Mental health status of children (14–17 years) in conflict with law residing in the correction homes in Bagmati Province, Nepal: a mixed method study

Abstract

Background

Children in conflict with the law are predisposed to mental health difficulties as they are already a vulnerable, misunderstood, and frequently stigmatized group. This mixed method study assessed the prevalence and associated factors of Depression, Anxiety, and Stress (DAS) among children (14–17 years) in conflict with the law.

Methods

A cross-sectional study was conducted from December 2022 to March 2023 using a mixed method approach among children (14–17 years) in two correction homes of Bagmati Province. The census was conducted due to the small population size. Nepali versions of the DASS-21 were administered to 182 children aged 14–17 years to collect quantitative data. The Depression Anxiety Stress Scales-21 (DASS-21) is a shortened version of the DASS-42, designed to measure emotional states of depression, anxiety, and stress comprising 21 items divided into three subsc ales. Key informant interviews were conducted with wardens and psychosocial counselors of correction homes. Data were analyzed using SPSS-21, and a thematic analysis handled qualitative data.

Results

More than half of the respondents had depression (58.2%) and stress (52.2%), while anxiety was prevalent among 76.4% of children (14–17 years). The odds of having depression were more than double among females in comparison to males (AOR = 2.25, 95%CI = 1.68–7.47), which was 5.43 times (AOR = 5.43, 95% CI = 1.42–20.72) in the case of stress. Similarly, the odds of having depression among the respondents who live with persons other than parents were 4.11 times more likely as compared to those who used to live with parents before coming to the corrections home (AOR = 4.11, 95% CI = 1.37–12.27, which was 5.21 times (AOR = 5.21, 95% CI = 1.25–11.72) for anxiety. The respondents who were isolated from family were 12.57 times (AOR = 12.57, 95% CI = 3.58–44.17) more likely to have anxiety than those who were not isolated from the family, adjusting for other explanatory variables included in the model. Family history of conflict (AOR = 1.84, 95% CI = 0.82–4.13) and history of punishment (AOR = 2.10, CI = 1.13–4.41) were also found to be correlated with depression and stress, respectively. Mental health issues were linked to family conflict, broken homes, abuse history, and isolation, supported by key informant interviews as well.

Conclusion

More than half of the children (14–17 years) in conflict with the law were having all three types of common mental health problems. These results highlight the urgent need for comprehensive and tailored intervention to address the mental health needs of the children in conflict with the law.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12888-025-07170-y.

Background

The United Nations Convention on the Rights of the Child (CRC) defines children as individuals under the age of eighteen and outlines 54 articles detailing their rights and the obligations of governments to ensure those rights are upheld. This includes meeting their basic needs and supporting their growth and development [1]. In Nepal, the Act Relating to Children, 2075 (2018) aligns with this definition, stating that a “minor” is someone under the age of eighteen years. This act defines “children in conflict with the law” as the children accused of committing an offense and the children convicted by the Juvenile Court for committing an offense [2].

Children who experience abuse from family members are more vulnerable, exhibit more long-term maladaptive tendencies, and engage mostly in criminal offenses as compared to children harmed by people outside the family [3]. Children engage in criminal acts due to various factors, including personal characteristics, low education, family life, poverty, and peer pressure. A lack of self-control and the inability to resist peer influence contribute to delinquent behavior [4]. Family dynamics play a crucial role, as parental conflict, divorce, emotional neglect, and lack of guidance create an unsafe environment for children. The absence of strong parental support affects adolescents’ self-confidence, self-regulation, and decision-making skills. Without moral guidance and fulfillment of their needs, children may resort to unlawful acts without considering the consequences [4].

