|Year : 2022 | Volume
| Issue : 3 | Page : 125-133
Child behavior and psychological comorbidities in relation to different forms of child abuse among working children
Amani S Ahmed1, Rania A Hamed2, Shaimaa Y Abd Elaziz2, Naglaa F Agba3
1 Department of Community, Environmental and Occupational Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt
2 Psychiatry, Faculty of Medicine (for Girls), Al-Azhar University, Cairo, Egypt
3 Pediatrics and Neonatology, Faculty of Medicine (for Girls), Al-Azhar University, Cairo, Egypt
|Date of Submission||10-Jan-2022|
|Date of Decision||05-Feb-2022|
|Date of Acceptance||02-May-2022|
|Date of Web Publication||16-Dec-2022|
Source of Support: None, Conflict of Interest: None
Background Childhood labor exposes children to the risk of violence and abuse that may adversely affect their psychological well-being.
Aim To explore psychological comorbidities and their relation to different forms of abuse among labored children and identify risk factors for exposure to abuse in working children.
Patients and methods This cross-sectional study included 158 male working children aged 12–17 years. Sociodemographic data, education level, and type of work were collected. The type of abuse was categorized into physical, emotional, and sexual abuse using the International Child Abuse Screening Tool (children’s version institution questionnaire). Social competence and behavioral problem assessment was done using the Child Behavior Checklist (the youth self-report). Regression analysis to determine predictors of abuse among working children was done.
Results About 59.5% of included children were exposed to at least one type of child abuse last year, 75% reported exposure during work time. The commonest form was psychological, followed by physical abuse, and last, sexual abuse. Social competence was impaired in abused children, regardless of the type of abuse. Behavioral problems were significantly higher in children exposed to physical and sexual abuse. Younger age (odds ratio 4.09; 95% confidence interval 1.03:16.18) and working in small industrial shops (odds ratio 3.28; 95% confidence interval 1.40:7.71) were risk factors for abuse exposure in working children.
Conclusion Working children at higher risk for child abuse adversely affect their social competence and increase their behavioral problems.
Keywords: abuse, psychological comorbidities, social competence, working children
|How to cite this article:|
Ahmed AS, Hamed RA, Abd Elaziz SY, Agba NF. Child behavior and psychological comorbidities in relation to different forms of child abuse among working children. Egypt J Psychiatr 2022;43:125-33
|How to cite this URL:|
Ahmed AS, Hamed RA, Abd Elaziz SY, Agba NF. Child behavior and psychological comorbidities in relation to different forms of child abuse among working children. Egypt J Psychiatr [serial online] 2022 [cited 2023 Feb 7];43:125-33. Available from: https://new.ejpsy.eg.net//text.asp?2022/43/3/125/363998
| Introduction|| |
Child labor is a worldwide issue, especially in developing countries. Children usually start working at a young age and under unsuitable conditions without any safety or insurance. Child labor exposes children to physical and psychological hazards that may threaten their lives (Santana et al., 2019). It is one of the child’s rights to be protected from violence and abuse. Identification of maltreatment practice and exploring its adverse impact on growing children is an area of great interest (Kassouf, 2019).
Despite several reports regarding exposure to abuse among labored children, there are no accurate statistics to determine the actual rate and burden of exposure to abuse among worker children in Egypt (Ibrahim et al., 2019). Psychological disorders represent a long-term squeal of exposure to abuse that is usually missed or underestimated. Exposure to child abuse has been identified as a risk factor for aggression and conduct disorders (McGee et al., 2019).
Adolescence is a critical period in a child’s mental and psychological development. Adverse experiences in early life increase the risk for behavioral disorders later on. Maltreatment at this age has a long-term impact that extends into adult life, which affects not only the patient but also their families and community (Larsen and Luna, 2018).
Egypt is one of the largest populations in African countries. Based on the 2014 Egypt Demographic and Health Survey, 7% of children aged 5–17 years old, about 1.6 million children, were engaged in child labor. Despite the increasing global concern about child abuse among working children, this problem has received little attention in Egypt. There is limited data regarding child-abuse prevalence and risk factors for child labor in Egypt (Khatab et al., 2019).
