How adolescent health influences education and employment: investigating longitudinal associations and mechanisms

<h3>Background</h3> Education is recognised as a strong determinant of health. Yet there is increasing concern that health in adolescence may also influence educational attainments and future life chances. We examined...

PurposeThere are increasing concerns about the intersection between NEET (not in education, employment, or training) status and youth mental ill-health and substance use. However, findings are inconsistent and differ across types of problems. This is the first systematic review and meta-analysis (PROSPERO-CRD42018087446) on the association between NEET status and youth mental health and substance use problems.MethodsWe searched Medline, EMBASE, Web of Science, ERIC, PsycINFO, and ProQuest Dissertations and Theses (1999–2020). Two reviewers extracted data and appraised study quality using a modified Newcastle–Ottawa Scale. We ran robust variance estimation random-effects models for associations between NEET and aggregate groups of mental ill-health and substance use measures; conventional random-effects models for associations with individual mental/substance use problems; and subgroup analyses to explore heterogeneity.ResultsWe identified 24 studies from 6,120 references. NEET status was associated with aggregate groups of mental ill-health (OR 1.28, CI 1.06–1.54), substance use problems (OR 1.43, CI 1.08–1.89), and combined mental ill-health and substance use measures (OR 1.38, CI 1.15–1.64). Each disaggregated measure was associated with NEET status [mood (OR 1.43, CI 1.21–1.70), anxiety (OR 1.55, CI 1.07–2.24), behaviour problems (OR 1.49, CI 1.21–1.85), alcohol use (OR 1.28, CI 1.24–1.46), cannabis use (OR 1.62, CI 1.07–2.46), drug use (OR 1.99, CI 1.19–3.31), suicidality (OR 2.84, CI 2.04–3.95); and psychological distress (OR 1.10, CI 1.01–1.21)]. Longitudinal data indicated that aggregate measures of mental health problems and of mental health and substance use problems (combined) predicted being NEET later, while evidence for the inverse relationship was equivocal and sparse.ConclusionOur review provides evidence for meaningful, significant associations between youth mental health and substance use problems and being NEET. We, therefore, advocate for mental ill-health prevention and early intervention and integrating vocational supports in youth mental healthcare.

Beating the Odds: Impact of the Economic Recession on Young People in the UK

BackgroundYoung people who are not in education, employment or training (NEET) are at an increased risk of long-term social and economic disadvantage. While previous research has linked various risk factors and individual characteristics to NEET status, evidence on the cumulative impact of early-life exposure to childhood adversity in the UK remains limited. We therefore aimed to investigate the association between trajectories of poverty and family adversity and NEET status in late adolescence, and to characterise socioeconomic differences, including household income and maternal education by NEET status.MethodsWe analysed longitudinal data on 8368 participants from the UK Millennium Cohort Study. Using a group-based multi-trajectory modelling approach, we identified six distinct exposure trajectories of poverty and family adversity (ie, low poverty and adversity, persistent poverty, persistent poor parental mental health, persistent parental alcohol use, persistent domestic violence and abuse, and persistent poverty and poor parental mental health) from aged 9 months to 14 years. NEET status was assessed at age 17. Adjusted ORs (aORs) and 95% CIs were estimated using logistic regression models. Population attributable fractions were calculated to estimate the proportion of NEET cases attributable to childhood poverty and family adversity.ResultsOverall, 3.5% of participants were NEET at age 17 years. NEET status was more prevalent among young people from socially disadvantaged backgrounds than their peers. Exposure to persistent family childhood adversities was associated with greater likelihood of being NEET. Young people exposed to both persistent poverty and poor parental mental health throughout childhood (9 months to 14 years) had five times greater odds of being NEET (aOR 5.0; 95% CI 3.4 to 7.5) compared with those in low poverty and adversity. An estimated 52.9% (95% CI 41.1% to 61.7%) of NEET cases were attributable to persistent exposure to poverty and family adversity.ConclusionFamily childhood adversities, particularly household poverty and poor parental mental health, are strongly associated with an increased risk of being NEET on transition to adulthood. Interventions that address early-life socioeconomic disadvantage and family functioning may be critical for preventing NEET and mitigating its long-term social and economic consequences.