Over 260,000 children who are in conflict with the law are reportedly detained globally. The number of children coming into contact with the justice system has steadily increased [5]. In Tajikistan, juvenile offenses rose from 565 cases in 2016 to 906 in 2018 [6]. In the U.S., over 43,000 juveniles were held in residential placement facilities daily in 2019. Brazil had the highest number of juveniles in correction institutions (23,725), followed by China, Thailand, and the U.S. [7]. In Nepal, child delinquency cases increased from 138 cases with 153 defendants in Fiscal Year (FY) 2015/016 to 235 cases with 347 defendants in Fiscal Year (FY) 2016/017, with only a few girls involved. In FY 2016/017, 119 out of 168 decided cases resulted in convictions [8]. As a result, correction centers are overcrowded and poor, depriving children of their rights in a variety of ways, including limiting access to health care and education [9]. Detained children suffer from various mental health problems as a result of solitary confinement, abuse, or neglect [9]. Multidimensional hurdles or life events may pose a risk of developing dissatisfaction with life, which can lead to mental health consequences [10]. Children in conflict with the law suffer from depression, a lack of personal attention, emotional deprivation, separation anxiety, a lack of bonding, a lack of creativity, low self-esteem, interpersonal relationship problems, concentration difficulty in mainstreaming, and difficulty adjusting to society [11]. Approximately two-thirds of children in detention or correction settings, compared to an estimated 9 to 22 percent of the general young population, have at least one diagnosable mental health problem [12]. Estimates revealed that approximately 50 to 75 percent of the 2 million youth encountering the juvenile justice system meet criteria for a mental health disorder. Approximately 40 to 80 percent of incarcerated juveniles have at least one diagnosable mental health disorder. Two-thirds of males and three-quarters of females in previous studies of juvenile offender detention facilities were found to meet criteria for at least one mental health disorder [13].

The goal of the juvenile justice system is not to produce criminals but rather to establish a suitable environment for the sound physical and mental development of children in order to facilitate the rehabilitation and reintegration of deviant adolescents through a reformative approach. The Children’s Act 2075 also establishes correction homes in eight districts throughout six provinces, including Morang, Parsa, Makwanpur, Bhaktapur, Kaski, Rupandehi, Banke, and Doti. Instead of being imprisoned, children who have been found guilty by the court in a variety of cases have been housed in correction homes [2]. These correction homes are established for the promotion of the child’s dignity and worth, which reinforces the child’s respect for human rights and fundamental freedoms, taking into account the child’s age and the desirability of promoting the child’s reintegration and the child’s assuming a constructive role in society [14]. The report suggests that juvenile delinquency is increasing [15]. The overall capacity of Child Correction Homes (CCHs) in Nepal is 502, but the current number of juveniles in CCHs is 735. Overcrowding is a major problem in CCHs [16].

Children in conflict with the law are predisposed to mental health difficulties because they are already a vulnerable, misunderstood, and frequently stigmatized group [17]. Children in conflict with the law are increasing at an alarming rate in Nepal, and data on their mental health status is in greater demand. Mental health issues of children in conflict with the law have been the subject of research mostly in developed countries [18]. But there isn’t much literature from developing nations, including Nepal. A comparative study on levels of depression, anxiety and stress among juvenile delinquents and the normal population between the ages of 12–18 years in Takyel of Imphal West district of Manipur showed that most of the population of juvenile offenders suffered from depression (95%), whereas only 5% were having depression in the normal population [19]. A study in Jharkhand, India, among children in conflict with the law showed significantly higher levels in emotional problems, internalizing attributes, prosocial behavior, level of alcohol/drug involvement, self-esteem, and strictness compared with children not in conflict with the law [20]. Another study among children in conflict with the law in Kenya showed that thought disturbance in boys was 58.9%. Clinically significant caution level scores were reported for somatic complaints (66.7%), angry-irritable (54.2%), and depressed-anxious (45.1%) [21].

As a result of the overcrowding in child correction homes, the children’s education, health, and nutrition needs may be compromised, and they may be more prone to psychological distress, leading to mental health problems [9]. Due to the solitary confinement and neglected environmental conditions in correction homes, children may experience physical or psychological issues throughout their stay [13]. To raise awareness about this issue in developing countries like Nepal, a study on the magnitude of mental health difficulties suffered by young children (14–17 years) is needed, and recognizing mental health problems may help in preventing future criminal behavior. This study assessed the depression, anxiety and stress among the children in conflict with the law residing in the child correction homes as well as the perspective of service providers.

Methods

Study design and study population

A cross-sectional study using a mixed methods approach was conducted among the children (14–17 years) residing in child correction homes of Bagmati Province, Nepal. The Bagmati Province was selected purposively because the highest number of children in conflict with the law were in this province, with this being the only province where female children are kept [16]. For the quantitative study, the study population was children in conflict with the law between the age group of 14 years to 17 years residing in child correction homes in Bagmati Province. A qualitative study was carried out to explore the factors associated with the poor mental health status of the children from the perspective of service providers and caretakers. For the qualitative study, the study population was wardens and psychosocial counselors of the correction homes of Bagmati Province. A warden in a child correction home is a person who oversees the security, welfare, and rehabilitation of children in conflict with the law. They work with counselors and educators to ensure children’s rights, safety, and rehabilitation through education, therapy, and life skills training.

