Prevalence and predictors of emotional and behavioral problems among institutionalized children in Kandy District, Sri Lanka

Child Abuse & Neglect 103 (2020) 104435

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Research article

Prevalence and predictors of emotional and behavioral problems among institutionalized children in Kandy District, Sri Lanka

T

Pabasari Ginige, Anuradha Baminiwatta*, Hasara Jayawardana Department of Psychiatry, Faculty of Medicine, University of Peradeniya, Sri Lanka

A R T IC LE I N F O

ABS TRA CT

Keywords: Institutionalized children Mental health behavior Sri Lanka

Background: Child care institutions (CCIs) in Sri Lanka (SL) provide residence to over 14,000 children. These children have a high risk of developing psychological problems. However, there has been no prior scientific inquiry into mental health issues of institutionalized children in SL. Objective: To investigate the emotional and behavioral problems of children living in CCIs in Kandy District, and to explore associated factors. Participants and setting: Ten CCIs in Kandy District were selected and all children aged 6–18 years were recruited. Methods: Child Behavior Checklist (6–18) –Sinhala version (CBCL-S) was filled by the caregivers, and pertinent problem scores were derived. Relevant socio-demographic data were also collected. Results: A total of 259 children participated. Of them, 66.8 % were female. The mean age was 13.9 years. The average duration in care was 4.3 years. Clinical levels of behavioral problems were found in 14 % of children, whereas 7% were borderline. Externalizing problems like rulebreaking and aggression were more common (23.3 %) than internalizing problems (6.6 %). Male children exhibited more behavioral problems (p = 0.034). Present age, age on admission, duration in care, history of sexual abuse, institutional transfers and frequency of family contact were not associated with behavioral problems. Conclusions: Institutionalized children showing high levels of externalizing problems may be a reflection of disturbed psychosocial development. However, internalizing problems may not be readily recognized, partly due to the shortage of trained caregivers in SL. Educating caregivers to detect and refer children with behavioral problems to psychiatric services is recommended.

1. Introduction 1.1. Early life deprivation Emotional, social and physical deprivation during early life has been linked to a wide array of acute and long-term mental health consequences (Sonuga-Barke et al., 2017; St. Petersburg-USA Orphanage Research Team, 2008). Pioneering observations on the deleterious effects of childhood deprivation due to institutionalization by Bowlby and colleagues (Bowlby, Miller, & Winnicott, 1939) have been corroborated by a plethora of subsequent research (Johnson, Browne, & Hamilton-Giachritsis, 2006; Sonuga-Barke et al., 2017). Disturbed attachment (Zeanah, Smyke, Koga, & Carlson, 2005) and self-concept (Vacaru, Sterkenburg, & Schuengel, 2018) have been postulated to mediate some of these mental health issues. Although children reared in institutions are conventionally

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Corresponding author at: 31, Hospital Road, Rambukkana, Sri Lanka. E-mail address: [email protected] (A. Baminiwatta).

https://doi.org/10.1016/j.chiabu.2020.104435 Received 12 March 2019; Received in revised form 15 February 2020; Accepted 24 February 2020 0145-2134/ © 2020 Elsevier Ltd. All rights reserved.