This article examines the transition from compulsory school to education and work for children of immigrants and native Danes by focusing on NEET (Not in Education, Employment or Training) status. Using administrative register data, I first examined the overrepresentation of children of immigrants in the NEET group three years after completion of compulsory school. I then analysed: (a) whether differences in family background and grades can explain this overrepresentation and (b) whether NEET status during this period is associated with a high risk of NEET status four years later (i.e., seven years after compulsory school completion). My results show higher NEET rates for children of immigrants than for native Danes. Regression analysis of three year groups suggests, unfavourable family characteristics explain the higher probability of NEET status among children of immigrants in two of these groups. NEET status in the three-year period after school completion is associated with higher risk of NEET status four years later for both children of immigrants and native Danes.

<h3>Aims</h3> Education is recognised as a social determinant of health with poor academic attainment linked to poorer health. Reverse causal pathways have been largely overlooked. Likewise, exploration of risk factors for youth unemployment have rarely examined the impact of poor adolescent health. This study longitudinally examines causal pathways from poor adolescent health to low academic attainment and unemployment in young adulthood. <h3>Methods</h3> We used nationally-representative data from the Longitudinal Study of Young People in England (LSYPE; Wave 1, age 13 N=15,770). Having a chronic condition, poor mental health and poor self-reported general health were assessed between ages 13 and 15. Outcome variables included poor academic performance (non-attainment of expected academic proficiency based on mandated school examinations) at age 16 and NEET status (not in education, employment or training) at age 19. We examined associations between health and subsequent outcomes, and conducted mediator analyses to assess the proportion of the association attributable to hypothesised mediators including school absences, classroom behaviour, truancy, social exclusion, health behaviours and psychological distress. <h3>Results</h3> Poor mental and general health and long-term conditions predicted low educational attainment at age 16. Poor mental health and poor general health (but not long-term conditions) predicted unemployment. Social exclusion was a consistent mediating variable. Long-term absences mediated associations between general health and mental health and later outcomes whereas school behaviour, truancy and substance use were significant mediators for general health and mental health. <h3>Conclusion</h3> Poor adolescent health disrupts educational and employment pathways. Due to the economic and social costs of educational underachievement and unemployment, policy interventions should focus on improving outcomes for unhealthy adolescents.

BackgroundResilience is broadly defined as the ability to maintain or regain functioning in the face of adversity. Recent work to harmonise the quantification and definition of resilience quantifies resilience as the residual variance in psychosocial functioning that remains after accounting for adversity exposure. However, there have been no published studies that have formally investigated the validity of this approach. Considering this, we examine the construct and predictive validity of the residuals approach using participants from the Avon Longitudinal Study of Parents and Children (ALSPAC), a multigenerational, longitudinal cohort study.MethodsWe regressed exposures of adolescent adversity on adolescent psychopathology scores using the Strength and Difficulties Questionnaire and obtained the residual variance. We investigated construct validity by analysing whether previously identified demographic and resilience factors significantly predicted resilience. Predictive validity of resilience was investigated by comparing the predictive power of resilience with other determinants of psychosocial functioning on two developmental outcomes: depressive symptoms at 18 years, measured by the Short Moods and Feelings Questionnaire, and NEET (Not in Employment, Education or Training) status at 17 and 23 years. The associations between depressive symptoms at 18, resilience, ACEs and covariates were tested using multiple linear regression. NEET status at 17 and 23 were run as separate binary multiple logistic regression models to test associations with resilience and known demographics previously associated with NEET status.ResultsSeven previously identified protective factors, including self-esteem, positive sibling relationship, temperament, and positive perception of school, significantly predicted resilience to adolescent psychopathology, thus providing strong construct validity. Resilience significantly predicted a reduction in depressive symptoms at 18 years, and significantly decreased the likelihood of having NEET status at both 17 years and 23 years, even after taking into account early childhood adversity and other risk factors. None of the socioeconomic factors were significantly associated with resilience.ConclusionsOur study demonstrates that the residuals method of operationalising resilience has good construct and predictive validity yet recommend replication studies. It has the potential to advance research into the mechanisms and modifiability of resilience.Trial Registration: Not applicable.

