmes de comportement étaient significativement plus élevés pour la classe de la trajectoire élevée du TOP comparé aux deux autres classes. Les jeunes de la classe de trajectoire modérée du TOP présentaient aussi des symptômes comorbides plus élevés à l'adolescence et au jeune âge adulte, comparé à la classe de trajectoire faible du TOP. Conclusion: L'identification précoce des enfants et des adolescents présentant des symptômes élevés ou modérés du TOP et les interventions qui prennent en charge simultanément le défi et l'irritabilité sont soutenues par les résultats.

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BACKGROUND: The social disparities in obesity may originate in early life or in adulthood, and the associations of socioeconomic position (SEP) with obesity could alter over time. It is unclear how lifetime-specific and life-course SEP influence adult obesity development in China. METHODS: Based on the China Health and Nutrition Survey (CHNS), three SEP-related indicators, including the father's occupational position and the participant's education and occupational position, were obtained. The life-course socioeconomic changes and a cumulative SEP score were established to represent the life-course SEP of the participants in the study. The growth mixture modeling was used to identify BMI trajectories in adulthood. Multinomial logistic regression was adopted to assess the associations between SEP and adult BMI trajectories. RESULTS: A total of 3,138 participants were included in the study. A positive correlation was found between the paternal occupational position, the participants' occupational position, education, and obesity in males, whereas an inverse correlation was observed among females. Males who experienced social upward mobility or remained stable high SEP during the follow-up had 2.31 and 2.52-fold risks of progressive obesity compared to those with a stable-low SEP. Among females, stable high SEP in both childhood and adulthood was associated with lower risks of progressive obesity (OR = 0.63, 95% CI: 0.43-0.94). Higher risks of obesity were associated with the life-course cumulative SEP score among males, while the opposite relationship was observed among females. CONCLUSIONS: The associations between life-course SEP and BMI development trajectories differed significantly by gender. Special emphasis should be placed on males experiencing upward and stable high socioeconomic change.

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Background: Multiple Sclerosis (MS) disease progression has notable heterogeneity among patients and over time. There is no available single method to predict the risk of progression, which represents a significant and unmet need in MS. Methods: MS and healthy control (HC) participants were recruited for a 2-year observational study. A latent-variable growth mixture model (GMM) was applied to cluster baseline 6-min walk gait speed trajectories (6MWGST). MS patients within different 6 MWGST clusters were identified and stratified. The group membership of these MS patients was compared against 2-year confirmed-disease progression (CDP). Clinical and patient-reported outcome (PRO) measures were compared between HC and MS subgroups over 2 years. Results: 62 MS and 41 HC participants completed the 2-year study. Within the MS cohort, 90% were relapsing MS. Two distinct patterns of baseline 6 MWGST emerged, with one cluster displaying a faster gait speed and a typical "U" shape, and the other showing a slower gait speed and a "flattened" 6 MWGST curve. We stratified MS participants in each cluster as low- and high-risk progressors (LRP and HRP, respectively). When compared against 2-year CDP, our 6 MWGST approach had 71% accuracy and 60% positive predictive value. Compared to the LRP group, those MS participants stratified as HRP (15 out of 62 MS participants), were on average 3.8 years older, had longer MS disease duration and poorer baseline performance on clinical outcomes and PROs scores. Over the subsequent 2 years, only the HRP subgroup showed a significant worsened performance on 6 MW, clinical measures and PROs from baseline. Conclusion: Baseline 6 MWGST was useful for stratifying MS participants with high or low risks for progression over the subsequent 2 years. Findings represent the first reported single measure to predict MS disease progression with important potential applications in both clinical trials and care in MS.

