Abstract
Abstract
The aim of this study was to explore the relation between mothers’ parenting stress and the functioning of the hypothalamic–pituitary–adrenal axis (HPAA), as expressed by daily salivary cortisol concentrations, in their children diagnosed with attention deficit hyperactivity disorder (ADHD). Seventy-five children aged 6–11 years diagnosed with ADHD predominant hyperactive-impulsive/combined (ADHD–HI/C, N = 49) and inattentive symptoms (ADHD–I, N = 26) and 45 healthy peers and their mothers participated in the study. Μothers completed measures assessing their children’s ADHD status, perceived parenting stress (Parenting Stress Index – Short Form, PSI–SF), mothers’ symptoms of psychopathology, social support and socioeconomic status. Children’s salivary cortisol samples were collected at six different time points on a single day. Mothers of children with ADHD–HI/C reported higher levels of parenting stress than mothers of children with ADHD–I and controls. All PSI–SF subscales showed significant associations with children’s cortisol awakening response (CAR) in both ADHD groups, with the exception of the parental distress subscale in the ADHD–I group. In both ADHD groups, the parent–child dysfunctional interaction subscale, the difficult child subscale and the PSI total score were significantly associated with children’s CAR. An interrelation is revealed between mothers’ high levels of parenting stress and HPAA functioning in children with ADHD. In this population, CAR has been identified as a sensitive peripheral measure of HPAA functioning in children.
Lay summaryThis study showed that in families of children diagnosed with ADHD, there is a complex relation between the mothers’ high levels of parenting stress and children’s atypical hypothalamic–pituitary–adrenal axis functioning.
Introduction
The association between children’s diagnosis of ADHD and parents’ elevated levels of parenting stress has been amply documented (Algorta et al., 2015; Graziano et al., 2011; Theule et al., 2012; Wiener et al., 2016). What is more, research evidence has shown that parents of children diagnosed with ADHD report higher levels of self-perceived parenting stress compared to parents of children with other health problems and disorders (Gupta, 2007). A broader understanding of the relation between parenting stress and children’s ADHD requires that research elucidates into the mechanisms involved (Theule et al., 2012). Current scientific evidence points to the role of the hypothalamic–pituitary–adrenal axis (HPAA), a physiological system that is deemed to have a key role in stress reactivity, as well as in the neurobiological mechanisms underlying ADHD symptoms (Fairchild, 2010).
A burgeoning amount of research has focused on investigating the role of the HPAA in ADHD (Fairchild, 2010), but findings remain inconclusive due to methodological inconsistencies and measurement discrepancies. Early evidence positing an attenuated diurnal cortisol pattern for children with ADHD (Kaneko et al., 1993), especially for those in the hyperactive/impulsive spectrum (ADHD-HI), has been both corroborated (Isaksson et al., 2012; Ma et al., 2011) and challenged by later researchers (Freitag et al., 2009; Sondeijker et al., 2007). The same ambiguity is present in studies examining cortisol secretion following stressful stimuli in children with ADHD. Albeit results remain contradictory, it has been suggested that an atypical cortisol response to stress may be associated with more disruptive (e.g. ADHD–combined type (ADHD–C)) and/or persistent ADHD symptoms, as well as with existing comorbidity with internalizing or externalizing disorders (Fairchild, 2010).
In stark contrast, there is clear consensus regarding the prominent role of parenting styles and practices in HPAA activity (Clowtis et al., 2016; Dougherty et al., 2013; Fairchild, 2010; Marceau et al., 2013, 2015; Martin et al., 2014). Children who are chronically exposed to insensitive, inconsistent, emotionally unavailable or even over–reactive, stressful and harsh parenting are at considerable risk of displaying aberrant HPAA functioning, including heightened, blunted and/or prolonged cortisol responses (Lucas-Thompson & Goldberg, 2011).
The aim of this study was to explore potential associations between mothers’ self–reported parenting stress and HPAA functioning in a sample of children with a clinical diagnosis of ADHD–hyperactive-impulsive/combined type (ADHD–HI/C), ADHD–inattentive type (ADHD–I) and healthy controls. We hypothesized that mothers of children with ADHD–HI/C and ADHD–I would report higher levels of parenting stress and that their heightened stress levels would be associated with a flattened diurnal cortisol pattern in their children. We also hypothesized that mothers of healthy children would display the lowest levels of parenting stress, while their children’s diurnal cortisol slopes were expected to be steeper than those of children with ADHD–HI/C and ADHD–I. In addition, we aimed to examine if and how distinct aspects of parenting stress were associated with HPAA functioning in nonaffected children and children with ADHD. Lastly, we intended to contribute to existing mixed evidence regarding HPAA functioning in children with an ADHD diagnosis. In investigating the above, parental socio–economic status (SES), social support, as well as mothers’ symptoms of psychopathology and children’s age and sex were controlled for.