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deemed to be orphans, recent studies from different regions of the world have revealed that over 80 % of children living in residential care have at least one living parent (Csaky, 2009; Rasanayagam et al., 2013). The common reasons for placing these children in institutional care included poverty, disability, discrimination and neglect (Csaky, 2009). The psychological damage ingrained by early life deprivation has been shown to persist into adult life, even if a nurturing environment is provided subsequently through alternative services such as adoption (Sonuga-Barke et al., 2017). 1.2. Unfavorable conditions in child care institutions In addition to the effects of initial adversity, the unfavorable environment in child care institutions per se is likely to adversely influence the psychosocial development of these children (Baldwin et al., 2019). Higher rates of physical, emotional and verbal child abuse have been reported in child care institutions worldwide (Pinheiro, 2006). Exposure to such abuse may in turn instigate problematic behavior in children (Segura, Pereda, Guilera, & Abad, 2016). In light of this evidence, international organizations overseeing child welfare, such as the United Nations Children's Fund, earlier known as United Nations International Children's Emergency Fund (UNICEF), and Save the Children, have urged governments to prevent children being sent to care homes and to take measures to direct these children to alternative avenues of care such as foster homes (Csaky, 2009; UNICEF, 2010). However, many developing countries like Sri Lanka have failed to develop proper strategies for deinstitutionalizing these children (Rasanayagam et al., 2013). 1.3. International data on prevalence Numerous studies conducted around the globe have demonstrated that mental health problems are more prevalent among institutionalized children compared to children in the community (Ayaz et al., 2012; Erol, Simsek, & Munir, 2010; Gearing, MacKenzie, Schwalbe, Brewer, & Ibrahim, 2013). The prevalence rates in those studies have been based on different screening questionnaires and diagnostic criteria. The most widely used questionnaires for the assessment of behavioral problems in such studies were the Child Behavior Check List (CBCL) and the Strengths and Difficulties Questionnaire (SDQ). Prevalence rates of clinically significant behavioral problems among institutionalized children, based on total problem scores on the CBCL, have ranged from 15 % in Turkey to 47 % in the United States and 72 % in Germany (Burns et al., 2004; Erol et al., 2010; Schmid, Goldbeck, Nuetzel, & Fegert, 2008). In contrast, lower rates such as 7.5 % and 13.8 % have been reported in the community (Erol et al., 2010; Ginige et al., 2014). However, these prevalence data were based on studies having many other differences among them such as in sample selection, data collection, analysis and interpretation methods. 1.4. Associated factors Analysis of predictors of behavioral problems among children in care homes has demonstrated several predictive factors, some remaining consistently significant across many studies; they include male gender, older age, duration of institutional care, younger age at the time of entry, a history of maltreatment prior to admission and transfers between institutions (Ayaz et al., 2012; Erol et al., 2010; Gearing et al., 2013). Externalizing problems such as rule-breaking and aggression have been demonstrated with higher prevalence among boys in institutional care (Gearing et al., 2013). 1.5. Sri Lankan context In Sri Lanka, according to a situational analysis conducted in 2013, there were 14,179 children living in 414 child care institutions around the island (Rasanayagam et al., 2013). UNICEF estimates from 2007 placed this figure even higher, around 21,100. Unfavorable conditions at home such as parental separation, alcoholism, lack of a supportive family environment, maternal migration and a risk of sexual abuse particularly for female children, were identified as the commonest reasons for institutionalization (Rasanayagam et al., 2013). Furthermore, about 15 % of these admissions were pursuant to court orders. The three-decade civil war and natural disasters may also have played a part in driving many children into out-of-home care in SL (Chandradasa & Kuruppuarachchi, 2017). Until recent years, child abuse and protection of children’s rights remained neglected topics in SL (de Zoysa, 2002). However, with the establishment and active engagement of the National Child Protection Authority and the Department of Probation and Child Care Services, the welfare of children in SL, including that of children living in care homes, has gained more recognition (Department of Probation & Child Care Services, 2019; National Child Protection Authority, 2019). The latter authority, consonant with the Orphanages Ordinance, registers and regulates the child care institutions located around the country. While most of these children’s homes are equipped with acceptable basic facilities and infrastructure for these children, a shortage of trained caregivers to supervise children has been highlighted (Rasanayagam et al., 2013). No prior literature on psychosocial issues among institutionalized children in Sri Lanka was available. Much of the mental health research conducted on children in SL have concerned post-traumatic effects of war and natural disasters (Catani, Jacob, Schauer, Kohila, & Neuner, 2008; Wickrama & Kaspar, 2007). A few studies have investigated the prevalence of behavioral problems among pre-school and school children in SL. In one study which investigated the prevalence of externalizing problems among preschool children using the CBCL, the estimated prevalence was 19.2 % (Samarakkody, Fernando, McClure, Perera, & De Silva, 2012). Male gender, low socio-economic status and parental loss were reported as significant predictors of externalizing problems. In another 2

