Journal of Pediatric Rehabilitation Medicine: An Interdisciplinary Approach 7 (2014) 341–352 DOI 10.3233/PRM-140303 IOS Press

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Depressive symptoms in parents of adolescents with myelomeningocele: The association of clinical, adolescent neuropsychological functioning, and family protective factors Timothy J. Breia,b,∗ , Stacey E. Woodromec, Philip S. Fastenauc,d, Constance F. Burane and Kathleen J. Sawinf,g a

Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA Developmental Pediatrics, Riley Hospital for Children at Indiana University Health, Indianapolis, IN, USA c Department of Psychology, Purdue School of Science, IUPUI, Indianapolis, IN, USA d Department of Psychiatry, Indiana University School of Medicine, IUPUI, Indianapolis, IN, USA e Ambulatory Administrations, Riley Hospital for Children at IU Health, Indianapolis, IN, USA f Children’s Hospital of Wisconsin, Milwaukee, WI, USA g College of Nursing, University of Wisconsin-Milwaukee, Milwaukee, WI, USA b

Abstract. PURPOSE: The purpose of this study is to determine if neuropsychological functioning and family protective factors are related to depressive symptoms in parents of adolescents with myelomeningocele (MMC). METHODS: Fifty adolescents (28 females, 22 males; predominately Caucasian; ages 12–21 years, M = 15.7, SD = 2.4) and their parents from a large Midwestern MMC Program participated in a cross-sectional descriptive mixed-methods study. Participants completed measures of adolescent clinical status (WeeFIM , Demographic and Clinical Information Form), neuropsychological (NP) functioning, family protective factors and parents’ depressive symptoms. RESULTS: Parents’ depressive symptoms correlated significantly with NP functioning in the domains of Mental Processing Speed, Psychomotor Speed, Executive Functioning, Fine Motor Skills, and Language, and with each self-reported family protective factor. Multiple regression analysis revealed independent main effects for the NP variable, Executive Functioning and the Family Protective Factors Composite (p < 0.05); there was no interaction (p > 0.10). CONCLUSION: Clinicians are especially encouraged to include assessment of parental depressive symptoms if the adolescent has executive functioning impairments or if the parents have few family protective factors. Keywords: Myelomeningocele, spina bifida, mental health, depressive symptoms, parents, cognition, adolescent

1. Background ∗ Corresponding

author: Timothy J. Brei, Seattle Children’s Hospital, 4800 Sand Point Way NE, OC.9.840, Seattle, WA 98105, USA. Tel.: +1 206 987 2210; Fax: +1 206 987 3824; E-mail: timothy.brei@ seattlechildrens.org.

Myelomeningocele (MMC) is one of the most frequently occurring chronic neurological conditions of childhood [1]. In addition to a wide variety of medical concerns including hydrocephalus and other neurosur-

c 2014 – IOS Press and the authors. All rights reserved 1874-5393/14/$27.50 

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gical concerns, urologic problems and varying degrees of mobility impairments, individuals with MMC have been noted to have an increased likelihood of mental health problems and restricted social supports [2,3]. Adolescents with MMC are at risk for reduced autonomy and underachievement as adults, resulting in unemployment or underemployment, decreased independent living, and social isolation [4,5]. Living with MMC can be conceptualized in an ecological model that integrates developmental systems and situational perspectives to explain individual adaptation [6,7]. This model is broadly based on a “strength perspective” of human development, which emphasizes strengths, resilience, competence and adaptive behavior, although risk factors are considered as well. Under this framework, neurobiological and medical factors of myelomeningocele pose developmental challenges to individual adaptation for adolescents with MMC and their families. In addition, family and environmental factors affect adaptation outcomes. One such challenge faced by adolescents with MMC is neuropsychological (NP) impairment. Various NP deficits have consistently been recognized in MMC, including limitations in visual motor speed, visual motor integration, oculomotor skills, variability in memory and learning, and executive functioning (e.g., planning, organization, attention) [8–10]. Deficits in executive functioning (e.g., planning, organization, attention) are prevalent in adolescents with MMC, even those with normal intelligence. Demands on executive functions increase as individuals move through adolescence into adulthood, and recent research suggests that deficits in executive functions in MMC may play a much more prominent role in succeeding at school, learning self-care, developing autonomy, and mastering social skills than previously understood [6,11–15]. The relationship between NP deficits and adaptive functioning (e.g., physical, psychological, social, academic, quality of life) has been documented in other pediatric medical conditions such as pediatric traumatic brain injury (TBI) and epilepsy; moreover, NP deficits and adaptive functioning have been associated with increased family and parental distress in those populations [16–20]. Therefore, just as NP deficits have been associated with increased parental distress in other pediatric neurological populations with similar adaptive challenges, it is likely that they would be associated with parental depressive symptoms (PDS) in MMC. In partial support of the impact of NP deficits on parental depressive symptoms, researchers have found