Participants and procedure
The study recruited children of both sexes aged 6–11 years old and their mothers in the years 2012–2013. The ADHD group sample was derived from the Outpatient Clinic of the Department of Child and Adolescent Psychiatry, University of Athens and “Aghia Sophia” Children's Hospital, whereas the control group was comprised of a convenience sample of healthy children emanating from the social circle of the ADHD group. The purpose of the study as well as the methods and procedures of data collection and processing were explained to all candidate participants by the primary researcher. Upon being provided with due information, parents were asked to sign an informed consent form to participate in the study and a copy was given to them. All data were entered into a SPSS (IBM Corp., Armonk, NY) database. Subjects’ privacy was protected by using a distinct personal code, whereas any demographic data that could lead to a subject’s identification were erased. Access to this database was strictly allowed to the research team. Ethical approval was attained from the Bioethical Committee of the Children’s Hospital. All procedures were according to the Declaration of Helsinki.
The sampling procedure, which is illustrated in Figure 1, was two–staged. Initially, all children were subjected to a thorough medical, mental and psychological assessment. At this first stage, children were excluded from the study if they were found to have an Intelligence Quotient (IQ) < 70, comorbid pervasive developmental disorders, comorbid autoimmune, endocrine or chronic disorders or conditions and/or if they were using corticosteroid medication. Children with genetic or chromosomal disorders were also excluded from the study. At the second stage, the K–SADS–PL was performed to both children and their mothers to verify the presence/absence of ADHD or other mental disorders according to DSM–IV criteria (American Psychological Association [APA], 2000). Children who were screened positive for an ADHD diagnosis according to the K–SADS–PL interview formed the ADHD group and were divided into the ADHD–HI, ADHD–C and the ADHD–I subgroups in accordance with DSM–IV diagnostic criteria. Children with ADHD–HI and ADHD–C were merged into a single category, forming the ADHD–HI/C group. This decision was based on the fact that the ADHD-HI group was comprised of a very small sample of children (2 males, aged 6 years old) that also manifested sub-threshold inattentive symptoms.
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28 March 2017![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/ists20/2017/ists20.v020.i02/10253890.2017.1303472/20170411/images/medium/ists_a_1303472_f0001_c.jpg"})
Figure 1. Sampling flowchart.
The presence of any (comorbid) psychiatric disorder was an exclusion criterion for both ADHD and control groups. Children were also excluded from the ADHD group if they were receiving any kind of pharmacological or psychotherapeutic treatment for ADHD prior to the assessment, as well as if the severity of the presenting ADHD symptoms was below threshold (<6) in accordance with DSM–IV diagnostic criteria. In parallel, children from the community sample with no indication of ADHD symptoms and no psychiatric condition according to the K–SADS–PL interview were placed in the control group. In cases of positive screening for ADHD or for other psychiatric condition in the community sample, children were excluded from the study and were subsequently referred to appropriate treatment.
Mothers of both groups were asked to complete a series of questionnaires intended to assess for presence of psychological problems and psychopathological symptoms, levels of parenting stress and levels of self–perceived social support. In addition, they provided sociodemographic information of their family. Inclusion criteria for mothers were adequate reading skills and living with the child participating in the study. Mothers of children in the study group received the saliva tubes (Salivette, Sarstedt Inc., Numbrecht, Germany) from the primary researcher. Oral and written sampling instructions were given to mothers and they were encouraged to contact the primary researcher for any further clarification.
In total, 168 children and their mothers were initially recruited and 159 of them agreed to participate (ADHD group, N = 105 children, control group, N = 54 children). Seven children were excluded from the control group due to indications of ADHD symptomatology narrowing the control group sample to 47 children. Twenty-seven children of the ADHD group were excluded from the study because of existing psychiatric comorbidity. Saliva collection kits contained six saliva sampling tubes to be used at the six preindicated sampling times. One hundred twenty five saliva collection kits were distributed and 123 kits were finally returned. Three of them were found unsuitable for further processing due to inefficient saliva concentration, after the centrifugation, in at least one sampling tube. Therefore, 120 saliva collection kits were finally processed and analyzed.
