A Preliminary Investigation of Cognitive Features Associated With Worry Among African American Youth

Abstract

Although knowledge of the cognitive factors that place children at risk for worry has grown, little is known about these processes within African American youth. The present study investigated cognitive factors associated with worry in a sample of 47 African American children, ages 8 to 13. Participants completed self-report measures of worry, intolerance of uncertainty, positive and negative beliefs about worry, and negative problem orientation. Results supported the hypothesis that cognitive factors demonstrated significant positive associations with worry. Based on a model predicting worry from all cognitive factors, negative beliefs about worry emerged as the only individual predictor. This is the first study to examine cognitive factors associated with worry in an African American sample of children and provides initial support for the applicability of these cognitive factors in future examinations of worry within this population. Future research should continue to explore cognitive as well as other factors that predispose African America children to worry.

Keywords

worry African American youth cognitive factors

Worry, or the cognitive elaboration of threatening possibilities, is a common phenomenon in children. Indeed, worry is present in children of various ages (Henker, Whalen, & O’Neil, 1995; Muris, Meesters, Merckelbach, Sermon, & Zwakhalen, 1998). For example, according to a study by Muris, Merckelbach, Meesters, and van den Brand (2002), worry was present in 60.1% of a 3- to 14-year-old child sample coming from predominantly European American backgrounds. Similar findings have been documented in a study analyzing the worry of children 5 to 12 years old, from a predominantly European America middle-class community, in which worrisome thoughts co-occurred with children’s anxious experiences across ages (Vasey, Crnic, & Carter, 1994).

Although worry itself is not atypical in children, worry that becomes excessive, feels uncontrollable, and is associated with distress is a clinical concern. Exploration of factors that contribute to worry is particularly important, as recent conceptualizations of worry suggest that it may be a transdiagnostic process (Kertz, Bigda-Peyton, Rosmarin, & Björgvinsson, 2012). For instance, Rabner, Mian, Langer, Comer, and Pincus (2017) found that worry was correlated with social anxiety symptoms in older children, as well as separation anxiety symptoms in younger children. Additional research has highlighted that worry may be an etiological factor in depressive and broader anxiety symptoms in children and adolescents (Pasarelu, Dobrean, Predescu, Sipos, & Lupu, 2015; Young & Dietrich, 2015). These findings highlight the importance of worry as a target of clinical intervention, warranting understanding its development in the early lifespan and factors that contribute to worry in youth. Worry has been conceptualized primarily as an internal, verbal activity, which has been associated with specific cognitive factors (i.e., intolerance of uncertainty; negative beliefs about worry; positive beliefs about worry; negative problem orientation) both in adult and child populations (Behar, DiMarco, Hekler, Mohlman, & Staples, 2009; Kertz & Woodruff-Borden, 2013). Better understanding the way in which these factors relate to worry is crucial to worry conceptualization and to inform worry assessment and interventions.

Despite significant progression in understanding worry in youth over the past several decades (Fialko, Bolton, & Perrin, 2012; Kertz & Woodruff-Borden, 2013; Laugesen, Dugas & Bukowski, 2003), knowledge about worry in ethnically diverse children remains limited (Silverman, La Greca, & Wasserstein, 1995). For instance, although initial research suggests that African American children may experience greater levels of worry (Silverman et al., 1995) and exhibit similar rates of generalized anxiety disorder (Gordon-Hollingsworth et al., 2015) compared with non-Hispanic White children, African American children have been underrepresented in worry research. This status is problematic as existing research suggests that there may be differential diagnostic and symptomatic patterns across ethnically diverse youth, including African American children (Austin & Chorpita, 2004; Last & Perrin, 1993). As such, research is warranted to determine whether there are different correlates, or if known risk and protective factors for worry development differentially correlate within this population.

To date, there have only been two studies that have investigated worry in African American children. Silverman et al. (1995) examined the relation of worry content and intensity to anxiety in a comparative sample of non-Hispanic White, Hispanic, and African American school children. Using a semistructured interview to assess worry across a variety of domains (e.g., school, family, health), results indicated that African American children endorsed a greater number of worries and more intense worry than their non-Hispanic and Hispanic counterparts. Subsequent analyses revealed that these differences were largely accounted for by more worries related to war, personal harm, and family. More recently, Folk, Zeman, Poon, and Dallaire (2014) examined the longitudinal relationship between emotional regulation strategies of discrete emotions (i.e., worry, anger, sadness), and anxiety and depressive symptoms in a sample of predominately African American (79.1% Black), low-income children. Results revealed that greater levels of worry dysregulation, worry inhibition (e.g., trying to suppress worry), and worry coping predicted the children’s reported anxiety and their caregiver’s report of the children’s depressive symptoms 2 years later. These findings suggest that dysregulated worry may predispose African American youth to both anxiety and depression over time.

