Abstract
The causes and effects of being “not in education, employment, or training (NEET)” differ according to countries, regions, and even individuals. In this study, the relationship between the causes of young people being NEET and the effects of being NEET is examined on young people in Turkey. The data and scales of cause and effect that have high validity and reliability coefficients were used from in-person field research conducted with 3158 NEET young people by Istanbul University between September and December 2020 in Turkey. The influence of the causes of being NEET scale on the effects of being NEET scale was analyzed by the multivariable regression method. As a result of the analysis, it was determined that the effects of the individual, familial, educational, environmental, and labor market dimensions of the causes of being NEET scale on the effects of being NEET scale were significant.
1. Introduction
Labor market policies that have hitherto predominantly focused on youth unemployment have been expanded to encompass young people who are not in education or employment. This concept, which is defined as “Not in Education, Employment, or Training” (NEET), includes unemployed youth, yet contains significant differences from the definition of employment []. The NEET status is defined as being out of the education system, training, and employment, and it represents a much wider group due to the fact that it also involves young people who have the potential to move into the labor market but remain outside the workforce [].
The state of being NEET refers not only to the condition of being unemployed and/or out of the workforce but also to the state of not being included in any official or unofficial education and training process. Within this framework, why the young are in this state and what sort of internal and external influences affect being in such conditions need to be examined. The research by Şahin et al. (2021), titled “A Profile Research on the Youth in Turkey who are “Not in Education, Employment, or Training” (NEET)”, analyzed the reasons for and influences of the NEET status of young people and developed the scales that are related to “the causes of being NEET” and “the effects of being NEET” and whose validity and reliability coefficients are at high levels [].
In most of the empirical studies examined in the literature review, the NEET variable is analyzed as a dependent variable using logistic models and based on the determiners of being NEET. When the research designs are taken into account, it is observed that they have not analyzed the causes or effects of being NEET as a whole. This study examines the reasons for and results of individuals’ NEET status within a holistic design by means of dimensioning. While qualitative research aimed at NEET individuals has been conducted in most studies, the determining factors and the results of being NEET were turned into a scale in this research. The causes of being NEET scale is composed of the dimensions of “education”, “individual”, “family”, “environment”, and “labor market” (29 items in total) (see Table A1). Gender [], age [], health status [], personal features [], and income level [] factors define the individual causes for being NEET in the literature. The educational level of parents [], family structure and household size [], family income level [], and marital status of individuals [] are the factors that define the familial causes for being NEET in the literature. Educational level and academic success [], dropping out of school early [], and education–labor market incompatibility [] are the factors of the educational causes for being NEET in the literature. Social environment factors [], the disadvantages of residential areas [], poverty [], and economic crises [] are the factors that define the environmental causes for being NEET in the literature. Labor market regulations [], discrimination in the labor market [], and unemployment and work (in)experience [] are the factors that define the labor-market-related causes for being NEET in the literature.
The effects of being NEET scale, on the other hand, consists of “family”, “individual”, “environment”, and “political approach” (35 items in total) (see Table A2). The factors family relations [] and a decrease in the rates of marriage and birth [] define the family effects of being NEET in the literature. The effects on life satisfaction [], effects on life quality [], effects on physical and mental health [], addiction [], and revenue loss [] are the factors that define the individual effects of being NEET in the literature. Social exclusion and inadaptability [], impoverishment [], and migration intent [] are factors that define the environmental effects of being NEET in the literature. Low political participation and unconcern [], and insufficient evaluation of the labor market and educational policies [] are the factors that define the political approach effects of being NEET in the literature.
In this study, the relationship between the dimensions of “the causes of being NEET” scale and “the effects of being NETT” scale is evaluated based on a correlation test. How the dimensions of “the causes of being NEET” scale influence “the effects of being NETT” scale and its dimensions, on the other hand, is determined through a multiple regression analysis as an advanced analysis type. Within this scope of this study, the scale of “the causes of being NEET” is considered an independent variable while the scale of “the effects of being NEET” is considered a dependent variable under four different models, and the fundamental hypotheses are developed accordingly.
2. Literature Review
Empirical findings from the literature review on the causes and effects of being NEET are shown in Table 1.