increased levels of psychosocial stress in parents of children with MMC compared to parents of children without a disability [21–23]. Vermaes et al. [24] in a meta-analysis of factors associated with parental distress, identified variables that correlate with parent’s psychological adjustment including: child factors, parent factors, family factors and environmental factors. Their meta-analysis did not find associations between the severity of the child’s physical disability and parental psychological adjustment. They concluded, “Associations of the child’s cognitive capacities with parents’ psychological adjustment were hardly reported, despite indications from noncategorical studies that cognitive limitations are likely to put extra strains on parents and despite indications from neuropsychological research that children with SB [spina bifida] have specific profiles of cognitive strengths and weaknesses. More research will be needed to understand the impact of children’s cognitive profiles on parents’ adjustment” [24]. Importantly, family factors can moderate the impact of NP deficits on behavioral outcomes in pediatric neurological populations [25,26]. Previous research has shown that family cohesion, ability to resolve conflict, and family resources are factors that may help families of children with disabilities cope with stresses that they experience [24,27–30]. Higher socioeconomic status (often defined by parent education, occupation, and/or family income) may be a protective factor as well [24, 29] Based on the above literature, one might theorize that if NP impairments contribute to problems in school (academic underachievement) and at home (reduced independence), it is likely that adolescents’ NP deficits contribute to PDS. Given the potential for PDS to adversely affect the family environment, it is essential to work toward a better understanding of parents’ adjustment to their children’s chronic health issues in order to increase the likelihood of functional success for this population. However, no studies were found in the literature that evaluated the relationship between NP function and parental depressive symptoms. Thus, the current study evaluated depressive symptoms in parents of adolescents with MMC and relationships with the adolescent’s NP functioning and family protective factors. Specifically, the following hypotheses were tested: After controlling for clinical variables, 1) Lower NP functioning in the adolescent will be associated with higher parental depressive symptoms; 2) Lower family protective factors will be associated with higher parental depressive symptoms;

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Table 1 Demographic variables, IQ estimates and self-reported parental depressive symptoms for total sample and for subgroup completing full neuropsychological battery Variable

Age K-BIT IQ Gender Race (% Caucasian) Handedness (% Right Handed) General Contentment Scale (Total)1

Total sample (N = 50) Mean (SD) 15 yrs, 0 mo (2 yrs, 5 mo) 90.9 (18.4) 28 Female 22 Male 92 78 27.3 (17.8)

Full test battery subgroup (N = 32) Mean (SD) 15 yrs, 0 mo (1 yr, 9 mo) 90.6 (15.9) 17 Female 15 Male 90 84 25.5 (18.7)

Screening test battery subgroup (N = 18) Mean (SD) 17 yrs, 4 mo.

t or x2

p

3.4

0.001

91.3 (22.7) 11 Female 7 Male 94 67 30.5 (16.1)

0.13 0.42

0.90 0.52

0.21 3.09 0.90

0.65 0.21 0.37

1 The

scoring algorithm yields a score from 0 to 100. A higher score on the General Contentment Scale reflects greater depressive symptoms. Scores above 30 suggest a clinically significant problem.

3) Family protective factors will moderate the impact of adolescents’ NP functioning on parental depressive symptoms.

2. Methods 2.1. Sample Participants in this study were part of a larger study evaluating adaptation in adolescents with MMC. The sample consisted of 50 adolescents with MMC and their parents, who were recruited from a multidisciplinary MMC clinic in a large Midwestern medical center. For the present study, the family was included if the adolescent was: (1) 12–21 years of age, (2) had no major medical condition (i.e., life-threatening, progressive or incapacitating disability) other than MMC, and (3) was in a regular class or learning resource class, but not in a class for students with mild, moderate, or severe intellectual disabilities. Adolescents completed a brief NP battery (approximately 11/2 hours) in addition to their routine clinical visits. Of the 50 adolescents, 32 participants, ages 18 or younger (because some tests were not developed or normed for adults), voluntarily completed additional NP measures (additional 3 hours) to explore other domains. Table 1 presents the demographic information and estimated intellectual ability on the sample. The total adolescent sample was predominately Caucasian, right handed, slightly more likely to be female, and with a mean IQ score in the normal range. The only difference between the adolescents in the brief battery versus full battery groups was in age, which was anticipated due to the age restriction (age 18 or younger) for the additional measures in the full battery. Parents were also primarily Caucasian. Seventy-six percent of