Measures
Children’s measures
Kiddie–schedule for affective disorders andschizophrenia–present and lifetime version(K–SADS–PL, v.1.0)
The K–SADS–PL (Kaufman et al., 1997) is a semi–structured diagnostic interview designed to assess current and past episodes of psychopathology in children and adolescents in accordance with DSM–IV criteria. It is administered by a trained interviewer to parent and child separately. For the purposes of the present study, the unstructured Introductory Interview, the Diagnostic Screening Interview, the appropriate Diagnostic Supplements (1. Affective Disorders, 2. Psychotic Disorders, 3. Anxiety Disorders, 4. Behavioral Disorders & 5. Substance Abuse and Other Disorders) and the Children's Global Assessment Scale (C–GAS) were completed. Ratings were completed by the interviewer after synthesizing all the data and resolving discrepancies in informants' reports. Scores ranged from 0 to 100, with higher values depicting optimal functioning in all areas. The K–SADS–PL has shown good psychometric features (Kaufman et al., 1997). The Greek version (1.0) of the K–SADS–PL (Kolaitis et al., 2003) was used in the present study (Cronbach α > 0.7).
Physical examination
A full clinical examination was performed in all children, including weight and height measurements and pubertal assessment by a board certified pediatrician.
Neuroendocrine evaluation
Salivary sampling was performed on a regular Sunday, at home and under the mother’s supervision. Sampling tubes were provided to collect saliva at six different time points (awakening time at approximately 08.30–09.00, 30’ after waking up, 12.30, 15.30, 18.30 and 21.30). Parents were instructed that the sampling be conducted after a thorough mouth washing with water and at least 30 min before eating, drinking or tooth brushing. In addition, sampling should not take place if the child had been engaged in intensive play or exercise, had an unusually big meal, had any uncommon intense experience or had consumed any medication, alcohol or smoking products. In such cases, parents were instructed to reschedule children’s salivary sampling for next Sunday. Children were asked to keep the cotton swabs in their mouth for approximately 2 min to ensure that the swab had been soaked with saliva. Subsequently, mothers placed the swabs in Salivette collection devices (Sarstedt Inc., Numbrecht, Germany), labeled each sampling tube to indicate the day and exact time of sampling and stored them in the refrigerator at the usual setting of 0–4 °C. To increase compliance with sampling instructions, mothers received a phone call prior to the sampling day from the primary researcher in order to ensure that the sampling procedure would be carried out as planned. Within two days from collection, the samples were given to the investigator for further processing. Salivary cortisol was extracted from the cotton by centrifuging the plastic tubes and cotton at 1000 g for 8 min to separate off the saliva into the outer tube. The cotton was then removed and all samples were stored at −80 °C. Samples were processed using the Elecsys Cortisol reagent kit produced by Roche Co (Basel, Switzerland). Salivary cortisol concentrations were measured using an electrochemiluminescence immunoassay (Roche Co., Basel, Switzerland). The intra- and interassay precision coefficients of variation for salivary cortisol concentrations was <0.036 μg/dl.
Maternal measures
Parenting Stress Index–Short Form (PSI–SF)
The PSI–SF is a 36-item self–report measure assessing enduring patterns of parental distress that are commonly linked to dysfunctional parenting (Abidin, 1995). The instrument consists of three subscales: parental distress, parent/child dysfunctional interaction and difficult child, as well as an overall parenting stress score. The parental distress subscale measures parent’s sense of parenting competence and personal stresses associated with restrictions on his/her life, conflict with the child’s other parent, social support and depression. The parent–child dysfunctional interaction subscale assesses parent’s perceptions and feelings of rejection, alienation and disappointment with respect to their child and their mutual interactions. The difficult child subscale shows how easy or difficult the parent perceives his/her child to be while the PSI Total Score indicates the overall stress parents may feel when they are parenting. Items are rated on a 5-point scale, ranging from “strongly agree” to “strongly disagree” with higher scores being indicative of higher parenting stress. The measure has well-established reliability and validity in both clinical and community populations (Haskett et al., 2006). Cronbach’s a coefficient in the present study was found to be satisfactory (α > 0.7).
The Symptom Checklist 90 Revised (SCL–90–R)
The SCL–90–R is a self-report inventory intended to measure symptom intensity on nine primary symptom dimensions (Derogatis, 1994). It consists of 90 items rated on a five-point scale of distress from 0 (none) to 4 (extreme). Clusters of 6–13 items are used to provide scores on nine different subscales: 1. Somatization (SOM), 2. Obsessive–compulsive (O–C), 3. Interpersonal sensitivity (I–S), 4. Depression (DEP), 5. Anxiety (ANX), 6. Hostility (HOS), 7. Phobic anxiety (PHOB), 8. Paranoid ideation (PAR) and 9. Psychoticism (PSY). The SCL–90–R also provides scores on three global indices of distress: 1. Global Severity Index (GSI), 2. Positive Symptom Distress Index (PSDI) and 3. Positive Symptom Total (PST). It has been standardized for use in Greek adult population (Donias et al., 1991) with good psychometric qualities (Cronbach α > 0.7).