Table 1.
Literature review on the causes and effects of being NEET.
Table 1 demonstrates how the determinants of being NEET shape the majority of the empirical literature on NEET. In accordance with this, statistical method preferences are based on logistic regression analyses. In this respect, the originality of this study’s method (multiple linear regression testing for hypotheses), according to the literature, is also noteworthy.
3. Materials and Methods
3.1. Dataset and Sample
This study discusses the relationship between “the causes of being NEET” and “the effects of being NEET”, which has been developed in accordance with the results of “A Profile Research on the Youth in Turkey who are “Not in Education, Employment, or Training” (NEET)”, conducted by Şahin and friends [] in September–December 2020. The related research was performed in 26 cities belonging to 26 subzones within the frame of Turkish Nomenclature of Units for Territorial Statistics (IBBS)—II. The target population of the study is the 15–29 age-range NEET youth throughout Turkey. The sample distribution was determined at 3300 for the purpose of acquiring strong analyses on a regional basis, and depending on the NEET rate (29.5%) announced by EUROSTAT, the number of surveys was distributed in accordance with the 15–29 age group city populations. In total, 3158 young individuals with NEET status were interviewed on the survey in question. While ethics committee approval was not required during the periods in which the field research was conducted in Turkey, research data were used with permission given by the research owner institution, the Turkish Republic Ministry of Youth and Sports, and the executive institution, Istanbul University Rectorate. In addition, with the supervision of the research institution, informed consent was obtained from all subjects involved in the study [].
3.2. The Causes of Being NEET Scale and the Effects of Being NEET Scale
At the end of “the causes of being NEET scale” reliability analysis, the general reliability value of the data (Cronbach alpha) was identified as 0.897. This result indicates that the questions that form the reasons have reliability at a high level. The alpha numbers obtained through the split-half reliability method were detected as 0.869 and 0.776, respectively. The Spearman Brown coefficient was found to be 0.82, and the Guttmann coefficient was identified as 0.810. The fact that these values are similar to one another points to the consistency between test scores. The causes of being on the NEET scale consist of the dimensions of education, individual, family, environment, and labor market, comprising 29 items in total [] (pp. 151–152).
In consequence of “the effects of being NEET scale” reliability analysis, the general reliability value of the data (Cronbach alpha) was detected as 0.931. This result shows that the questions that constitute the effects have a high reliability level. The alpha numbers acquired by means of the split-half reliability method were, respectively, identified as 0.882 and 0.866. The Spearman Brown coefficient as spotted as 0.926, and the Guttmann coefficient was found to be 0.925. The effects of being on the NEET scale consist of the dimensions of family, individual, environment, and political approach, comprising 35 items in total [] (pp. 153–155).
3.3. Definition of Variables and Analysis Methodology
The relationship between the dimensions of “the causes of being NEET scale” and the dimensions of “the effects of being NEET scale” was evaluated by means of a correlation test. How the dimensions of “the causes of being NEET scale” influence the “effects of being NEET scale” and its dimensions were determined by means of multiple regression analysis as an advanced analysis type. Accordingly, in line with the methodology of our study and under four different models, the causes of being on the NEET scale are regarded as the independent variables, while the effects of being on the NEET scale are treated as the dependent variables. In order to use the Likert-type scales in a statistical model as dependent and/or independent variables in regression analysis, factor analysis was first applied to the related scales, and the items in the scales were divided into subgroups. Afterwards, the total points of each factor were calculated and transformed into a single variable. Later, regression analysis was made based on the obtained variables. The fact that the items available in the factors were included in the analysis through their total points does not indicate any difference in terms of the findings of the analysis. The fundamental hypotheses that were put to test in this study are as follows:
H1:
The dimensions of “the causes of being NEET scale” (individual, education, family, environmental, and labor market) have no effect on the dimension of the individual effects related to “the effects of being NEET scale”.
H2:
The dimensions of “the causes of being NEET scale” (individual, education, family, environmental, and labor market) have no effect on the dimension of the environmental effects related to “the effects of being NEET scale”.
H3:
The dimensions of “the causes of being NEET scale” (individual, education, family, environmental, and labor market) have no effect on the dimension of familial effects related to “the effects of being NEET scale”.
