Intensity of Social Support Matters: A Latent Class Analysis to Identify Levels of Social Support Associated with Optimal Health Outcomes Among Women Living with HIV.
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ABSTRACT:
SUBMITTER: Chandran A
PROVIDER: S-EPMC8776899 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesResearch suggests that abuser risk factors differ across elder mistreatment types, but abuse interventions are not individualized. To move away from assumptions of perpetrator homogeneity and to inform intervention approaches, this study classifies abusers into subtypes according to their behavior profiles.MethodData are from the Older Adult Mistreatment Assessment administered to victims by Adult Protective Service (APS) in Illinois. Latent class analysis was used to categorize abusers (N = 336) using victim and caseworker reports on abusers' harmful and supportive behaviors and characteristics. Multinomial logistic regression was then used to determine which abuser profiles are associated with 4 types of mistreatment-neglect, physical, emotional, and financial-and other sociodemographic characteristics.ResultsAbusers fall into 4 profiles descriptively labeled "Caregiver," "Temperamental," "Dependent Caregiver," and "Dangerous." Dangerous abusers have the highest levels of aggression, financial dependency, substance abuse, and irresponsibility. Caregivers are lowest in harmful characteristics and highest in providing emotional and instrumental support to victims. The 4 profiles significantly differ in the average age and gender of the abuser, the relationship to victims, and types of mistreatment committed.DiscussionThis is the first quantitative study to identify and characterize abuser subtypes. Tailored interventions are needed to reduce problem behaviors and enhance strengths specific to each abuser profile.
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Project description:BACKGROUND AND AIMS:Identifying typologies of social determinants of health (SDoH) vulnerability influencing drug use practices among women living with HIV (WLWH) can help to address associated harms. This research aimed to explore the association of SDoH clusters with drug use among WLWH. DESIGN:Latent class analysis (LCA) was used to identify the distinct clusters of SDoH. Inverse probability weighting (IPW) was employed to account for confounding and potential selection bias. Associations were analyzed using generalized linear model with log link and Poisson distribution, and then weighted risk ratio (RR) and 95% confidence intervals (CI) were reported. SETTING AND PARTICIPANTS:Data from 1422 WLWH recruited at time-point 1 of the Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS, 2013-15), with 1252 participants at 18 months follow-up (time-point 2). MEASUREMENTS:Drug use was defined as use of illicit/non-prescribed opioids/stimulants in the past 6 months. SDoH indicators included: race discrimination, gender discrimination, HIV stigma, social support, access to care, food security, income level, employment status, education, housing status and histories of recent sex work and incarceration. FINDINGS:LCA identified four SDoH classes: no/least SDoH adversities (6.6%), discrimination/stigma (17.7%), economic hardship (30.8%) and most SDoH adversities (45.0%). Drug use was reported by 17.5% and 17.2% at time-points 1 and 2, respectively. WLWH with no/least SDoH adversities were less likely to report drug use than those in economic hardship class (weighted RR = 0.13; 95% CIs = 0.03, 0.63), discrimination/stigma class (weighted RR = 0.15; 95% CIs = 0.03, 0.78), and most SDoH adversities class (weighted RR = 0.13; 95% CIs = 0.03, 0.58). CONCLUSIONS:Social determinants of health vulnerabilities are associated with greater likelihood of drug use, underscoring the significance of addressing interlinked social determinants and drug use through the course of HIV care and treatment.