Taken together, the extant research that examines worry indicates that African American youth may experience greater levels and intensity of worry than European American youth, and that greater levels of worry place these youth at risk for anxious and depressive symptoms over time (Folk et al., 2014; Silverman et al., 1995). As such, it is imperative to understand factors that place African American children at risk for worry development, including whether current models of risk apply to this population. Presently, both distal and proximal risk factors for worry development have been identified in existing research (see Kertz & Woodruff-Borden, 2011, for review). Distal factors include age, sex, genetics, environment, and parenting (Kertz & Woodruff-Borden, 2011). Proximally, cognitive factors have been increasingly linked to worry in youth samples (Fialko et al., 2012; Kertz & Woodruff-Borden, 2011; Laugesen et al., 2003). These factors are particularly important, as they have significant treatment implications and may be mutable to mitigate pathological worry development. As such, the current study will examine the relationship of cognitive factors to worry in African American youth.

Cognitive Factors in Worry

Worry in adults has been associated with several cognitive factors, including intolerance of uncertainty (Buhr & Dugas, 2002), metacognition (Wells, 1995), and negative problem orientation (Dugas, Gagnon, Ladouceur, & Freeston, 1998). More recently, these factors have been explored in child samples, providing support for the relation of these cognitive constructs to worry in youth (Boelen, Vrinssen, & van Tulder, 2010; Fialko et al., 2012; Kertz & Woodruff-Borden, 2013). Intolerance of uncertainty has been defined as “the tendency to react negatively on an emotional, cognitive, and behavioral level to uncertain situations and events” (Buhr & Dugas, 2006, p. 223). Research in children and adolescents has demonstrated relatively consistent relationships between intolerance of uncertainty and worry in younger populations (Boelen et al., 2010; Comer et al., 2009; Fialko et al., 2012; Kertz & Woodruff-Borden, 2013; Laugesen et al., 2003). For example, self-reported measures of intolerance of uncertainty have been significantly correlated with worry (Boelen et al., 2010; Comer et al., 2009). Furthermore, in empirical investigations of the application of cognitive models of worry to children and adolescents, intolerance of uncertainty has consistently emerged as a robust predictor of worry (Fialko et al., 2012; Kertz & Woodruff-Borden, 2013; Laugesen et al., 2003). A recent meta-analysis examining the relationship of intolerance of uncertainty and worry in child and adolescent samples found that this cognitive factor had a large effect (r = .63) and accounted for nearly 40% of the variance in worry (Osmanağaoğlu, Creswell, & Dodd, 2018).

Metacognition related to worry involves positive and negative beliefs associated to both the content and process of worrying, including appraisals regarding the utility and potential danger of worry (Wells, 1995, 2004). Positive beliefs about worry (e.g., worry is useful) are thought to maintain worries about daily life events (e.g., finances; Ellis & Hudson, 2010). Negative beliefs or appraisals about the process and consequences of worry (e.g., worry is uncontrollable) are posited to contribute to the development of pathological worry. Emergent work has begun to demonstrate the association of metacognitions and worry in children and adolescents (Bacow, Pincus, May, & Brody, 2009; Donovan, Holmes, & Farrell, 2016; Donovan, Holmes, Farrell, & Hearn, 2017; White & Hudson, 2016). Within this body of work, negative beliefs about worry have been found to be a consistent predictor of worry in children and adolescents (Bacow et al., 2009; Donovan et al., 2017). There has been more inconsistency in the association between positive beliefs about worry and worry in youth across development, with more associations found in adolescent samples (Esbjørn et al., 2015; Fialko et al., 2012; Thielsch, Andor, & Ehring, 2015; White & Hudson, 2016; Wilson & Hughes, 2011). For example, within the evaluation of the relationship of a cognitive model to worry in a sample of children and adolescents, Fialko et al. (2012) found that positive beliefs about worry emerged as a unique contributor to worry in adolescents. However, positive beliefs about worry failed to independently contribute to worry in children, which the authors attributed to the possibility that positive beliefs about worry increase with age. Other work examining cognitive factors in child samples suggests a unique contribution of negative beliefs to worry when regressed with other cognitive factors (Donovan et al., 2017; Kertz & Woodruff-Borden, 2013). Interestingly, in discriminant analyses within the same study, positive beliefs about worry emerged as a significant individual predictor of clinical worry (Kertz & Woodruff-Borden, 2013). In a clinical comparison sample of children, Donovan et al. (2016) found that children with GAD endorsed more negative beliefs about worry as compared with clinical controls; however, no difference in positive beliefs about worry were found between samples.