H4:
The dimensions of “the causes of being NEET scale” (individual, education, family, environmental, and labor market) have no effect on the dimension of political approach effects related to “the effects of being NEET scale”.
In accordance with these hypotheses, the literature has contributed by separately analyzing the influence of each cause dimension existing in “the causes of being NEET scale” upon each effect dimension in “the effects of being NEET scale”.
4. Results
4.1. Correlation Analysis
The relationship between the variables that were acquired after the scale had been developed was examined by means of Pearson correlation. The correlation between the variables is provided in Figure 1 below.

Figure 1.
Pearson correlation analysis findings.
According to the correlation analysis given in Figure 1, except for the relationship between the educational dimension of “the causes of being NEET scale” and the political approach dimension of “the effects of being NEET scale”, a meaningful correlation was detected between all the dimensions of the causes and effects (p < 0.05). The fact that a meaningful and relatively high positive correlation was identified between the causes and effects is of particular importance on behalf of this study. Based on this correlation coefficient, the causes and effects act together by approximately 62%. Again, the statistically meaningful and positive correlation of the dimensions of “the causes of being NEET scale” with the dimensions of “the effects of being NEET scale” is attention-grabbing. From another angle, the reality that the dimensions of “the causes of being on the NEET scale” have a positive correlation with the effects is another finding of the analysis. The availability of a statistically meaningful correlation relationship between the causes, effects, and dimensions of being NEET indicates the presence of a linear relationship between the variables shown in Figure 1. The related findings obtained from the correlation analysis in this study also revealed that analyzing the relationship between the variables more deeply by using regression analysis will be appropriate.
4.2. Regression Models
In order to test the hypotheses stated above, four different regression models, in which the dimensions of “the effects of being NEET scale” are dependent variables and the dimensions of “the causes of being NEET scale” are independent variables, were formed. Regarding the regression models in Table 2, the dependent variables were defined as the Environmental Effect in Model 1, the Familial Effect in Model 2, the Individual Effect in Model 3, and the Political Approach Effect in Model 4.

Table 2.
The model summaries, the ANOVA test, and the regression coefficients.
The findings of the regression analysis conducted are given in Table 2. Here, when the formed models are analyzed, the coefficients of determination of the cause dimensions and their influences on the effect dimensions (R2) vary between 0.403 and 0.500. These figures point to medium-level demonstrativeness. Given the fact that the variables are the data obtained from the sum of variables that are acquired through the interval scale, this can be regarded as a high value. The model with the lowest model demonstrativeness is the familial effect model (0.403), while the highest demonstrativeness is available in the individual effect model (0.500). As for the remaining models, the model demonstrativeness value of the environmental effect model is 0.438, and that of the political approach effect model is 0.424.
According to the ANOVA test results regarding each model, the whole dimensions of “the causes of being NEET scale” (labor market, familial, environmental, educational, and individual causes) are the meaningful descriptors of the dimensions of the environmental, familial, individual, and political approach (respectively) effects of being NEET at a 95% confidence level. In line with these findings, it was detected that each regression model is meaningful in general.