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study conducted on school children aged 7−11 years, the prevalence of total problems, externalizing problems and internalizing problems based on the CBCL were 13.8 %, 8.8 % and 8.8 % respectively (Ginige et al., 2014). Though the situational analysis cited above provides a general idea about the current status of child care institutions in SL, the depth and the breadth of the issue remains poorly understood, due to the paucity of related research. Hence, this study aims to broaden our understanding of the social background and the behavioral problems prevailing among institutionalized children. This unprecedented insight gained into the mental health of institutionalized children in SL will be useful for the local authorities for formulating and modifying policies to ensure better short-term and long-term outcomes for these underprivileged children. 2. Method 2.1. Sample Kandy District is one of the 25 districts in SL, located in the central region of the island. At the time of this study, there were 20 child care institutions in Kandy District, registered under the Department of Probation and Child Care Services, accommodating about 550 children, who would constitute the study population (Rasanayagam et al., 2013). In order to save the cost and time of travelling to 20 different locations within Kandy District, the researchers opted to draw a sample from this population. In order to select this sample, background data on the number of children in each of the 20 institutions were gathered from their respective matrons over the phone, prior to commencement of the study. Although only children between the ages of 6 and 18 were to be recruited in order to preserve the validity of the research instrument, as information on the age structure of the study population was inadequate, the population size was assumed to be 550. The minimum sample size required to make valid inferences about this study population was calculated using the following equations. n = N*X/(X + N – 1) X = Zα/22*p*(1-p) /MOE2 Zα/2is the critical value at α/2 ( = 1.96), MOE is the margin of error ( = 5%), p is the sample proportion ( = 50 %), and N is the population size ( = 550). n is the sample size corrected for population. The resultant sample size, after 10 % correction for possible non-responders, was 253. It was assumed that recruiting all the residents from 10 out of the 20 institutions would achieve this sample size. However, the number of residents in these 20 homes showed a wide variation, ranging from 5 to 85, the average being 27.5. Therefore, categorizing these institutions based on the number of residents and choosing a proportionate number of institutions from each category was deemed a more suitable method of selection. As facilities and other conditions in institutions may vary with their size, potentially affecting the behavioral outcomes of their residents, this proportionate allocation method was preferred by the researchers. Accordingly, the 20 children’s homes were categorized based on their size into “small” (1–15 residents), “medium” (16–40 residents) and “large” (more than 40 residents) institutions. A proportionate number of children’s homes from each of these categories was randomly selected by drawing lots. The 10 randomly selected care homes thus included 4 small institutions, 4 medium-sized institutions and 2 large institutions, with an estimated total of 273 residents. Later, during the data collection process, children who were less than 6 years or over 18 years were excluded from the study. 2.2. Measures Child Behavior Check List-S (CBCL-S), the validated Sinhala language version of a widely used tool in the assessment of emotional and behavioral problems of children aged between 6 and 18 was used with the permission of the original author (Achenbach, 2019; Senaratna, Perera, & Fonseka, 2008). CBCL-S has 113 items related to a wide array of emotional and behavioral problems in the child. Validity and reliability statistics comparable to the English version have been reported for the Sinhala version. A sensitivity of 90 % and a specificity of 88 % for boys, and a sensitivity of 89 % and a specificity of 92 % for girls have been demonstrated among Sri Lankan children. The Area under the curve for the CBCL-S was 0.95 indicating an excellent criterion validity. Although the internal consistency of the CBCL-S, as shown by a Cronbach alpha of 0.74, was lower compared to the English version (Cronbach alpha = 0.9), it fell within satisfactory limits. Test-retest reliability, as demonstrated by an intra-class correlation coefficient of 0.8 and a Cohen’s kappa of 0.86, was excellent. Inter-interviewer reliability was also satisfactory (Cohen’s kappa = 0.78). CBCL is generally administered to a respondent who knows the child well (usually a parent or other close caregiver). Background information indicated that on average about 12 children in Sri Lankan child care institutions were looked after by one caregiver. However, researchers noted that in most of the institutions where the study was carried out, each child was not allocated to one particular caregiver. Hence, a caregiver who has regular contact with the child, as recommended by the matron in charge of the care home, was recruited in most instances. The questionnaire was completed by the caregiver, responses being marked on a 3-point Likert scale for each item (not true = 0, somewhat or sometimes true = 1, and very true or often true = 2). The researchers decided not to include the self-report version of the CBCL, known as the Youth Self Report, as it is applicable for only older children (11–18 years) and has not been formally validated in the local language. Several measures of problematic behavior are subsequently derived from these responses; three broad-band scales (Internalizing, Externalizing, and Total Problems) and two types of narrow-band scales (Syndrome scales and DSM-oriented scales) are generated. 3