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BACKGROUND: Hypertension has become increasingly prevalent in Chinese children and adolescents in recent decades, which affects growth and development of children, leads to cognitive decline and multiple target organ damage. Here, we assessed the impact of different body mass index (BMI) trajectories on the occurrence of hypertension in children and adolescents using a cohort study in Northeast China. MATERIALS AND METHODS: Children and adolescents aged 5-18 years was extracted for physical examination in Fuxin City, Liaoning Province, China during the 2009-2015 period. A latent category growth mixed model (LCGMM) was used to classify BMI changes and analyze the effect of different BMI trajectories on the risk of occurrence of hypertension in these participants within 5 years. RESULTS: All participates were divided into five BMI trajectories by LCGMM method: slow increasing group (n = 2616, 30.8%), overweight and obesity (OW/OB) group (n = 1141, 13.4%), normal decreasing group (n = 232, 2.7%), stable normal group (n = 4383, 51.6%), and fast-increasing group (n = 120, 1.4%). Compared with the stable normal group, the slow increasing group [adjusted odds ratio (AOR): 1.610, 95% confidence interval (CI): 1.304-1.989], the OW/OB group (AOR: 3.172, 95% CI: 2.500-4.023) and the fast-increasing group (AOR: 2.708, 95% CI: 1.445-5.074) all increased the risk of developing hypertension in children and adolescents. CONCLUSION: The potential of developing hypertension varies among groups of children aged 5-18 with different BMI trajectories. Children and adolescents in the normal BMI range (the slow growth group) still need to be aware of the change in BMI trajectory to stop or slow down the progression of BP abnormalities.

Five body mass index trajectories from ages 5­18 years were determined using the LCGMM method, which labeled as the slow increasing group, overweight and obesity (OW/OB) group, normal decreasing group, stable normal group, and fast-increasing group.Different BMI trajectories in children and adolescents aged 5­18 years are differentially associated with the development of hypertension.Increased BMI levels in children and adolescents increase the risk of hypertension. Moreover, even within the normal BMI range, a modest growth might raise the risk of high-normal BP.

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INTRODUCTION: This study explores the trend of urolithiasis in various countries and categorizes the countries in terms of how their urolithiasis incidence rate has changed over time. METHODS: The incidence rate of urolithiasis in 204 countries from 1990 to 2019, extracted from the Global Burden of Disease study, has been analyzed. RESULTS: According to the results, all regions had experienced an increasing trend in urolithiasis rate, except for Eastern Europe, Central Europe, and Southeast Asia regions (decreasing rates of -71.4, -56.2, and -9.2 per 100000, respectively). Moreover, the Caribbean region had the highest increasing trend of urolithiasis rates, and Central Asia was in the next rank (increasing rate of 48.3 and 34.3 per 100,000, respectively, p-value < .05). Also, African regions revealed significant increasing trends over time (p-value < 0.05). The outstanding findings in cluster analysis showed that Afghanistan, Andorra, and Comoros had the most decreasing trend in urolithiasis rates over time (decreasing rate of -128.2 per 100000, p-value < .001). Cuba, Cyprus, Czechia, the Democratic People's Republic of Korea, Denmark, and Djibouti were in the next rank in terms of decreasing rate (decreasing rate of -92.3 per 100000, p-value < .001). In addition, urolithiasis rates in Congo, Eswatini, Gabon, and Grenada have the most increasing trend (increasing rate of 116.1 per 100000, p-value < .001). CONCLUSION: The trend of urolithiasis rates was significantly increased in most countries, and Congo, Eswatini, Gabon, and Grenada had the highest trend among others. Also, Afghanistan, Andorra, and Comoros revealed the most decreasing rates, and the trend has dropped remarkably in several other countries.

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OBJECTIVE: Depression poses a significant threat to the health and well-being of adolescents with traumatic brain injury. Existing research has limitations in longitudinal follow-up period, consideration of sample heterogeneity, and outcome measurement modeling. This study aimed to address these gaps by applying the second-order growth mixture model (SO-GMM) to examine the 10-year post-injury depression trajectories in adolescents with TBI. METHODS: A total of 1,989 adolescents with TBI 16-21 years old from the Traumatic Brain Injury Model System National Data Bank were analyzed up to 10 years post-injury. Depressive symptoms were measured by Patient Health Questionnaire-9. Covariates included age, sex, race/ethnicity, employment, Functional Independence Measure Cognition, TBI severity, pre-injury disability, and substance use. Longitudinal measurement invariance was tested at the configural, metric, and scalar levels before SO-GMM was fit. Logistic regression was conducted for disparities in depression trajectories by covariates. RESULTS: A 2-class SO-GMM was identified with a low-stable group (85% of the sample) and a high-increasing group (15% of the sample) on depression levels. Older age, being a Native American, and having Hispanic origin was associated with a higher likelihood of being in the high-increasing class (odds ratios [ORs] = 1.165-4.989 and 1.609, respectively), while patients with higher education and being male were less likely to be in the high-increasing class (ORs = 0.735 and 0.557, respectively). CONCLUSIONS: This study examined the disparities in depression among two distinct longitudinal groups of adolescents with TBI 10 years post-injury. Findings of the study are informative for intervention development to improve long-term mental health in adolescents with TBI.