Sample size and sampling process

Census was carried out for the quantitative study among all eligible children residing in child correction homes during the study period (N = 182); 45 children were from the child correction home of Makwanpur district, and 137 children (14–17 years) were from the child correction home of Bhaktapur district, which is a correction home of all three districts; Kathmandu, Bhaktapur and Lalitpur. All the eligible participants, who were residing in both mentioned child correction homes, aged 14 to 17 years, were included in the study because they left the correction homes once they completed 18 years of age. In this study, children below 14 years were excluded as they were not able to respond to the questions due to their still-growing intellectual capability [22]. For the qualitative study, a total of 10 key informant interviews were conducted, and data collection was stopped after the data saturation.

Data collection tools

To collect quantitative data from children (14–17 years), a structured, validated Nepali version of the DASS-21 (N-DASS21) scale was used. DASS-21 is a psychological screening instrument capable of differentiating symptoms of DAS. Depression, anxiety, and stress are three subscales, and there are 7 items in each subscale. Each item is scored on a 4-point Likert scale, which ranges from 0 (did not apply to me at all) to 3 (applied to me very much) [23]. Scores for DAS were calculated by summing the scores for the relevant items and multiplying by two. A face-to-face interview with children was carried out by a trained public health professional with the help of a psychosocial counselor for quantitative data. Pretesting was done in 10% (19) of the sample in the Child Correction Home of Biratnagar, Koshi Province, which was not selected as the study area, which helped to ensure face validity. For the validity of the study tools, a standard questionnaire that has been tested and validated in the national context was used, and for general information, questions were developed based on various previously conducted studies in close guidance with a subject expert and adequate literature review, ensuring the content validity of the tools. The NDASS-21 scale had shown good internal consistency of α for each scale (0.91 in the stress subscale, 0.79 in the anxiety subscale, and 0.93 in the depression subscale) in a study conducted in older adults aged ≥ 60 years in Nepal [23].

For the qualitative part, the Key Informant Interview (KII) guidelines were prepared based on the objective and were reviewed by the subject expert and then pre-tested. The pre-testing was done in a child correction home located in Biratnagar of Koshi Province, Nepal. The pre-testing also explored family conflict, history of abuse, and punishment linked to the poor mental health status of children residing in correction homes. The qualitative interviews during the pre-testing were conducted by the same public health professional who collected the data later from two correction homes in the main study. To collect qualitative data from wardens and psychosocial counsellors, the KII guideline was used. The trustworthiness in the qualitative study was maintained by member checking and keeping the audit trial. During the member checking, the researcher returns the transcript to the participants (warden and psychosocial counselor) after the interview to validate or verify the accuracy and interpretation of the data gathered. It ensures that the data and insights reflect the informant’s views and experiences accurately and helps build trust between the researcher and the participants. The translated word file was converted to a text file and imported to R Package for Qualitative Data Analysis (RQDA) for coding. All the translated files are coded independently by two coders, and the codes by both coders are observed, assessed the matched and non-matched codes and inter-coder reliability was calculated. Inter Coder Reliability (ICR) was assessed and was found to be 75%. The tools used in the study are provided in the supplementary file (Supplementary file_1).

Data management and analysis

A codebook was prepared, and the data collected was entered in Microsoft Excel 2019 using the validation criteria, which involves using a predefined range to minimize the errors and ensure the data are entered with accuracy. The data was imported to the Statistical Package for Social Sciences (SPSS) version 21.0 for analysis. For all relevant dependent and independent variables, percentage, frequency, mean, and standard deviation were calculated. Inferential statistical measures such as correlation were used to determine the strength of the association between independent variables and the dependent variable. The chi-square test was used for the analysis of categorical independent variables. The variables found to be statistically significant in bivariate analysis were included in the multivariate binary logistic regression for multivariable analysis to calculate the adjusted odds ratio (aOR). The variance inflation factor (VIF) test was performed among selected independent variables to manage the issue of multicollinearity. The VIF > 2 was taken as an indication of multicollinearity [24]. The p-values < 0.05 were taken as statistically significant.

For qualitative data, the key informant interviews were audio-recorded. The recordings were transcribed into Nepali and then translated into English. Further, the translated files were converted to text format and imported into the RQDA (R Package for Qualitative Data Analysis) software for coding and categorization of code. Braun and Clarke’s six-step thematic analysis was used for the qualitative data, where, after reading and re-reading the translated file, the codes were generated. The similar codes are merged to make code categories. The initial themes were made and reviewed by the research team to finalize the themes. Presentation of findings based on the theme was also done with appropriate verbatim. The themes generated are shown in Table 6.