Negative problem orientation, which is characterized by beliefs that problems are personally threatening to one’s well-being, doubts about one’s ability to effectively solve problems, and the anticipation of subsequent negative outcomes, has been linked to worry (Dugas, Freeston, & Ladouceur, 1997; Dugas, Letarte, Rheaume, Freeston, & Ladouceur, 1995; Ladouceur, Blais, Freeston, & Dugas, 1998). Within child samples, there is growing support for the relationship of negative problem orientation to worry in both clinical and nonclinical child and adolescent samples (Donovan et al., 2016; Donovan et al., 2017; Kertz & Woodruff-Borden, 2013; Laugesen et al., 2003; Wilson & Hughes, 2011). For example, in an evaluation of a cognitive model of worry in a community sample of adolescents, Laugesen et al. (2003) found negative problem orientation to contribute unique variance to worry scores when regressed with other cognitive factors (i.e., intolerance of uncertainty, positive beliefs about worry, cognitive avoidance). In similar studies in community samples of children, negative problem orientation has not emerged as a significant individual predictor of worry when regressed with other cognitive factors; however, correlational analyses reveal a significant association between negative problem orientation and self-reported worry (Donovan et al., 2017; Kertz & Woodruff-Borden, 2013). Furthermore, Donovan et al. (2016) found that children diagnosed with GAD endorsed significantly greater negative problem orientation as compared to nonclinical youth.

Despite the growing awareness of the cognitive factors that are related to worry in children, little is known about whether these cognitive factors demonstrate similar relationships to worry in African American children. Indeed, the studies described above used predominately non-Hispanic White samples. Within studies on intolerance of uncertainty, the inclusion of African American participants ranged from 1.2% to 34.7% (Comer et al., 2009; Cowie, Clementi, & Alfano, 2016; Fialko et al., 2012; Kertz & Woodruff-Borden, 2013; Laugesen et al., 2003; Read, Comer, & Kendall, 2013). Although African American children made up nearly half of one child sample, between-group and within-group analyses were not conducted (Sanchez et al., 2017). Fewer studies have examined negative problem orientation; however, they continue to rely on predominately non-Hispanic White samples (Kertz & Woodruff-Borden, 2013). Of the studies that examined metacognitions and included the inclusion rates by race, the rates of African American participants ranged from 6.8 to 24.5% (Bacow et al., 2009; Fialko et al., 2012). This post hoc consideration of race in the majority of studies limits the ability to detect differences between and within groups and diminishes understanding whether these relationships hold within African American child samples. Although several of the studies examined the correlation between race and outcome factors (Comer et al., 2009; Laugesen et al., 2003) to determine whether to control race in main analyses, none of the existing work has specifically explored the relationship of cognitive factors to worry within African American children.

The Current Study

The current study aims to address the aforementioned gaps in the psychological literature by examining the relationship between worry and cognitive factors in a sample of African American youth. Specifically, in this study, we examined the relationship between worry and intolerance of uncertainty, metacognitions (i.e., positive and negative beliefs about worry), and negative problem orientation. We hypothesized that worry would be positively associated with all cognitive factors. In addition to examining the relationship between worry and cognitive features, we also examined the extent to which these cognitive features explained worry. Based on mixed results regarding the association between worry and multiple cognitive factors in child populations (e.g., Kertz & Woodruff-Borden, 2013; Laugesen et al., 2003), we did not formulate a hypothesis regarding which cognitive factors would be stronger predictors of worry but conducted this analysis as exploratory.

Method

Participants

Participants in the current study were 47 African American children between ages 8 and 13 (M = 10.36; SD = 1.80) recruited from the community of a large Midwestern city as a part of a larger study examining anxiety, worry, and related constructs in an ethnically diverse sample of parent-child dyads. Twenty-nine (61.7%) participants were girls and 18 (38.3%) were boys. The education of parents of the child participants ranged from having completed some high school to obtaining a postgraduate degree. Six of the parents reported that they did not complete high school (12.8%), 5 earned a high school diploma (10.6%), 13 completed some college (27.7%), and 23 (48.9%) parents had completed at least a college education. Over half of the parents reported a yearly household income of $10,000 or less (53.2%; n = 25); 6.4% (n = 3) between $10,000 and $19,999; 14.19% (n = 7) between $20,000 and $29,999; 10.6% (n = 5) between $30,000 and $39,999; 6.4% (n = 3) between $40,000 and $49,999; 2.1% (n = 1) between $70,000 and $79,999; 4.3% (n = 2); between $80,000 and $89,999; and 2.1% (n = 1) higher than $100.000. No parents endorsed three income levels (i.e., $50,000-$59,999; $60,000-$69,999; $90,000-$99,999). The current study initially had 50 participants, but three of the participants were excluded from the final analysis due to missing data (i.e., one was missing income level, another was missing the entire Metacognitive Questionnaire for Children, and another participant was missing Items 14 to 24 of the Metacognitive Questionnaire), yielding a final sample size of 47.