The current study aimed to explore child behavior and psychological comorbidities and their relation to different forms of abuse among labored children, and identify risk factors for exposure to abuse in working children.
| Patients and methods|| |
This cross-sectional study was conducted on working children in Cairo City. Data were collected from June to September summer of 2020.
Sample size and sampling technique
The study was conveyed in five areas in Cairo City, which were chosen by simple random-sampling techniques, as shown in [Figure 1]. The total number of study participants who accepted to participate in the study was 158 working children. Two hundred fifteen working children were invited to participate in the study from the selected five areas, while 158 of them accepted to participate, with a response rate of 73.49%.
All working children in the selected five areas aged less than 18 years old who consented to participate in this study were included.
A pilot study was done on 15 working male children from the selected areas in April 2020 to test the response to different items of the questionnaires and to test the questionnaire with the most appropriate terms. The reliability coefficients for all questionnaires were suitable for scientific purposes (Cronbach’s alpha ranged from 0.78 to 0.86). All working children of the pilot study were excluded from the results of the study.
All working children who participated in the study were subjected to the following:
- A questionnaire regarding sociodemographic and work characteristics: age, sex, child’s order in the family, family number, child’s education level, living arrangement, father’s and mother’s education level, and type of work of working children.
- The International Child Abuse Screening Tool Children’s Version (ICAST-C) institution questionnaire (Zolotor et al., 2009): the ICAST-C Institution has 44 items developed to identify the different types of child victimization at work. Eighteen items for physical victimization, 15 items for psychological victimization, and 11 items for sexual victimization.
- The Child Behavior Checklist for Youth Self-Report (CBCLY-SR) (Achenbach and Rescorla, 2001): youth self-report form was used, a validated questionnaire that assesses social competence, emotional and behavioral problems, as well as somatic functioning. It consists of two main domains; social competence and problem checklist.
The social-competence domain covers three areas: physical activities (spending time on sports, hobbies or games, and performance compared with same-age peers), social relations (relationships with close friends and family members, how independent they are when playing or working alone), and self-reported academic performance. Each item is calculated as 0 (not true), 1 (somewhat or sometimes true), or 2 (very true or often true). T scores are categorized for social competence as: the normal T score range is above 35, the borderline clinical range is 31–35, and the clinical range is less than 31.
Problem checklist comprises eight syndrome scales: anxious/depressed, withdrawn/depressed, somatic complaints, social problems, thought problems, attention problems, rule-breaking behavior, and aggressive behavior. T scores are categorized for syndromes as follows: the normal T score range for all syndromes is less than 65, the borderline clinical range is 65–69, and the clinical range is above 69. While for total behavior problems, the normal T score range is less than 60, the borderline clinical range is 60–63, and the clinical range is above 63.
Data were entered and statistically analyzed using the Statistical Package for the Social Sciences (SPSS, Armonk, NY: IBM Corp), version 21.0. Qualitative data were presented in the form of frequency and percentage, and the χ2 test or Fisher’s exact test (as appropriate) was used for comparison between groups. Quantitative data were presented in the form of measures of central tendency (arithmetic mean) and measures of dispersion (SD). A t test was applied for comparing the two means. T scores are presented for all subscales and syndromes of the Child Behavior Checklist for Youth Self-Report (CBCLY-SR). T scores of the data were calculated by converting the raw data of subscales and syndromes to z score, then the z score was converted to T scores having a mean=50 and SD=10. Regression analysis was used for detecting the predictor variables. The difference was considered statistically significant when the P value was less than 0.05.
| Results|| |
[Table 1] reveals that all the included participants were males, their ages ranged from 12 to 17 years. About 49.4% of the studied group works in small industrial shops, whereas 21.5 and 29.1% were working as shop sellers and street vendors. About 62% of them live with both parents. Children in the family were four and more in nearly 78%. Regarding the education level of the child, 53.2% were in preparatory education. The majority of mothers of participants had no formal education (57.6%), whereas fathers were educated up to the primary level (37.3%); 3.8% of fathers and 0.6% of mothers had a completed graduation degree.
|Table 1 Sociodemographic and work characteristics of the studied working children|
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[Figure 2] indicates that among our studied children, 59.5% were exposed to at least one type of child abuse last year, 76.5% reported exposure to abuse during work. The commonest form was psychological abuse, physical abuse, and sexual abuse. All abused children were exposed to psychological abuse. In addition to psychological abuse, 39.9 were also exposed to physical abuse, and 5.1% were exposed to sexual abuse, while 19% were only exposed to psychological abuse.
