The Psychometrics of the Children’s Depression Inventory When Used With Children Who Are Chronically Ill and Matched Community Comparison Peers

Abstract

The Children’s Depression Inventory (CDI) is used to screen for depression in children aged 7 years to 16 years. The purpose of this study is to examine the psychometrics of the CDI in a sample of children who are chronically ill (N = 350) and in a sample of matched community comparison peers (N = 357), and determine if the psychometrics of the scale are similar in both groups. Data were aggregated from previous reports examining social and emotional functioning of children with six chronic diseases and matched comparisons. The CDI was completed in the homes of all participants. No significant differences between groups on CDI scores, distributions, reliability, or validity were observed. Findings suggest that the psychometrics of the CDI are similar for children with chronic diseases compared with typically developing children. The CDI may be an effective screening tool for use with children who have chronic health conditions.

Keywords

validity reliability factor analysis depression health and well-being

Introduction

A diagnosis of major depression is characterized by having a depressed mood, irritability, and a loss of interest or pleasure for a period of 2 weeks or more (American Psychiatric Association, 2013). The cause of symptoms must also not be attributable to the psychological effects of another medical condition. It is estimated that by the age of 18 years, 8%-15% of children will have been clinically diagnosed with major depression (Merikangas et al., 2010; National Institute of Mental Health, 2007). However, it is important to note that these are clinical estimates, and do not include children who experience symptoms of depressive disorder, but have not been diagnosed by a behavioral health specialist. The actual prevalence of the disorder may be greater than reported. For example, findings from the Centers for Disease Control and Prevention (CDC) Youth Risk Behavior Surveys (YRBS) show that approximately 30% of high school youth reported a two-week period where they experienced depressed mood and/or loss of interest or pleasure within the last year (“CDC,” 2009-2013). These high rates of depressive symptoms highlight the need for screening. Although depression is recognized as widespread, screening for childhood depression to improve early detection is uncommon, even among youth who are at high risk.

Children with chronic medical diseases are one group that may be at an increased risk of depression or depressive symptoms due to their illness, medication side effects, or lifestyle limitations. Having a chronic disease can have consequences such as chronic pain, fatigue, challenges to normal sleep, limitations on activities, changes in physical appearance, and missed school days all of which could lead to symptoms of depression (Chapman, Perry, & Strine, 2005). As a result, tertiary care pediatric settings may be an ideal place to screen these children for symptoms of depression, especially as they often require regular visits.

The Children’s Depression Inventory (CDI) is a brief 27-item self-report measure used to screen for symptoms of depression in children between the ages of 7 years and 16 years (Kovacs, 1992). The scale has been widely used and has been shown to be reliable and valid (Gomez, Vance, & Gomez, 2012; Masip, Amador-Campos, Gómez-Benito, & del Barrio Gándara, 2010; Saylor, Finch, Spirito, & Bennett, 1984; Sitarenios & Stein, 2004). Given the brief nature of the measure and its demonstrated psychometrics, its use in tertiary care pediatric settings seems feasible. Unfortunately, the psychometrics of the CDI when used with children with chronic diseases has not yet been reported (Sharp & Lipsky, 2002).

The CDI includes questions about the presence of specific symptoms over the past 2 weeks to screen children for depression. Although all of the items on the CDI directly pertain to symptoms of depression, some items could occur as side effects of chronic disease. For example, the measure has items pertaining to appearance, school work, fatigue, eating habits, and aches and pains, all signs of depression which have the potential to be directly related to having a chronic disease. Thus, before the CDI can be used as a reliable screening measure among children with a chronic disease, it is important to have a clear understanding of whether its psychometric properties are compromised by these distinct circumstances.

Although the CDI has been widely used, to our knowledge, only one study has previously examined the psychometrics of the CDI in children who are chronically ill. However, this study focused exclusively on inflammatory bowel disease (IBD), lacked a comparison group, and looked more specifically at the factor structure of the CDI in this population (Thompson et al., 2012). Although this study provides an initial report about the psychometrics of the CDI, knowledge of the scale’s psychometric properties for children with other chronic diseases remains incomplete.

This study aims to examine the psychometric properties of the CDI when used with children who have a chronic disease and matched community comparison peers, and examine if the psychometrics of the measure are similar in both populations. This study seeks to fill gaps in research knowledge by specifically examining the psychometrics (internal consistency reliability, construct validity, factor structure) of the CDI for a large group of children with a variety of chronic diseases (N = 350), and a large group of matched classroom comparison peers (N = 357).

