Explore the vast range of titles available.

IntroductionPsychiatrists need access to professional resources to care for their patients. In mental health settings, clinical innovations such as a new therapeutic approach, clinical guidelines or new drugs can diffuse more or less, depending on the social capital of these clinicians. The Resource Generator developed by Snijders & Van Der Gaag (2004) measures access to resources within a social network for the general population. It may therefore not capture access to social capital in the professional field of psychiatry.ObjectivesWe aimed to develop and validate the Resource Generator for Psychiatrists and to detect factors influencing the social capital of clinicians.MethodsThe development of the final 11-item questionnaire followed multiple steps. First, the items were selected and adapted by an expert in the sociology of mental health to match the sector of psychiatry. Content validity and detection of important issues or misunderstandings were ensured by cognitive interviews with a panel of 6 clinicians. Each item has a 6-point response scale, rated from 0 to 6. Answers were coded “0” when the respondent did not need a certain resource or it was not applicable to their situation, while answering the closest resource was coded “6”. The online self-completion questionnaire was administered through a link sent by email to all adult psychiatrists and psychiatric residents licensed to work in Belgium. Additional warm contacts were performed for psychiatrists working in ambulatory care. An exploratory factor analysis was conducted. Internal consistency was ensured with Pearson’s correlation, item-total correlation and Cronbach’s alpha. Test-retest reliability was also measured. Multivariable linear regression analysis assessed the association between psychiatrist demographics and the RG-Psy total score.ResultsThe Resource Generator for Psychiatrists questionnaire completed by 152 psychiatrists showed a normal distribution with a mean of 32.5 (SD=12), good test-retest reliability (ICC=0.81), and good total Cronbach’s alpha (0.74). Exploratory factor analysis revealed two main subtypes in psychiatrists’ social capital: “attention and access to advice” and “practical assistance, knowledge and expertise”, with Cronbach’s alpha of 0.62 and 0.7 respectively. Clinicians attending institutional seminars (β=5.5221, p=0.013) and working in multidisciplinary settings such as hospitals (β=4.7448, p=0.023) or a mobile team (β=8.7475, p=0.014) were more likely to have higher social capital.ConclusionsPsychiatrists’ access to professional resources can be reliably measured by a 11-item questionnaire and can be used to test the influence of their professional social capital on different outcomes.Disclosure of InterestNone Declared

Background The relationship between socioeconomic position (SEP) and adolescent physical activity is uncertain, as most evidence is limited to specific settings and a restricted number of SEP indicators. This study aimed to assess the magnitude of socioeconomic differences in adolescent vigorous physical activity (VPA) across various European countries using a wide range of SEP indicators, including family-based (education, family affluence, perceived social standing, parents’ employment, housing tenure) and adolescent-based (academic performance and pocket money) ones. Methods We used data from a survey among 10,510 students aged 14–17 from 50 schools in six European cities: Namur (BE), Tampere (FI), Hannover (DE), Latina (IT), Amersfoort (NL), Coimbra (PT). The questionnaire included socio-demographic characteristics and the amount of time spent in VPA. Results The mean time spent practicing VPA was 60.4 min per day, with lower values for Namur (BE) and Latina (IT), and higher values for Amersfoort (NL). In the multivariable analysis, both categories of SEP indicators (family-based and adolescent based indicators) were independently associated with VPA. For each SEP indicator, lower levels of VPA were recorded in lower socioeconomic groups. In the total sample, each additional category of low SEP was associated with a decrease in mean VPA of about 4 min per day. Conclusions This study showed that across European cities adolescent VPA is positively related to both family-based SEP and adolescents’ own SEP. When analysing socioeconomic differences in adolescent VPA, one should consider the use of multiple indicators of SEP.