Table 6.

Findings of the thematic analysis

Themes	Focus area	Sub themes	Key findings
Mental Health Status of Children in Conflict with Law	Perception and Experience towards children of age 14–17	Positive changes by continuous positive interactions with better understanding	Positive perception towards children as seen them evolve gradually into better people Females are more sensitive and full of emotions
			First-hand experience to understand their feelings and thoughts
			Many people assume that they are inherently “bad or troubled”; however they are dealing with significant challenges and are on the path of recovery
	Prevalence and possible causes for Mental Health problems	Childhood experiences and separation for mental health problems	Some of these children have experienced abuse, come from broken families and their past living status is usually leading to aggressiveness and making them anxious and depressed
			Children are sometimes depressed, anxious and at times stressed
			Being away from family members and their family background can be the major cause
	Areas for Improvement	Proper care and support for the prevention of mental health problems from government	Increase staff training and support Correction homes should be established in each district to fulfill the overall needs of children Timely checkup facilities for children Awareness program for reintegration

Results

The mean age of the respondents was 16.25 ± 0.89 years. The majority of the respondents were male (89.6%). One out of four respondents were school dropouts, while about half (47.8%) had a basic level of education (up to class 8). In terms of length of stay, more than half of the respondents had been there for over a year (52.7%), whereas rape/attempted rape (41.8%) was the most common offense. The majority of respondents lived with their parents prior to correction home (82.4%), and the majority of respondents’ parents were living together (81.9%), 26.9% of the respondents had a history of conflict in the family, and 17% had a history of being abused. More than half of them had a positive attitude towards correction homes (Table 1).

Table 1.

Sociodemographic and behavioral characteristics of the respondents

Characteristics	Category	Frequency	Percentage (%)
Age (in years) Mean ± SD = 16.25 ± 0.89 years)	≤ 16	89	48.9
	> 16	93	51.1
Sex	Male	163	89.6
	Female	19	10.4
Educational level	Basic Education	87	47.8
	Secondary level	49	26.9
	Drop out	46	25.3
Length of stay (years)	≤ 1	86	47.3
	> 1	96	52.7
Type of offense	Rape/attempted rape	76	41.8
	Theft	32	17.6
	Drug abuse	23	12.6
	Murder/attempt to Murder	29	15.9
	Others	22	12.1
Past living status	Parents	150	82.4
	Others	32	17.6
Marital status of parents	Together	149	81.9
	Divorced	11	6.0
	Separated	22	12.1
History of abused	Yes	31	17.0
	No	151	83.0
Family conflict	Yes	49	26.9
	No	133	73.1
Attitude towards correction home	Positive	99	54.4
	Negative	83	45.6

The majority (41.8%) of the respondents had a normal level of depression scale, whereas 9.9% had severe levels of depressive symptoms, and 6.6% had an extreme severe level of depressive symptoms. Nearly one out of four (23.6%) individuals’ anxiety scores were within the normal range, whereas 18.1% scored in the severe range, and 23.6% scored in the extreme severe range. Almost half of the respondents had a normal range of stress scores (47.8%), whereas 14.8% had experienced severe symptoms, and 4.4% of individuals reported to have extreme stress symptoms (Table 2).

Table 2.

Depression, anxiety, and stress among the respondents

DAS classification	Frequency	Percentage (%)
Depressive Symptoms Classification
Normal (0–9)	76	41.8
Mild (10–13)	39	21.4
Moderate (14–20)	37	20.3
Severe (21–27)	18	9.9
Extreme severe (≥ 28)	12	6.6
Anxiety Symptoms Classification
Normal (0–7)	43	23.6
Mild (8–9)	15	8.2
Moderate (10–14)	48	26.4
Severe (15–19)	33	18.1
Extreme severe (≥ 20)	43	23.6
Stress Symptoms Classification
Normal (0–14)	87	47.8
Mild (15–18)	25	13.7
Moderate (19–25)	35	19.2
Severe (26–33)	27	14.8
Extreme severe (≥ 34)	8	4.4

There was a significant association between sex (p = 0.010), education level (p = 0.019), and past living status (p = 0.012), family conflict (p = 0.011). Other variables like age, sex, and type of offense showed no association. A significant association of anxiety was observed with educational level (p = 0.039) and past living status (p = 0.011), which was observed with abuse (p = 0.027), isolation from family (p < 0.001), and family conflict (p = 0.010). There was no association observed with other variables like age, sex, marital relation of parents, and so on (Table 3).