Norbeck Social Support Questionnaire (NSSQ)
The NSSQ is a multidimensional self-administered questionnaire designed to measure supportive social networks, the types of support and its functional components (emotional and tangible aid) (Norbeck et al., 1981). Mothers were called to identify persons who provided social support and to rate the extent to which each of the persons listed provided that support on an emotional (affect and affirmation) and tangible level. Items were rated on a five-point Likert scale (from 0 = not at all to 4 = a great deal). Reliability and validity of NSSQ have been previously established (Norbeck et al., 1983). The Cronbach α coefficient in the present study was above 0.7.
The Hollingshead Four Factor Index of Socioeconomic Status
The Hollingshead Four Factor Index of Socioeconomic Status is a tool designed to measure social status of an individual based on four domains: marital status, retired/employed status, educational attainment and occupational prestige (Hollingshead, 1975). It generates a total SES score based upon maternal and paternal education and occupation. It was completed by the primary researcher based on information provided by the mothers on the socio–demographic form that was designed for the present study. The latter contained information regarding the child’s basic demographic data and the parents’ current marital, educational and employment status.
Statistical analysis
Quantitative variables were expressed as mean values (SD), while categorical variables were expressed as absolute and relative frequencies. For the comparison of proportions chi–square tests were used. Analysis of variance (ANOVA) was used for the comparison of mean values of participants’ characteristics between the three groups. Analysis of covariance (ANCOVA) was used for the comparison of PSI subscales including sex as a covariate. Bonferroni correction was used to control for multiple testing. Effect sizes were computed using partial eta-squared (η2) and interpreted as follows: small = 0.01; medium = 0.06; large = 0.14 (Sink & Stroh, 2006). Partial correlation coefficients (r) adjusted for sex were computed in order to explore the association of baseline, maximum measurements along with % change of cortisol, CAR and area under the curve (AUC) with PSI subscales and total score. To longitudinally assess changes in cortisol, mixed linear regression models spline with time (knot was selected at 30 min after awakening) were fitted that accounts for multiple measurements per individual obtained at different time points. All analyses were conducted using a random coefficient model with the intercept being random and a covariance structure of variance components. Mixed linear models were also used in order to evaluate changes of cortisol over time in association with PSI subscales and total score. Regression coefficients (β) with standard errors (SE) were computed from the results of the models. All reported p values are two-tailed. Statistical significance was set at p < .05 and analyses were conducted using SPSS statistical software (version 19.0) (International Business Machines [IBM], 2010).
Results
The study sample consisted of 75 children with a confirmed diagnosis of ADHD (N = 26 ADHD–I group and N = 49 ADHD–HI/C group) and 45 healthy peers. Demographics are presented in Table 1. All three groups were similar in terms of sex, age, SES and total SCL–90 scores (p > .05). Also, the NSSQ subscale mean values were similar between the three groups (Table 1).
Table 1. Participants’ characteristics in the three study groups.
Higher scores on the Parental Distress and Difficult Child subscales (p < .01) were found in the ADHD–HI/C group than the ADHD–I and control groups (Table 2). In the Parent–Child Dysfunctional Interaction subscale, controls had significantly lower score compared to the ADHD–I and to the ADHD–HI/C group (p < .05). Also, total PSI score was significantly higher (p < .01) in the ADHD–HI/C group than the ADHD–I and control groups. Effect sizes of the differences were large for all PSI dimensions.
Table 2. Mean levels on PSI subscales and total score in the three study groups.
Correlation coefficients between cortisol (baseline, maximum and % change), AUC, CAR and PSI subscales in the three study groups are shown in Table 3. In the control group, a significant and positive correlation was found between the area under the curve with respect to Increase (AUCi) and the difficult child subscale (p < .01). Also, in both ADHD–I and ADHD–HI/C groups, Parent–Child Dysfunctional Interaction, Difficult Child and PSI total score were negatively associated with the CAR. In the ADHD–HI/C group, in addition to the aforementioned subscales, a significant negative correlation was also found between the Parental Distress subscale and the CAR (p < .05).
Table 3. Partial correlation coefficients adjusted for gender, between cortisol (baseline, % change and maximum), AUC, CAR and PSI subscales in the three study groups.