Method

Overview

Data for this study were initially reported in a series of papers examining the social and emotional functioning of children with a chronic disease and classroom comparison peers (Noll et al., 1999; Noll et al., 2000; Noll, Reiter-Purtill, Vannatta, Gerhardt, & Short, 2007; Reiter-Purtill et al., 2008; Trzepacz, Vannatta, Davies, Stehbens, & Noll, 2003; Vannatta et al., 2008). Although previous publications included the data reported in this study, no previous manuscripts have aggregated these data to examine the psychometrics of the CDI.

The original studies were conducted in two phases, each requiring informed consent. Phase 1 was conducted in classrooms that were selected because they included a child with a chronic disease. Schools included a diverse sample with inner city, suburban, private, and rural schools. During this initial phase, peer, teacher, and self-reports on perceptions of children’s social functioning were obtained. Phase 2 occurred in the homes of both children with chronic diseases and comparison classmates. Comparison peers were matched one-to-one from classrooms on race, gender, and closest date of birth to each respective child with a chronic disease. The CDI was administered during Phase 2 in the home.

Participants

Children with chronic diseases

The sample included 350 children with chronic diseases between the ages of 7 years and 16 years (all from different classrooms). Participants were recruited through tertiary care pediatric clinics at a large children’s hospital and included a variety of chronic diseases, including cancer (n = 95), sickle cell disease (n = 71), hemophilia (n = 23), juvenile rheumatoid arthritis (n = 64), chronic migraine (n = 47), and neurofibromatosis (n = 61). Nearly all of the children with these conditions in the region received treatment at this children’s hospital. Recruitment was meticulously done so that every eligible child was asked to participate. The only exclusion criteria was for children who were in full-time special education or home-schooled, which occurred in less than 5% of patients. Overall rates of recruitment ranged from 76% to 96% of eligible children with chronic diseases for the cluster of projects.

Classroom comparison peers

During Phase 1 of data collection, children with chronic diseases and their classmates were eligible for participation. Although all children with chronic diseases returned consent forms and participated in the study, approximately 10% of classmates did not return consent forms and another 10% were absent on the day of data collection. After initial classroom data collection, children with chronic diseases were matched to their classmates based on the patient’s gender, race, and age. Of eligible controls, the parents of the child who had the closest date of birth to the child with a chronic disease were contacted first. If parents declined participation, the parents of the child with the next closest date of birth on the list were contacted. Recruitment rates of controls were acceptable, with greater than 80% of first-choice families agreeing to participate, with the exception of controls for children with chronic migraine (62% of first-choice families agreeing to participate). A total of 357 comparison participants were recruited. Families of seven children with chronic diseases declined to participate in home data collection, accounting for the greater number of comparison peers.

Materials

CDI

The CDI is a 27-item self-report instrument used to screen for depression in children between the ages of 7 years and 17 years (Kovacs, 1992). Each item has three response options, from which the child selects the one that most closely reflects to his or her thoughts and feelings over the past two weeks. Each item receives a score of 0 to 2 points with a highest possible total score of 54. A score of 19 or above is considered to be in the clinical range for depression (≥ 90th percentile; Kovacs, 1992). The CDI is said to have five measured factors, which include negative mood, interpersonal problems, ineffectiveness, anhedonia, and negative self-esteem (Kovacs, 1992).

The CDI has been widely used in both clinical and nonclinical populations (Hetrick, Parker, Robinson, Hall, & Vance, 2012; Vannatta, Ramsey, Noll, & Gerhardt, 2010) and to screen for depression in children who are chronically ill (Gordijn et al., 2013; Mazur-Mosiewicz et al., 2015; Pinquart & Shen, 2011; Smith, Modi, Quittner, & Wood, 2010). The scale has also been used in intervention and therapy research both to characterize depression in children, as well as to evaluate the efficacy of these programs (Cuijpers et al., 2011; O’Neil & Kendall, 2012; Roberts et al., 2010). Within the past five years, the CDI has been reported as a measure in hundreds of studies.