Table 3.

Association of depression and anxiety with background factors

Variables	Depression status		P-value	Anxiety		P-value
	Depressed (%)	Non Depressed (%)		Anxiety (%)	No Anxiety (%)
Age interval
≤ 16	50(56.2)	39 (43.8)	0.581	33(37.1)	56 (62.9)	0.942
> 16	56 (60.2)	37 (39.8)		34 (36.6)	59 (63.4)
Sex
Male	91(55.8)	72(44.2)	0.053*	120(73.6)	43(26.4)	0.101
Female	15(78.9)	4(21.1)		15(78.9)	4(21.1)
Educational Level
Literate	86(63.2)	50(36.8)	0.019*	109(80.1)	27(19.9)	0.039*
Drop out	20(43.5)	26(56.5)		30(65.2)	16(34.8)
Lngth of stay (years)
≤ 1	49(57.0)	37(43.0)	0.743	35(40.7)	51(59.3)	0.304
> 1	57(59.4)	39(40.6)		32(33.3)	64(66.7)
Type of offense
Rape/attempted rape	48(63.2)	28(36.8)	0.255	24(31.6)	52(68.4)	0.215
Others	58 (54.7)	48(45.3)		43(40.6)	63(59.4)
Past living status
Parents	81(54.0)	69(46.0)	0.012*	109(72.7)	41(27.3)	0.011*
Others	25(78.1)	7(21.9)		30(93.8)	2(6.3)
Marital status of parents
Together	82(55.0)	67(45.0)	0.062	58(38.9)	91(61.1)	0.209
Other	24(72.7)	9(27.3)		9(27.3)	24(72.7)
History of abuse
Yes	21(67.7)	10(32.3)	0.239	61(40.4)	90(59.6)	0.027*
No	85(56.3)	66(43.7)		6(19.4)	25(80.6)
Family conflict
Yes	36(73.5)	13(26.5)	0.011*	58(43.6)	75(56.4)	0.010*
No	70(52.6)	63(47.4)		9(18.4)	40(81.6)
Isolation from family
Yes	102(63.0)	60(37.0)	< 0.001*	131(80.9)	31(19.1)	< 0.001*
No	4(20.0)	16(80.0)		8(40.0)	12(60.0)
Attitude towards correction home
Positive	69(69.7)	30(30.3)	0.215	21(44.7)	26(55.3)	0.194
Negative	37(44.6)	46(55.4)		46(34.1)	59(65.9)

^*Significance at p < 0.05

There was a significant association of stress with sex (p = 0.003), education level (p = 0.017), past living status (p = 0.014), marital status of parents (p = 0.026), history of punishment (p = 0.017), isolation from family (p = 0.035), and family conflict (p = 0.013). There was no association observed with other variables like age, length of stay, type of offense, and so on (Table 4).

Table 4.

Association between stress and background factors

Variables	Stress
	Stress (%)	No Stress (%)	p-value
Age
≤ 16	53(58.4)	37(41.6)	0.319
> 16	61(65.6)	32(34.4)
Sex
Male	79(48.5)	84(51.5)	0.003*
Female	16(84.2)	3(15.8)
Educational level
Literate	78(57.5)	58(42.5)	0.017*
Drop out	17(55.1)	29(44.9)
Length of stay (years)
≤ 1	58(67.4)	28(32.6)	0.159
> 1	55(57.3)	41(42.7)
Type of offense
Rape/attempted rape	44(57.9)	32(42.1)	0.324
Others	69(65.1)	37(34.9)
Past living status
Parents	99(66.0)	51(34.0)	0.014*
Others	14(43.8)	18(56.3)
Marital status of parents
Together	98(65.8)	51(34.2)	0.026*
Other	15(45.5)	18(54.5)
History of abuse
Yes	98(64.9)	53(35.1)	0.057
No	15(48.4)	16(51.6)
Isolation from family
No	16(80.0)	4(20.0)	0.035*
Yes	97(59.9)	65(40.1)
Family conflict
No	91(68.4)	42(31.6)	0.013*
Yes	22(44.9)	27(55.1)

^*Significance at p < 0.05

The odds of having depression were more than double among females in comparison to males (AOR = 2.25, CI = 1.68–7.47). This is convergent with the finding from the qualitative study. One of the key informants said, “I have had the opportunity to work closely with children in conflict with the law. Through my experience, compared to boys, we have found that girls experience more emotional difficulties. They frequently cry, exhibit depressing emotions, and struggle to fit in at the correction home setting.”