Cortisol levels showed a significant increase from baseline to 30 min in the control group (mean change: 4.1, p < .001), whereas in the ADHD–I (mean change: 0.23, p = .899) and ADHD–HI/C (mean change: −0.2, p = .811) groups, there were no significant changes. After the 30 min, a significant but similar reduction in cortisol levels (p < .001) was observed in the three groups.
Table 4 presents results of mixed–model regression analysis for cortisol in association with PSI subscales in the ADHD–I group. Scores on PSI subscales were divided according to median values on high and low levels. Scores on Parental Distress were not associated with cortisol changes during follow-up. Cases with high scores on the Parent–Child Dysfunctional Interaction subscale had higher baseline cortisol values (p = .028). Additionally, a significant interaction effect of Parent–Child Dysfunctional Interaction (p = .003), Difficult Child (p = .039) and PSI total score (p = .014) with time until 30 minutes were found, indicating that in inattentive cases with high scores on the aforementioned subscales there was a decrease on cortisol levels, while in Inattentive cases with low scores on the same subscales, cortisol levels remained unchanged. Cortisol changes during follow–up in Inattentive cases according to PSI total score levels are shown in Figure 2.
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28 March 2017Figure 2. Linear predictors for cortisol in children with ADHD–I in association with mothers’ high/low levels of PSI total score.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/ists20/2017/ists20.v020.i02/10253890.2017.1303472/20170411/images/medium/ists_a_1303472_f0002_b.jpg"})
Figure 2. Linear predictors for cortisol in children with ADHD–I in association with mothers’ high/low levels of PSI total score.
Table 4. Results of mixed–model regression analysis for cortisol in association with PSI subscales in the ADHD–I group.
Results of mixed–model regression analysis for cortisol in association with PSI subscales in the ADHD–HI/C group are shown in Table 5. Scores on Parental Distress were not associated with cortisol changes in the ADHD–HI/C group during follow-up. Cases with high scores on Parent–Child Dysfunctional Interaction had higher baseline cortisol values, similarly with inattentive cases (p = .034). Furthermore, a significant interaction effect of Parent–Child Dysfunctional Interaction (p < .001), Difficult Child (p = .006) and PSI total score (p = .019) with time until 30 min was found. This indicates that in hyperactive-impulsive/combined cases with high scores on the aforementioned subscales, there was a greater decrease of cortisol levels, than in ADHD–HI/C cases with low scores. Cortisol changes during follow-up in the ADHD–HI/C group according to PSI total score levels are shown in Figure 3. The results for both ADHD groups were similar after adjusting the analysis for children’s sex & age, as well as for maternal psychopathology and mothers’ reports of social support and SES.
Published online:
28 March 2017Figure 3. Linear predictors for cortisol in children with ADHD–HI/C in association with mothers’ high/low levels of PSI total score.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/ists20/2017/ists20.v020.i02/10253890.2017.1303472/20170411/images/medium/ists_a_1303472_f0003_b.jpg"})
Figure 3. Linear predictors for cortisol in children with ADHD–HI/C in association with mothers’ high/low levels of PSI total score.
Table 5. Results of mixed-model regression analysis for cortisol in association with PSI subscales in the ADHD–HI/C group.
Discussion
The primary aim of this study was to cast light upon the association between parenting stress and HPAA functioning in a sample of children diagnosed with ADHD and nonaffected controls. Children with ADHD–HI/C and ADHD–I showed nonsignificant changes in their cortisol levels from baseline to 30 min later, whereas their cortisol levels during the rest of the day manifested a downward pattern. In the control group, on the other hand, a reduction of cortisol levels was demonstrated from baseline to 30 min later and until the end of the day. Our finding resonates with previous studies documenting diminished morning cortisol levels and attenuated CAR among children with ADHD (Kaneko et al., 1993; Ma et al., 2011) and no comorbid conditions (Blomqvist et al., 2007; Isaksson et al., 2012, 2013). Yet, one should not neglect existing research evidence that has either failed to reveal any differences in the CAR between children with ADHD and nonaffected children (Sondeijker et al., 2007) or has demonstrated that such differences are attributed to comorbid conditions, especially ODD (Freitag et al., 2009). It should be noted that, even though children with ADHD and comorbid disorders were excluded from the present study, it is possible that our findings may have been partially affected by the children’s subthreshold comorbid symptoms.