Several studies have been conducted evaluating the reliability and validity of the CDI as a screening tool. The CDI has demonstrated good internal consistency reliability and moderate test–retest reliability (Saylor et al., 1984; Sitarenios & Stein, 2004; Smucker, Craighead, Craighead, & Green, 1986). The validity of the scale has also been confirmed through a variety of analyses, including correlations supportive of validity and factor analyses (see Sitarenios & Stein, 2004 for a comprehensive overview). The CDI has been shown to be effective for use in both patients with and without known depressive disorders (Gomez et al., 2012; Masip et al., 210). Although the CDI as an overall screening tool has demonstrated solid reliability and validity, the strength of its five-factor structure exhibits mixed results and is not as robust (García, Aluja, & Del Barrio, 2008; Steele et al., 2006; Thompson et al., 2012; Weiss et al., 1991). Results on the sensitivity and specificity of the scale have not reached a clear consensus. Some studies claim that the CDI has both high sensitivity and high specificity, whereas other studies support neither the sensitivity nor the specificity of the scale (Comer & Kendall, 2005; Masip et al., 2010; Timbremont, Braet, & Dreessen, 2004).

Children’s Loneliness Questionnaire (CLQ)

The CLQ is a 24 item self-report instrument used to assess feelings of loneliness in children and adolescents (Asher, Hymel, & Renshaw, 1984). The questionnaire has 16 items that center around feelings of loneliness and social dissatisfaction, and eight items asking about hobbies and interests used as filler questions (Asher & Wheeler, 1985). The CLQ has been shown to be effective in identifying loneliness, particularly in identifying children who are socially rejected by their peers (Asher & Wheeler, 1985; Cassidy & Asher, 1992). The scale has demonstrated reliability for use in children of varying ages from kindergarten through high school (Cassidy & Asher, 1992).

Self-Perception Profile for Children (SPPC)

The SPPC is a 36-item measure that evaluates a child’s self-perception in six distinct domains (Harter, 1985). For the purpose of this study, we are most interested in the domains of global self-worth and social acceptance. The other domains in the measure (i.e., athletic competence, behavioral conduct, etc.) concentrate on specific areas of self-worth that are less likely to be related to depression. Global self-worth gives an overall score of self-perception, while a low score on social acceptance has been previously shown to be associated with depression (King, Naylor, Segal, Evans, & Shain, 1993).

Each item in the measure receives a score between 1 through 4 with 1 representing low self-concept and 4 representing high self-concept. The scale has been shown to have acceptable internal consistency (Eapen, Naqvi, & Al-Dhaheri, 2000) and test–retest reliability (Muris, Meesters, & Fijen, 2003; Van Dongen-Melman, Koot, & Verhulst, 1993). The scale has also exhibited concurrent validity through positive correlations with other measures of self-concept (Muris et al., 2003).

Procedure

Phase 1 (school visit)

The parents of each child with a chronic disease were contacted, and permission was requested to contact the child’s school regarding data collection in the child’s classroom. Out of contacted schools, greater than 80% agreed to participate. After schools agreed, parents received a permission slip (i.e., informed consent) to sign and return to the teacher before their child could participate. After consent was obtained, researchers distributed surveys to all children in the class whose parents agreed to participation. The research was described as a “friendship study,” and the child with a chronic disease was never mentioned to ensure that they were not stigmatized.

Phase 2 (home visit)

After data were collected in classrooms, families with a child who had a chronic disease and matched classmates were contacted to determine interest in participating in Phase 2 of the study. This part of the study included a lengthy home visit (approximately three hours) focusing on child, parent, and family functioning. For the purpose of the current study, reported data obtained in Phase 2 includes information from the demographic questionnaire; and scores from the CDI, CLQ, and SPPC.

Analytic plan

Descriptive statistics were calculated for overall CDI scores and individual items (mean, SD, mean difference). Overall distributions in both groups were examined to observe if there were differences in skewness or in the shapes of the two distributions. Coefficient αs were calculated in both samples and within each disease cohort to determine internal consistency reliability. Construct validity was examined through correlations of CDI scores with other measures conceptually linked to the CDI in both groups. A confirmatory factor analysis was conducted in each sample to determine if the model fit of these data was consistent with the factor structure proposed in the CDI manual.

Results

Demographic and Background Factors

The participants in this study included children between the ages of 7 years and 16 years for both the chronically ill and the comparison groups. Collectively, 47% of children were female and 53% were male. Approximately 71% of participants were of Caucasian decent and 28% were African American. Less than 1% of participants were of another race/ethnicity, which reflected the demographic characteristics of the region where the data were collected.

Descriptive Statistics

Means, standard deviations, and mean differences were calculated for total CDI scores and for each of the individual items for both groups (Table 1). Note that the overall CDI scores are in the normal range for both cohorts, indicating minimal depression. The distributions of total CDI scores between the chronically ill and comparison children were compared using the two sample Kolmogorov–Smirnov test. No significant differences were found in the shapes of the distributions between the two samples (Figures 1 & 2).