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The Total problems score indicates the overall behavioral status of the child. Classification of problems into syndrome scales elucidates a wide arrange of emotional and behavioral problems of each child. The syndrome scales include, (1) Anxious/depressed, (2) Withdrawn/depressed, (3) Somatic complaints, (4) Social problems, (5) Thought problems, (6) Attention problems, (7) Rule-breaking behavior and (8) Aggressive behavior. Externalizing problems score is the sum of scores on rule-breaking and aggressive behavior scales, whereas the sum of anxiousdepressed, withdrawn-depressed, and somatic complaints scales form the internalizing problems score. CBCL also generates another form of narrow-band scales known as DSM-oriented scales, where items on the CBCL found to be consistent with different diagnostic categories of the Diagnostic and Statistical Manual of Mental Disorders (DSM) are used to produce scores on 9 such narrow-band scales. The DSM-oriented scales comprise, (1) Depressive problems, (2) Anxiety problems, (3) Somatic problems, (4) Attention deficit hyperactive disorder (ADHD), (5) Oppositional Defiant Disorder (ODD), (6) Conduct disorder, (7) Sluggish cognitive tempo, (8) Obsessive Compulsive Disorder (OCD) and (9) Stress problems. 2.3. Analysis Achenbach System of Empirically Based Assessment (ASEBA) software authorized by the original author was used for data entry as well as for the interpretation of problem scores. This software converts the raw scores on each scale to standard t scores, based on normative data for age and gender. Normative data for Sri Lankan children were not available. The t scores are scaled so that 50 is average for the child’s age and gender, with a standard deviation of 10 points. Cut-offs for the t scores prescribed by the original author were used in classifying each score as “clinical”, “borderline” or “normal” (Achenbach & Rescorla, 2001). For narrow-band scales (Syndrome scales and DSM-oriented scales), t scores of 65–69 are in the borderline clinical range, which indicates a possible need for professional help. Scores above 69 are in the clinical range, indicating a probable need for professional help. For broad-band scales (Internalizing, Externalizing, Total Problems), t scores of 60–63 are in the borderline clinical range, indicating a possible need for professional help. Scores above 63 are in the clinical range, indicating a probable need for professional help. Further statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) Software version 22. Prevalence data were assessed using descriptive statistics. The effect of gender on behavioral scores was demonstrated on a contingency table and tested for significance using Chi-square tests. A multiple regression analysis was conducted to investigate the effect of potential predictors on Internalizing, Externalizing and Total Problems scores separately. Seven such predictor variables- (1) gender, (2) present age, (3) age on admission, (4) duration of care, (5) a history of sexual abuse, (6) institutional transfers and (7) frequency of family contact- were analyzed. Prerequisite assumptions for a multiple regression model were tested on the statistical software. Normality of distribution of problem scores was ascertained using Shapiro Wilk test. Residuals were also found to be normally distributed on the normal P-P plot. Scatter-plot of residuals confirmed homoscedasticity of data. No outliers were noted on the scatter-plot. Multicollinearity of independent variables was excluded using a correlation matrix. Statistical significance in all the foregoing tests was inferred against a p value of 0.05. 3. Results 3.1. Socio-demographic background A total of 259 children aged 6–18 years living in 10 orphanages in Kandy District participated in the study. Of them, 66.8 % were female. The mean age of the sample was 13.9 years (SD = 2.7). The age and gender constitution of the sample is further demonstrated in Table 1. The mean age at the time of admission to a care home was 8.8 years (SD = 4). Children who had been living in care homes for durations ranging from 1 month up to 15 years were included in the sample; the average duration of time spent in care homes was 4.3 years (SD = 3.4). 44 children (16.9 %) had previously been in a different institution before being transferred to the current location. Among the reasons for institutionalization, the predominant cause was an unfavorable family situation (52.5 %). While 27 children (10.4 %) were admitted following exposure to child sexual abuse, pursuant to court orders, 25 children (9.6 %) had been found abandoned prior to admission. The rest of the sample (27.5 %) comprised children institutionalized for various other reasons including behavioral issues of the child. Homosexual behavior of the child was reported as the reason for institutionalization in 5 cases. Both parents of 145 (56 %) subjects were known to be alive. Only one parent was alive while the other was known to be deceased Table 1 Age and gender constitution. Age group (years)

Males

Females

Total

Percentage (%)

6–9 10–12 13–15 16–18 Total

15 17 29 25 86

12 23 70 68 173

27 40 99 93 259

10.4 15.4 38.2 35.9 100 %

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Table 2 Mean scores on broad-band and narrow-band scales and the corresponding percentages of children falling into clinical, borderline and normal categories (N = 259). Problem scale

Mean score (SD)

Clinical (%)

Borderline (%)

Normal (%)

Broad-band scales Total problems Externalizing problems Internalizing problems

49.2 (12.2) 51.9 (13.2) 47.6 (10.1)

14 23.3 6.6

7 6.2 4.7

79 70.4 88.7

52.9 55.8 51.7 54.4 53.2 55.4 56.3 56.8

(5.3) (7.9) (4.0) (6.3) (5.1) (8.8) (8.4) (9.2)