The influence of the environmental, familial, individual, educational, and labor market dimensions, which are the dimensions of “the causes of being NEET scale”, on the environmental effect dimension of “the effects of being NEET scale” is examined in Model 1 by means of multivariable regression analysis. Accordingly, the dimensions of “the causes of being NEET scale” (educational, individual, familial, environmental, and labor market) explain the environmental effect dimension of being NEET, which is a dependent variable, by approximately 44% (F = 349.52; sig = 0.00). Nearly 56% of the dependent variable that signifies the environmental effect dimension of being NEET is expressed by the other independent variables, which were not included in the related model. In this model, the independent variable of education makes a positive contribution (t = 8.68; sig = 0.00 < 0.05). Accordingly, a one-unit increase in the educational dimension of “the causes of being NEET scale” leads to a 0.27-unit rise in the environmental effect dimension of “the effects of being NEET scale”. This result indicates that the increases in causes related to the educational dimension give rise to the environmental effects of being NEET. The influence of the dimension of the individual reasons within “the causes of being NEET scale” on the environmental effect dimension of “the effects of being NEET scale” was not found to be meaningful (t = −1.19; sig = 0.24 > 0.05). The independent variable of familial causes (t = 11.42; sig = 0.00 < 0.05) affects the model positively. In this context, a one-unit increase in the familial dimension of “the causes of being NEET scale” brings on a 0.45-unit rise in the environmental effect dimension of “the effects of being NEET scale”. The rise in the familial causes dimension increases the environmental effects of being NEET. The independent variable of environmental causes (t = 14.18; sig = 0.00 < 0.05) has a positive effect on the model. Accordingly, a one-unit increase in the environmental dimension of “the causes of being NEET scale” results in a 0.34-unit rise in the environmental effect dimension of “the effects of being NEET scale”. The increases in the environmental causes dimension give rise to the environmental effects of being NEET. Lastly, the variable labor market also has a positive influence on the model (t = 10.87; sig = 0.00 < 0.05). Within this scope, a one-unit rise in the labor market dimension of “the causes of being NEET scale” leads to an almost 0.21-unit increase in the environmental effect dimension of “the effects of being NEET scale”. This result demonstrates that the increases in labor market dimension-related causes give rise to the environmental effects of being NEET.
According to the coefficient of determination for Model 2 (R2), the dimensions regarding “the causes of being NEET scale” (education, individual, familial, environmental, and labor market), which are independent variables, explain the familial dimension belonging to “the effects of being NEET scale”, which is a dependent variable, by approximately 40% (F = 424.87; sig = 0.00). All variables in the model contribute positively to the model, and as can be seen in Table 2, the coefficients of the variables are statistically meaningful (p < 0.05). Accordingly, a one-unit rise in the educational dimension of “the causes of being NEET scale” leads to a nearly 0.12-unit increase in the familial effect dimension of “the effects of being NEET scale”. It is seen that the rise in educational-dimension-related reasons increases the effects of being NEET on the family. A one-unit rise in the individual dimension of “the causes of being NEET scale” results in an almost 0.02-unit increase in the familial effect dimension of “the effects of being NEET scale”. It was detected that the increases in individual dimension-related causes give rise to the effects of being NEET on the family. A one-unit increase in the familial dimension of “the causes of being NEET scale” results in a 0.22-unit rise in the familial effect dimension of “the effects of being NEET scale”. The rises in the familial-dimension-related reasons increase the effects of being NEET on family. A one-unit rise in the environmental dimension of “the causes of being NEET scale” gives way to an approximately 0.11-unit increase in the familial effect dimension of “the effects of being NEET scale”. This finding indicates that the increases in environmental-dimension-related causes lead to an increase in the effects of being NEET on family. A one-unit rise in the labor-market-related dimension of “the causes of being NEET scale” results in an almost 0.09-unit increase in the familial effect dimension of “the effects of being NEET scale”. It was identified that the rises in causes related to the labor market dimension increase the effects of being NEET on family.
In Model 3, the causes of being NEET (education, individual, familial, environmental, and labor market), which are independent variables, explain the individual effect dimension of being NEET by 50% (F = 631.06; sig = 0.00). In this model, it was found that when the family-based subdimension effect is not meaningful (p > 0.05), the individual effect has a negative influence, while the environmental, educational, and labor-market-related effects influence positively and are meaningful (p < 0.05). Within this frame, when a one-unit increase occurs in the variables, the education variable increases the individual effect dimension of being NEET by approximately 0.84 units, the individual variable decreases it by almost 0.22 units, the environment variable increases it by nearly 1.33 units, and the labor market variable increases it by more or less 0.76 units. These results demonstrate that the individual effects of being NEET are increased by the rises in the educational-dimension-based causes, decreased by the rises in the individual-dimension-related causes, increased by the rises in the environmental-dimension-oriented causes, and increased by the labor-market-dimension-related causes.