Table 1.

CDI: Descriptive Statistics.

Children’s Depression Inventory	Chronic disease		Comparison		Mean difference
Children’s Depression Inventory	M	SD	M	SD	Mean difference
Item 1 (sadness)	0.120	0.397	0.090	0.305	0.03
Item 2 (pessimism)	0.314	0.523	0.283	0.487	0.031
Item 3 (self-deprecation)	0.109	0.363	0.092	0.326	0.017
Item 4 (anhedonia)	0.354	0.514	0.277	0.467	0.077*
Item 5 (misbehavior)	0.097	0.374	0.112	0.380	−0.015
Item 6 (pessimistic worrying)	0.383	0.720	0.333	0.539	0.05
Item 7 (self-hate)	0.114	0.399	0.098	0.342	0.016
Item 8 (self-blame)	0.154	0.406	0.182	0.441	−0.028
Item 9 (suicidal ideation)	0.220	0.454	0.213	0.443	0.007
Item 10 (crying spells)	0.103	0.380	0.087	0.336	0.016
Item 11 (irritability)	0.317	0.596	0.303	0.554	0.014
Item 12 (reduced social interest)	0.129	0.419	0.106	0.351	0.023
Item 13 (indecisiveness)	0.631	0.713	0.644	0.649	−0.013
Item 14 (negative body image)	0.280	0.542	0.333	0.523	−0.053
Item 15 (school work difficulty)	0.440	0.707	0.415	0.668	0.025
Item 16 (sleep disturbance)	0.343	0.622	0.353	0.644	−0.01
Item 17 (fatigue)	0.351	0.628	0.381	0.658	−0.03
Item 18 (reduced appetite)	0.289	0.633	0.283	0.628	0.006
Item 19 (somatic concerns)	0.443	0.643	0.403	0.609	0.04
Item 20 (loneliness)	0.200	0.496	0.157	0.401	0.043
Item 21 (school dislike)	0.403	0.606	0.353	0.560	0.05
Item 22 (lack of friends)	0.246	0.481	0.230	0.447	0.016
Item 23 (school performance decrement)	0.286	0.575	0.249	0.537	0.037
Item 24 (self-deprecation via peers)	0.403	0.615	0.429	0.589	−0.026
Item 25 (feeling unloved)	0.089	0.348	0.048	0.261	0.041
Item 26 (disobedience)	0.283	0.511	0.232	0.461	0.051
Item 27 (fighting)	0.160	0.438	0.134	0.365	0.026
CDI totals	7.260	6.557	6.821	5.858	0.439

Note. CDI = Children’s Depression Inventory.

Significant with p < .05.

Figure 1.

Chronic illness CDI distribution.

Figure 2.

Comparison CDI Distribution.

Inferential Statistics

No significant differences were found in total CDI scores between the chronically ill children (N = 350) and comparisons (N = 357) in the overall sample. Examination of specific items in the CDI showed one significant difference. Children with chronic diseases reported having less fun than did comparison children (Table 1). Note that 6.9% of children with a chronic disease and 4.8% of the comparison children reported a CDI score above the cutoff of 19, which is indicative of depression. These proportions were not significantly different.

Internal Consistency Reliability

Coefficient αs were calculated for the overall groups (Chronically ill α = 0.85, Comparison α = 0.84), as well as for each disease cohort (Table 2). All values were acceptable (α ≥ 0.75).

Table 2.

Coefficient Alpha by Disease Cohort.

Cohort	Chronic illness	Comparison
Cancer	0.864 (n = 94)	0.873 (n = 98)
Hemophilia	0.922 (n = 21)	0.771 (n = 20)
JRA	0.859 (n = 64)	0.760 (n = 65)
Migraine	0.806 (n = 47)	0.851 (n = 51)
Neurofibromatosis	0.851 (n = 53)	0.855 (n = 51)
Sickle cell	0.812 (n = 71)	0.785 (n = 72)

Note: JRA = Juvenile Rheumatoid Arthritis.

Construct Validity

CDI scores were compared in both groups with two other measures of emotional functioning using the Spearman Rho coefficient (Table 3). CDI scores exhibited acceptable correlation coefficients with the CLQ and the Social and Global subscales of the SPPC. All correlations are significant with p < .01 level. No differences in correlations between the chronically ill and comparison groups were found.

Table 3.

Correlations With Other Measures Related to the CDI.