This study delves into the complex issue of NEET (Not in Employment, Education, or Training) status in Italy, using Latent Class Analysis (LCA) to identify distinct profiles within this heterogeneous group. The research, based on a survey of 970 young Italian NEETs, goes beyond broad categorizations to explore the socio-demographic, economic, and motivational factors that contribute to their situations. Six distinct classes of NEETs were identified, each with unique characteristics, including “Affluent Rural Caregivers in Northern Italy,” “Young Educated Unemployed,” “Long-Term NEETs in Southern Italy,” “Disadvantaged Caregivers in Southern Italy,” “Disadvantaged Rural Men in Northern Italy,” and “Affluent Discouraged NEETs”. The study investigates the relationship of these profiles with Public Employment Services (PES), revealing different motivations for seeking assistance and varied willingness to accept employment conditions such as relocation or temporary work. Significant associations were found between NEET class and the motivation for economic support, willingness to move abroad or within Italy, and acceptance of part-time or temporary work. The findings emphasize the need for tailored interventions that address the specific needs and barriers of each NEET subgroup, rather than a one-size-fits-all approach. The research highlights the complex interplay of geographic, economic, educational, and gender factors in shaping NEET status in Italy.

There has been significant recent research and policy interest in issues of young people's occupational aspirations, transitions to employment and the antecedents of NEET (not in employment, education or training) status. Many have argued that changes to the youth labour market over the past 30 years have led to transitions to work becoming more individualised, complex and troublesome for many, particularly those from poorer backgrounds. However, little research has examined the connection between early uncertainty or misalignment in occupational aspirations and entry into NEET status. This paper draws on the British Cohort Study to investigate these issues, and finds that young people with uncertain occupational aspirations or ones misaligned with their educational expectations are considerably more likely to become NEET by age 18. Uncertainty and misalignment are both more widespread and more detrimental for those from poorer backgrounds. These findings are discussed in the context of recent research and debates on emerging adulthood and the youth labour market.

Understanding the Health and Well-Being of Early Adolescents Throughout the World: Findings From the 2017–2018 Survey of Health Behavior in School-Aged Children

This systematic review and meta-analysis examines the factors contributing to NEET (Not in Education, Employment, or Training) status among youth. We identify 43 studies that meet our inclusion criteria in Scopus, PsycINFO, ERIC, British Education Index, Social Science Citation Index, Conference Proceedings Index, IEEE Xplore, SpringerLink, and ScienceDirect, covering the period from 2010 to October 2023. We find significant associations between NEET status and various demographic, familial, educational, socio-economic, and health-related factors. Gender-specific disparities and evolving trends within distinct demographic cohorts are revealed. Our findings highlight that NEET is associated with a higher suicide risk (OR = 2.8, 1.8–3.8), criminal behaviour (OR = 2.06, 1.47–2.65), and unemployment experience (OR = 1.98, 0.72–3.25), while higher education levels (OR = 0.81, 0.67–0.95) act as a protective factor. These findings underscore the urgent need for comprehensive interventions tailored to the challenges faced by NEET youth. Future research should explore these relationships further to inform policy and practice effectively.

