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:In many European countries, including the Netherlands, the healthcare system is financed according to the principles of solidarity. It is important, therefore, that public support for solidarity in healthcare financing is sufficient in order to ensure that people remain willing to contribute towards solidarity-based systems. The high willingness to contribute to the healthcare costs of others in the Netherlands suggests that support is generally high. However, there are differences between groups. Previous research has focused on mechanisms at the individual and institutional level to explain these differences. However, people's social context may also play a role. Little research has been conducted into this. To fill this gap, we examined the role of perceived social support and social norms in order to explain differences in the willingness to contribute to other people's healthcare costs. In November 2021, we conducted a survey study in which a questionnaire was sent to a representative sample of 1,500 members of the Dutch Healthcare Consumer Panel. This was returned by 837 panel members (56% response rate). Using logistic regression analysis, we showed that people who perceive higher levels of social support are more willing to contribute to the healthcare costs of others. We also found that the willingness to contribute is higher when someone's social context is more supportive of healthcare systems that are financed according to the principles of solidarity. This effect does not differ between people who perceive low and high levels of social support. Our results suggest that, next to the individual and institutional level, the social context of people has to be taken into consideration in policy and research addressing support for solidarity in healthcare financing.
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Project description:With Latent Class Analysis applied on data of 98 children with autism spectrum disorder (ASD) (9-12 years; 17 girls) participating in social skills training (SST) in a randomized controlled trial (Dekker et al. 2019), four subgroups were detected, based on social-communicative skills before, and response patterns to training. Two subgroups improved after SST. Characterizing the subgroups based on participant and intervention characteristics showed that improvement was related to lower parent-reported perceived difficulty of social-communicative skills at start, higher verbal ability, younger age and milder symptoms of ASD and anxiety. The lowest performing non-improving subgroup participated more often in SST without parent/teacher involvement, compared to all other subgroups. Response to SST in ASD seems to vary depending on participant characteristics.
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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.
| S-EPMC6992379 | biostudies-literature
Project description:BackgroundAsymptomatic carriage of malaria parasites is common in high transmission intensity areas and confounds clinical case definitions for research studies. This is important for investigations that aim to identify immune correlates of protection from clinical malaria. The proportion of fevers attributable to malaria parasites is widely used to define different thresholds of parasite density associated with febrile episodes. The varying intensity of malaria transmission was investigated to check whether it had a significant impact on the parasite density thresholds. The same dataset was used to explore an alternative statistical approach, using the probability of developing fevers as a choice over threshold cut-offs. The former has been reported to increase predictive power.MethodsData from children monitored longitudinally between 2005 and 2017 from Junju and Chonyi in Kilifi, Kenya were used. Performance comparison of Bayesian-latent class and logistic power models in estimating malaria attributable fractions and probabilities of having fever given a parasite density with changing malaria transmission intensity was done using Junju cohort. Zero-inflated beta regressions were used to assess the impact of using probabilities to evaluate anti-merozoite antibodies as correlates of protection, compared with multilevel binary regression using data from Chonyi and Junju.ResultsMalaria transmission intensity declined from over 49% to 5% between 2006 and 2017, respectively. During this period, malaria attributable fraction varied between 27-59% using logistic regression compared to 10-36% with the Bayesian latent class approach. Both models estimated similar patterns of fevers attributable to malaria with changing transmission intensities. The Bayesian latent class model performed well in estimating the probabilities of having fever, while the latter was efficient in determining the parasite density threshold. However, compared to the logistic power model, the Bayesian algorithm yielded lower estimates for both attributable fractions and probabilities of fever. In modelling the association of merozoite antibodies and clinical malaria, both approaches resulted in comparable estimates, but the utilization of probabilities had a better statistical fit.ConclusionsMalaria attributable fractions, varied with an overall decline in the malaria transmission intensity in this setting but did not significantly impact the outcomes of analyses aimed at identifying immune correlates of protection. These data confirm the statistical advantage of using probabilities over binary data.
| S-EPMC9652045 | biostudies-literature
Project description:BackgroundChildren receive care and support from social services due to the risk of harm or impeded development or because of disability. This study aimed to identify typologies of adversity experienced by children receiving care and support from social services and to explore how typologies differ by sociodemographic characteristics.MethodsThis is a cross-sectional study of 'Children Receiving Care and Support' (N = 12 792) during 2017/2018 in Wales, UK. We sought to (1) examine the prevalence of household adversities experienced by children in receipt of care and support from social services; (2) identify typologies of household adversities; and (3) explore how typologies of household adversities differ by family characteristics (demographics, measures of social disadvantage, perinatal and care factors).ResultsWe found evidence for multiple risk factor constellations. The four-class solution suggested four distinct classes of adversities: child disability (50.0%), low adversities (20.3%), family poor health (6.7%) and multiple risks (23.0%). Children in the 'multiple risk' class were significantly more likely to be younger, more deprived and 'looked after' by the local authority compared with those in the 'low adversities' class.ConclusionsGiven the presence of different constellations of household adversities, policies and interventions that address multiple risk factors simultaneously may be more effective and have longer-lasting benefits.
| S-EPMC10946723 | biostudies-literature
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.
| S-EPMC7532840 | biostudies-literature