Procedure

Children participating in the current study were recruited from the community through flyers, brochures, and presentations at local community centers, health fairs, public libraries, churches, and through word of mouth. Participants were recruited as a part of a larger study, which aimed to examine resilience to anxiety symptoms, including worry, and related constructs in an ethnically diverse sample of parent-child dyads. The children participating in the current study attended a single session during which they completed self-report questionnaires. All data collection was conducted by the study coordinator who identifies as non-Hispanic White and trained research assistants identifying as either non-Hispanic White or African American. Prior to the initiation of data collection, informed consent and assent were reviewed with the parent and child participant, and an opportunity to ask questions prior to signing the consent documents was provided. Once consent and assent were obtained, the participants were given a packet of self-report questionnaires, including the current study’s measures, to complete. A research assistant, who was a non-Hispanic White, female doctoral student in the clinical psychology program, was present during the completion of the measures to assist with any questions asked by the parent or child. The questionnaires were presented in a randomized sequence to control for order effects. Dyads received $27 compensation for their time and participation in the study; this amount was given to the parent. The Institutional Review Board reviewed and approved the current study.

Measures

Demographic questionnaire

A demographic questionnaire was created for the current study. The demographic questionnaire consisted of 11 items that obtained information pertaining to the participant’s gender, age, parental marital status, parental education level, family size, and annual household income.

Penn State Worry Questionnaire for Children

The Penn State Worry Questionnaire–Child Version (PSWQ-C; Chorpita, Tracey, Brown, Collica, & Barlow, 1997) is a 14-item self-report measure designed to assess worry in children and adolescents ages 7 to 18. Participants indicate the extent to which each item is accurate for them utilizing a 4-point Likert-type scale with verbal anchors (i.e., 0 = never true, 3 = always true). Three items are reverse scored and the total score is computed by summing all items. Higher PSWQ-C scores indicate a greater tendency to worry. Its scores have demonstrated excellent internal consistency in previous samples (Cronbach’s α = .91; Pestle, Chorpita, & Schiffman, 2008). The PSWQ-C has shown convergent validity with other measures of worry in children, such as the Revised Children’s Manifest Anxiety Scale Worry/Oversensitivity subscale (r = .71; Chorpita et al., 1997), and The PSWQ-C has been found to discriminate between worry and anxiety symptoms and between worry and other forms of repetitive negative thought, such as rumination (Muris, Roelofs, Meesters, & Boomsma, 2004).

Intolerance of Uncertainty Scale–Child Adaptation

The Intolerance of Uncertainty Scale–Child Adaptation (IUS-C) is a 27-item self-report measure that was adapted from the adult Intolerance of Uncertainty Scale (Comer et al., 2009). The measure is used to assess a child’s perceptions of the unacceptability of uncertainty, and beliefs that uncertainty of ambiguous situations results in frustration, stress, and difficulty taking action. Participants rate the extent to which they agree with each item on a 5-point Likert-type Scale (i.e., 1 = not at all, 3 = somewhat, 5 = very much). Item responses are summed, with higher scores reflecting greater intolerance of uncertainty. The IUS-C’s scores have demonstrated excellent internal consistency in previous samples (Cronbach’s α = .95; Cowie et al., 2016). Convergent validity has been supported through correlations with related constructs, including worry, anxious symptomatology, and reassurance-seeking behavior, in a mixed sample of community and anxiety-disordered youth (i.e., children ages 7-8 and adolescents ages 16-17; Comer et al., 2009). The IUS-C also discriminated between a GAD clinical sample and a nonclinical sample (Khawaja & Yu, 2010). The total score of the IUS-C was used in the current study to represent intolerance of uncertainty.

Metacognitive Questionnaire for Children

The Metacognitive Questionnaire for Children (MCQ-C) is a 24-item self-report measure that assesses levels of cognitive monitoring, positive meta-worry, negative meta-worry, and superstitious responsibility (SPR) beliefs in children 7 to 17 years of age (Bacow et al., 2009). The MCQ-C asks children to indicate the extent to which they agree with statements on a 4-point Likert-type scale (i.e., 1 = do not agree, 4 = agree very much). There are four subscales within the measure, including Cognitive Monitoring, Positive Meta-Worry, Negative Meta-Worry, and SPR Beliefs. In the present study, the Positive Meta-Worry and Negative Meta-Worry subscales were used. Scoring consists of the sum of the eight items representing each subscale and higher scores indicate the existence of more symptoms (i.e., positive or negative meta-worry).