|Figure 2 Prevalence of different types of abuse among the studied group in the last year and during work life. All children exposed to physical and sexual abuse were also exposed to psychological abuse. Sexual victimization was in the form of touching the private part and talking sexually, with no case of a complete sexual act.|
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[Table 2] reveals that the younger age of children, lower level of children’s education, and work in small industrial shops were significantly associated with greater exposure to child abuse.
|Table 2 Association between sociodemographic and work characteristics and exposure to abuse among working children|
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[Table 3], a comparison of social competence with abuse, shows statistical significance impairment of activities, social relations, and total social competence in children exposed to abuse. In contrast, no significant difference was detected in school performance between both groups. Furthermore, a comparison between both groups regarding behavioral problems showed a significant increase in anxiety/depression, social problems, attention problems, and rule-breaking behavior in children exposed to abuse than those who were not exposed to abuse. There was no statistically significant difference between abused and nonabused groups regarding withdrawal, somatic complaints, thought problems, and aggressive behavior.
|Table 3 According to the Child Behavioral Checklist, social competence and behavioral problems in relation to abuse exposure among working children|
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[Table 4] demonstrates that exposure to psychological, physical, or sexual abuse is associated with impaired social competence related to physical activities and social relations, but no difference in school performance. However, exposure to physical and sexual abuse but not psychological abuse was associated with significant anxiety, social, attention, and rule-breaking behavior problems.
|Table 4 Social competence and behavioral problems with different types of abuse among working children according to Child Behavioral Checklist|
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[Table 5], multivariate logistic regression analysis revealed that younger age (odds ratio 4.09; 95% confidence interval 1.03:16.18) and work in small industrial shops (odds ratio 3.28; 95% confidence interval 1.40:7.71) were risk factors for abuse exposure in working children.
|Table 5 Multivariate logistic regression analysis for sociodemographic and work characteristic risk factors of abuse exposure among working children|
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| Discussion|| |
Working children represent a high-risk population for child abuse (Dhakal et al., 2019). Several children and family characteristics are associated with an increased risk of exposure to child abuse. Poverty (Bhat and Rather, 2009; Kotb et al., 2011) and illiteracy (Shikdar et al., 2013) represent the most notable reasons for child labor worldwide. Among our studied children, poor education, family size, and the order of children were the predominant sociodemographic characteristics associated with child labor. Egyptian working children are involved in different types of work that vary according to residency (Shoman et al., 2015). As the current study was conducted in Cairo, child labor was limited to small industrial shops (49.4%), street workers (29.1%), or working as shop sellers (21.5%).
Children are considered more vulnerable to abuse than adults because they are more obedient and easier to control. There are comprehensive controversial reports regarding the frequency and type of abuse among worker children that greatly reflect variation in the nature, place of work, lack of family support, and community protection. Among our studied working children, 59.5% were exposed to abuse last year; most reported exposure during work. The most familiar form of abuse was psychological abuse, physical abuse, and sexual abuse. Öncü et al. ((2013)) demonstrated that 62.5% of Turkish working children suffered from abuse at their workplaces (21.8% reported physical abuse, 53.6% reported emotional abuse, and 25.2% reported sexual abuse). Celik and Baybuga ((2009)) demonstrated that 50% of street-working children were exposed to verbal and physical abuse, while 65% were exposed to sexual abuse. This higher rate of sexual abuse is related to the inclusion of street-working children who were mostly homeless. Mohammed et al. ((2014)) reported that 18% of working Egyptian children had been exposed to physical abuse, while 28% were exposed to verbal abuse. The lower rate of child abuse in the previous study may be explained as all the included children have worked in specific places and were living with their families or relatives.
Our study revealed that the younger age of children, lower level of children’s education, and work in small industrial shops were significantly associated with greater exposure to child abuse. Similar findings were reported by Khatab et al. ((2019)) that children aged 11–15 are more at risk of abuse than those aged over 15 years. In Bangladesh, Hadi ((2000)) reported that physical abuse was more prevalent among younger children, while other forms of abuse were more prevalent among older children. Multivariate analysis suggested that the uneducated children were more likely to be abused than others when age and sex confounders were eliminated. Poreddi et al. ((2016)) reported that the risk for abuse is negatively correlated with the child’s age.