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BACKGROUND: The available evidence indicates that the severity of metabolic syndrome tends to worsen progressively over time. We assessed the trajectory of age and sex-specific continuous MetS severity score (cMetS-S) and its association with the development of diabetes during an 18-year follow-up. METHODS: In a prospective population-based Tehran Lipid and Glucose Study, 3931 eligible participants free of diabetes, aged 20-60 years, were followed at three-year intervals. We examined the trajectories of cMetS-S over nine years using latent growth mixture modeling (LGMM) and subsequent risks of incident diabetes eight years later. The prospective association of identified trajectories with diabetes was examined using the Cox proportional hazard model adjusting for age, sex, education, and family history of diabetes, physical activity, obesity (BMI ≥ 30 kg/m2), antihypertensive and lipid-lowering medication, and baseline fasting plasma glucose in a stepwise manner. RESULTS: Among 3931 participants, three cMetS-S trajectory groups of low (24.1%), medium (46.8%), and high (29.1%) were identified during the exposure period. Participants in the medium and high cMetS-S trajectory classes had HRs of 2.44 (95% CI: 1.56-3.81) and 6.81 (95% CI: 4.07-10.01) for future diabetes in fully adjusted models, respectively. Normoglycemic individuals within the high cMetS-S class had an over seven-fold increased risk of diabetes (HR: 7.12; 95% CI: 6.05-12.52). CONCLUSION: Although most adults exhibit an unhealthy metabolic score, its severity usually remains stable throughout adulthood over ten years of follow-up. The severity score of metabolic syndrome has the potential to be utilized as a comprehensive and easily measurable indicator of cardiometabolic dysfunction. It can be employed in clinical settings to detect and track individuals at a heightened risk of developing T2DM, even if their glucose levels are normal.

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Screen use is a known risk factor for adverse physical and mental health outcomes during childhood and adolescence. Moreover, racial/ethnic disparity in screen use persists among adolescents. However, limited studies have characterized the population sharing similar longitudinal patterns of screen use from childhood to adolescence. This study will identify and characterize the subgroups of adolescents sharing similar trajectories of screen use from childhood to adolescence. Study participants of the Adolescent Brain Cognitive Development Study (2016-2021) in the U.S with non-missing responses on self-reported screen use at each year of the study were included in the analysis. Growth mixture modeling was used to identify the optimal number of subgroups of adolescents with similar trajectories. Subsequently, socio-demographic characteristics, familial background, and perceived racism and discrimination during childhood was assessed for each subgroup population. Perceived discrimination was measured using the Perceived Discrimination Scale. There were two major subgroups of individuals sharing similar trajectories of screen use: Drastically Increasing group (N = 1333); Gradually Increasing group (N = 10336). Higher proportions of the Drastically Increasing group were racial/ethnic minorities (70%) as compared to the Gradually Increasing group (45%). Moreover, the Drastically Increasing group had higher proportions of individuals reporting perceived racism and discrimination during childhood.

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AIMS: We aimed to investigate the association of household crowding in childhood with trajectories of depressive symptoms in middle-aged and older adults. METHODS: We studied 47,010 participants (56 % women, 63 years at baseline) from SHARE. Using multinomial logistic regression, we estimated odds ratio (OR) with 95 % confidence interval (CI) for the association of household crowding in childhood (number of household members/number of rooms at the age of 10) with trajectories of depressive symptoms (EURO-D scale), which were generated with growth mixture modeling. We adjusted for resources in childhood, sociodemographic and health-related characteristics in mid-life and older age and tested effect modification by sex. RESULTS: We identified four trajectories of depressive symptoms: constantly low (n = 33,969), decreasing (n = 5595), increasing (n = 5574) and constantly high (n = 1872). When compared to the those with constantly low depressive symptoms and adjusting for all covariates, household crowding in childhood was associated with greater odds of constantly high (OR 1.12; 95 % CI 1.08-1.17), decreasing (OR 1.11; 95 % CI 1.07-1.15) and increasing (OR 1.09; 95 % CI 1.06-1.13) depressive symptoms. The associations were stronger in women than in men. CONCLUSIONS: Prevention of household crowding in childhood may ameliorate the development of constant as well as transient depressive symptoms during ageing. The effect can be stronger in women than in men.