parents participating were married; with 20% single (never married, widowed, divorced) or choosing not to report marital status (4%). Respondents included biological/adoptive mothers (77%), stepmothers (6%), female legal guardian (4%), biological/adoptive fathers (10%) and male legal guardians (2%). Mothers’ and fathers’ mean education reflected at least some college or technical school education. 2.2. Procedure This report is a portion of a larger cross-sectional, mixed method study including both quantitative and qualitative components. The larger study was reviewed and approved by the Institutional Review Board of the associated university. After referral of a potential participant to the study, the adolescent and his/her parent were contacted through a letter of invitation. Personal invitations from clinic and study staff were also made in order to explain the study further, to obtain written informed consent from both the adolescent and his/her parent, and to schedule the interviews. The primary caregiving parent or guardian (N = 50) participated in a structured interview that included multiple instruments, qualitative questions, demographic data, and clinical data. The structured interviews took place in the home (32%) or via telephone (69%). The instruments used in this analysis are delineated in the instrument section. Psychometrists administered the NP testing to adolescents; all were trained, certified and supervised by a licensed clinical neuropsychologist (author P.S.F.). 2.3. Instruments 2.3.1. Clinical information The Demographic and Clinical Information Form (DCIF) developed by the researchers was used to col-

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lect demographic and clinical data. The shunt status index was created from the DCIF to reflect the total number of shunt procedures (0 for none, 1 for initial shunt, 2 for first revision, etc.). One author (CB) determined the level of lesion by chart review using a 4-category classification scheme based on functional criteria. Qualitative data are reported elsewhere [31]. The1 WeeFIM instrument bladder and bowel ratings, which reflect both continence and independence in managing the bladder or bowel program, were used for the regression analysis. The WeeFIM instrument is scored from 1 = dependence/incontinence to 7 = independence/continence. The bowel and bladder scores were the lowest of the 18 WeeFIM instrument items. Generally, many of the other items had ceiling effects (e.g., upper body dressing M = 6.4, SD = 0.6) and/or restricted variability in this sample. Therefore, they were not included in the analyses. 2.3.2. Neuropsychological tests The Screening Battery consisted of four tests typically used to assess Mental Processing Speed, Attention, Psychomotor Speed, and Executive Functioning: Conners’ Continuous Performance Test [32], Trail Making Test [33], Wisconsin Card Sorting Test [34], and the age-appropriate Symbol Search subtest of the Wechsler intelligence scales [35]. The Full Battery added measures which are regularly used to assess Fine Motor Skills (Grooved Pegboard) [36], Language (Clinical Evaluation of Language Fundamentals – 3rd Edition) [37], and Memory (Wide Range Assessment of Memory and Learning) [38]. For all NP scores reported here, higher scores reflect higher neuropsychological functioning and lower scores reflect more neuropsychological deficits. The specific test variables used to measure each construct are identified in Table 2. 2.3.3. Family protective measures Several established instruments and parental demographics (parental education) from the DCIF provided information for the family protective measures. Family cohesion was assessed by the Cohesion Subscale of the Family Adaptability and Cohesion Scale [39]. Family satisfaction was measured by the Family Adaptation/ Partnership/Growth/Affection/Resolve Scale (Family APGAR) [40]. Family Mastery/Health and Family Es1 WeeFIM is a trademark of Uniform Data System for Medical Rehabilitation, a division of UB Foundation Activities, Inc.