1.9 7 1.2 3.1 2.3 7 9.3 13.2

2.7 5.4 0.8 6.2 2.3 7 8.2 9.3

95.3 87.5 98.1 90.7 95.3 86 82.5 77.4

53.7 53.3 51.7 54.6 55.4 58.3 53.8 53.2 54.1

(5.9) (5.3) (4.2) (6.8) (8.1) (10.3) (6.3) (5.4) (6.3)

2.7 1.9 1.2 4.3 10.5 16.7 5.4 1.2 2.7

3.1 3.9 1.6 6.6 7.8 10.9 3.1 3.1 6.2

94.2 94.2 97.3 89.1 81.7 72.4 91.4 95.7 91.1

Narrow-band scales Syndrome scales Anxious/depressed Withdrawn/depressed Somatic complaints Social problems Thought problems Attention problems Rule-breaking behavior Aggressive behavior DSM-oriented scales Depressive problems Anxiety problems Somatic problems ADHD ODD Conduct Sluggish cognitive tempo OCD Stress problems

Note: Mean t scores on each scale are reported along with standard deviations within parentheses. For broad-band scales, t scores of 60–63 were considered borderline while scores above 63 were considered clinical. For narrow-band scales, t scores of 65–69 were considered borderline while scores above 69 were considered clinical.

in 57 (22 %) subjects. In 47(18.2 %) cases, one parent was alive while the status of the other parent was unknown. Both parents were known to be deceased in only 4 (1.5 %) cases. For six children (2.3 %), whether the parents were alive or not was not known. Data on the frequency of visits by family members revealed that 63.6 % of children had contact with a family member (parent, sibling or grandparent) at least once every 3 months.

3.2. Emotional and behavioral problems Based on caregiver reports, 14 % of the children (n = 36) in orphanages had a clinically significant level of emotional and behavioral problems, indicating a probable need for professional help. While 7% (n = 18) fell into the borderline category implying a possible need for professional help, the rest (79 %) were considered normal in terms of the sum of problems. In this sample, clinically significant externalizing problems were observed in 23.3 % of the children whereas only 6.6 % of the children demonstrated clinical levels of internalizing problems. As demonstrated by the breakdown of behavioral problems into syndrome scales in Table 2, rule-breaking and aggressive behavior were the commonest behavioral problems reported by caregivers. DSM-oriented scales also signify the higher prevalence of problems in the conduct and oppositional defiant domains. However, only 12 children (4.6 %) had come into contact with mental health services at any point in their life.

3.3. Associated factors Behavioral problems were found to be more common among male children compared to their female peers (Table 3). While 19.8 % of boys exhibited clinical levels of problematic behavior based on total problems, the corresponding percentage for girls was 11 %. Both externalizing and internalizing problems were more common among boys. These gender differences were found to be statistically significant. A multiple regression analysis was performed to investigate the effects of several hypothesized predictors on behavioral problem scores (Table 4). The low R2 value of the regression model (R2 = 0.037) indicated that these predictor variables all together failed to sufficiently explain the variability of problem scores. However, male gender alone was found to be a significant predictor of scores on externalizing (p = 0.015) and total problem scores (p = 0.034). None of the other predictors (present age, age on admission, duration of care, history of sexual abuse, institutional transfers and frequency of family contact) showed such individually significant associations.

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Table 3 Proportions of boys and girls exhibiting clinical, borderline and normal range behavior on the three broad-band scales (N = 259). Behavior category

Clinical Borderline Normal Total

Total problems

Externalizing problems

Internalizing problems Boys

Girls

11 (12.8 %) 6 (7%) 69 (80.2 %) 86 (100 %) χ2 = 10.1*, p = 0.006

6 (3.5 %) 6 (3.5 %) 161 (93.1 %) 173 (100 %)

Boys

Girls

Boys

17 (19.8 %) 8 (9.3 %) 61 (70.9 %) 86 (100 %) χ2 = 5.3, p = 0.07

19 (11 %) 10 (5.8 %) 144 (83.2 %)

27 32 (31.4 %) (18.5 %) 7 10 (8.1 %) (5.8 %) 52 131 (75.7 %) (60.5 %) 86 173 (100 %) (100 %) χ2 = 6.3*, p = 0.037

173 (100 %)

Girls

Note: The frequencies of boys and girls classified into each behavior category are reported. Percentages calculated for each gender separately appear within parentheses, Chi square test results comparing behavioral problems of girls and boys are reported separately for each broadband scale at the bottom. * =p < 0.05. Table 4 Multiple linear regression analysis of predictors of emotional and behavioral problems among institutionalized children (N = 220). Variable

Total problems

Externalizing problems

Internalizing problems

1. 2. 3. 4. 5. 6. 7.