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BACKGROUND: Sex-specific physical and mental functioning trajectory classification could offer a way of understanding the differences in healthcare use at older age. METHODS: Using latent growth mixture models, sex-specific physical and mental functioning trajectory classes were formed for 1991 participants (mean age 61.5 years) of the Helsinki Birth Cohort Study. Physical and mental functioning were evaluated with the SF-36 survey conducted in clinical examinations in 2001-2004, 2011-2013, and 2017-2018. First and follow-up outpatient visits, emergency visits, and hospital days were extracted from a national register between the first clinical examination and the year 2017. We used regression models to examine the associations between healthcare use and trajectory classes. RESULTS: Two physical and mental functioning trajectory classes, high and intermediate, were observed for both sexes. The intermediate physical functioning trajectory class was associated with higher utilization rates of all examined specialized healthcare services (fully-adjusted IRRs varying 1.36-1.58; 95% CI = 1.03-1.79, 95% CI = 1.21-2.05) compared to the high trajectory class. Relative to the high trajectory class, the intermediate mental trajectory class was associated with the use of first outpatient visits (fully-adjusted IRRs 1.17, 95% CI = 1.03-1.33 for men, and 1.16, 95% CI = 1.04-1.30 for women). The findings were similar among both sexes. CONCLUSIONS: Compared to the high trajectory class, the intermediate physical functioning trajectory class was associated with greater specialized healthcare use and the intermediate mental trajectory class with first outpatient visits. Public health interventions should be considered to support functioning with aging.

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PURPOSE: This study was designed to explore the impact of a new cancer diagnosis on resilience of patients and whether the resilience patterns could predict Quality of Life (QoL) in the first year. METHODS: An exploratory linear piecewise growth mixture modeling (PGMM) with one hypothetical dot (3 months since diagnosis, T1) was employed to identify different resilience patterns and growth in 289 patients with different cancer diagnoses at five assessment occasions (T0-T4). Logistic regression analysis was performed to select potential predictors and receiver operating characteristic (ROC) curve analysis was utilized to test PGMM's discriminative ability against 1-year QoL. RESULTS: Five discrete resilience trajectories with two growing trends were identified, including "Transcendence" (7.3%), "Resilient" (47.4%), "Recovery" (18.7%), "Damaged" (14.9%) and "Maladaption" (11.8%). Advanced stage, colorectal cancer, and receiving surgery therapy were significant predictors of negative resilience trajectories ("Damaged" or "Maladaption"). Discriminative ability was good for PGMM (AUC = 0.81, 95%CI, 0.76-0.85, P < 0.0001). CONCLUSION: Heterogeneity is identified in resilience growth before and after 3 months since diagnosis. 26.7% newly diagnosed patients need additional attention especially for those with advanced colorectal cancer and receiving surgery therapy.

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Background: Despite the growing attention given to adolescent behavior problems, little is known about the trajectories and factors that have influenced adolescent procrastination during the COVID-19 pandemic. This study monitors changes in procrastination behavior among Chinese adolescents during the pandemic and identifies vulnerable groups. Methods: A four-wave study using a representative sample of 11-to 18-year-olds in China was conducted, with baseline data collected in June 2020 (n = 4,156; 49% girls) and follow-ups in December 2020 (n = 3,392; 50% girls), August 2021 (n = 2,380; 48% girls), and October 2021 (n = 1,485; 49% girls). Procrastination behavior was assessed using the General Procrastination Scale. Latent growth curve models, latent growth mixture modes, and multivariate logistic regression models were used to describe the trajectory of procrastination and identify predictors of deterioration. Results: The proportion and overall trends of adolescent procrastination increased with the pandemic. Higher parental over-protection was a contributing factor to the higher baseline levels leading to the faster growth of adolescent procrastination. The model identified three distinct trajectories of low-increasing [including 2,057 participants (49.5%)], moderate-stable [including 1,879 participants (45.2%)], and high-decreasing procrastination [including 220 participants (5.3%)]. More daily leisure screen-time, lower frequency of exercise weekly, and dissatisfaction with distance learning were the top three risk factors for moderate-stable and high-decreasing procrastination compared to low-increasing procrastination. Adolescents with mothers with a higher level of education were more liable to be high-decreasing procrastination than moderate-stable procrastination. Conclusion: The proportion and overall trends of adolescent procrastination increased with the pandemic. The categories of procrastination among adolescents during that time period were probed. Also, the study further clarified the risk factors for severe and moderate procrastination relative to no procrastination. Thus, effective procrastination prevention and intervention strategies need to be implemented to support adolescents, particularly those at risk.