Measure	Chronic illness	Comparison
CLQ	.474	.474
SPPC social	−.354	−.359
SPPC global	−.368	−.310

Note. All correlations are significant with p < .01. CDI = Children’s Depression Inventory; CLQ = Children’s Loneliness Questionnaire; SPPC = Self-Perception Profile for Children.

Confirmatory Factor Analysis

A confirmatory factor analysis using a weighted least squares mean and variance estimation method was performed in both samples of children to determine the fit of our data with the published five-factor structure of the CDI (Kovacs, 1992). In the chronically ill group, the comparative fit index (CFI) was 0.843, the Tucker–Lewis index (TLI) was 0.827, and the root mean square error approximation (RMSEA) was 0.007. In the comparison group, the CFI was 0.763, the TLI was 0.739, and the RMSEA 0.001. This suggests that the five-factor structure is an inadequate fit in both populations.

Exploratory Factor Analysis

Given the results of the confirmatory factor analysis, an exploratory factor analysis using an oblique rotation was conducted. Using the criteria of eigenvalues greater than or equal to 1, seven factors were extracted in the chronically ill group, and eight factors were extracted in the comparison group. An additional parallel analysis was conducted which supported the decision to retain seven factors in the chronically ill group, and eight factors in the comparison group (O’connor, 2000). However, approximately 54% of the variance was explained in both groups from these factors, suggesting that using the CDI to measure multiple factors should be done with caution.

Discussion

This study examined the psychometric properties of the CDI in a large sample of children with chronic diseases who were matched one-to-one with comparison peers on gender, race, and age from their elementary or middle school. Findings suggest the psychometrics of the CDI are strikingly similar for children who are chronically ill and comparison children. All measures of reliability and validity were notably similar for the two groups of children. Means of CDI scores in the overall samples did not differ on total scores and differed significantly in only one (anhedonia) of the 27 items. This work represents the first examination of the psychometrics of the CDI with children who have chronic illness and comparison peers. Findings strongly suggest that a screening tool such as the CDI is a psychometrically viable tool to screen for depression.

Shapes of the distributions of scores were similar in both overall groups. Both distributions displayed a skew to the right, meaning fewer children had scores indicative of depression in both groups. This suggests that as a whole, children with chronic diseases report roughly the same levels of depression as do matched comparisons without a chronic disease. No significant differences in any measures of reliability or validity were found between the chronically ill and comparison groups. The internal consistency reliability of the CDI was acceptable in both groups and within each disease cohort, suggesting that children generally endorse similar answers across items regardless of disease status. We expected specific items such as those related to sleep, appearance, or fatigue might be especially problematic in the chronically ill population; this was not the case.

The construct validity of the two groups was examined by comparisons with the CLQ, and two domains of the SPPC. Results suggest that scores on the CDI as a whole correlate as expected with other constructs related to depression or depressive symptoms. Correlations were moderate in size and not significantly different between chronically ill children and comparisons suggesting that the scale’s validity is similar between the two groups. To our knowledge, these exact scales have not been previously assessed for construct validity with the CDI. However, these results are consistent with other studies examining the relationship between these constructs (King et al., 1993; Qualter, Brown, Munn, & Rotenberg, 2010). This further suggests that the CDI is a psychometrically valid tool that is measuring the constructs it has been designed to measure in all children, even those with a chronic illness.

Results of the confirmatory and exploratory factor analyses suggest that the CDI can be used to screen for depression, but is inadequate in measuring the suggested five separate constructs related to depression and depressive symptoms originally proposed in the CDI manual (Kovacs, 1992). Results of the factor analyses do not vary greatly between groups, suggesting that the proposed factor structure is insufficient for use regardless of disease status. Given these results, the CDI appears to be an acceptable screening tool to measure depression, but should not be endorsed to measure specific dimensions of depression in typically developing children or in chronically ill children. This is consistent with findings from other studies. In general, factor analyses of the CDI do not produce consistent results, and studies have been unable to match the five-factor structure suggested in the manual (Stark & Laurent, 2001; Steele et al., 2006; Thompson et al., 2012).