The Positive Meta-Worry subscale scores have demonstrated good internal consistency (Cronbach’s α = .86) and the Negative Meta-Worry subscale scores have demonstrated acceptable internal consistency (Cronbach’s α = .75) in previous samples (Bacow et al., 2009). A factor analysis indicated the presence of four factors in the MCQ-C, positive meta-worry, negative meta-worry, SPR beliefs, and cognitive monitoring (Bacow et al., 2009). The MCQ-C has demonstrated good concurrent validity, with all MCQ-C subscales significantly correlated with excessive worry (Bacow et al., 2009), while discriminant validity of the MCQ-C and its scales has yet to be investigated. The Positive Meta-Worry and Negative Meta-Worry subscales served as indicators of positive beliefs about worry and negative beliefs about worry, respectively, in the current study.

Negative Problem Orientation–Child Version

Measures assessing negative problem orientation in children and adolescents are currently absent from the literature. Given this limited availability of extant measures, an adaptation of the Negative Problem Orientation Questionnaire (NPOQ; Robichaud & Dugas, 2005a) was used. The NPOQ is a 12-item self-report measure that assesses one’s level of negative problem orientation, including the tendency to perceive problems as threatening, doubt one’s problem-solving abilities, and anticipate negative outcomes associated with problems. For the purposes of the current study, the 12 items of the NPOQ were revised to increase accessibility to children and adolescents. Specifically, the items were rewritten to reflect a third-grade reading level according to the Flesch-Kincaid test. Each item change was reviewed by the lab director and three clinical psychology doctoral students and further adapted until consensus was reached (e.g., “I see problems as a threat to my well-being” became “I see problems as scary”). Participants indicate the extent to which each item reflects the way they react or think when confronted with a problem using a 5-point Likert-type scale (i.e., 1 = not at all true of me, 5 = extremely true of me). The NPOQ items are summed to obtain a total score. Higher NPOQ scores indicate increased negative problem orientation.

Prior studies have indicated that the NPOQ scores demonstrated excellent internal consistency (Cronbach’s α = .93). The NPOQ has demonstrated convergent validity through its strong association with the Negative Problem Orientation Scale of the Social Problem-Solving Inventory–Revised–Short Form (D’Zurilla, Nezu, & Maydeu-Olivares, 1998). This measure has displayed discriminant validity in relation to measures of pessimism, subjective anxiety, depression, worry, and problem-solving ability (Robichaud & Dugas, 2005a, 2005b).

Results

Descriptive Statistics of Sample Characteristics

The Statistical Package for the Social Sciences, 21st version, was used in conducting all statistical analyses. Descriptive statistics, means, standard deviations, skew, kurtosis, reliability estimates, and correlations of the study variables are presented in Table 1. Three cases were removed due to missing data and no outliers were detected. The multiple regression assumptions (i.e., linearity, multivariate normality, absence of multicollinearity, and homoscedasticity) were met. Normality was determined based on skewness and kurtosis values (Field, 2005) that were between +/−1 for all study variables. Despite the high correlations among predictors (see Table 1), the variance inflation factors were within acceptable limits (Hair, Anderson, Tatham, & Black, 1995).

Table 1.

Descriptive Statistics of the Major Study Variables.

	1	2	3	4	5
1.Worry	—
2. IU	.71	—
3. Positive beliefs	.49	.62	—
4. Negative beliefs	.73	.84	.42	—
5. NPO	.68	.86	.42	.76	—
M	16.98	64.74	11.84	13.11	28.56
SD	8.29	25.45	4.70	4.65	11.36
Skewness	0.44	0.57	0.58	0.29	0.80
Kurtosis	−0.09	−0.23	−0.56	−0.90	0.25
Minimum	2.00	27.00	6.00	6.00	12.00
Maximum	38.00	135.00	24.00	23.00	60.00
Internal consistency	.85	.95	.85	.77	.89

Note. N = 47. IU = intolerance of uncertainty; NPO = negative problem orientation. Positive and negative beliefs refer to the meaning of the variables; the terms are unrelated to the directionality of the relationships. p < .01 are in italics; p < .001 are in boldface.

Study variables were analyzed in relation to the demographic variables of gender, age, income level, and parent’s educational level. Given the 15 tests performed with demographic and study variables (i.e., five independent-samples t test for gender, five correlations for income, and five ANOVAs for education level), alpha level for these analyses was established at .003. Independent samples t tests revealed that there were no statistically significant differences in worry, t(45) = −1.29, p = .20, intolerance of uncertainty, t(45) = 0.29, p = .77, positive beliefs about worry, t(45) = −0.36, p = .72, negative beliefs about worry, t(45) = −0.20, p = .84, and negative problem orientation, t(45) = 0.87, p = .39, based on gender.

