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Background Young adults in Neither in Employment, Education nor Training (NEET) are at risk of adverse labour market outcomes. Earlier studies often measured NEET status at one time point or compared persistent NEETs with non-NEETs, neglecting other patterns of NEET status. Evidence on early life factors associated with NEET patterns is lacking. This study aims to (i) identify patterns of NEET status over time and (ii) examine whether factors in childhood and adolescence are associated with these patterns. Methods Data were used from 1499 participants of the TRacking Adolescents' Individual Lives Survey (TRAILS), a Dutch prospective cohort study with 15-year follow-up. NEET status was assessed at ages 19, 22 and 26. Socioeconomic status of parents (SES), intelligence and negative life events were measured at age 11, educational attainment at age 26 and mental health problems at ages 11, 13.5 and 16. Data were analyzed using multinomial logistic regression analysis. Results Four NEET patterns were identified: (i) non-NEETs (85.2%), (ii) early NEETs (4.5%), (iii) late NEETs (5.7%) and (iv) persistent NEETs (4.5%). Reporting internalizing problems at age 11 was a risk factor for early and late NEETs [odds ratio (OR) 2.77, 95% confidence interval (CI) 1.16–6.62; OR 5.00, 95% CI 2.22–11.3, respectively]. Low parental SES, lower intelligence scores and negative life events (≥3) were risk factors for persistent NEETs (OR 4.45, 95% CI 2.00–9.91; OR 0.96, 95% CI 0.94–0.98; OR 4.42, 95% CI 1.62–12.08, respectively). Conclusions The results highlight the importance of timing and duration of NEET status and emphasize the need for tailored interventions to prevent specific NEET patterns. [ABSTRACT FROM AUTHOR]

Background and Objectives: Suicide is an intentional attempt to end someone's life that results in death. Suicidality comprises suicidal thoughts, plans, and actions. Knowing the risk factors associated with suicide may help in its reduction. The study's aims were to ascertain the sociodemographic characteristics of suicidal patients and suicidality- associated risk factors. Methods: A retrospective case-control study recruited 60 participants aged between 18 and 53 years within eight months. Sociodemographic characteristics, risk factors associated with suicide attempts among the studied samples such as personal, maltreatment during childhood, community- associated risk factors, and suicide methods used. The data was analyzed through binary logistic regression. Results: In total, there were (26.6%) cases in the age group 18-29; the majority of the recruits were female (38.3%); most of the participants had a university degree (23.33%), and (26.6%) had never married. Regarding their occupational status, most of the patients had paid work, and populated urban areas. Among positive suicide cases, (89.3%) had experienced previous suicide attempts, mental illness; such as depression, was present in (57.1%). About )50% (of the suicidal participants experienced physical abuse and maltreatment during childhood. Binary logistic regression analysis showed that previous suicide attempts, mental illnesses such as depression, job problems or loss, and barriers to health care access P-value< 0.040, 0.008, 0.023, 0.043 had a highly significant association with suicide. Conclusions: There was no association between the sociodemographic characteristics of suicidal and non-suicidal individuals. Individuals with associated characteristics, such as a history of repeated suicide attempts and generalized anxiety disorders, require special consideration. Mental illnesses, such as depression, job loss or problems, a previous suicide attempt, and barriers to health care were the highest risk factors. [ABSTRACT FROM AUTHOR]