Although previous studies on the comorbidity of psychiatric disorders with chronic diseases have mixed results, the original manuscripts presenting the data in this study show depression rates did not differ significantly across groups. This could inherently question the effectiveness of the CDI as a screening tool. The CDI has the potential to be psychometrically inadequate when used with children who are chronically ill due to its nature in asking questions directly related to consequences of chronic disease. There is a possibility that the experience of having a chronic disease would predispose children to more frequently endorse negative responses on specific items of the CDI. However, the psychometrics exhibited from the current study suggest that the CDI is adequately measuring depression in children who are chronically ill. This suggests that rates of depression may not differ across groups, and that children who are chronically ill may be resilient to depression or depressive symptoms, at least in the home environment. It does seem feasible that the current results and those reported for earlier cohorts from these data reflect children’s status when they are not feeling sick or are not facing challenging situations in clinic or hospital, and that administering the CDI in the home environment may result in different depression scores.

To our knowledge, this is the first study to date which has examined the psychometrics of the CDI in a large cohort of children who are chronically ill and comparison peers. Although there are many strengths to this work, this study has some limitations. The first limitation is the types of reliability and validity that were measurable given the nature of these data. For example, participants were not tested again at a later point to determine test–retest reliability of the CDI. In addition, sensitivity and specificity could not be measured given that the prevalence of clinical depression was not known in this sample. Future work could add a semistructured psychiatric interview to allow examination of this issue. The second limitation is that these data included only six pediatric chronic diseases. Although this study encompasses many common chronic diseases, it is possible that the CDI may not be psychometrically robust with other pediatric chronic diseases that were not included in this study. Third, the CDI data in this sample were collected exclusively in the home environment in both samples. Although children who are chronically ill will often regularly require treatment and doctor visits, for the most part they are not at their sickest when in the home environment, and it is also feasible that they are less distressed in general. It is possible that CDI scores would be elevated if data from children with chronic diseases were obtained during high intensity periods of disease or symptoms, or in the hospital/clinic. The final limitation of this study is that data were collected using the original CDI. A newer version of the CDI (CDI-2) is currently available. The revised measure is similar to the original CDI (Kovacs & Staff, 2011).

Results of this study suggest that the psychometrics of the CDI are robust for children with chronic diseases, and that the CDI could be used as a screening measure in tertiary care pediatric settings. There are viable alternative approaches to screening, such as the recent introduction of the Patient Reported Outcomes Measurement Information System (PROMIS), that uses an eight-item short form to evaluate depressive symptoms (Pilkonis et al., 2011). Notably, the PROMIS depression short form has exhibited preliminary evidence for adequate reliability and validity and is particularly attractive due to the brief nature of the measure (Irwin et al., 2010). However, it has not yet been thoroughly examined for use, particularly in children who are chronically ill. Future research should not only examine newer scales, but also examine additional elements of psychometrics, such as sensitivity and specificity. Further research can also examine the psychometrics of the CDI-2 in other disease cohorts. The psychometrics of the CDI-2 and of other patient reported outcome measures should also be examined in different settings such as in hospitals and clinics to determine if scores vary by setting, and if psychometrics are affected based on how ill a child is feeling.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5. Retrieved from http://dsm.psychiatryonline.org/book.aspx?bookid=556

Asher

S. R.

Hymel

Renshaw

P. D.

(1984). Loneliness in children. Child Development, 55, 1456-1464.

Asher

S. R.

Wheeler

V. A.

(1985). Children’s loneliness: A comparison of rejected and neglected peer status. Journal of Consulting and Clinical Psychology, 53, 500-505.

Cassidy

Asher

S. R.

(1992). Loneliness and peer relations in young children. Child Development, 63, 350-365. doi:10.1111/j.1467-8624.1992.tb01632.x

Centers for Disease Control and Prevention. (2009-2013). Youth risk behavior surveillance system. Retrieved from http://www.cdc.gov/healthyyouth/data/yrbs/overview.htm

Chapman

D. P.

Perry

G. S.

Strine

T. W.

(2005). The vital link between chronic disease and depressive disorders. Preventing Chronic Disease, 2(1), Article 14.

Comer

J. S.

Kendall

P. C.

(2005). High-end specificity of the children’s depression inventory in a sample of anxiety-disordered youth. Depression and Anxiety, 22, 11-19. doi:10.1002/da.20059

Cuijpers

Geraedts

A. S

van Oppen

Andersson

Markowitz

J. C.

van Straten

(2011). Interpersonal psychotherapy for depression: A meta-analysis. The American Journal of Psychiatry, 168, 581-592.

Eapen

Naqvi

Al-Dhaheri

(2000). Cross-cultural validation of Harter’s self-perception profile for children in the United Arab Emirates. Annals of Saudi Medicine, 20, 8-11.

10.

García

L. F.

Aluja

Del Barrio

(2008). Testing the hierarchical structure of the Children’s Depression Inventory: A multigroup analysis. Assessment, 15, 153-164.

