NEET status among young Greeks: Association with mental health and substance use

Basta, Maria; Karakonstantis, Stamatis; Koutra, Katerina; Dafermos, Vassilis; Papargiris, Antonis; Drakaki, Maria; Tzagkarakis, Stylianos Ioannis; Vgontzas, Alexandros N.; Simos, Panagiotis G.; Papadakis, Nikos

doi:10.1016/j.jad.2019.04.095

Cited by 23 publications

(19 citation statements)

References 37 publications

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“…2 presents forest plot by each type of problem. The evidence most consistently pointed to an association between NEET and symptoms of mood disorders [ 12 , 14 , 17 , 38 , 40 , 41 ] ( k = 6 non-overlapping studies; OR 1.43, CI 1.21–1.70); behavioural disorders [ 12 , 14 , 19 , 42 – 44 ] ( k = 6; OR 1.49, CI 1.21–1.85); cannabis use problems [ 14 , 17 , 38 , 40 , 44 , 45 ] ( k = 6; OR 1.62, CI 1.07–2.46); drug use problems [ 12 , 14 , 19 , 40 , 46 ] ( k = 5; OR 1.99, CI 1.19–3.31); any psychiatric disorder [ 12 , 18 , 44 ] ( k = 3; OR 1.72, CI 1.37–2.16); and suicidal behaviours [ 12 , 14 , 18 , 40 ] (k = 4; OR 2.84, CI 2.04–3.95).…”

Section: Resultsmentioning

confidence: 99%

“…The evidence was more mixed—with fewer than 50% of non-overlapping studies reporting a significant finding—for NEET status being associated with anxiety disorders [ 12 , 14 , 18 , 40 , 46 ] ( k = 5 non-overlapping studies; OR 1.55, CI 1.07–2.24); alcohol use problems ( k = 5; OR 1.28, CI 1.12–1.46); and psychological distress ( k = 7; OR 1.10, CI 1.01–1.21). Results were similar when we excluded low quality studies.…”

Section: Resultsmentioning

confidence: 99%

“…Six studies conducted gender-stratified analysis [ 19 , 20 , 42 , 46 , 49 , 50 ]. In Bania et al [ 42 ], conduct problems at age 15–16 predicted becoming NEET 9 years later among men (OR 1.17, CI 1.07–1.28) and women (OR 1.25, CI 1.17–1.33), while emotional problems were associated with lower odds of becoming NEET in men (OR 0.88, CI 0.81–0.97), but not women (OR 1.04, CI 0.97–1.11).…”

Section: Resultsmentioning

confidence: 99%

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The mental health of young people who are not in education, employment, or training: a systematic review and meta-analysis

Gariépy

Danna

Hawke

et al. 2021

Soc Psychiatry Psychiatr Epidemiol

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Purpose There 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. Methods We 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. Results We 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. Conclusion Our 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.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The mental health of young people who are not in education, employment, or training: a systematic review and meta-analysis

Gariépy

Danna

Hawke

et al. 2021

Soc Psychiatry Psychiatr Epidemiol

View full text Add to dashboard Cite

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“…Some researchers also reported a strong relationship between disease and NEET. For example, Gladwell et al [50], Basta et al [51], Robertson [52], Iyer et al [53] and Goldman-Mellor et al [54] concluded that the presence of physical and mental disorders increases the NEET problem. In addition to the aforementioned studies, Baggio et al [55] and Henderson et al [56] identified that young people using drugs are more likely to be included in the NEET group.…”

Section: Literature Reviewmentioning

confidence: 99%

Strategic Mapping of Youth Unemployment With Interval-Valued Intuitionistic Hesitant Fuzzy DEMATEL Based on 2-Tuple Linguistic Values

et al. 2020

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This study aims to identify the factors that affect youth unemployment in emerging countries. For this purpose, 3 dimensions and 12 criteria are selected as a result of literature review. The analysis process has 3 different steps. Firstly, interval-valued intuitionistic fuzzy sets are created with the help of 2-tuple linguistic data. Additionally, relation matrix is generated by considering these fuzzy sets. In the second process, defuzzification process is occurred. Finally, the dimensions and criteria are weighted with Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach by using defuzzified data sets. The findings indicate that economic and social inequalities play the most significant role for youth unemployment in emerging countries. On the other side, it is also identified that economic crisis and insufficient education conditions are also important issues which lead to youth unemployment in these countries. Hence, it is recommended that governments should implement fair tax management practices in these countries to minimize economic and social inequalities. Furthermore, education conditions should be improved in the countries. In this framework, an effective education plan can be designed by cooperating with companies in the industry. Thus, labor needs in industry can be identified and education system can be designed according to the needs in the market. With the help of these implementations, it can be much easier for young people to find a job. INDEX TERMS2-tuple linguistic values, interval-valued intuitionistic fuzzy environment, fuzzy DEMATEL, NEET, emerging economies.

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“…There are several key factors associated with a higher probability of becoming a NEET. These include: personal characteristics, such as belonging to an older age group, being a female and/or being part of an ethnic and religious minority; low educational level or its poor quality in terms of provision; exclusion or suspension from school; migrant status; poor physical or mental health; disability; early marriage and early childbirth; having experienced unemployment; and, having unemployed friends (Caroleo et al, 2017;Basta et al, 2019;Quintano et al, 2018;Vancea & Utzet, 2018;Salvà-Mut et al, 2018;Ciccarelli & Fabrizi, 2017;Tamesberger & Bacher, 2014). The NEETs rate varies significantly across European countries (and sometimes also within the countries themselves), where identical personal characteristics can easily correspond to starkly different propensities to being NEET (Caroleo et al, 2020).…”

Section: Socio-economic Risk Factorsmentioning

confidence: 99%

Manual for the classification of intervention best-practices with rural NEETs

Bojnec¹,

Erdoğan²,

Fernandes‐Jesus³

et al. 2020

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targeting rural NEETs. In my opinion, this is the most outstanding contribution of this manual, and also an original one, considering that to date no other efforts have been made with the intention of developing a grid of how to describe interventions dealing with rural NEETs. This manual offers, therefore, valuable contributions for upcoming research efforts within and beyond RNYN, including: (a) a complete methodological framework for future case stu-dies; (b) practical tools to conduct field research than can be combined with many different methodological approaches (qualitative, mixed-methods, etc.); and, (c) strategic criteria for conducting research in complex settings such as community-based programs. In addition, this manual sets the necessary conditions to present evidence-based conclusions about programs targeting rural NEETs, further aiding policy-makers to opt for solutions that clearly produce better results. This manual would not have been possible without the efforts and best knowledge from its editorial team. Therefore, as the Chair of RNYN, but also in a more personal note, I would like to thank Claudia Petrescu, Emre Erdogan and Paul Flynn for the impeccable and rigorous way in which they conducted all the process. I would also like to thank the Working Group 2 mem-bers traversing many countries who contributed to this document.

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NEET status among young Greeks: Association with mental health and substance use

Cited by 23 publications

References 37 publications

The mental health of young people who are not in education, employment, or training: a systematic review and meta-analysis

The mental health of young people who are not in education, employment, or training: a systematic review and meta-analysis

Strategic Mapping of Youth Unemployment With Interval-Valued Intuitionistic Hesitant Fuzzy DEMATEL Based on 2-Tuple Linguistic Values

Manual for the classification of intervention best-practices with rural NEETs

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