Correlations were used to test whether there was a relation between age and the study variables, but no statistically significant associations emerged, worry, r(47) = .07, p = .63; intolerance of uncertainty, r(47) = .09, p = .55; positive beliefs about worry, r(47) = −.18, p = .22; negative beliefs about worry, r(47) = .17, p = .24; negative problem orientation, r(47) = .08, p = .62. Spearman’s rho correlations between income level, treated as an ordinal scale with 11 levels, and the study variables (i.e., intolerance of uncertainty, positive beliefs about worry, negative beliefs about worry, and negative problem orientation) revealed that income level and positive beliefs about worry, r(47) = −.45, p = .002 were significantly correlated. That is, children with lower parent income tended to have more positive beliefs about worry. Thus, income was controlled for in subsequent analyses. Five one-way ANOVAs were conducted on the various study variables with education level as the factor (seven levels). No statistically significant effect for parent education level was found for any of the study variables, worry, F(4, 42) = 0.43, p = .79; intolerance of uncertainty, F(2, 42) = 1.03, p = .40; positive beliefs about worry, F(2, 42) = 0.35, p = .84; negative beliefs about worry, F(2, 42) = 1.55, p = .21; negative problem orientation, F(2, 42) = 1.49, p = .22.

Hypothesis Testing

In regards to the hypotheses, all cognitive variables significantly correlated with worry, intolerance of uncertainty, r(47) = .71, p < .001; positive beliefs about worry, r(47) = .49, p = .001; negative beliefs about worry, r(47) = .73, p < .001; negative problem orientation, r(47) = .68, p < .001. Correlations between all study variables are presented in Table 1.

For exploratory purposes, a hierarchical multiple regression was conducted on worry with all cognitive variables as the predictors. Income, as noted above, was entered in Block 1, and all the cognitive variables (i.e., intolerance of uncertainty, positive beliefs about worry, negative beliefs about worry, and negative problem orientation) were entered in Block 2. The first model was not statistically significant, F(1,45) = 2.64, p = .11, R² = .05. The second model was statistically significant, F(5,41) = 12.60, p < .001, and accounted for an additional 55% of the variance in worry. Within the model, negative beliefs about worry emerged as the only individual predictor of worry, β = .51, t(46) = 2.72, p = .01, sr² = .07. That is, the overall cognitive variate, comprised intolerance of uncertainty, negative and positive beliefs about worry and negative problem orientation, was predictive of worry. Additionally, negative beliefs about worry emerged as the strongest individual predictor of worry (beyond income level) when controlling for the contribution of the other cognitive factors. Details about the regression model can be found in Table 2.

Table 2.

Hierarchical Multiple Regression Predicting Worry From Cognitive Variables.

	B	SE B	β	t	p	sr ²
Model 1
Constant	19.08	1.76		10.85	<.001
Income level	−0.80	0.49	−0.023	−1.62	.11	.05
Model 2
Constant	−2.62	3.36		−0.78	.44
Income level	−0.16	0.35	−0.05	−0.47	.64	.01
IU	−0.05	0.10	−0.15	−0.51	.61	.01
Positive beliefs	0.37	0.24	0.21	1.53	.14	.02
Negative beliefs	0.92	0.34	0.51	2.72	.01	.07
NPO	0.24	0.15	0.32	1.58	.12	.02

Note. N = 47. IU = intolerance of uncertainty; NPO = negative problem orientation; sr² = semipartial correlation squared. Positive and negative beliefs refer to the meaning of the variables; the terms are unrelated to the directionality of the relationships.

F_{model 1}(1, 45) = 2.64, p = .111, R² = .05; F_{model 2}(5, 41) = 12.60, p < .001, Change in R² = .55.

Post Hoc Analyses

As the present study represented one of the first examinations of worry in an exclusively African American child sample, the means of the current study measures were examined in relation to existing community samples and established psychometrics where available. No literature exists on the NPO-C for comparative purposes. Mean worry, 16.98 (SD = 8.29); t(46) = 3.31, p = .002, intolerance of uncertainty, 64.74 (SD = 25.45); t(46) = 3.22, p = .002, and positive beliefs about worry, 11.84 (SD = 4.70); t(46) = 2.48, p = .017, as measured by the PSWQ-C, IUS-C, and MCQ-C, respectively, were significantly elevated as compared to means found in previous samples. Specifically, Pestle et al. (2008) reported a PSWQ-C mean of 12.96 (SD = 7.02), Comer et al. (2009) reported an IUS-C mean of 52.81 (SD = 18.00), and Bacow et al. (2009) reported MCQ-C positive beliefs subscale mean of 10.15 (SD = 2.91) in community samples of predominately non-Hispanic White children. Effect sizes (i.e., Cohen’s d) for these mean differences fell in the small to medium range. The mean of the negative beliefs subscale of the MCQ-C in the current sample, 13.11 (SD = 4.65), was not statistically different than that found previously in a nonclinical child sample. Specifically, the original validation of the MCQ-C reported a mean of 12.50 (SD = 4.11) on this subscale (Bacow et al., 2009). The findings are summarized in Table 3.

