Variations in patterns of involuntary hospitalisation and in legal frameworks: an international comparative study

Background Rising annual incidence of involuntary hospitalisation have been reported in England and some other higher-income countries, but the reasons for this increase are unclear. We aimed to describe the extent of variations in involuntary annual hospitalisation rates between countries, to compare trends over time, and to explore whether variations in legislation, demographics, economics, and health-care provision might be associated with variations in involuntary hospitalisation rates. Methods We compared annual incidence of involuntary hospitalisation between 2008 and 2017 (where available) for 22 countries across Europe, Australia, and New Zealand. We also obtained data on national legislation, demographic and economic factors (gross domestic product [GDP] per capita, prevalence of inequality and poverty, and the percentage of populations who are foreign born, members of ethnic minorities, or living in urban settings), and service characteristics (health-care spending and provision of psychiatric beds and mental health staff). Annual incidence data were obtained from government sources or published peer-reviewed literature. Findings The median rate of involuntary hospitalisation was 106·4 (IQR 58·5 to 150·9) per 100 000 people, with Austria having the highest (282 per 100 000 individuals) and Italy the lowest (14·5 per 100 000 individuals) most recently available rates. We observed no relationship between annual involuntary hospitalisation rates and any characteristics of the legal framework. Higher national rates of involuntary hospitalisation were associated with a larger number of beds (β coefficient 0·65, 95% CI 0·10 to 1·20, p=0·021), higher GDP per capita purchasing power parity (β coefficient 1·84, 0·30 to 3·38, p=0·019), health-care spending per capita (β coefficient 15·92, 3·34 to 28·49, p=0·013), the proportion of foreign-born individuals in the population (β coefficient 7·32, 0·44 to 14·19, p=0·037), and lower absolute poverty (β coefficient −11·5, −22·6 to −0·3, p=0·044). There was no evidence of an association between annual involuntary hospitalisation incidence and any other demographic, economic, or health-care indicator. Interpretation Variations between countries were large and for the most part unexplained. We found a higher annual incidence of involuntary hospitalisation to be associated with a lower rate of absolute poverty, with higher GDP and health-care spending per capita, a higher proportion of foreign-born individuals in a population, and larger numbers of inpatient beds, but limitations in ecological research must be noted, and the associations were weak. Other country-level demographic, economic, and health-care delivery indicators and characteristics of the legislative system appeared to be unrelated to annual involuntary hospitalisation rates. Understanding why involuntary hospitalisation rates vary so much could be advanced through a more fine-grained analysis of the relationships between involuntary hospitalisation and social context, clinical practice, and how legislation is implemented in practice

Mapping review of interventions to reduce the use of restrictive practices in children and young people's institutional settings: The CONTRAST study

Restrictive practices are often used harmfully with children in institutional settings. Interventions to reduce their use do not appear to have been mapped systematically. Using environmental scanning, we conducted a broad-scope mapping review of English language academic databases, websites and social media, using systematic methods. Included records (N = 121) were mostly from the United States and contained details of 82 different interventions. Children's participation was limited. Reporting quality was inconsistent, which undermined claims of effectiveness. Overall, despite a multitude of interventions, evidence is limited. Leaders should consider the evidence, including children's perspectives, before introducing poorly understood interventions into children's settings

Components of interventions to reduce restrictive practices with children and young people in institutional settings: the Contrast systematic mapping review