Knowledge regarding the complexity of life circumstances of children exposed to parental substance use disorder may be important to reduce negative consequences related to parental substance use disorder, such as NEET status. Welford, Danielsson & Manhica [1] have reported that exposure to parental substance use disorder (SUD) before the age of 17 years is associated with increased risk of being not in education, employment or training (NEET) during early adulthood. This conclusion is founded upon register-based analyses, adjusted for birth year, domicile, origin, psychiatric diagnosis, household income and parental psychiatric diagnosis. This is an acknowledged analysis strategy we have often applied ourselves. However, are we at risk of losing information regarding complexity on our path to reduce bias? Results from the study also indicated that most children of parents with SUD had experienced multiple difficult life circumstances, including low income and parental psychiatric diagnosis. In line with these results, other studies have reported that offspring of parents with alcohol use disorders are more likely to have multiple adverse experiences [2, 3]. However, by adjusting for factors that may be causally related to NEET status we can lose sight of the complexity of difficult childhood circumstances, an understanding of which is important in order to tailor interventions to groups at risk. Studies within the addiction field could benefit from research within the area of adverse childhood experiences (ACE), which have shown a cumulative negative effect on a range of adverse outcomes related to the total load of adverse life experiences [4-6]. The adverse life circumstances described in the study from Welford et al., such as parental SUD, parental psychiatric diagnosis and low income, are most probably long-lasting characteristics of the childhood situation. It is therefore likely that the total load of life difficulties matters when it comes to affecting how life develops for these children, and that life difficulties often are inter-related [7]. In line with results from the study of Welford et al., previous studies have reported that adverse childhood experiences, including household substance disorders, are socially patterned [8, 9]. Individuals with low socio-economic statuses report more ACEs [8]; however, ACEs are also thought to impact adult income, education attainment and employment [10]. In the study by Welford et al., four out of 10 exposed to parental SUD were in the lowest income quintile at age 16 years, which is more than twice as many as those who were not exposed to parental SUD. Thus, in addition to growing up within a family environment that may be dysfunctional due to parental SUD [2], life opportunities may also be limited by household income. Low household income may be a result of low parental education, unemployment or other conditions that may cause economic instability. Welford et al. account for this by adjusting for income; however, some of the complexity of children growing up with multiple life difficulties may be lost. The study presents inadequate parenting due to parental SUD as a possible mechanism as to why children with parental SUD have an increased risk of becoming NEET. However, low parental education or marginalization within the labour market among parents with SUD could also limit parental resources in supporting their children academically. Adjusting analyses for income may be insufficient to account for these possible factors. Further, the majority of children exposed to parental SUD were also exposed to other parental psychiatric diagnoses (80%), compared to a very small minority among children not exposed to parental SUD (2.3%). This also contributes to a heavier life load on these children, making it understandable that educational attainment may be difficult to pursue. Investigating the complexity of the situation of children exposed to parental SUD is essential for the development of multi-faceted interventions that could reduce negative consequences of parental SUD, such as NEET status. Interventions should be tailored according to the complexity of the situation for each youth and address multiple systems such as school, family and leisure time and social activities. They could, for example, include help with homework or other educational supportive interventions, treatment related to parental SUD and/or mental illness, parenting programmes to support the development of parenting skills, work or educational opportunities to parents to improve family economy, therapeutic support or group therapy to children to deal with adverse consequences of living with parents who have SUD and/or mental illness and financial support specifically aimed at inclusion of the children in leisure activities. Such broad approaches would probably also be beneficial linked to other adverse outcomes related to parental SUD than NEET status. None. None. Siri Haugland: Conceptualization. Tonje Stea: Conceptualization.

Internalising and externalising problems during adolescence and the subsequent likelihood of being Not in Employment, Education or Training (NEET) among males and females: The mediating role of school performance

BackgroundThe high level of young people not in education, employment or training (NEET) has been an important long-standing issue in Scotland. The experience of being NEET has long term detrimental effects.&#x0D; Main AimIdentify risk factors that could inform interventions aimed at reducing the number of NEETs.&#x0D; MethodsWe use the Scottish Longitudinal Study (SLS) which provides a 5.3% representative sample of Scotland’s population based around the Censuses of 1991, 2001 and 2011. The SLS includes Vital Event data, Census data for the SLS sample and also those living in the same household and, since 2007, school census data.&#x0D; This allows us to study two cohorts of 16-19 year olds (the ages used in Scotland when considering NEET status) over a period of 10 years:&#x0D; &#x0D; those 6-9 years old at the time of the 1991 Census to the 2001 Census when they were 16-19 years old&#x0D; those 6-9 years old at the time of the 2001 Census to the 2011 Census when they were 16-19 years old&#x0D; &#x0D; We used logistic regression to investigate whether NEET status is associated with individual, family and household characteristics measured 10 years previously and later data including school qualification, school behaviour, areal characteristics and teenage pregnancy.&#x0D; ResultsThese analyses found several factors were associated with the likelihood of being NEET for both cohorts, including having no qualifications, teenage pregnancy and living in an area where there was a relatively high level of NEETs (100% census data). For the later cohort, school census data were available and school behaviour were important factors, whereas household characteristics at childhood were important factors for the earlier cohort.&#x0D; ConclusionA number of factors are associated with NEET but those closer in time to the NEET ages of 16-19 appear to be more important than childhood factors.

Adolescents and risks: Why not change our paradigm?