teem/Communication are two sub-scales of the Family Inventory of Resource Management (FIRM) [41]; they capture a sense of mastery over family events, family support resources, family esteem, and communication. Mother’s education and father’s education completed the family protective measures. 2.3.4. Parental depressive symptoms PDS were measured by the Hudson’s General Contentment Scale (GCS), a measure frequently used in social work clinical practice [42]. The 25-item GCS, which is scored on a 1 (none of the time) to 7 (all of the time) response pattern, was designed to measure the degree, severity, or magnitude of nonpsychotic depressive symptoms [43]. Twelve items are positively worded and are recoded. Items include questions such as “I feel powerless to do anything about my life; I feel downhearted, I feel my life is hopeless; it is easy for me to enjoy myself; or I have a full life.” The scoring algorithm yields a score from 0 to 100. A higher score on the GCS reflects greater depressive symptoms. Scores above 30 suggest a clinically significant problem [42]. The Cronbach alpha reliability of the scale was strong across 7 studies of a total of 2,140 adults (mean α = 0.92; range = 0.89–0.96). Construct validity of the GCS was supported by strong correlations with the Zung Depression Scale (r = 0.91) and Beck Depression inventory (r = 0.85) [43]. In addition, the construct validity of the GCS was supported by factor analysis. Data from a number of studies has also supported discriminate validity of the GCS [44, 45]. Hudson found that the error rate of under- or overidentifying depressive symptoms was 13.8% in a sample of individuals diagnosed with depression [43]. 2.4. Statistical analysis Frequencies were used to report characteristics of the sample. Scale scores were calculated per instrument protocol. To control for Type I error, NP variables were reduced into seven domain scores based on a priori, theoretical models (Mental Processing Speed, Attention, Psychomotor Speed, Executive Functioning, Fine Motor Skills, Language, and Memory). To compute domain scores, variables in each domain were first corrected for age effects using the best available published norms. Then, scores were converted to a common scale (M = 100, SD = 15). The variables within each domain were averaged (unweighted mean) to produce the domain score. For these domain scores, higher scores always represent better performance.

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Table 2 Measures of clinical factors, neuropsychological function and family protective factors Variables a Myelomeningocele Clinical Factors (N = 50) Shunt Status N/A4 N/A4 N/A4 Neuropsychological Screening Battery (N = 50) Mental Processing Speed 0.951 Attention 0.66 Psychomotor Speed

nr2

Executive Functioning

0.81

Full Neuropsychological Test Battery (N = 32) Fine Motor Skills 0.91 Language

0.84

Memory

0.78

Family Protective Factors Composite

0.725

Measure

M

SD

Shunt + Number of Revisions WeeFIM – Parent Bladder Rating Wee FIM – Parent Bowel Rating

2.4 4.7 4.3

1.8 1.9 2.5

CPT Hit RT (T) CPT % Omissions (T) CPT RT SE (T) WISC-III/WAIS-III Symbol Search (T) Trail Making WCST % Errors (T) WCST % Perseverative Errors (T)

47.5 57.0 58.9 43.2 42.5 44.1 46.0

13.1 14.2 14.0 12.6 23.0 11.8 12.4

Grooved Pegboard Dominant Hand (z)3 Grooved Pegboard Non-Dominant Hand (z)3 CELF-3 Receptive Language Index (SS) CELF-3 Expressive Language Index (SS) WRAML Design Memory (ss) WRAML Story Memory (ss) WRAML Verbal Learning (ss)

4.2 5.3 83.8 82.7 7.0 7.8 9.2

3.8 6.1 19.3 16.0 3.1 3.1 3.0

Family Cohesion6 Family Satisfaction6 Family Mastery7 Family Esteem7 Mother’s Education8 Father’s Education8

3.68 3.80 2.07 2.26 5.59 5.47

0.67 0.82 0.47 0.52 1.13 1.20

Note: T = T score (M = 50, SD = 10), Z = Z-score (M = 0, SD = 1), SS = Standard Score (M = 100, SD = 15), and ss = Scaled Score (M = 10, SD = 3); † p < 0.10 (trend) ∗ p < 0.05 ∗∗ p < 0.01 ∗∗∗ p < 0.005 ∗∗∗∗ p < 0.001 one-tailed; 1 Because only one variable was used in this domain (thereby precluding computation of internal consistency), split-half reliability from the publisher is reported here. The reliability on the original test was reported in revised test-manual [46]; 2 Nr = internal consistency not reported as test-retest is the appropriate value for a timed test and not available from this cross-sectional study; 3 As shown in the table, a higher Grooved Pegboard score (longer time to completion) reflects worse performance. When creating the NP Composite Score, the z-scores were reversed so that all neuropsychological scores were in the same direction; 4 Coefficient alpha could not be computed because variables consist of only one item; 5 Cronbach alpha for composite using family variables scale scores; 6 5-category response pattern 1–5 (with higher score reflecting more cohesion and satisfaction); 7 4-category response pattern 1–4 (with higher score reflecting more mastery and esteem); 8 Parent education was a categorical variable ranging from 1 (“No Formal School”) to 5 (“Completed High School”) to 9 (“Completed Post-Graduate Training”).