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Project description:BackgroundLiving alone has increased globally and especially in Finland where 45% of all households are single occupancy. Epidemiological research has found that living alone a risk factor for a wide range of adversities related to quality of life but the rapidly-changing demographics of people living alone calls for a more detailed investigation of their subjective health status.MethodsUsing a cross-sectional survey sent for a random sample of Finnish residents in single-person households (n = 884), we explored with latent class analysis whether the respondents form different health profiles based on the three health dimensions defined by the World Health Organization: physical, social, and mental well-being. The identified groups were then compared in terms of demographic characteristics with the χ2 test and quality of life using linear regression models. Sensitivity analyses were run using more refined, manual 3-step BCH method.ResultsFour distinct health profiles were found: Languishing (4%), Managing (35%), Healthy (30%), and Flourishing (31%). The groups differed in most socio-demographic aspects such as marital and employment status, but not in terms of geographic location or gender (apart from group Languishing that contained more men). Controlling for these socio-demographic differences, all groups showed different average levels of perceived quality of life to the expected direction.ConclusionsOur findings suggest that people living alone are indeed a very heterogeneous group in terms of subjective health. Instead of seeing living alone as a mere risk for low quality of life, concept of living alone should be understood more broadly both in public discussion and scientific research.
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Project description:Cyberbullying is a common social maladjustment that has negative repercussions on the wellbeing and development of adolescents, but numerous questions remain as to the relationship between cyberbullying and social anxiety in adolescence. This study analyzes cyberbullying profiles (screening of harassment among peers) and assesses whether these profiles vary with respect to the level of social anxiety (social anxiety scale for adolescents). The sample consisted of 1412 Spanish secondary education students aged 12 to 18 (M = 14.36, SD = 1.65). Latent class analysis and ANOVA were performed. Analyses revealed three profiles: high cyberbullying (high victimization, aggression, and aggression-victimization), low cyberbullying (moderate victimization, aggression, and aggression-victimization), and non-cyberbullying. The cyberbullying patterns varied significantly for all social anxiety subscales. Students with the high cyberbullying profile (bully-victims) presented high scores on social avoidance and distress in social situations in general with peers, whereas these students presented lower levels of fear of negative evaluation and distress and social avoidance in new situations as compared to the low cyberbullying (rarely victim/bully) and non-involved student profiles. Implications for psychologists and educational counselors and cyberbullying preventive interventions are discussed.
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Project description:Nightclubs are a setting in which young adults purposefully seek out experiences, such as drug use and alcohol intoxication that can expose them to physical harm. While physical harm occurs fairly frequently within clubs, many patrons have safe clubbing experiences. Further, not all patrons experience potential harms the same way, as there are differences in aggression and intoxication. In this article we draw on data from a research study in which we sought to better understand the role of social drinking groups in experiences of risk within nightclubs, as the majority of patrons attend with others. We collected data from 1,642 patrons comprising 615 social drinking groups as they entered and exited nightclubs in a major U.S. city. We focused on six experiences that might cause physical harm: alcohol impairment, alcohol intoxication, drug use, physical aggression, sexual aggression, and impaired driving. We aggregated patron responses across social groups and used latent class statistical analysis to determine if and how experiences tended to co-occur within groups. This analysis indicated there were five distinct classes which we named Limited Vulnerability, Aggression Vulnerability, Substance Users, Impaired Drivers and Multi-Issue. We assessed the groups within each class for distinctions on characteristics and group context. We found differences in the groups in each class, such as groups containing romantic dyads experienced less risk, while those groups with greater familiarity, greater concern for safety, and higher expectations for consumption experienced more risk. Group composition has an impact on the experiences within a club on a given night, in particular when it comes to risk and safety assessment.