Manual working in small industries with no protective measures besides lack of insurance exposes children to significant physical hazards. Furthermore, psychological abuse was reported as a tool to force children to continue working under hazardous conditions, accept the low financial outcome, and deny exposure to any trauma during work. The small body built by children and their limited capacity to resist physical violence makes them victims of physical and sexual abuse. Lack of sufficient education makes those children less aware of their rights, unable to call for ‘society’s help, and more efficiently to be controlled (Betcherman et al., 2004). The type of child labor is the most critical determinant of the incidence of work-related hazards (Ismayilova and Karimli, 2020).
Among our studied worker children, exposure to abuse adversely impairs social competence and increases the frequency of behavioral problems, including anxiety, depression, attention, and rule-breaking behavior problems.
Numerous studies have associated childhood abuse with a variety of adverse effects, such as mood and anxiety disorders (Gilbert et al., 2009; Kessler et al., 2010), suicidal behaviors (Dube et al., 2001; Molnar et al., 2001), rule-breaking, and substance use (Torchalla et al., 2012; Vachon et al., 2015).
In particular, childhood abuse has consistently been linked to depressive disorders in adulthood in retrospective studies (Hovens et al., 2010; Braithwaite et al., 2017) and prospective studies (Widom et al., 2007).
The present study revealed no statistically significant difference between abused and nonabused groups regarding withdrawal, somatic complaints, thought problems, and aggressive behavior. At the same time, some studies have reported an association between a history of physical abuse and multiple outcomes. These studies reported externalizing difficulties, including conduct problems, impulsivity, anger, aggression, disruptive and delinquent behaviors, and some violent offenses committed (Petrenko et al., 2012; Van der Put et al., 2015). The difference between the results of these researches and ours is that we investigated child behavior and psychological comorbidities with abuse among working children. In contrast, other researchers investigate this problem among school children.
Working children at higher risk for child abuse adversely affect their social competence and increase their behavioral problems. Raising the community’s awareness about this problem and legislation should be implemented to protect them from abuse and its negative consequences.
Financial support and ponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Achenbach TM, Rescorla LA (2001). Manual for the ASEBA school-age forms & profiles: an integrated system of multi-informant assessment Burlington, VT: University of Vermont. Research Center for Children, Youth, & Families; 2001, 1617.
Betcherman G, Fares J, Luinstra A, Prouty R (2004). Child labor, education, and children’s rights. World Bank Social Protection Discussion Paper Series 1:412.
Bhat BA, Rather TA (2009). Child labour in the handicrafts home industry in Kashmir: a sociological study. Int NGO J 4:391–400.
Braithwaite EC, O’Connor RM, Degli-Esposti M, Luke N, Bowes L (2017). Modifiable predictors of depression following childhood maltreatment: a systematic review and meta-analysis. Transl Psychiatry 7:e1162.
Celik SS, Baybuga MS (2009). Verbal, physical, and sexual abuse among children working on the street. Austr J Adv Nurs 26:14–22.
Dhakal S, Niraula S, Sharma NP, Sthapit S, Bennett E, Vaswani A et al.
(2019). History of abuse and neglect and their associations with mental health in rescued child labourers in Nepal. Austr New Zeal J Psychiatry 53:1199–1207.
Dube SR, Anda RF, Felitti VJ, Chapman DP, Williamson DF, Giles WH (2001). Childhood abuse, household dysfunction, and the risk of attempted suicide throughout the life span: findings from the Adverse Childhood Experiences Study. JAMA 286:3089–3096.
Gilbert R, Widom CS, Browne K, Fergusson D, Webb E, Janson S (2009). Burden and consequences of child maltreatment in high-income countries. Lancet 373:68–81.
Hadi A (2000). Child abuse among working children in rural Bangladesh: prevalence and determinants. Public Health 114:380–384.
Hovens JG, Wiersma JE, Giltay EJ, Van Oppen P, Spinhoven P, Penninx BW, Zitman FG (2010) Childhood life events and childhood trauma in adult patients with depressive, anxiety, and comorbid disorders vs. controls. Acta Psychiatrica Scandinavica 122:66–74.