3.95* (1.86) −0.05 (0.36) 0.41 (0.31) 0.19 (0.32) −1.59 (2.85) 3.84 (2.52) 0.02 (1.77)

4.85* (1.97) −0.12 (0.39) 0.48(0.33) 0.12 (0.34) −1.47 (3.03) 3.66 (2.68) 0.93 (1.89)

2.50 (1.50) 0.15 (0.29) 0.15 (0.25) −0.26 (0.26) −0.93 (2.31) 3.01 (2.04) −1.16 (1.44)

Gender Present age Age at admission Duration of care Sexual abuse History of transfers Family contact frequency

Note: Unstandardized regression coefficients (standard errors) are reported for each independent variable as a predictor of the three broad-band scale scores separately. R2 for models predicting total problems, externalizing problems and internalizing problems were 0.037 (F(7,212) = 1.154, p = 0.33), 0.047 (F (7,212) = 1.49, p = 0.17) and 0.042 (F(7,212) = 1.32, p = 0.24) respectively, indicating a poor model fit in each case. For gender, male = 1, female = 0. Present age, age at admission and duration of care were recorded in years. For sexual abuse and transfers, yes = 1 and 0 = no. Exclusion of 39 cases with missing data in at least one of the dependent or independent variables has led to the sample size of 220 for this regression model. * =p < 0.05.

4. Discussion Children brought up in care institutions are at a greater risk of mental health problems compared to children growing up with families (Ayaz et al., 2012; Erol et al., 2010; Gearing et al., 2013). However, this is the first time the mental health status of children living in institutional care in SL was investigated. About 1 in 7 children in this sample exhibited behavioral problems in the clinical range, warranting professional help. A similar prevalence rate (13.8 %) has been previously observed among 7−11 year old school children in Kandy District, SL in 2014 (Ginige et al., 2014). Although the same questionnaire was used in both these studies, several differences in methodology restrict making valid comparisons between them. In the precedent study, the informant was a parent, and the data collection took place in the setting of a parent-teacher meeting. Informant-related variations in the ratings on behavior assessment scales have already been documented (Doku & Minnis, 2016; Erol et al., 2010). A review of literature based on European and American populations revealed remarkably higher prevalence rates of clinical range problems among institutionalized children. For instance, prevalence rates of 44 %, 47.9 % and 72 % have been reported among children in residential care in the UK (Blower, Addo, Hodgson, Lamington, & Towlson, 2004), USA (Burns et al., 2004) and Germany (Schmid et al., 2008) respectively. Crosscultural variations in the research instrument and its cut-offs may have partly contributed to this discrepancy of prevalence rates. Sociocultural and legal thresholds for placing children in residential care, and the primary reasons for institutionalization also vary between countries. The USA study which showed a prevalence of 47.9 % was conducted on children placed under the care of child welfare agencies after reported child maltreatment (Burns et al., 2004). In comparison, a history of child abuse was reported in only 10.4 % of the children in the present study. Therefore, the remarkably higher prevalence of behavioral problems reported in Western studies can be, at least in part, attributed to the larger proportion of abused children in the study population. Nevertheless, there are some studies where a prevalence rate comparable to the current study has been reported from other parts of the world; a prevalence of 15 % was reported among Turkish children in institutions based on caregiver reports of CBCL (Erol et al., 2010). While there is a scarcity of comparable data from the South Asian region, a prevalence rate of 16.8 % has been reported in India, albeit using a different assessment tool (Kaur, Vinnakota, Panigrahi, & Manasa, 2018). 6