The appropriateness of these domain scores was tested by reliability analysis on the present sample. Typically the most accurate reliability score for a timed test such as the Mental Processing Speed domain score or Psychomotor Speed domain score is test-retest reliability, not internal consistency. Unfortunately, with only cross-sectional data, test-retest reliability could not be computed. For the Mental Processing Speed domain score, because it included only one variable, the split-half reliability from the publisher is reported (see Table 2) [46]. Pearson correlations were computed between all clinical, NP, family protective, and PDS variables. Power analysis indicated that for a hierarchical multiple regression, assuming large effect size, p of 0.05, power of 0.80 and 6–8 predictor’s variables we would needed a sample of 39–43 participants. Thus the entire sample (N = 50) was required to test the third hypoth-

esis in this model. Consequently, the analysis was limited to the four NP domain scores that were obtained on the entire sample. While Executive Functioning had the strongest bivariate relationship to the outcome, the other NP domains were significant or approached significance. Due to the recommendation by Vermaes et al. [24] to identify specific NP constructs related to PDS, a preliminary analysis was conducted to determine if one or more of the NP domain scores were more salient and should be used to represent NP function. The relationship of Mental Processing Speed, Attention, Psychomotor Speed, and Executive Functioning domains to parent depressive symptoms were evaluated, controlling for clinical variables, with a stepwise regression. In this analysis only Executive Functioning remained significant in predicting PDS. Acknowledging that the sample with all 7 NP domains was even smaller (n = 32) the stepwise regression analysis was

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T.J. Brei et al. / Parent’s depressive symptoms in myelomeningocele Table 3 Correlations between context, process and outcome variables 1

Context (Clinical)l variables 1. Shunt Status 2. Bladder status edge 3. Bowel Status Process variables 4. Mental Processing Speed 5. Psychomotor Speed 6. Attention 7. Executive Functioning 8. Fine Motor+ 9. Language+ 10. Memory+ 11. Family Cohesion 12. Family Satisfaction 13. Family Mastery 14. Family Composite Outcome variable 15. Parent Depression

1.00 −0.03 0.20

2

3

1.00 0.43∗

0.21 0.07 0.36 −0.10 0.40∗ 0.47∗ −0.24 0.26 0.10 −0.16 0.36 0.26 ∗ 0.36 0.26 −0.36 −0.10 0.19 0.19 −0.24 0.41∗ 0.32 0.11 0.05 0.03 0.10 0.08 −0.06 0.11 0.13 0.17 0.13 −0.03 0.05 −0.10

5

6

7

8

9

10

11

12

13

14

1.00 0.14 0.10 0.32 0.27

1.00 0.60∗ 0.47∗ 0.79∗

1.00 0.51∗ 0.76∗

1.00 0.73∗

1.00

15

1.00

∗

0.09

4

0.05

1.00 0.51∗ 0.41∗ 0.41∗ 0.31 0.57∗ 0.36 0.16 0.21 0.44∗ 0.37∗ −0.26

1.00 0.50∗ 0.58∗ 0.43 0.52∗ 0.44 0.01 0.10 0.34∗ 0.14 −0.27

1.00 0.63∗ 0.25 0.63∗ 0.38∗ 0.08 0.07 0.19 0.17 −0.26

1.00 0.37∗ 0.73∗ 0.57∗ 0.26 0.24 0.35∗ 0.32∗

1.00 0.25 0.46∗ 0.19 0.21 0.52∗ 0.27

1.00 0.61∗ 0.24 0.16 0.31 0.42∗

−0.46∗ −0.36∗ −0.43∗ −0.28 −0.55∗ −0.76∗ −0.73∗ −0.68∗ 1.00

Note. All comparisons were two-tailed and Pearson’s r statistics. ∗ Correlation is significant at < 0.05 level (2-tailed).

repeated with the same results. Only Executive Functioning remained significant in the regression on PDS. Thus Executive Functioning was included in the hierarchical multiple regression analysis as the most salient NP domain. The family variables were evaluated in the same manner. Two out of the three family variables (satisfaction and mastery) remained significant in the stepwise regression and cohesion approached significance. Due to the small sample size, the correlations between the family variables and the acceptable reliability of a three-score family composite, a family composite score was created for the full regression analysis. These scores were standardized to z scores within the sample. The standardized scores were then averaged (unweighted mean) to yield a score representing a global family protective variable (Family Protective Factor Composite Score). Marital status was examined as a potential protective factor, but it dropped out in the composite reliability analysis (suppressed Cronbach’s alpha by 0.17). A hierarchical multiple regression analysis was then conducted to determine if, after controlling for clinical variables, Executive Functioning and family protective factors were associated with parent depressive symptoms and if family protective factors moderated the relationship between adolescents’ Executive Functioning and PDS. No clinical variable had a direct significant relationship with PDS but three were retained in the analysis for comprehensiveness of the evaluation. The clinical variables (shunt status, bowel continence and bladder continence) were entered into the first step. The two independent variables (Executive Functioning and the Family Protective Factor Composite) were entered in the second step. Because clinical variables