Table 3.

Comparison of Cognitive Variable Means Between the Present Study and Previous Studies.

Study	Nonclinical sample	Measure/scale	M (SD)	N	Present study (N = 47)	Comparisons (t; p)	Cohen’s d
Pestle et al. (2008)	5-19 years old; majority multiethnic	PSWQ-C	12.96 (7.02)	98	16.98 (8.29)	3.31; .002	.48
Comer et al. (2009)	7-17 years old; majority Caucasian	IUS-C	52.81 (18.00)	124	64.74 (25.45)	3.22; .002	.47
Bacow et al. (2009)	7-17 years old; majority Caucasian	Positive Beliefs	10.15 (2.91)	20	11.84 (4.70)	2.48; .017	.36
Bacow et al. (2009)	7-17 years old; majority Caucasian	Negative Beliefs	12.50 (4.11)	20	13.11 (4.65)	0.91; .370	.13

Note. IUS-C = Intolerance of Uncertainty Scale–Child Adaptation; Positive Meta-Worry (Positive Beliefs) and Negative Meta Worry (Negative Beliefs) = subscales of the Metacognitive Questionnaire for Children (MCQ-C); PSWQ-C = Penn State Worry Questionnaire for Children.

Discussion

The purpose of the current study was a preliminary investigation of cognitive factors related to worry in African American children. Specifically, we examined the associations between worry and intolerance of uncertainty, metacognitions (i.e., positive and negative beliefs about worry), and negative problem orientation. We expected that these cognitive factors would be positively associated with worry and this hypothesis was supported. Furthermore, we explored the extent to which worry would be predicted by the cognitive variables (i.e., intolerance of uncertainty, negative and positive beliefs about worry, and negative problem orientation) and found that these variables together predicted worry, and that negative beliefs about worry emerged as the strongest individual predictor. Similar investigations have been conducted in predominantly non-Hispanic White child samples (Kertz & Woodruff-Borden, 2013), but this study was the first examination of the association between worry and cognitive variables in a sample of African American children. Given the small sample size of the present study, results are preliminary in nature and should be interpreted with caution.

The hypothesis that cognitive factors would demonstrate a positive association with worry was examined and supported. Intolerance of uncertainty, positive and negative beliefs about worry, and negative problem orientation were all significantly and positively correlated with self-reported worry in African American youth. These findings are consistent with previous relationships established with predominately non-Hispanic White and nonclinical samples of children and adolescents, and the strength of the observed correlations in the current study were analogous to some previous findings (Kertz & Woodruff-Borden, 2013) and stronger than others (Bacow et al., 2009; Fialko et al., 2012; Laugesen et al., 2003).

Furthermore, the cognitive factors together predicted worry and negative beliefs about worry emerged as the strongest predictor. These results are consistent with studies that tested these cognitive factors in non-Hispanic White samples. For instance, Kertz and Woodruff-Borden (2013) found that intolerance of uncertainty, positive beliefs about worry, negative beliefs about worry, and negative problem orientation predicted self-reported worry in children ages 8 to 12, and that negative beliefs about worry was the only significant individual predictor. While all cognitive factors in the current study are relevant in the prediction of worry among African American children, the current results indicate that negative beliefs about worry may be the best predictor. The cognitive factors are considered important in conceptualizations of worry in children (see Kertz & Woodruff-Borden, 2011, for a review); however, no studies to date have been conducted regarding similarities or overlap between these factors.

Although the current study provides preliminary evidence for the association between these specific cognitive factors and worry in African American children, additional studies are needed to further validate and explore these relations. With continued investigation, the cognitive factors highlighted in this study may inform future treatments of childhood worry. Findings regarding the utility of these factors as treatment targets are promising, but these treatments have not yet been studied among African American children. Specifically, treatments that target intolerance of uncertainty, faulty beliefs about problem solving, and beliefs about the utility of worry have been related to decreases in worry among adults (Dugas & Ladouceur, 2000; Ladouceur et al., 2000). More recently, metacognitive therapy has accrued evidence of its efficacy in reducing worry in adults by addressing both positive and negative beliefs about the usefulness and controllability of worry (Wells & King, 2006; Wells et al., 2010). Given the present findings that these cognitive factors are associated with worry in African American youth (particularly negative beliefs about worry), it is possible that these therapies could be adapted into developmentally appropriate treatments of worry in this population.