BackgroundSocio-economic inequalities in suicide remain substantial and persistent in most European countries. The mechanism driving these inequalities, however, remains obscure. Two causal mechanisms have been attributed varying degrees of importance: low socio-economic status may directly increase the risk of suicide (hereafter ‘causation’) or low socio-economic status and suicide may share confounders (hereafter, ‘confounding’). This paper aims to assess whether educational inequalities in suicide (EIS) are due to causation or to confounding.MethodsThe DEMETRIQ study collected and harmonised register-based data on mortality follow-up of forty population censuses from fifteen Northern, Southern, Western, and Eastern European populations. More than 89,554 suicides were registered over 300 million person-years. Four tests of causation vs confounding were implemented. Test 1: whether a decreasing (increasing) EIS over the lifecycle supports confounding (or causation). Test 2: whether greater (lower) EIS in males than in females supports confounding (or causation). Test 3: At the country level, whether EIS is more related to the Gini income inequality index (causation) or to the proportion of suicides that take place among the younger age group (confounding). Test 4 applied an instrumental variable approach that exploits changes in the legislation on compulsory educational age to instrument educational status. Tests 1 and 2 were performed with multilevel Poisson Regressions (SAS), test 3 with linear regression, and test 4 used two-stage Poisson Regression (STATA).ResultsFor test 1, we found that educational inequalities in suicide decreased over the life cycle. The risk of suicide among the less educated as compared to the more highly educated declined from RR=1.85 (95%CI: 1.6–2.07) in those aged 35–39 to RR=1.27 (95CI%, 1.12–1.44) for those aged 75–79. Test 2 indicated that educational inequalities in suicide were systematic and of greater magnitude in males (all countries, RR=2.51, 95%CI: 2.44–2.58) than in females (all countries RR=1.32, 95%CI: 1.26–1.38). For test 3, EIS decreased with mean age of suicide (std Beta=-0.59, t-test=-5.0) and increased with the Gini coefficient (std beta=0.47, t-test=2.8). Test 4 indicated that there was no association between higher education and suicide.ConclusionWe found stronger support for the confounding explanation than for causation. Educational inequalities in suicide should be addressed by early targeting of vulnerable groups who struggle to complete their education.

Nicotine dependence during adolescence increases the risk of continuing smoking into adulthood. The magnitude of nicotine dependence among adolescents in the European Union (EU) has not been established. We aimed to estimate the number of nicotine dependent 15-year-old adolescents in the EU, and identify high-risk groups. The number of nicotine dependent 15-year-olds in the EU was derived combining: (i) total number of 15-year-olds in the EU (2013 Eurostat), (ii) smoking prevalence among 15-year-olds (2013/2014 HBSC survey) and (iii) proportion of nicotine dependent 15-year-olds in six EU countries (2013 SILNE survey). Logistic regression analyses identified high-risk groups in the SILNE dataset. We estimated 172 636 15-year-olds were moderately to highly nicotine dependent (3.2% of all 15 years old; 35.3% of daily smokers). In the total population, risk of nicotine dependence was higher in males, adolescents with poor academic achievement, and those with smoking parents or friends. Among daily smokers, only lower academic achievement and younger age of smoking onset were associated with nicotine dependence. According to our conservative estimates, more than 172 000 15-year-old EU adolescents were nicotine dependent in 2013. Prevention of smoking initiation, especially among adolescents with poor academic performance, is necessary to prevent a similar number of adolescents getting addicted to nicotine each consecutive year.

Background The COVID-19 pandemic and subsequent restrictions increased the psychological distress of the population while the use of on-site mental health care decreased. The provision of online mental health care was therefore scaled up in many European countries. The extent to which online care can deliver services to all people (horizontal equity) according to their needs (vertical equity) is unknown. This study assessed whether online advice-seeking was related to mental health needs and whether different population subgroups were equally likely to seek advice. Methods A longitudinal, online survey was carried out in Belgium in April, June, and November 2020. 13,150 different individuals participated in at least one study wave. At the end of each wave, information on how to receive help was provided. Psychological distress was measured using the GHQ-12. We used logistic regression to compare the association between psychological distress and online advice-seeking across waves and sociodemographic groups. Results 29% of the respondents sought online advice in April, and one fifth in June and November. The frequency of advice-seeking was associated with higher psychological distress (OR = 1.24, 95% CI:1.22–1.26). Women, young people, respondents with higher education, and respondents with less social support were more likely to seek advice online. Conclusions Online mental health advice seems to achieve vertical equity. Sociodemographic variables were, however, better predictors of psychological distress than advice-seeking. More attention should be paid to older and less well educated men, who were less likely to seek advice. In the longer term, the responsiveness of online services needs to be assessed.