and independent variables were fixed, they remained in the equation in Step 3. In the third step, the interaction term (the product of the Executive Functioning and Family Factor Composite) was tested as the moderating variable. 3. Results Descriptive data on the clinical variables, NP variables, and family protective factors are summarized in Tables 1 and 2. Although 82% of the sample had a shunt, the mean shunt status score reflected relatively few revisions (Table 2). Nine adolescents (18%) had never had a shunt; four (8%) had a shunt but no revisions; 18 (36%) had one revision and 19 (48%) had 2–6 revisions. The adolescents had primarily thoracic/high lumbar (32%) or lumbar lesions (35%) lesions with fewer having lumbosacral (14%) and sacral (18%) lesions. Scores on the NP measures, on average, were approximately two-thirds to one full standard deviation below the national means for most tests. On Fine Motor Skills, this sample was four to five standard deviations slower than normal. Mental Processing Speed was more variable than was observed in the national sample, but the average performance for this sample was in the normal range. Parent’s perceptions generally reflected positive family satisfaction, cohesion, mastery and esteem. Descriptive data on the dependent variable (parental depressive symptoms) are reported in Table 1. It is important to note that 48% of the parents reported a GCS score over 30 which suggests a clinically significant problem with depressive symptoms even though the parent’s mean score on the GCS was in the normative range (M = 27.3; SD = 17.8)

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Table 4 Hierarchical regression analyses testing the proposed model Step and Variable 1. No. of Shunts WeeFIM Bladder WeeFIM Bowel 2. No. of Shunts WeeFIM Bladder WeeFIM Bowel Executive Functioning1 Family Protective Composite Score2 Interaction Term4

B 1.22 −1.26 1.11 −0.17 −0.54 1.54 −0.27

Standardized Error B 1.55 1.58 1.31 0.75 1.07 0.86 0.12

β 0.13 −0.14 0.16 −0.03 −0.06 0.22 −0.293

−14.31

2.84

−0.583

R2

R2 Change

F Change

p

0.02

0.02

0.34

0.80

0.54 0.55

0.52 0.01

22.38 1.18

0.00 0.28

Note: F value reported is the F associated with the change in R2 from the previous step. 1 Executive Functioning – standard score; 2 The Family Protective Factor Composite Score is comprised of the averaged (unweighted mean) scores from the Family APGAR, Cohesion Subscale of the FACES-III, Family Esteem and Communication and Family Mastery and Esteem Subscales of the FIRM, and mother and father levels of education that had been standardized to z scores within the sample; 3 Significant @ p  0.05; 4 The Interaction Term is the product of the Executive Functioning Score and the Family Protective Factor Composite Score.

3.1. Factors associated with parental depressive symptoms The results of the correlation analysis are summarized in Table 3. No demographic variables (parent age, gender, or education) had a significant correlation to depressive symptoms. Adolescents’ Mental Processing Speed, Psychomotor Speed, Executive Functioning, Fine Motor Skills, and Language correlated negatively and significantly with parental depressive symptoms. Memory and Attention had effect sizes in the same range as the other predictors, suggesting that they would likely be statistically significant in a larger sample. For all of these cognitive domains, PDS increased as adolescent NP functioning decreased. In contrast, self-reported depressive symptoms decreased as family protective factors increased. As parents endorsed greater family cohesion, satisfaction, mastery and esteem, they also endorsed significantly lower levels of depressive symptoms. The results of the hierarchical regression can be found in Table 4. Contrary to the third hypothesis, multiple regression analysis did not reveal an interaction between any of the family protective factors and adolescents’ NP abilities. After entering the three clinical variables and the two independent variables (Executive Functioning and Family Protective Factors Composite), the interaction term (moderating variable) failed to enter the model (p > 0.10). Clinical factors were not significant in the regression. The overall model (with only the two main effects of Executive Functioning and Family Protective Factors) explained 57% of the variance in PDS (Multiple R = 0.76, F change = 27.1, p < 0.00001). The partial correlation of the interaction term with parental depressive symptoms (after control-