Consistent with previous findings (Graziano et al., 2011; Pimentel et al., 2011; Weinberger et al., 2015), mothers of children with ADHD–HI/C had higher scores in all PSI dimensions and total score than mothers of children with ADHD–I and nonaffected ones (apart from a statistically insignificant difference regarding the Parent–Child Dysfunctional Interaction between the ADHD–HI/C and ADHD–I group). The magnitude of observed differences in the present study is in line with previous research in mothers of children with ADHD-HI/C (Weinberger et al., 2015) and persistent ADHD symptoms (Gau & Chang, 2013). Mothers are largely affected by children’s ADHD symptoms (Gau & Chang, 2013; Lifford et al., 2008) granted that they are actively involved in monitoring and disciplining behavior, negotiating demands of daily life and scaffolding children’s organizational and social skills (Gau & Chang, 2013). Children with ADHD–HI/C manifest more complex needs and disruptive behaviors than children with ADHD–I or nonafflicted ones that tax on mothers’ physical and emotional resources (Weinberger et al., 2015). It has been hypothesized that mothers’ accentuated parenting stress may fuel poor quality parenting and set the stage for an unfavorable parent-child relationship (Gau & Chang, 2013; Lifford et al., 2008). Therefore, addressing mothers’ parenting stress and practices should constitute an integral part of any comprehensive ADHD-tailored treatment planning.
Furthermore, we attempted to assess whether different dimensions of parenting stress were associated with distinct cortisol levels in the control and the ADHD groups. Only the Difficult Child Subscale displayed any significant association with children’s cortisol levels across all three groups under study. In the control group, a significant positive association was shown between the Difficult Child subscale and AUCi, a cortisol measurement that assesses the pattern of cortisol change over time. This correlation indicates a link between mother’s difficulties in regulating their child’s behavior and children’s greater HPAA sensitivity, suggesting that mother’s stress in that particular domain is related to their child’s accentuated cortisol levels over the course of the day. This finding may generate several hypotheses: it may be hypothesized that the child’s accentuated cortisol levels may be associated with more disruptive behaviors, challenging, thus, the mother’s skills in regulating her child’s behavior. On the other hand, we may also hypothesize that the mother’s increased stress in regulating her child’s behavior might either constitute a stressful condition per se or lead to poor parenting or discipline practices, which in turn may be linked to children’s aberrant HPAA functioning. Within this frame of reference, increased cortisol concentration appears to serve an adaptive function, as it helps children adjust to their mothers’ heightened stress levels.
In stark contrast, the Difficult Child and the Parent–Child Dysfunctional Interaction Subscales, along with the PSI total score, showed robust negative associations with children’s CAR in both ADHD groups. These findings suggest that mothers of children with ADHD, especially with ADHD–HI/C, experience significant burden in most aspects of their parenting role, and this caregiving strain is related to a blunted CAR in their children. However, a reciprocal relation could be hypothesized as well: a child’s inattentive or hyperactive-impulsive/combined symptoms could exacerbate the mother’s parenting distress, thus hampering the mother’s competence in tuning into and meeting her child’s needs; in turn, this may constitute an adverse rearing condition for the child with potential impact on his/her HPAA functioning. In addition, the hypothesis that the children’s ADHD symptoms are both related to an attenuated HPAA functioning, in the form of a blunted CAR, and to their mother’s increased stress, is also possible and noteworthy. However, it should be emphasized that the aforementioned findings in the context of our cross-sectional study reveal a reciprocal association between a) mothers’ increased stress in regulating their children’s behavior and non-afflicted children’s accentuated cortisol levels over the course of the day (control group) and b) mothers’ increased overall parenting stress and children’s blunted CAR in the ADHD group, claiming no causal inferences regarding the direction of these relationships in both cases.
To elaborate further on the cortisol changes observed in children with ADHD according to mothers’ high or low levels of parenting stress, we conducted mixed linear regression analysis separately for children with ADHD–HI/C and ADHD–I. Results were similar for both groups and were not affected by adjusting for child’s age and sex, mother’s psychopathology, SES and social support. The Parent–Child Dysfunctional Interaction Subscale along with the Difficult Child Subscale and the PSI Total Score were significant predictors of children’s CAR, indicating that mothers’ higher overall parenting stress and more negative feelings and perceptions regarding their children have an effect on children’s HPAA functioning in the form of significant decrements in their CAR. Specifically, the Parent–Child Dysfunctional Interaction Subscale was the most robust predictor for children’s CAR. This subscale is an assessment of parents’ feelings of disappointment with and alienation from their child, indicative of a poor relational bonding. In practice, these feelings may be expressed through the parents’ lack of warmth or meager initiatives to interact with their child (Modesto-Lowe et al., 2008). We hypothesize, although this cannot be proven in a cross sectional setting, that such negative parental disposition and feelings towards the child may well be distressing for children at a neurobiological level. A significant body of studies has documented that lack of warm parent–child interactions and insensitive parenting are associated with aberrant stress regulatory abilities and less adaptive emotional and behavioral responses to stress in children (Clowtis et al., 2016; Deault, 2010; Dougherty et al., 2013; Gau & Chang, 2013; Lucas-Thompson & Goldberg, 2011; Pesonen et al., 2011) and with the continuation of early inattentive − hyperactive behavior problems (Keown, 2012).