Similarly, the odds of having depression among the respondents who live with persons other than parents were 4.11 times more likely as compared to those who used to live with parents (AOR = 4.11, 95% CI = 1.37–12.27). The respondents who were isolated from the family were 9.63 times (AOR = 9.63, 95% CI = 2.36–35.20) more likely to get depression than those who were not isolated from the family. The odds of having depression among the respondents with a family history of conflict were 1.84 times (AOR = 1.84, 95% CI = 0.82–4.13) more likely as compared to those without conflict in the family. A warden said, “Many children who come here talk about frequent fights at home. Some say they ran away because they couldn’t bear the constant shouting and violence.” Another key informant said, “The majority of these children are from broken families that have experienced neglect or domestic abuse in the past. They share their painful stories, which exacerbates their emotional problems.”

The odds of having anxiety among respondents who live with others than parents were 5.21 times (AOR = 5.21, 95% CI = 1.25–11.72) more likely than those who live with their parents before coming to the correction home. The respondents who were isolated from the family were 12.57 times (AOR = 12.57, 95% CI = 3.58–44.17) more likely to have anxiety than those who were not isolated from the family, adjusting for other explanatory variables included in the model. The warden of the correction home said, “The children were found isolated from the family and had a history of frequent abuse and domestic violence in their home. They share that their parents were heavy alcohol drinkers and abusive. Even when they arrive here. They don’t talk, don’t engage in anything initially.”

It has been revealed that the odds of having stress were 5.43 times more likely in females than males (AOR = 5.43, 95% CI = 1.42–20.72). Similarly, the odds of having stress among respondents who were punished were 2.10 (AOR = 2.10, 95% CI = 1.13–4.41) times more likely than those who were not adjusting other explanatory variables included in the model. A psychosocial counselor said, “Extreme stress is seen in children who have experienced severe punishment in the past. They struggle to fall asleep, are afraid, and frequently feel uncared for” (Table 5).

Table 5.

Logistic regression of depression, anxiety and associated factors

Variables	Category	COR	95% (Lower- upper limit)		p- value		AOR	95% CI (Lower- upper limit)	p- value
Depression
Sex	Male Female	Ref 2.96	0.94–9.33		0.063		2.25	1.68–7.47	0.018*
Educational level	Literate Drop out	2.24 Ref	1.13–4.41		0.020		1.17	0.08–3.62	0.157
Past living Status	Parents Others	Ref 3.04	1.24–7.46		0.015		4.11	1.37–12.27	0.011*
Isolation from family	Yes No	6.80 Ref	2.17–21.28		0.001		9.63	2.36–35.20	0.001*
Family conflict	Yes No	2.49 Ref	1.23–5.11		0.013		1.84	0.82–4.12	0.013*
Anxiety
Educational level	Literate Drop out	2.15 Ref	1.03–4.50		0.042		1.84	0.08–4.15	0.144
Past living Status	Parents Others	Ref 5.64	1.29–24.68		0.022		5.21	1.25–11.72	0.01*
History of Abuse	Yes No	2.350 Ref	0.773–7.14		0.013		2.031	0.51–8.11	0.316
Isolation from family	Yes No	6.34 Ref	2.17–16.28		0.001		12.57	3.58–44.17	0.001*
Family conflict	Yes No	3.52 Ref	1.29–9.55		0.014		2.04	0.65–6.43	0.223
Stress
Sex	Male Female	Ref 5.67	1.59–20.20		0.007		5.43	1.42–20.71	0.013*
Educational level	Literate Drop out	2.29 Ref	1.15–4.56		0.018		1.15	0.53–2.53	0.721
Past living Status	Parents Others	Ref 2.77	1.20–6.39		0.017		2.32	0.86–6.23	0.096
Marital status of parents	Together Divorced	Ref 2.46	1.09–52.00		0.029		1.79	0.86–6.24	0.219
Isolation from family	Yes No	6.34 Ref	2.17–16.28		0.001		2.56	3.58–44.17	0.088
Family conflict	Yes No	3.52 Ref	1.29–9.55		0.014		1.86	0.65- 6.43	0.119
History of punishment	Yes No	2.33 Ref	1.15–4.69		0.019		2.12	1.18–4.02	0.012*

^*Significance at p < 0.05

Table 6 illustrates the list of codes obtained from thematic analysis of the qualitative study. Most of the informants were supportive of children and had a positive attitude towards them. They were happy to see their positive changes and were concerned about their background and future.