ling for variance explained by the clinical, Executive Functioning, and Family Protective Factor composite) was not significant (rp = −0.01, p = 0.97). 4. Discussion The current results reveal that many parents of adolescents with MMC have a clinically significant problem with depressive symptoms. This level of PDS is higher than those reported for parents of adolescents with other chronic health conditions [47]. Parents of adolescents with lower NP functioning, specifically Executive Functioning, reported higher levels of depressive symptoms, as predicted in Hypothesis 1. Rose and Holmbeck also found executive functioning in adolescents contributed to a related outcome, parenting behaviors [10]. Even though PDS and parenting behaviors are distinct parental outcomes, the parallel findings highlight the importance of executive functioning on parent outcomes. In addition, parents who endorsed stronger family protective factors were less likely to report depressive symptoms, as predicted in Hypothesis 2. These data lend further support to the findings of others regarding the importance of various family protective factors for improving psychosocial symptoms in parents of children with MMC [27–29] as well as other pediatric populations with chronic illness [48–56], and both adult and pediatric traumatic brain injury populations [20, 56,57]. In contrast, Hypothesis 3 was not supported. Although Family Protective Factors and adolescents’ Executive Functioning were independently related to parental depression symptoms, when examined in in-

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teraction, increased family resources did not attenuate the impact of adolescents’ Executive Functioning challenges on parents’ depression symptoms. Other recent studies have shown that family factors modify the impact of NP deficits on child and adolescent outcomes [25,26]; however, we found no studies that examined the modifying role of family factors on parent outcomes. The present study was an initial exploration into the potential protection of family factors. We were unable to detect that modifying effect. Some methodological factors in our study might have limited our ability to detect such a relationship. For example, the test of the interaction might have been underpowered due to small sample size. In addition, our study focused on executive functioning; other neuropsychological deficits might better reflect the protective role of family factors in MMC. Although homogeneity within a sample on independent or dependent variables can limit the ability to detect an interaction, that does not appear to have played a role in this instance because there were moderate to strong univariate relationships between PDS and executive functioning (r = 0.46) and between PDS and all four family factors (r = 0.55– 0.76) in Table 3. Future research on the role of protective family factors with a larger sample and additional neuropsychological domains is warranted. 4.1. Implications for practice These results have several implications for health care professionals and their interactions with parents of children with not only MMC but with other chronic health issues as well. While PDS can be attributed to multiple risk factors [58] the data from this study would indicate that clinicians should assess for depressive symptoms in parents who have children with MMC, especially those with more severe NP challenges or who have reduced family resources. Implementing this practice into the evaluation of the patient will be a valuable step toward more comprehensive treatment of adolescents with MMC. It is likely that PDS may negatively impact parenting quality and put children at risk for additional negative outcomes [58]. Helping to identify and manage a parent’s depressive symptoms is increasingly recognized and supported as an important part of caring for children with chronic conditions [59,60]. In addition, clinicians need to assess family protective factors in all families with MMC due to the direct relationship of these family variables with depressive symptoms. Providers should determine the sup-

portive resources available to parents of these adolescents. Importantly, this study suggests that weak family resources explain a significant amount of the variance in parental depressive symptoms. These findings also suggest that clinicians should be aware of the valuable role neuropsychologists can play in the treatment of adolescents with MMC and their families. The relationship observed in this study among parental depressive symptoms, family resources, and adolescents’ Executive Functioning suggests that if deficits are identified through NP assessment, not only could the adolescent benefit from subsequent NP interventions but the results could serve as a red flag to clinicians to assess for parental depressive symptoms. Given that the relationship between neuropsychological deficits and increased family distress has been documented in other pediatric medical populations [16–19], clinicians working with these groups may also want to explore for the presence of PDS when neuropsychological deficits are documented. 4.2. Implications for future research Future research should examine the differences in the impact of the neuropsychological functioning of adolescent’s with MMC on maternal and paternal depression separately. Research suggests that not only are paternal experiences under-researched but also that mothers and fathers might experience depression differently [54]. Another important area for future research is intervention. For example, the next step in this area could be to explore the benefit of parental education to explain how MMC-related NP deficits and family resources are associated with depressive symptoms in parents. In addition, research in pediatric traumatic brain injury suggests that family distress and psychological problems are often present [53,56,61] and supportive resources appear to alleviate this reported distress [62]. If a similar association is present in MMC, clinicians may be able to play a role in providing such resources. More specifically, provision of information about a pediatric medical condition and child development by a clinician is considered by families to be a useful resource [63,64]. In addition, recent research has indicated that ethnicity may influence both parent distress and the factors associated with this distress in families of children with MMC [65]. This sample was primarily Caucasian; investigating factors related to PDS and parental well-being in a more diverse sample is indicated. It may also be valuable to examine whether adolescence, as a developmental period, further complicates