Finally, in Model 4, the causes of being NEET (education, individual, familial, environmental, and labor market) explain the political approach dimension of being NEET by 42% (F = 463.54; sig = 0.00). In the related model, the variables of family, individual, and education have negative effects, whereas the environment and labor market variables have positive effects and are meaningful (p < 0.05). To what extent the variables change the political approach effects in the case of a one-unit increase in them is given in Table 2. The findings available in the table indicate that the political approach effects of being NEET are decreased by the rises in the educational-dimension-based causes, are decreased by the rises in the individual-dimension-related causes, are decreased by the rises in the familial-dimension-oriented causes, are increased by the rises in the environmental-dimension-related causes, and are increased by the rises in the labor-market-dimension-based causes.
Based on the findings of this study, the fact that the cause dimensions are influential and statistically meaningful for the effect dimensions as a whole shows compatibility with the majority of the literature.
5. Discussion
As the coefficients standardized for Model 1 are examined, it is seen that what influences the dimension of the environmental effect of being NEET most in the sense of flexibility is the environmental dimension of “the causes of being NEET scale”. Based on the scale statements, this implies, for example, that one of the biggest reasons for feeling excluded from society, which is one of the environmental effects of being NEET, is due to social inequalities, which is one of the causes of being NEET. The following influencers on the dimension of the environmental effect of being NEET are, respectively, the labor market and family-related dimensions of “the causes of being NEET scale”, while the least influential one is the educational dimension of “the causes of being NEET scale”. When the outcomes obtained from Model 1 are compared to the literature, they show parallelism with such results that can be considered statistically meaningful environmental effects, as in the findings of Ruesga-Benito et al. [] and Bonnard [], who claim that NEET individuals have a high possibility of social exclusion, Nordenmark et al. [], who argue that NEET individuals are in a less healthy condition than the standard unemployed ones and in a poor scoring level in terms of social activities and social welfare, Pattinasarany [], who states that the participants of religious and social activities have a low possibility of being NEET, and Pemberton [], who suggests that peer effect determines the NEET status of individuals.
When the coefficients standardized for Model 2 are analyzed, it is understood that what influences the familial dimension of “the effects of being NEET scale” most in the sense of flexibility is the familial dimension of “the causes of being NEET scale”. Based on the scale statements, this result implies that one of the primary reasons for the familial unrest, which is one of the familial effects of being NEET, stems from either the presence of a family member for whom one is obligated to care or the parents’ negative attitudes towards continuing education. The other effective dimensions, respectively, include the labor market, educational, and environmental dimensions, whereas the least influential one is the individual dimension. The majority of the analysis in the literature by Erdoğan et al. [], Gutiérrez-Garca et al. [], Salvà-Mut et al. [], Tamesberger [], and Yang [] focuses on how family status affects being NEET. These studies state that the risk of being NEET in married individuals and those with low household income is higher. The results in Model 2, on the other hand, show that the effect of being NEET on family is statistically meaningful; therefore, a statistically meaningful relationship exists between the dimensions of “the causes of being NEET scale” and the familial dimension of “the effects of being NEET scale”, regardless of the causality aspect.
When the coefficients standardized for Model 3 are assessed, it is found that what influences the individual dimension of “the effects of being NEET scale” most is the environmental dimension of “the causes of being NEET scale”. This finding suggests that environmental causes of being NEET, such as economic crises or social inequalities, lead the NEET individual to despair, which is an individual effect. The remaining influential dimensions, respectively, involve the labor market and education-related dimensions, while the least effective one is the individual dimension in a negative sense. The findings of Model 3 bear a resemblance to those of Berry 36], who claims that NEET individuals show symptoms of depression more than those that are not in NEET status, and Gutiérrez-García et al. [], who state that NEET individuals have a greater tendency towards psychological diseases, drug and alcohol addiction, and suicide.