| S-EPMC6156006 | biostudies-literature
Project description:BackgroundSocial network members influence risk and health behaviors, yet little is known about the support that persons who inject drugs (PWID) receive from their closest ties.Methods970 participants from the AIDS Linked to the IntraVenous Experience (ALIVE) study completed a social network survey between April 2016 and June 2017 about their five closest ties. Our analysis: 1) identified latent classes of support received by participants; 2) determined whether class membership differed by current (≤12 months) vs. former (>12 months) injection drug use; 3) compared classes of support by individual and network characteristics.Results970 participants listed 3,388 network members. We identified three support classes: (1) Moderate (n = 249): probabilities of support <0.40; (2) High (n = 366): probabilities of support 0.58-0.82; (3) Very high (n = 355): probabilities of support 0.91-0.99. In adjusted analysis compared to moderate support, the odds of high and very high support increased as the mean age of network members increased (Adjusted Odds Ratio [AOR]:1.03; 95 % CI: 1.01, 1.05) and as the number of network members with whom they interacted daily increased (AOR-high: 1.33; 95 % CI:1.14, 1.56 and AOR-very high: 1.54; 95 % CI: 1.30, 1.83). While current injection drug use was associated with lower unadjusted odds of high and very high support, the associations were not statistically significant in adjusted analysis.ConclusionsSupport was higher among networks of older ties and more frequent interaction, but differences did not appear to be driven by injection drug use status. Findings point to the importance of the closest social ties.
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Project description:Youth involved with the juvenile justice system have higher rates of unmet social and psychological service needs than the general population. Yet, scant research has addressed the potentially complex needs of youth on probation. This study is thus a first step in improving our ability to promote positive youth development and improved outcomes from youth on probation. It uses administrative data on probation youth from FY2011-2013 in a mid-Atlantic state. We estimated latent class models based on the ordinal scoring (high, moderate, none/low) of the 25 subscales from a standardized assessment administered at intake. In order to test whether groups were distinct, we examined a range of variables, including the official risk classification and recidivism rates measured by officieal rearrests and reconvictions. We report the demographic differences between the estimated groups, as well as adverse childhood experiences, school and employment status, previous legal history, and substance use history. Ultimately, the seven-class model produced four groups that others have noted: a relatively low needs (lowest need), relatively high needs (complex needs), substance use service needs, and mental health service needs. The other three groups that emerged include two gender specific groups (one for male and one for female high-need groups) and a group with skills needs that lacks supportive and protective skills. The analyses will facilitate a better appreciation for the service needs of moderate risk youth. Youth on probation are not a uniform population; they reflect tremendous heterogeneity, and probation systems should embrace systemic responsivity to provide appropriate services to improve youth outcomes. Advancing efforts to provide a broader spectrum of services that address multi-morbid conditions can ensure that youth have opportunities to improve their quality of life during the period of supervision.
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Project description:Background: There is controversy whether masked hypertension (MHT) requires additional intervention. The aim of this study is to evaluate whether MHT accompanied with high-risk metabolic syndrome (MetS), as the subphenotype, will have a different prognosis from low-risk MetS. Methods: We applied latent class analysis to identify subphenotypes of MHT, using the clinical and biological information collected from High-risk Cardiovascular Factor Screening and Chronic Disease Management Programme. We modeled the data, examined the relationship between subphenotypes and clinical outcomes, and further explored the impact of antihypertensive medication. Results: We included a total of 140 patients with MHT for analysis. The latent class model showed that the two-class (high/low-risk MetS) model was most suitable for MHT classification. The high-risk MetS subphenotype was characterized by larger waist circumference, lower HDL-C, higher fasting blood glucose and triglycerides, and prevalence of diabetes. After four years of follow-up, participants in subphenotype 1 had a higher non-major adverse cardiovascular event (MACE) survival probability than those in subphenotype 2 (P = 0.016). There was no interaction between different subphenotypes and the use of antihypertensive medications affecting the occurrence of MACE. Conclusions: We have identified two subphenotypes in MHT that have different metabolic characteristics and prognosis, which could give a clue to the importance of tracing the clinical correlation between MHT and metabolic risk factors. For patients with MHT and high-risk MetS, antihypertensive therapy may be insufficient.
| S-EPMC8424076 | biostudies-literature
Project description:ImportanceMedically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date.ObjectiveTo define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters.Design, setting, and participantsThis cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles.Main outcomes and measuresComplex patient profiles, 1-year health care utilization, and mortality outcomes by profile.ResultsThe analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management.Conclusions and relevanceThe findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.
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