A key informant said, “Through my experience, I have come to understand that many of these children have underlying mental health issues that have not been addressed, and this has contributed to their involvement in criminal activities as well. Being depressed, anxious and stressed is most commonly seen. Possible causes of mental health problems among children in conflict with the law include a history of abuse or neglect, punishment, marital status of their parents, and family conflict. Also, being away from their family led to major emotional disturbance, which may be a consequence of all these mental health problems.” The broken family was also the reason for poor mental health status. One of the psychosocial counselors said, “Children from broken families tend to have a higher level of anxiety and depression. They often ask us, ‘Why did my parents leave me?’.

Discussion

This study revealed a high prevalence of depression (58.2%), anxiety (76.4%), and stress (52.2%) among the children (14–17 years). A study among children in conflict with law in Kenya also showed high thought disturbance in boys (58.9%). Clinically significant caution levels were highest for somatic complaints (66.7%), angry-irritable behavior (54.2%), and depression-anxiety (45.1%) [21]. Similarly, a comparative study in India also revealed that children in conflict with the law had significantly higher levels of emotional problems as compared to the children not in conflict with the law. The findings of this study are also consistent with a study on school-going adolescents in Chandigarh, which also reported the prevalence of depression, anxiety, and stress as 65.53%, 80.85%, and 47.02%, respectively [25]. This may be because of the similar demographic characteristics, including the age group and cultural background, of the study populations in spite of the difference in study setting. Adolescents in school often experience high levels of distress brought about by academic pressure, competitiveness in examinations, and societal expectations, which could be the reason why high levels of depression, anxiety, and stress (DAS) were noted in adolescents [26]. In contrast, the study conducted on inmates in district jail, Rohtak, Haryana, showed that the total prevalence of depression was 18.5%, whereas anxiety was 8% and stress was 7.3% [27]. These differences may be due to the age gap between children (14–17 years) and inmates, where adults have mature minds and can deal with problems compared to children.

Additionally, the present study revealed an anxiety prevalence of 76.4%, which agrees with another study conducted in Abha, where the prevalence rate of anxiety was reported to be 66.2% [28]. The concurrence of the studies demonstrates that anxiety among adolescents is a widespread issue, which could be driven by school pressure, peer pressure, and parental expectations [28]. The present study found females are associated with more depression. Similar to this study, a study among children in conflict with the law in Kenya also revealed gender differences, with female participants reporting higher levels of somatic complaints, suicidal ideation, and traumatic experiences [21]. Similarly, the study in the urban municipality found that women were 1.8 times more likely to have anxiety (AOR = 1.82, 95% CI = 1.23–2.71), a finding that is similar to this study (AOR = 1.83, 95% CI = 0.812–4.153) [29]. The reason may be that women tend to enter puberty earlier than men, making them emotionally and psychologically vulnerable at an earlier stage. Literature shows that this gender disparity in depression is present throughout the life course [30]. Further, variations in gender can be influenced by the effect of such factors as age, place, education, and household prosperity [31]. A study among adolescents in public schools found that females were 1.7 times more likely to be stressed (OR = 1.786, 95% CI: 0.862–6.238), which is in line with the results of this study. Furthermore, adolescents who were abused were twice as likely to be stressed (OR = 2.08, 95% CI = 1.05–4.10) [32]. This is in line with the fact that adolescent girls are more sensitive to psychologic stressors and more self-aware of affective changes, making them more vulnerable to anxiety and stress [26].

This study among children (14–17 years) in conflict with the law revealed a significant association between family conflict and the prevalence of depression, anxiety, and stress. This is in line with a research study that was conducted among adolescents from two secondary schools in Dharan, where one-third of the students with family conflict had mental illness [33]. Similarly, a study from Chandigarh Indians noted a greater risk of mental disorders among adolescents with family conflict [26]. Family conflict may result in parental neglect, reducing positive parent–child interactions that eventually result in detrimental mental outcomes [34].

Furthermore, in the present study, it was seen that children (14–17 years) who were staying with others than their parents were 2.3 times more likely to be developing stress than children staying with their parents, although the association was not found to be significant. A study among children in conflict with law in Jharkhand, India, also showed the significant association between living arrangement and stress. The children who used to stay with others than their parents were more likely to have stress [20]. On the other hand, a study in Kathmandu found that the children staying away from their parents had significantly increased stress (AOR = 1.70, 95% CI = 1.11–2.61) [25]. Similar findings were also made by Arif et al. [35] in India, Uttar Pradesh. One of the possible reasons behind this trend is that children who are separated from their parents may spend extended periods of time lonely, missing opportunities for meaningful familial interaction and emotional support [36]. This loneliness may lead to them feeling disconnected and isolated, which would increase their stress further [37].