When the coefficients standardized for Model 4 are studied, it is seen that what influences the political approach dimension of “the effects of being NEET scale” most in the sense of flexibility is the environmental dimension of “the causes of being NEET scale”. This result indicates that economic crises and/or social inequalities, which are environmental causes of being NEET, lead to a negative perspective towards public policies, which is one of the political effects of being NEET. The other following influential dimensions, respectively, include the familial, labor-market-related, and individual dimensions, whereas the least effective dimension is the educational one. However, it is essential to remember that this education dimension negatively affects the political approach dimension of the individual and family variables. There exists a similarity between the findings obtained from Model 4 and some studies in the literature, like that of Caroleo et al. [], who state that NEET individuals are influenced by the operation of the workforce market and institutional factors; Maguire and Rennsion [], who argue that the educational support provided through educational policies (Education Maintenance Allowance (EMA)) has an effect on the political perceptions of NEET individuals; and Pemberton [], who claims that the inequality of opportunity in education increases individuals’ possibility of being NEET. Yet, it can be stated that this study shows contrast with the findings of Yang [], who argues that party membership has a statistically meaningless association with being NEET; as in our study, a statistically meaningful relationship between being NEET and political approach was detected.
6. Conclusions
According to the correlation analysis, except for the relationship between the educational dimension of “the causes of being NEET scale” and the political approach dimension of “the effects of being NEET scale”, a meaningful correlation was detected between the all-cause and effect dimensions. The identification of a meaningful and relatively high positive correlation between the causes and effects is especially significant for the related study. In accordance with this correlation coefficient, the causes and effects of being NEET move together approximately by 62%. Moreover, four different regression models, in which the dimensions of “the effects of being NEET scale” are dependent variables while the dimensions of “the causes of being NEET scale” are independent ones, were constituted within the scope of this study. Regarding these regression models, the dependent variables were defined as the Environmental Effect in Model 1, the Familial Effect in Model 2, the Individual Effect in Model 3, and the Political Approach Effect in Model 4. At the end of each model examination within the regression analysis, the fundamental hypotheses H1, H2, H3, and H4 were rejected. Among the cause subdimensions, the factors that most affected the effect subdimensions were determined with standardized coefficients. The primary findings that require policy development are as follows:
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- One of the biggest reasons for feeling excluded from society, which is one of the environmental effects of being NEET, is due to social inequalities, which is one of the causes of being NEET.
- −
- One of the primary reasons for the familial unrest, which is one of the familial effects of being NEET, is either the presence of a family member for whom one is obligated to care or the parents’ negative attitudes towards continuing education.
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- Environmental causes of being NEET, such as economic crises or social inequalities, lead the NEET individual to despair, which is an individual effect.
- −
- Economic crises and/or social inequalities, which are environmental causes of being NEET, lead to a negative perspective towards public policies, which is one of the political effects of being NEET.
The findings of this study are compatible with the literature, and it was detected that the cause dimensions of being NEET are influential on the effect dimensions of being NEET as a whole and are statistically meaningful as well. In this context, in order to prevent the negative effects of individuals becoming NEET, it is essential to first prevent the causes of becoming NEET.
Author Contributions
Conceptualization and literature, L.Ş., M.E.K. and A.M.B.; research design and methodology, İ.D., M.E.K. and O.A.; data curation and analysis, İ.D., M.E.K. and A.M.B.; evaluation of the findings, L.Ş., H.Y.E., İ.D., M.E.K., O.A. and A.M.B.; writing—original draft preparation, İ.D., M.E.K. and A.M.B.; writing—review and editing, L.Ş., H.Y.E., İ.D., M.E.K. and A.M.B.; resources, M.E.K. and A.M.B.; supervision: L.Ş., H.Y.E. and İ.D. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Ethical review and approval were waived for this study because this study was prepared using data from the NEET survey conducted in Turkey in 2020, and ethics committee approval was not required during the periods in which the field research was conducted. However, the research data were used with permission given by the research owner institution the Turkish Republic Ministry of Youth and Sports, and the executive institution Istanbul University Rectorate.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Research data can be used with the permission of the Turkish Republic Ministry of Youth and Sports.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A

Table A1.
The dimensions and articles of “The Causes of Being NEET Scale”.
Table A1.
The dimensions and articles of “The Causes of Being NEET Scale”.