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the relationships among parental depressive symptoms, family resources and NP deficits in adolescents with MMC [66]. Analysis of data from our larger study suggests that adolescents with MMC might not be participating in activities such as decision-making and peer interactions to such an extent as to facilitate a healthy transition into adulthood [67]. Moreover, the challenges faced by younger adolescents with MMC and their families may be different than those faced by older adolescents [68]. In addition, it would be important to determine if PDS differs in younger age groups. For some families, school entry or transition to middle school may be high-risk ages for the child and impact PDS. Finally, parental mental health or well-being may be more than the opposite of parent depression. Three different components of parental psychosocial functioning (parenting stress, individual psychosocial adjustment, and marital satisfaction) contributed independently to adolescent adjustment in a previous study [69]. Similarly, in a related study of factors associated with well-being in parents of children with cerebral palsy, family functioning, caregiver demands and child behavior had the largest direct effects on psychosocial heath, whereas self-perception, social support and stress management had indirect effects [48]. Understanding the factors related both indirectly and directly to the negative parental outcome (parental depressive symptoms) and the positive outcome (wellbeing) might provide evidence for preventing the former and strengthening the latter. 4.3. Limitations There are limitations to this study that might affect the strength of the study conclusions. First, the small sample size raises the possibility that there was insufficient power to detect the moderating effect. The present sample was sufficient to detect the moderate to large direct effects in the overall model; the incremental change in variance explained by the moderating variable (above and beyond the two independent variables) was near zero and would have been nonsignificant even in a very large sample. Therefore, statistical power does not appear to be a culprit for the moderating effect but may have impacted the ability to determine other factors with small to medium relationships to PDS as sample size limited the number of variables included in the model. The findings of this study provide preliminary direction for future model building. More comprehensive models with additional con-

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cepts need to be tested in the future to provide a better understanding of parent depressive symptoms. As a second limitation, this sample was fairly well educated and may not be reflective of the range of education or socioeconomic status of families with spina bifida. Further, the single measure of socioeconomic status was a limitation. Although education has been supported as a valuable measure of socioeconomic status in the literature, measuring this variable more comprehensively and engaging a more diverse sample would be critical in future studies. Another potential limitation is that the relationship between family protective factors and parent depressive symptoms may be inflated due to common method variance. Alternative observational measures of family functioning such as family communication or problems solving simulations might provide useful data. Correlational studies such as this one are limited in addressing issues of causality. As a methodological consideration, this study cannot provide definitive evidence that the adolescent’s NP deficits are causing the parent’s depressive symptoms. It is possible that parent’s depressive symptoms contribute to depressive symptoms in the child, with a subsequent adverse impact on the child’s NP functioning. Another alternative is that some third variable (e.g., severity of the disorder) is causing both the NP deficits and the parent’s depressive symptoms. However, in our data no support was found for a direct relationship between clinical data that are commonly thought to represent severity of the disorder (i.e., shunt status, bowel or bladder status) and parental depressive symptoms. Similarly, in his meta-analysis, Vermaes noted that most studies found no association between the degree of the physical disability and parents’ psychological adjustment [24].

5. Conclusions This study found fairly high levels of depressive symptoms in parents of adolescents with MMC and delineated multiple correlations between NP and family variables to the outcome. Multiple hierarchical regressions identified two significant factors, Executive Function and Family Protective Composite. Although, the study was limited by a single site, and a sample that lacked diversity, the findings do give preliminary direction to clinicians working with parents of adolescents with MMC. Clinicians are encouraged to include assessment of parental depressive symptoms in routine

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care of families who have an adolescent with MMC, and to identify as priorities for screening and treatment, parents whose adolescent has executive functioning impairments or parents who have few family protective factors.

Acknowledgments This project was funded in part by the Clarian Health Partners, American Association of Spinal Cord Injury Nurses, NIH Institutional National Research Service Award # 5 T32 NR07066 and MCHB’s Leadership Education in Adolescent Health, Indiana University. In addition, the authors thank Janet Kain, Susan Modlin, Vanessa Patrick, Brenna C. LeJeune, Patricia A. Taylor-Cooke, Sherry Mullinix Pryor, Erin Hundley, and Elizabeth “Raven” Cuellar for their assistance with data collection and database management.

Conflict of interest The authors have no conflict of interest to declare.

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