A social network analysis approach to assess COVID19-related disruption to substance use treatment and informal social interactions among people who use drugs in Scotland.

AIMS: To assess the extent of Coronavirus-related disruption to health and social care treatment and social interactions among people with lived or living experience of substance use in Scotland, and explore potential reasons for variations in disruption. DESIGN: Cross sectional mixed methods interview, incorporating a social network 'egonet interview' approach asking about whether participants had interactions with a range of substance use, health, social care or third sector organisations, or informal social interactions. SETTING: Five Alcohol and Drug Partnership Areas in Scotland. PARTICIPANTS: 57 (42% women) participants were involved in the study, on average 42 years old. MEASUREMENTS: Five-point Likert scale reporting whether interactions with a range of services and people had gotten much better, better, no different (or no change), worse, or much worse since COVID19 and lockdown. Ratings were nested within participants (Individuals provided multiple ratings) and some ratings were also nested within treatment service (services received multiple ratings). The nested structure was accounted for using cross classified ordinal logistic multilevel models. FINDINGS: While the overall average suggested only a slight negative change in interactions (mean rating 2.93), there were substantial variations according to type of interaction, and between individuals. Reported change was more often negative for mental health services (Adjusted OR = 0.93 95% CI 0.17,0.90), and positive for pharmacies (3.03 95% CI 1.36, 5.93). The models found between-participant variation of around 10%, and negligible between-service variation of around 1% in ratings. Ratings didn't vary by individual age or gender but there was variation between areas. CONCLUSIONS: Substance use treatment service adaptations due to COVID19 lockdown led to both positive and negative service user experiences. Social network methods provide an effective way to describe complex system-wide interaction patterns, and to measure variations at the individual, service, and area level.

The Impacts of Benefit Sanctions: A Scoping Review of the Quantitative Research Evidence.

In recent decades, the use of conditionality backed by benefit sanctions for those claiming unemployment and related benefits has become widespread in the social security systems of high-income countries. Critics argue that sanctions may be ineffective in bringing people back to employment or indeed harmful in a range of ways. Existing reviews largely assess the labour market impacts of sanctions but our understanding of the wider impacts is more limited. We report results from a scoping review of the international quantitative research evidence on both labour market and wider impacts of benefit sanctions. Following systematic search and screening, we extract data for 94 studies reporting on 253 outcome measures. We provide a narrative summary, paying attention to the ability of the studies to support causal inference. Despite variation in the evidence base and study designs, we found that labour market studies, covering two thirds of our sample, consistently reported positive impacts for employment but negative impacts for job quality and stability in the longer term, along with increased transitions to non-employment or economic inactivity. Although largely relying on non-experimental designs, wider-outcome studies reported significant associations with increased material hardship and health problems. There was also some evidence that sanctions were associated with increased child maltreatment and poorer child well-being. Lastly, the review highlights the generally poor quality of the evidence base in this area, with few studies employing research methods designed to identify the causal impact of sanctions, especially in relation to wider impacts.

Mental health disorders and adolescent peer relationships.

RATIONALE: Mental health disorders often arise during adolescence, with disruptive behavior disorders and anxiety disorders among the most common. Given the salience of peer relationships during adolescence, and research suggesting that mental health disorders negatively impact social functioning, this study uses novel methodology from social network analysis to uncover the social processes linking disruptive behavior disorders and anxiety disorders with adolescent friendships. In particular, the study focuses on peer withdrawal, peer popularity, and peer homophily in relation to both disorders. METHODS: Data come from 15-year old students in four Scottish secondary schools (N = 602). Diagnoses of disruptive behavior disorders and anxiety disorders were produced using the Diagnostic Interview Schedule for Children, and peer relationship data were obtained through a friendship nomination survey. Exponential random graph models were used to estimate the probability of peer withdrawal, peer popularity, and peer homophily based on each disorder. RESULTS: Results demonstrated that adolescents with disruptive behavior disorders were more popular than their peers without disruptive behavior disorders (OR: 1.47, CI: 1.20, 1.87). Friendship was also more likely between two adolescents both with or both without disruptive behavior disorders (OR: 1.26, CI: 1.07, 1.47), demonstrating peer homophily. There was no evidence that anxiety disorders were related to adolescent peer relationships. CONCLUSIONS: Findings from this study suggest that disruptive behavior disorders may be socially rewarded (e.g., peer popularity) and socially clustered (e.g., homophily), whereas anxiety disorders show no such trends. Thus, intervention efforts must account for the peer social status that may be gained from engaging in disruptive behavior during this developmental period. Further, given that similarity in DBD status is associated with an increased likelihood of friendship, adolescents are likely to be surrounded by peers who reinforce their behaviors.

Cardiology patients' medicines management networks after hospital discharge: A mixed methods analysis of a complex adaptive system.