Ibrahim A, Abdalla SM, Jafer M, Abdelgadir J, De Vries N (2019). Child labor and health: a systematic literature review of the impacts of child labor on child’s health in low-and middle-income countries. J Public Health (Bangkok) 41:18–26.
Ismayilova L, Karimli L (2020). Harsh parenting and violence against children: a trial with ultrapoor families in Francophone West Africa. J Clin Child Adolesc Psychol 49:18–35.
Kassouf AL (2019). Child labour and children’s right to a better life. Lancet Child Adolesc Health 3:845–847.
Kessler RC, McLaughlin KA, Green JG, Gruber MJ, Sampson NA, Zaslavsky AM et al.
(2010). Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. Br J Psychiatry 197:378–385.
Khatab K, Raheem MA, Sartorius B, Ismail M (2019). Prevalence and risk factors for child labour and violence against children in Egypt using Bayesian geospatial modelling with multiple imputation. PLoS One 14:e0212715.
Kotb SA, Mohamed AG, Abdel Khalek EM, Yones DA (2011). Agricultural labor among school children in rural Assiut, Egypt. Life Sci J 8:423–439.
Larsen B, Luna B (2018). Adolescence as a neurobiological critical period for the development of higher-order cognition. Neurosci Biobehav Rev 94:179–195.
McGee Z, Alexander C, Cunningham K, Hamilton C, James C (2019). Assessing the linkage between exposure to violence and victimization, coping, and adjustment among urban youth: findings from a research study on adolescents. Children 6:36.
Mohammed ES, Ewis AA, Mahfouz EM (2014). Child labor in a rural Egyptian community: an epidemiological study. Int J Public Health 59:637–644.
Molnar BE, Berkman LF, Buka SL (2001). Psychopathology, childhood sexual abuse and other childhood adversities: relative links to subsequent suicidal behaviour in the US. Psychol Med 31:965–977.
Öncü E, Kurt AÖ, Esenay FI, Özer F (2013). Abuse of working children and influencing factors, Turkey. Child Abuse Negl 37:283–291.
Petrenko CL, Friend A, Garrido EF, Taussig HN, Culhane SE (2012). Does subtype matter? Assessing the effects of maltreatment on functioning in preadolescent youth in out-of-home care. Child Abuse Negl 36:633–644.
Poreddi V, Pashapu DR, Kathyayani BV, Gandhi S, El-Arousy W, Math SB (2016). Nursing students’ knowledge of child abuse and neglect in India. Br J Nurs 25:264–268.
Santana VS, Kiss L, Andermann A (2019). The scientific knowledge on child labor in Latin America. Cad Saúde Púb 35:e00105119.
Shikdar MK, Biswas AK, Tanvir S, Tabassum T (2013). Mitigating problems of destitute children; dropping out from school and involving in under aged labour. Re J Soc Sci 2:33–41.
Shoman AE, Mostafa NS, Musslem AA (2015). Nutritional status and parasitic infestation among working children in a village in Egypt: a comparative study. J Egypt Public Health Assoc 90:80–84.
Torchalla I, Strehlau V, Li K, Schuetz C, Krausz M (2012). The association between childhood maltreatment subtypes and current suicide risk among homeless men and women. Child Maltreat 17:132–143.
Vachon DD, Krueger RF, Rogosch FA, Cicchetti D (2015). Assessment of the harmful psychiatric and behavioral effects of different forms of child maltreatment. JAMA Psychiatry 72:1135–1142.
Van der Put CE, Lanctôt N, De Ruiter C, Van Vugt E (2015). Child maltreatment among boy and girl probationers: does type of maltreatment make a difference in offending behavior and psychosocial problems?. Child Abuse Negl 46:142–151.
Widom CS, DuMont K, Czaja SJ (2007). A prospective investigation of major depressive disorder and comorbidity in abused and neglected children grown up. Arch Gen Psychiatry 64:49–56.
Zolotor AJ, Runyan DK, Dunne MP, Jain D, Péturs HR, Ramirez C et al.
(2009). ISPCAN Child Abuse Screening Tool Children’s Version (ICAST-C): instrument development and multi-national pilot testing. Child Abuse Negl 33:833–841.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]