11.

Gomez

Vance

Gomez

(2012). Children’s Depression Inventory: Invariance across children and adolescents with and without depressive disorders. Psychological Assessment, 24, 1-10. doi:10.1037/a0024966

12.

Gordijn

M. S.

van Litsenburg

R. R.

Gemke

R. J.

Huisman

Bierings

M. B.

Hoogerbrugge

P. M.

Kaspers

G. J. L.

(2013). Sleep, fatigue, depression, and quality of life in survivors of childhood acute lymphoblastic leukemia. Pediatric Blood & Cancer, 60, 479-485. doi:10.1002/pbc.24261

13.

Harter

(1985). Manual for the self-perception profile for children. Denver, CO: University of Denver.

14.

Hetrick

S. E.

Parker

A. G.

Robinson

Hall

Vance

(2012). Predicting suicidal risk in a cohort of depressed children and adolescents. Crisis: The Journal of Crisis Intervention and Suicide Prevention, 33, 13-20.

15.

Irwin

D. E.

Stucky

Langer

M. M.

Thissen

DeWitt

Jin-Shei

. . . DeWalt

D. A.

(2010). An item response analysis of the pediatric PROMIS anxiety and depressive symptoms scales. Quality of Life Research, 19, 595-607. doi:10.1007/s11136-010-9619-3

16.

King

C. A.

Naylor

M. W.

Segal

H. G.

Evans

Shain

B. N.

(1993). Global self-worth, specific self-perceptions of competence, and depression in adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 32, 745-752. doi:10.1097/00004583-199307000-00007

17.

Kovacs

(1992). Children’s Depression Inventory: Manual. Toronto, ON: Multi-Health Systems.

18.

Kovacs

Staff

(2011). Children’s Depression Inventory 2 (CDI2). North Tonawanda, NY: Multi-Health Systems.

19.

Masip

A. F.

Amador-Campos

J. A.

Gómez-Benito

del Barrio Gándara

(2010). Psychometric properties of the Children’s Depression Inventory in community and clinical sample. The Spanish Journal of Psychology, 13, 990-999.

20.

Mazur-Mosiewicz

Carlson

Hartwick

Laliberte

Tam

Sherman

E. S.

Brooks

(2015). Rates of reporting suicidal ideation and symptoms of depression on Children’s Depression Inventory in a paediatric neurology sample. Journal of Pediatric Neuropsychology, 15, 3-13. doi:10.1007/s40817-015-0002-8

21.

Merikangas

K. R.

J. P.

Burstein

Swanson

S. A.

Avenevoli

Cui

. . . Swendsen

(2010). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry, 49, 980-989. doi:10.1016/j.jaac.2010.05.017

22.

Muris

Meesters

Fijen

(2003). The self-perception profile for children: Further evidence for its factor structure, reliability, and validity. Personality and Individual Differences, 35, 1791-1802. doi:10.1016/S0191-8869(03)00004-7

23.

National Institute of Mental Health. (2007). Depression in children and adolescents (Fact sheet). Bethesda, MD.

24.

Noll

R. B.

Gartstein

M. A.

Vannatta

Correll

Bukowski

W. M.

Davies

W. H.

(1999). Social, emotional, and behavioral functioning of children with cancer. Pediatrics, 103, 71-78.

25.

Noll

R. B.

Kozlowski

Gerhardt

Vannatta

Taylor

Passo

(2000). Social, emotional, and behavioral functioning of children with juvenile rheumatoid arthritis. Arthritis & Rheumatism, 43, 1387-1396.

26.

Noll

R. B.

Reiter-Purtill

Vannatta

Gerhardt

C. A.

Short

(2007). Peer relationships and emotional well-being of children with sickle cell disease: A controlled replication. Child Neuropsychology, 13, 173-187.

27.

O’connor

B. P.

(2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers, 32, 396-402.

28.

O’Neil

K. A.

Kendall

P. C.

(2012). Role of comorbid depression and co-occurring depressive symptoms in outcomes for anxiety-disordered youth treated with cognitive-behavioral therapy. Child & Family Behavior Therapy, 34, 197-209. doi:10.1080/07317107.2012.707086

29.

Pilkonis

P. A.

Choi

S. W.

Reise

S. P.

Stover

A. M.

Riley

W. T.

Cella

(2011). Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): Depression, anxiety, and anger. Assessment, 18, 263-283. doi:10.1177/1073191111411667

30.