Background Incidents in which children or young people experience severe distress or harm or cause distress or harm to others occur frequently in children and young people’s institutional settings. These incidents are often managed using restrictive practices, such as restraint, seclusion, sedation or constant observation; however, these also present significant risks of physical and psychological harm to children and young people as well as staff. Numerous interventions aim to reduce the use of restrictive techniques, but research is hampered by limited attention to specific intervention components. The behavior change technique taxonomy may improve reporting by providing a common language for specifying the content and mechanisms of behaviour change. This study aimed to identify, standardise and report the effectiveness of components of interventions to reduce restrictive practices in children and young people’s institutional settings. Objectives To map interventions aimed at reducing restrictive practices in children and young people’s institutional settings internationally, to conduct behaviour change technique analysis of intervention components, to identify process elements, and to explore effectiveness evidence to identify promising behaviour change techniques and compare the results with those found in adult psychiatric inpatient settings in a companion review. Design Systematic mapping review with programme content coding using the behavior change technique taxonomy. Review methods Eleven relevant English-language health and social care research databases 1989–2019 [including Applied Social Sciences Index (ASSIA), Criminal Justice Abstracts, Educational Resources Information Center (ERIC), MEDLINE and PsycInfo®], grey literature and social media were searched during 2019 (updated January 2020). Data extraction, guided by Workgroup for Intervention Development and Evaluation Research (WIDER), Cochrane Library and theory coding scheme recommendations, included intervention characteristics and study design and reporting. Screening and quality appraisal used the Mixed Methods Appraisal Tool. The behavior change technique taxonomy was applied systematically, and interventions were coded for behaviour change technique components. Outcomes data were then related back to these components. Results There were 121 records, including 76 evaluations. Eighty-two interventions, mostly multicomponent, were identified. Evaluation approaches commonly used a non-randomised design. There were no randomised controlled trials. Behaviour change techniques from 14 out of a possible 16 clusters were detected. Four clusters (i.e. goals and planning, antecedents, shaping knowledge, and feedback and monitoring) contained the majority of identified behaviour change techniques and were detected in over half of all interventions. Two clusters (i.e. self-belief and covert learning) contained no identified behaviour change techniques. The most common setting in which behaviour change techniques were found was ‘mental health’. The most common procedure focused on staff training. The two most common behaviour change techniques were instruction on how to perform the behaviour and restructuring the social environment. Promising behaviour change techniques included instruction on how to perform the behaviour, restructuring the social environment, feedback on outcomes of behaviour and problem-solving. Compared with the companion review, service user perspectives were more sparse and there was more interest in trauma-informed approaches. Effectiveness evidence, range of interventions and reporting were broadly similar. Limitations Poor reporting may have prevented detection of some behaviour change techniques. The finding that the evidence was weak restricted the feasibility of examining behaviour change technique effectiveness. Literature searches were restricted to English-language sources. Conclusions This study generated, to our knowledge, the first review of evidence on the content and effectiveness of interventions to reduce restrictive practices in children and young people’s institutional settings. Interventions tend to be complex, reporting is inconsistent and robust evaluation data are limited, but some behaviour change techniques seem promising. Future work Promising behaviour change techniques could be further explored. Better evidence could help address the urgent need for effective strategies. Study registration This study is registered as PROSPERO CRD42019124730. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 10, No. 8. See the NIHR Journals Library website for further project information. </jats:sec

Maximizing the positive and minimizing the negative: Social media data to study youth mental health with informed consent.

Social media usage impacts upon the mental health and wellbeing of young people, yet there is not enough evidence to determine who is affected, how and to what extent. While it has widened and strengthened communication networks for many, the dangers posed to at-risk youth are serious. Social media data offers unique insights into the minute details of a user's online life. Timely consented access to data could offer many opportunities to transform understanding of its effects on mental wellbeing in different contexts. However, limited data access by researchers is preventing such advances from being made. Our multidisciplinary authorship includes a lived experience adviser, academic and practicing psychiatrists, and academic psychology, as well as computational, statistical, and qualitative researchers. In this Perspective article, we propose a framework to support secure and confidential access to social media platform data for research to make progress toward better public mental health

Cohort profile:The Social media, smartphone use and Self-harm in Young People (3S-YP) study-A prospective, observational cohort study of young people in contact with mental health services

Objectives The Social media, Smartphone use and Self-Harm (3S-YP) study is a prospective observational cohort study to investigate the mechanisms underpinning associations between social media and smartphone use and self-harm in a clinical youth sample. We present here a comprehensive description of the cohort from baseline data and an overview of data available from baseline and follow-up assessments. Methods Young people aged 13-25 years were recruited from a mental health trust in England and followed up for 6 months. Self-report data was collected at baseline and monthly during follow- up and linked with electronic health records (EHR) and user-generated data. Findings A total of 362 young people enrolled and provided baseline questionnaire data. Most participants had a history of self-harm according to clinical (n = 295, 81.5%) and broader definitions (n = 296, 81.8%). At baseline, there were high levels of current moderate/severe anxiety (n = 244; 67.4%), depression (n = 255; 70.4%) and sleep disturbance (n = 171; 47.2%). Over half used social media and smartphones after midnight on weekdays (n = 197, 54.4%; n = 215, 59.4%) and weekends (n = 241, 66.6%; n = 263, 72.7%), and half met the cut-off for problematic smartphone use (n = 177; 48.9%). Of the cohort, we have questionnaire data at month 6 from 230 (63.5%), EHR data from 345 (95.3%), social media data from 110 (30.4%) and smartphone data from 48 (13.3%). Conclusion The 3S-YP study is the first prospective study with a clinical youth sample, for whom to investigate the impact of digital technology on youth mental health using novel data linkages. Baseline findings indicate self-harm, anxiety, depression, sleep disturbance and digital technology overuse are prevalent among clinical youth. Future analyses will explore associations between outcomes and exposures over time and compare self-report with user-generated data in this cohort.</p