INTRODUCTION: The complex healthcare system that provides patients with medicines places them at risk when care is transferred between healthcare organisations, for example discharge from hospital. Consequently, understanding and improving medicines management, particularly at care transfers, is a priority. OBJECTIVES: This study aimed to explore the medicines management system as patients experience it and determine differences in the patient-perceived importance of people in the system. METHODS: We used a Social Network Analysis framework, collecting ego-net data about the importance of people patients had contact with concerning their medicines after hospital discharge. Single- and multi-level logistic regression models of patients' networks were constructed, and model residuals were explored at the patient level. This enabled us to identify patients' networks with support tie patterns different from the general patterns suggested by the model results. Qualitative data for those patients were then analysed to understand their differing experiences. RESULTS: Networks comprised clinical and administrative healthcare staff and friends and family members. Networks were highly individual and the perceived importance of alters varied both within and between patients. Ties to spouses were significantly more likely to be rated as highly important and ties to community pharmacy staff (other than pharmacists) and to GP receptionists were less likely to be highly rated. Patients with low-value medicines management networks described having limited information about their medicines and a lack of understanding or help. Patients with high-value networks described appreciating support and having confidence in staff. CONCLUSIONS: Patients experienced medicines management as individual systems within which they interacted with healthcare staff and informal support to manage their treatment. Multilevel models indicated that there are unexplained variables impacting on patients' assessments of their medicines management networks. Qualitative exploration of the model residuals can offer an understanding of networks that do not have the typical range of support ties.

Ethnic differences in women's use of mental health services: do social networks play a role? Findings from a national survey.

OBJECTIVES: The reasons for ethnic differences in women's mental health service use in England remain unclear. The aims of this study were to ascertain: ethnic differences in women's usage of mental health services, if social networks are independently associated with service use, and if the association between women's social networks and service use varies between ethnic groups. DESIGN: Logistic regression modelling of nationally representative data from the Ethnic Minority Psychiatric Illness Rates in the Community (EMPIRIC) survey conducted in England. The analytic sample (2260 women, aged 16-74 years) was drawn from the representative subsample of 2340 women in EMPIRIC for whom data on mental health services, and social networks were available. RESULTS: Pakistani and Bangladeshi women were less likely than White women to have used mental health services (Pakistani OR = 0.23, CI = 0.08-0.65, p = .005; Bangladeshi OR = 0.25, CI = 0.07-0.86, p = .027). Frequent contact with relatives reduced mental health service use (OR = 0.45, CI = 0.23-0.89, p = .023). An increase in perceived inadequate support in women's close networks was associated with increased odds of using mental health services (OR = 1.91, CI = 1.11-3.27, p = .019). The influence of social networks on mental health service use did not differ between ethnic groups. CONCLUSIONS: The differential treatment of women from Pakistani and Bangladeshi ethnic groups in primary care settings could be a possible reason for the observed differences in mental health service use.

Pakistani women's use of mental health services and the role of social networks: a systematic review of quantitative and qualitative research.

Pakistani women in the UK are an at-risk group with high levels of mental health problems, but low levels of mental health service use. However, the rates of service use for Pakistani women are unclear, partly because research with South Asian women has been incorrectly generalised to Pakistani women. Further, this research has been largely undertaken within an individualistic paradigm, with little consideration of patients' social networks, and how these may drive decisions to seek help. This systematic review aimed to clarify usage rates, and describe the nature of Pakistani women's social networks and how they may influence mental health service use. Ten journal databases (ASSIA, CINAHL Plus, EMBASE, HMIC, IBSS, MEDLINE, PsycINFO, Social Sciences Abstracts, Social Science Citation Index and Sociological Abstracts) and six sources of grey literature were searched for studies published between 1960 and the end of March 2014. Twenty-one studies met inclusion criteria. Ten studies (quantitative) reported on inpatient or outpatient service use between ethnic groups. Seven studies (four quantitative, three qualitative) investigated the nature of social networks, and four studies (qualitative) commented on how social networks were involved in accessing mental health services. Pakistani women were less likely than white (British) women to use most specialist mental health services. No difference was found between Pakistani and white women for the consultation of general practitioners for mental health problems. Pakistani women's networks displayed high levels of stigmatising attitudes towards mental health problems and mental health services, which acted as a deterrent to seeking help. No studies were found which compared stigma in networks between Pakistani women and women of other ethnic groups. Pakistani women are at a considerable disadvantage in gaining access to and using statutory mental health services, compared with white women; this, in part, is due to negative attitudes to mental health problems evident in social support networks.

Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula, in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

Multiple-membership multiple-classification models for social network and group dependences.

The social network literature on network dependences has largely ignored other sources of dependence, such as the school that a student attends, or the area in which an individual lives. The multilevel modelling literature on school and area dependences has, in turn, largely ignored social networks. To bridge this divide, a multiple-membership multiple-classification modelling approach for jointly investigating social network and group dependences is presented. This allows social network and group dependences on individual responses to be investigated and compared. The approach is used to analyse a subsample of the Adolescent Health Study data set from the USA, where the response variable of interest is individual level educational attainment, and the three individual level covariates are sex, ethnic group and age. Individual, network, school and area dependences are accounted for in the analysis. The network dependences can be accounted for by including the network as a classification in the model, using various network configurations, such as ego-nets and cliques. The results suggest that ignoring the network affects the estimates of variation for the classifications that are included in the random part of the model (school, area and individual), as well as having some influence on the point estimates and standard errors of the estimates of regression coefficients for covariates in the fixed part of the model. From a substantive perspective, this approach provides a flexible and practical way of investigating variation in an individual level response due to social network dependences, and estimating the share of variation of an individual response for network, school and area classifications.