In broad lines, our findings show that aspects of parenting a child with ADHD could be exceptionally stressful for mothers and that their inflated stress levels have a genuine association with children’s HPAA functioning, mainly in terms of an attenuated CAR. Controlling for children’s age and sex did not affect these findings, in accordance with previous studies (Freitag et al., 2009; Hastings et al., 2009; Hatzinger et al., 2007; Isaksson et al., 2012; Randazzo et al., 2008). Figure 4 illustrates the multiple possible relationships between mother’s increased parenting stress, children’s ADHD condition and their blunted CAR. A potential interpretation of our findings lies on the basis of the Behavioral Inhibition System (BIS), a neuropsychological motivational mechanism that governs humans’ responses to punishment and fear/anxiety provoking stimuli. A dysfunctional BIS has been implicated in symptoms of ADHD, including hyperactivity and deficits in executive functioning, notably in working memory and emotion regulation (Fairchild, 2010; Johnson, 2015), through a hypothesized pathway linking BIS underactivity with reduced cortisol levels both at neutral and stressful conditions (Fairchild, 2010). Therefore, adaptive arousal responses to daily life stress are hindered. An under–active BIS has a central role in explaining hypocortisolism in ADHD and is a crucial feature of current ADHD theoretical models (Barkley’s theory of poor response inhibition (Barkley, 1997), Sonuga–Barke’s Dual Pathway Model (Sonuga-Barke, 2005)). On the other hand, hypocortisolism may flag an adaptive HPAA functioning, in cases where stress is either chronic or overwhelming. It has been documented that elevated levels of parenting stress emerge early and tend to remain relatively stable across time (Koch et al., 2010; Ostberg et al., 2007; Treacy et al., 2005). Thus, it is plausible that the hypocortisolism observed in the ADHD children of our study actually reflects an adjustment of the HPAA functioning in the face of chronic exposure to high levels of parenting stress (Pesonen et al., 2011).
Published online:
28 March 2017Figure 4. Bidirectional Relations between Mothers' Parenting Stress (as assessed by the Parenting Stress Index) and Children's Stress Levels (as assessed by salivary cortisol levels) in children with ADHD.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/ists20/2017/ists20.v020.i02/10253890.2017.1303472/20170411/images/medium/ists_a_1303472_f0004_b.jpg"})
Figure 4. Bidirectional Relations between Mothers' Parenting Stress (as assessed by the Parenting Stress Index) and Children's Stress Levels (as assessed by salivary cortisol levels) in children with ADHD.
Our findings should be viewed in light of the limitations of the present study. First and foremost, our study sample (ADHD and control group) was neither large in number nor randomly recruited; therefore, we cannot infer generalizability of our findings. As in many relevant studies, boys outnumbered girls in both ADHD subgroups as well as in the control group. It should be mentioned, however, that our results remained the same after adjusting for children’s sex and age. Second, the cross–sectional design indicates a complex, bidirectional relation between parenting stress and HPAA functioning in children with ADHD, but it does not allow us to make causal inferences. With respect to cortisol collection, although we took measures to enhance compliance with suggested collection guidelines, we cannot verify that the collection times and procedures of the cortisol samples were recorded or performed accurately. In addition, to avoid a more demanding research protocol and risk increased attrition rates, we limited our sampling procedures to multiple collection times in the same day. Cortisol sampling across at least two days is strongly advised. Another limitation stems from focusing exclusively on mothers’ parenting stress, as there is current evidence supporting that father’s parenting practices are differentially related to children’s ADHD symptoms (Keown, 2012; Lifford et al., 2008). Furthermore, we did not include assessment of genetic, prenatal, postnatal and early childhood factors, such as early adversity, that have been documented to influence the development and functioning of children’s HPAA (Isaksson et al., 2013; Koch et al., 2010). We would strongly encourage future prospective research to account for these factors in assessing HPAA functioning in children with ADHD.