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Although the prevalence rate for total problems among institutionalized children was not remarkably different from that of school children in Kandy District, a preponderance of externalizing problems was observed in the former population; 23.3 % of children in residential care exhibited clinical-range externalizing behavior, in sheer contrast to the prevalence of 8.8 % observed among school children (Ginige et al., 2014). This finding corroborates some previous studies which inferred that externalizing problems were more common than internalizing problems among institutionalized children (Doku & Minnis, 2016; Erol et al., 2010). These externalizing problems may reflect the children’s reaction to adverse circumstances, as there is evidence to support the notion that adverse experiences such as maltreatment can inspire externalizing behavior in children (Hecker, Hermenau, Isele, & Elbert, 2014; Segura et al., 2016). However, the possibility of underreporting of internalizing problems by caregivers due to ignorance must be considered before drawing inferences on comparisons. Higher rates for internalizing problems based on self-reports in comparison to caregiver ratings have been observed previously (Doku & Minnis, 2016). Aggressive and rule-breaking behavior are more likely to garner the attention of caregivers, whereas internalizing problems such as being withdrawn and depressed may go unnoticed. As noted in the situational analysis conducted 2013, the child care institutions in SL are in dire shortage of caregivers who have received any form of training in child supervision or counseling (Rasanayagam et al., 2013). Making matters worse, there were only 477 caregivers and 644 matrons to supervise over 14,000 children distributed over 414 institutions, i.e. the ratio between caregivers and children was roughly 1:12. A decline in the recruitment of trained caregivers attributed to inadequate salaries was also noted. This setting envisages grim outcomes for the children brought up in care institutions in SL. The vast majority of these children raised in institutions (78 %) having at least one living parent is compatible with findings from other parts of the world, substantiating the notion that the majority of children brought up in “orphanages” are not true orphans (Csaky, 2009). Disrupted family setting despite the existence of one or both living parents was the predominant reason necessitating institutionalization. However, the data on the frequency of family contact in this study indicates that the majority of these children receive some level of social support either from parents or other relatives. However, the qualitative aspects of such family contact and social support are questionable. Separation from parents may underlie the development of behavioral deviances in this population, in tandem with attachment theory (Bowlby, 1960). In fact, it was Bowlby’s earlier observations on the behavior of institutionalized children separated from parents that later fostered his theories on attachment (Bowlby et al., 1939). Disturbance of attachment among these children has since been studied extensively; a greater risk for insecure and disorganized attachment has been established (Lionetti, Pastore, & Barone, 2015). More than 10 % of the children in this study had been placed in residential care following exposure to child sexual abuse, generally in contact with the law. Attitudes and perceptions of child sexual abuse in SL are diverse, and until recent years, this issue remained shrouded in ignorance and misconceptions. Some evidence has emerged demonstrating the growing acknowledgment of child abuse in SL (de Zoysa, 2002; Ginige, Tennakoon, Perera, & Baminiwatta, 2018). Although a higher prevalence of psychiatric problems was expected among those who had been institutionalized owing to sexual abuse, our data failed to demonstrate this association. It is noteworthy that several children had been placed in institutions because of homosexual behavior shown by them, reflecting the country’s general attitude and perception on a major facet of sexuality, which in itself needs to be addressed at a broader national level in order to achieve a change in attitude. Epidemiological studies in the community have established that most of the behavioral disorders in children, apart from a few such as specific phobias, eating disorders and depression after puberty, are more prevalent among male children (Harrison, Cowen, Burns, & Fazel, 2017). Thus, the higher rates of total, externalizing and internalizing problems among boys in this study compared to girls are in keeping with known epidemiology. Past studies conducted on institutionalized children have also yielded similar results (Gearing et al., 2013). However, all the other hypothesized predictors of problematic behavior investigated in this study failed to reach statistical significance, incongruous with findings from some studies conducted in different countries (Ayaz et al., 2012; Erol et al., 2010; Gearing et al., 2013). Older age, younger age at the time of admission, duration of care in institutions and transfers between institutions have been previously shown to elevate the risk of behavioral issues. This incompatibility with past literature suggests that other factors may be confounding or modifying this relationship in our sample. Inadequate sample size may be another reason for this possible error. 4.1. Policy and research implications Sri Lanka has a National Policy on the Alternative Care of Children and it outlines policy solutions for children at risk of family separation and facing adversities such as child abuse, neglect, child labor, poverty, addiction, imprisonment, human trafficking, mental and physical disabilities, sexually transmitted disorders, domestic violence, abandonment and displacement (Rasanayagam et al., 2013). This policy supports a systematic deinstitutionalization through limiting the required duration of stay and restructuring existing residential facilities by down-sizing and creating more child friendly places temporarily while awaiting reunification or transfer to some family-based care. The current study is expected to guide the work of relevant government authorities, specialists in child mental and physical health including professional bodies such as SL College of Psychiatrists and SL College of Pediatricians, as well as private-sector establishments including non-governmental organizations for children operating within SL, and all the other stakeholders, in implementing their obligations towards children deprived of or at risk of losing family environment. As 14 % of the children growing up in care institutions exhibited clinically significant levels of behavioral problems based on caregiver reports, such children need to be referred to psychiatric services for further evaluation and treatment as indicated. However, currently there is no proper method in place to refer children in whom such problems are identified by caregivers. This is 7