A core question in the debate about how to organise mental healthcare is whether in- and out-patient treatment should be provided by the same (personal continuity) or different psychiatrists (specialisation). The controversial debate drives costly organisational changes in several European countries, which have gone in opposing directions. The existing evidence is based on small and low-quality studies which tend to favour whatever the new experimental organisation is.We compared 1-year clinical outcomes of personal continuity and specialisation in routine care in a large scale study across five European countries. This is a 1-year prospective natural experiment conducted in Belgium, England, Germany, Italy and Poland. In all these countries, both personal continuity and specialisation exist in routine care. Eligible patients were admitted for psychiatric in-patient treatment (18 years of age), and clinically diagnosed with a psychotic, mood or anxiety/somatisation disorder.Outcomes were assessed 1 year after the index admission. The primary outcome was re-hospitalisation and analysed for the full sample and subgroups defined by country, and different socio-demographic and clinical criteria. Secondary outcomes were total number of inpatient days, involuntary re-admissions, adverse events and patients' social situation. Outcomes were compared through mixed regression models in intention-to-treat analyses. The study is registered (ISRCTN40256812). We consecutively recruited 7302 patients; 6369 (87.2%) were followed-up. No statistically significant differences were found in re-hospitalisation, neither overall (adjusted percentages: 38.9% in personal continuity, 37.1% in specialisation; odds ratio = 1.08; confidence interval 0.94-1.25; p = 0.28) nor for any of the considered subgroups. There were no significant differences in any of the secondary outcomes. Whether the same or different psychiatrists provide in- and out-patient treatment appears to have no substantial impact on patient outcomes over a 1-year period. Initiatives to improve long-term outcomes of psychiatric patients may focus on aspects other than the organisation of personal continuity v. specialisation.

Background Adolescents of lower socio-economic status initiate smoking earlier and smoke more frequently than those of higher socio-economic status. Tobacco control policies, such as school tobacco policies, aim to reduce adolescent smoking, but their implementation has been found to vary greatly from one school to another. Such differences in the implementation might therefore contribute to social inequalities in smoking. This study examines whether school tobacco policies are implemented where they are most needed, and how this implementation according to needs has changed over time. Methods Student (n = 18,805) and staff surveys (n = 438) were conducted in 2013 and 2016 in 38 schools from six European cities in six countries. School tobacco policies were measured as a 10-point score taking into account their multidimensionality, and the perceptions of both students and staff. We used concentration curves and indices to measure the inequality in the implementation of these policies depending on the smoking prevalence and on adolescents’ socio-economic status. Results A concentration curve below the perfect equity line indicated a concentration of school tobacco policies where smoking prevalence was lower. Moreover, this inequality was larger in 2016 compared to 2013 (concentration indices of .038 in 2013 and .041 in 2016). On the contrary, a concentration curve overlaying the perfect equity line indicated no inequality in the implementation of these policies depending on adolescents’ socio-economic status (concentration indices of .016 in 2013 and -.013 in 2016). Conclusions School tobacco policies have been developed to reduce adolescent smoking. They, however, seem to be less implemented in schools where they are most needed. This confirms that smoking prevention is still driven by the inverse prevention law. Next to evaluating the impact of such policies on smoking outcomes, research should also focus on their contribution to social inequalities in adolescent smoking. Key messages • School tobacco policies, developed to reduce adolescent smoking, might contribute to social inequalities in smoking. • School tobacco policies are less implemented where they are most needed.

Study objective: There is an increasing body of evidence about socioeconomic inequality in preventive use, mostly for cancer screening. But as far as needs of prevention are unequally distributed, even equal use may not be fair. Moreover, prevention might be unequally used in the same way as health care in general. The objective of the paper is to assess inequity in prevention and to compare socioeconomic inequity in preventive medicine with that in health care. Design: A cross sectional Health Interview Survey was carried out in 1997 by face to face interview and self administered questionnaire. Two types of health care utilisation were considered (contacts with GPs and with specialists) and four preventive care mostly delivered in a GP setting (flu vaccination, cholesterol screening) or in a specialty setting (mammography and pap smear). Setting: Belgium. Participants: A representative sample of 7378 residents aged 25 years and over (participation rate: 61%). Outcome measure: Socioeconomic inequity was measured by the HIwvp index , which is the difference between use inequality and needs inequality. Needs was computed as the expected use by the risk factors or target groups. Main results: There was significant inequity for all medical contacts and preventive medicine. Medical contacts showed inequity favouring the rich for specialist visits and inequity favouring the poor for contacts with GPs. Regarding preventive medicine, inequity was high and favoured the rich for mammography and cervical screening; inequity was lower for flu immunisation and cholesterol screening but still favoured the higher socioeconomic groups. In the general practice setting, inequity in prevention was higher than inequity in health care; in the specialty setting, inequity in prevention was not statistically different from inequity in health care, although it was higher than in the general practice setting. Conclusions: If inequity in preventive medicine is to be lowered, the role of the GP must be fostered and access to specialty medicine increased, especially for cancer screening.