Pinquart

Shen

(2011). Depressive symptoms in children and adolescents with chronic physical illness: An updated meta-analysis. Journal of Pediatric Psychology, 36, 375-384.

31.

Qualter

Brown

S. L.

Munn

Rotenberg

K. J.

(2010). Childhood loneliness as a predictor of adolescent depressive symptoms: An 8-year longitudinal study. European Child & Adolescent Psychiatry, 19, 493-501.

32.

Reiter-Purtill

Schorry

E. K.

Lovell

A. M.

Vannatta

Gerhardt

C. A.

Noll

R. B.

(2008). Parental distress, family functioning, and social support in families with and without a child with neurofibromatosis 1. Journal of Pediatric Psychology, 33, 422-434.

33.

Roberts

C. M.

Kane

Bishop

Cross

Fenton

Hart

(2010). The prevention of anxiety and depression in children from disadvantaged schools. Behaviour Research and Therapy, 48, 68-73.

34.

Saylor

C. F.

Finch

A. J.

Spirito

Bennett

(1984). The Children’s Depression Inventory: A systematic evaluation of psychometric properties. Journal of Consulting and Clinical Psychology, 52, 955-967. doi:10.1037/0022-006X.52.6.955

35.

Sharp

L. K.

Lipsky

M. S.

(2002). Screening for depression across the lifespan: A review of measures for use in primary care settings. American Family Physician, 66, 1001-1008.

36.

Sitarenios

Stein

(2004). Use of the Children’s Depression Inventory. Mahwah, NJ: Lawrence Erlbaum.

37.

Smith

B. A.

Modi

A. C.

Quittner

A. L.

Wood

B. L.

(2010). Depressive symptoms in children with cystic fibrosis and parents and its effects on adherence to airway clearance. Pediatric Pulmonology, 45, 756-763. doi:10.1002/ppul.21238

38.

Smucker

Craighead

W. E.

Craighead

Green

(1986). Normative and reliability data for the Children’s Depression Inventory. Journal of Abnormal Child Psychology, 14, 25-39. doi:10.1007/BF00917219

39.

Stark

K. D.

Laurent

(2001). Joint factor analysis of the Children’s Depression Inventory and the Revised Children’s Manifest Anxiety Scale. Journal of Clinical Child & Adolescent Psychology, 30, 552-567.

40.

Steele

R. G.

Little

T. D.

Ilardi

S. S.

Forehand

Brody

G. H.

Hunter

H. L.

(2006). A confirmatory comparison of the factor structure of the Children’s Depression Inventory between European American and African American youth. Journal of Child and Family Studies, 15, 773-788.

41.

Thompson

R. D.

Craig

A. E.

Mrakotsky

Bousvaros

DeMaso

D. R.

Szigethy

(2012). Using the Children’s Depression Inventory in youth with inflammatory bowel disease: Support for a physical illness-related factor. Comprehensive Psychiatry, 53, 1194-1199. doi:10.1016/j.comppsych.2012.04.006

42.

Timbremont

Braet

Dreessen

(2004). Assessing depression in youth: Relation between the Children’s Depression Inventory and a structured interview. Journal of Clinical Child & Adolescent Psychology, 33, 149-157. doi:10.1207/s15374424jccp3301_14

43.

Trzepacz

A. M.

Vannatta

Davies

W. H.

Stehbens

J. A.

Noll

R. B.

(2003). Social, emotional, and behavioral functioning of children with hemophilia. Journal of Developmental and Behavioral Pediatrics, 24, 225-232.

44.

Van Dongen-Melman

Koot

Verhulst

(1993). Cross-cultural validation of Harter’s self-perception profile for children in a Dutch sample. Educational and Psychological Measurement, 53, 739-753.

45.

Vannatta

Getzoff

E. A.

Powers

S. W.

Noll

R. B.

Gerhardt

C. A.

Hershey

A. D.

(2008). Multiple perspectives on the psychological functioning of children with and without migraine. Headache: The Journal of Head and Face Pain, 48, 994-1004.

46.

Vannatta

Ramsey

R. R.

Noll

R. B.

Gerhardt

C. A.

(2010). Associations of child adjustment with parent and family functioning: Comparison of families of women with and without breast cancer. Journal of Developmental and Behavioral Pediatrics, 31, 9-16.

47.

Weiss

Weisz

J. R.

Politano

Carey

Nelson

W. M.

Finch

A. J.

(1991). Developmental differences in the factor structure of the Children’s Depression Inventory. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 3, 38-45.