Dimension | Causes |
---|---|
Education-based Causes | My education has been left half-completed. |
I did not intend to continue with my education because I had no liking for my educational institution/major/field of study. | |
I could not/cannot continue with my education as I had/have no access to educational institutions. | |
Personal Causes | I did not/do not continue with my education by choice. |
I could not/cannot continue with my education due to the insufficiency of my financial situation. | |
I could not continue with my education due to my disability, and/or I could not/cannot find employment. | |
I could not continue with my education because my health status is not suitable and/or I could not/cannot find employment. | |
My lack of education is my sole responsibility. | |
My being out of employment is under my sole responsibility. | |
I did not/do not intend to work, even if any person or institution provided/provides me with employment. | |
I did not/do not intend to work/get employed, as my financial status is sufficient. | |
I do not have the self-confidence necessary for participating in professional life. | |
Environmental Causes | My immediate circle (parents, siblings, spouse, and friends) were/are influential in my being out of education. |
My immediate circle (parents, siblings, spouse, and friends) were/are influential in my being out of employment. | |
I could not/cannot find employment because I do not have the necessary social network. | |
I could not/cannot find employment due to the economic crises experienced in the country. | |
I could not/cannot find employment due to the social inequalities (inequality of opportunity, discrimination, etc.) available in the country. | |
Familial Causes | I believe that the approach of my parents has negative effects on my education. |
I could not/cannot continue with my education as I have children/disabled people/elderly people that I am obliged to look after in my family. | |
I could not/cannot find employment because I have children/disabled people/elderly people that I am obliged to look after in my family. | |
Labor Market-related Causes | I could not/cannot find employment in the professional field I have received education/training in. |
I could not/cannot find employment as I do not have a sufficient level of education. | |
I could not/cannot find employment as I have no work experience. | |
I have no idea what job-seeking channels I need to use to find employment. | |
I do not seek jobs, as I have lost hope of getting employed. | |
I do not believe in the availability of employment in my residential area, which is appropriate for my education and competencies. | |
I can look for work in a different city or area, but the social and economic uncertainties in that region prevent me from seeking employment. | |
I prefer remaining unemployed to working on a low salary. | |
I do not intend to work/get employed, as the working conditions challenge me a lot. |
Appendix B

Table A2.
The dimensions and articles of “The Effects of Being NEET Scale”.
Table A2.
The dimensions and articles of “The Effects of Being NEET Scale”.
Dimension | Causes |
---|---|
Familial Effects | The fact that I am out of education or employment leads to domestic unrest. |
My family puts pressure on me due to the fact that I am out of education or employment. | |
My family has no concern for my being out of education or employment. | |
Individual Effects | Being out of school makes me feel hopeless regarding my future. |
Being out of employment makes me feel hopeless regarding my future. | |
Life has become so complicated for me that I have difficulty finding a way out. | |
I believe that other people do not recognize the worth of the things I have accomplished. | |
If I died today, I would feel that my life had been wasted. | |
If I came to this world again, I would change almost nothing in my life. | |
I hope that I will be successful in issues that are important to me in the future. | |
When I look to the future, I expect to be happier than today. | |
When I consider everything in my life, I feel quite unhappy. | |
Being out of education or employment decreases my self-esteem. | |
I cannot reveal my potential because I am out of education or employment. | |
I feel that I am of no use at times. | |
I believe that being out of education or employment negatively affects my mental health. | |
Being out of education or employment creates a desire to harm myself. | |
Being out of education or employment makes me consider suicide. | |
I feel worthless due to the fact that I am out of education or employment. | |
I have become computer-internet-social media addicted due to being out of education or employment. | |
I cannot meet my needs as I am out of employment. | |
I receive financial help from my family/social circle as I am out of employment. | |
I believe that I am getting poor because I am out of employment. | |
Environmental Effects | I believe that being out of education or employment has moved me away from my social life (fun activities). |
I believe that being out of education or employment has isolated me. | |
I feel excluded from society. | |
I find it difficult to adapt to my social environment (society). | |
I am ignored/taken no notice of in the environments in which I am present. | |
There are people who regard me as a bad example. | |
Political Approach Effects | I do not find the employment policies of the state sufficient. |
I do not find the education policies of the state sufficient. | |
My being out of employment causes me to adopt a negative point of view towards public policies. | |
I adopt an indifferent attitude towards the developments in the country. | |
I do not expect to find employment through the Turkish Employment Agency (İŞKUR). | |
I do not find it right when the state transfers funds to those who hold non-native status, like inflowing people (immigrants, refugees, etc.). |
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