The current study identified that children (14–17 years) with a history of punishment were 2.1 times more likely to be stressed compared to children without punishment. This is also consistent with a finding in a study conducted in Brazil, whereby children who had been punished had significantly higher probabilities of having mental disorders [36]. The psychological distress resulting from punishment can stem from feelings of shame, fear, and loss of self, thereby contributing to the levels of stress [38]. This study showed the strong association between family isolation and depression, anxiety, and stress prevalence. This aligns with arguments made in literature that residing outside the family and alone in institutions places people in contact with fewer social contacts and hence more at risk for mental disorders [39]. The qualitative information agreed with such findings as well, illustrating children in conflict with the law as having high anxiety levels, stress, and depression. Most of the participants came from dysfunctional families, had a background of abuse and punishment, and lived with relatives, friends, or guardians instead of their parents.

This study has several notable strengths. As a mixed-methods study, it effectively identifies factors associated with the mental health status of children in conflict with the law residing in correction homes. The qualitative findings offer deeper insights into the underlying causes of poor mental health, enriching the overall understanding of the issue. Additionally, the study utilizes validated standard tools, enhancing the reliability of its findings, and contributes significantly to a field with limited existing research.

However, some limitations must be acknowledged. The findings are based on data from only two correction homes in Bagmati Province, limiting their generalizability to other regions. Additionally, reliance on self-reported data may introduce recall bias potentially affecting response accuracy. Gender bias in reporting psychiatric symptoms and social desirability bias in interviews with caretakers may also occur. Future research should further explore the challenges faced in child correction homes and examine the efforts made to improve the mental health of the children (14–17 years) residing there.

Conclusion

Most children (14–17 years) in conflict with the law at the Bagmati Province correction home experience high levels of depression, anxiety, and stress, with key contributing factors including past living status, isolation, family conflict, and experiences of abuse or punishment. Depression is more among female, those living with others than parents in the past, those isolated from family, and children (14–17 years) with history of family conflict, while anxiety is more associated with those living with others than parents in the past and those children who were isolated from the family. Stress is more associated with female and children with history of punishment. The study emphasizes the need for government follow-up mechanisms in correction homes to address underlying issues and prevent future criminal involvement. Regular family visits should be facilitated to reduce isolation, and families should receive support to better meet children’s needs through education, healthcare, and protective policies. More studies are required to establish the causes of mental illness and its preventive measures among the study population on a larger scale.

Abbreviations

CCH

Child Correction Home

CI

Confidence Interval

CRC

Convention on the Rights of the Children

DAS

Depression, Anxiety, and Stress

ICR

Inter Coder Reliability

IRC

Institutional Review Committee

KII

Key Informant Interview

RQDA

R Package for Qualitative Data Analysis

SPSS

Statistical Package for Social Sciences

VIF

Variance Inflation factor

Authors’ contributions

Conceptualization: LG, AG, AB Data curation: AG Formal analysis: LG, AG, AB Funding acquisition: LG, AG Methodology: LG, AG Writing – original draft: LG, AB Writing – review & editing: LG, AG, AB.

Funding

The authors received no funding for this study.

Data availability

Data will be available from the corresponding author under reasonable request.

Declarations

Ethics approval and consent to participate

All methods of this study were carried out under the Helsinki Declaration of ethical principles for medical research involving human subjects. Ethical approval was taken from the Institutional Review Committee (IRC) of NEHCO-Nepal, Manmohan Memorial Institute of Health Sciences (Ref: 79/137). Approval was taken from the Ministry of Women, Children, and Senior Citizens and the Secretariat of the Central Child Justice Committee, Shreemahal, Lalitpur, and managers of the respective Child Correction Home. The legal guardians were requested to provide written informed consent prior to data collection. The participants were informed about the objectives, methods, and anticipated benefits of the study before providing assent. The participant had the right to withdraw from the study at any point, if they wished, without any negative repercussions. The anonymity of the identity of the participants and Child Correction Homes were ensured. Privacy and confidentiality of collected information were ensured throughout the process of data collection and dissemination. All the children (14–17 years) whose mental health status was severe and extremely severe were referred for clinical diagnosis and treatment.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.