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exemplified by the fact that only 4.6 % of these children had ever come into contact with psychiatric services. Therefore, a system of referral to the nearest child psychiatry clinic should be installed. As noted earlier, these children’s homes are short of trained personnel. As stigma surrounding mental illness is still prevalent in SL, these caregivers themselves may be harboring negative attitudes and misconceptions regarding mental disorders, leading to poor and delayed detection (Fernando, Deane, & McLeod, 2017). Improving the mental health literacy of the caregivers and matrons working in these care homes is likely to facilitate early detection of mental health problems amongst these children. For this purpose, educational programs such as seminars and workshops on mental health can be organized for them, in collaboration with mental health professionals. The researchers like to propose introducing a valid tool such as CBCL to be filled by a caregiver mandatorily upon registration of a child at an institution. Therefore, all caregivers should be trained on using a screening tool for identifying mental health needs of these children. Recruiting educated and trained personnel for child care supervision in institutions has been a particular challenge owing to the inadequacy of remuneration provided for their services. Hence, the Department of Probation and Child Care Services needs to mediate remedial action at the administrative level to enhance recruitment of trained caregivers. While the international authorities on child welfare are making a case for deinstitutionalizing children and placing them in the care of foster families, citing the untoward effects of institutionalization and the lack of a nurturing family milieu, countries like SL are at a very fetal stage in achieving this task (Csaky, 2009; UNICEF, 2010). The child adoption scenario in SL is rife with many legal and practical barriers (Lucas, 2015). As the majority of children in institutions have living parents and other family members, measures to strengthen social support systems for these children would be a feasible course of action to improve long-term outcomes for these children. Particular attention should be paid to the behavior of boys growing up in institutions, as they display a higher prevalence of behavioral issues. In Sri Lankan culture, externalizing behaviors of male children are often considered normal and disregarded (Ginige et al., 2014). Unless caregivers are made more conscious of the features of behavioral disorders such as conduct disorder and oppositional defiant disorder, such underlying pathology would continue to go undetected. Research to further explore predictors of mental health problems in institutionalized children using a larger population and different geographical regions of the country is indicated. Longitudinal studies may provide better insight into the causal relationship between mental health problems and various predictors, and may illustrate their long-term trajectories. Assessment of attitudes, perceptions and knowledge among caregivers regarding mental health would also provide complementary data to inform future policies. The nature and prevalence of maltreatment occurring in these institutions should also be properly investigated. 4.2. Study strengths and limitations The use of a validated translation of a well-established research tool with good psychometric properties enhanced the validity of present results. As the sample was selected from 10 care homes, with proportional representation from different sizes, the consequent findings should adequately reflect the true situation in care homes in Kandy District. However, as the sample of institutionalized in children in the current study was drawn from a single District of Sri Lanka, generalizability of these findings to the whole country is limited; geographical variation due to cultural and socioeconomic differences is likely. Moreover, girls aged 13–18 years were overrepresented in the sample, creating a bias with respect to gender and age. Also, due to the cross-sectional nature of the study, causal links between predictors and problematic behavior could not be inferred. 5. Conclusions The prevalence of mental health problems among children living in child care institutions in Kandy District, SL is relatively lower compared to findings from the Western part of the world. Externalizing problems such as rule-breaking and aggressive behavior seem to be more common than internalizing problems in this group of children, particularly among male children. However, mental health problems, especially the internalizing problems, may not be adequately detected by caregivers due to their lack of knowledge and conducive attitudes. An unduly large number of children coming under the supervision of one caregiver is likely to be a major barrier for detection of problems. As one in seven children exhibited behavioral problems in the clinical range, a proper channel for referring these children to mental health services for further professional evaluation and intervention should be instituted. Increasing the recruitment of trained caregivers, educating institutional staff on mental health, strengthening social support for the children and endorsing an efficient and well-regulated system of foster care are recommended interventions to achieve better long-term mental health outcomes for these vulnerable children. Acknowledgments We thank Avanthi Herath, Tharindu Dissanayake and Ishanka Balage for their contribution as research assistants in this study. We are grateful to Thomas M. Achenbach for waiving off the fees for Child Behavior Check List and ASEBA software. References Achenbach, T. (2019). ASEBA research updates from around the world. Retrieved fromhttp://www.aseba.org/research/research.html. Achenbach, T. M., & Rescorla, L. A. (2001). Manual for the ASEBA school-age forms & profiles. University of Vermont, Research Center for Children, Youth, & Families.

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