Limitations

Although the current study was characterized by several strengths, its findings are restricted by the following limitations. The cross-sectional design used in the present study hinders understanding the directionality of effects. The study findings and previous research (e.g., Kertz & Woodruff-Borden, 2013) suggest that a relationship exists between cognitive factors and worry in youth, but there is limited attention as to whether intolerance of uncertainty, metacognitive beliefs, and negative problem orientation serve as causal mechanisms to worry development. Furthermore, the high correlations between the predictors pose the question of whether they are indeed measuring different constructs. An important limitation is that post hoc analyses demonstrated that statistical power was not ideal; although significant results were detected, future research should use a larger sample size in replicating the present study. Additionally, the current sample demonstrated somewhat higher levels of worry than expected in a community sample. Additional, larger studies examining worry in community samples of African American youth would be beneficial to determine the validity of this finding. Although the distribution of ages was roughly even in the sample, the small number of participants at each age limits the observation of age-related effects. A larger sample size using equal numbers of children at each age would also be beneficial in clarifying whether these findings regarding worry and cognitive factors are valid across childhood.

Implications and Directions for Future Research

This study makes an important initial contribution to the scarce literature regarding worry in African American children. It represents the first study to go beyond examining the phenomenological experience of worry to explore factors associated with worry manifestation in this population. While valuable in understanding cognitive factors associated with worry among this population, the close association between these factors found in this and previous studies (e.g., Kertz & Woodruff-Borden, 2013) indicates more research is necessary in order to understand the way these factors are related to one another and with worry. Future studies should examine common method biases associated with these factors in order to better define and differentiate them, as well as use multitrait multimethod approaches in understanding the way in which these factors relate to or constitute worry (Millsap, 1995; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Future research is needed to continue to clarify the role of cognitive factors in worry manifestation in African American children throughout development, including cognitive factors (e.g., information processing biases, cognitive avoidance) not assessed in the current study. Specifically, research indicates that these cognitive factors are likely dynamically related and interact differentially over the course of cognitive development (Kertz & Woodruff-Borden, 2011). As such, future research is needed to disentangle these relationships to determine which cognitive processes are most salient to worry at varying points in development. Understanding the temporal relationships between these factors and the timing and levels with which they become problematic will be important for prevention efforts. Given that worry levels in the current sample were somewhat higher than in previous studies, including community samples of non-Hispanic White children (Caes, Fisher, Clinch, Tobias, & Eccleston, 2016) and more comparable to clinical samples (Pestle et al., 2008), future research should explore this finding. Specifically, considering the links between racial stress, SES and worry, research should seek to explore the mechanisms between these environmental experiences and higher levels of worry (Rucker, West, & Roemer, 2010). Furthermore, more recent conceptualizations of worry suggest that it may be a transdiagnostic process, including displaying relationships to social anxiety, separation anxiety, and depression (Pasarelu et al., 2015; Rabner et al., 2017; Young & Dietrich, 2015). As such, research should continue to explore the underpinnings of worry and how these relate to pathways to various disorders of negative affect. Relatedly, future research should investigate differences in cognitive factors related to worry across youth from different ethnic groups in order to determine whether worry stems from similar pathways in African American children as compared to other ethnicities.

In addition, the validation of other factors that predispose African American children to worry is needed, including temperament, emotional functioning, and parenting. The validation of these factors should continue to clarify potential within-group and cross-ethnic variation. This focus is warranted given research suggesting differential patterns between risk factors and anxiety across African American families and non-Hispanic White families, indicating that differential patterns between risk factors and worry may exist as well. For example, research suggests that the relationship between parental control and child anxiety may not hold in African American parent-child dyads (Lamborn, Dornbusch, & Steinberg, 1996). The consideration of culture and ethnicity will be crucial to creating a complete empirical picture of how these processes affect African American youth.

Finally, future research should determine whether these cognitive factors are relevant to clinical samples of African American youth. As previously stated, the participants in the current study endorsed higher levels of worry than previously reported but it is unknown whether the findings would generalize to children who are diagnosed with an anxiety disorder, specifically GAD. As such, continued research on the influence of cognitive factors and other vulnerability factors (e.g., specific parenting practices) is needed in clinical samples of African American children and adolescents. Investigating what factors place children at risk of, as well as those that protect them from, the development of pathological worry will be essential for early prevention and intervention.

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.

ORCID iDs

Elena M.C. Geronimi

Colette Gramszlo

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