Conclusions
Within the limitations noted, our study takes an important, initial step towards mapping the interrelation of parenting stress and HPAA functioning in children with ADHD diagnosis. Mothers’ high parenting stress – usually exacerbated by children’s ADHD symptoms (Gau & Chang, 2013; Lifford et al., 2008; Weinberger et al., 2015) – was associated with aberrant cortisol profiles in children with ADHD, revealing possible interactions at a neurobiological level. Resonating with previous research (Chida & Steptoe, 2009; Freitag et al., 2009), the CAR was highlighted as a sensitive neurobiological indicator of HPAA functioning in middle childhood. Disentangling the multiple contextual factors that impinge on children’s HPAA functioning will deepen our understanding of the environmental contributions to the clinical picture of ADHD. Such an endeavor gains prominence in view of recent, promising research evidence supporting that HPAA malfunctioning can be regulated by psychosocial interventions targeting both children and their parents (Slopen et al., 2014). Comprehensive interventions that enhance parental competence, social networking and support and introduce optimal strategies for positive parent–child interactions and age–appropriate discipline could be particularly beneficial for mothers of children with ADHD, especially ADHD–HI/C. It is of paramount importance to translate such research evidence into clinical practice for families of children with ADHD in an effort to interrupt the vicious circle of negative interactions that not only hampers children’s neurobiological and psychosocial adjustment but also hinders their present and future achievements.
| Control | ADHD–I | ADHD–HI/C | ||
|---|---|---|---|---|
| N (%) | N (%) | N (%) | p | |
| Gender | ||||
| Boys | 28 (62.2) | 15 (57.7) | 39 (79.6) | .082b |
| Girls | 17 (37.8) | 11 (42.3) | 10 (20.4) | |
| Mean (SD) | Mean (SD) | Mean (SD) | p | |
| Age | 8.4 (1.7) | 9.4 (1.7) | 8.6 (2.0) | .066a |
| Socioeconomic status | 42.1 (7.4) | 40.7 (10.9) | 38.7 (9.5) | .204a |
| Total scl–90 (past) | 0.82 (0.29) | 0.85 (0.49) | 1.03 (0.58) | .180a |
| Total scl–90 (present) | 0.87 (0.35) | 1.02 (0.63) | 1.13 (0.59) | .233a |
| Emotional support score (NSSQ) | 127.1 (46.9) | 120.0 (53.8) | 115.7 (48.4) | .728a |
| Tangible support score (NSSQ) | 58.3 (22.5) | 57.1 (24.0) | 59.8 (22.4) | .803a |
| Total functional support score (NSSQ) | 185.4 (68.7) | 178.2 (75.4) | 175.5 (67.9) | .812a |
| Total network score (NSSQ) | 91.3 (31.1) | 89.7 (36.5) | 85.6 (34.0) | .690a |
| Total loss score (NSSQ) | 1.61 (2.73) | 1.65 (2.69) | 1.63 (1.71) | .757a |
| Average duration score (NSSQ) | 4.85 (0.28) | 4.80 (0.19) | 4.72 (0.36) | .273a |
| Average functional support score (NSSQ) | 20.2 (2.3) | 20.2 (3.7) | 19.0 (3.4) | .531a |
a ANOVA.
b Pearson’s chi–square test.
| Control (A) | ADHD–I (B) | ADHD–HI/C (C) | |||||
|---|---|---|---|---|---|---|---|
| Mean(SD) | Mean(SD) | Mean(SD) | pa A vs. B | pa A vs. C | pa B vs. C | Effect size η2 | |
| Parental distress | 25.6 (5.2) | 28.5 (7.9) | 35 (10.4) | .799 | <.001 | .010 | 0.84 |
| Parent–child dysfunctional interaction | 18.2 (4.4) | 26.1 (8.8) | 31.3 (11.4) | .021 | <.001 | .085 | 0.98 |
| Difficult child | 21.9 (6.4) | 28.5 (10.1) | 38.6 (12.2) | .116 | <.001 | .001 | 0.91 |
| PSI total score | 80.3 (15) | 99 (28.2) | 124.5 (34.4) | .109 | <.001 | .002 | 0.94 |
a ANCOVA after Bonferroni correction adjusted for gender.
| Baseline cortisol | Cortisol (% change) | Maximum cortisol | AUCg | AUCi | CAR | |
|---|---|---|---|---|---|---|
| Controls | ||||||
| Parental distress | −0.42 | 0.14 | −0.25 | −0.36 | −0.20 | −0.04 |
| Parent–child dysfunctional interaction | 0.05 | −0.08 | −0.10 | −0.30 | −0.04 | −0.19 |
| Difficult child | 0.19 | −0.30 | 0.43 | 0.32 | 0.72b | −0.12 |
| PSI total score | −0.09 | −0.12 | 0.04 | −0.17 | 0.18 | −0.10 |
| ADHD–I | ||||||
| Parental distress | −0.24 | 0.14 | 0.19 | 0.25 | 0.18 | −0.30a |
| Parent–child dysfunctional interaction | −0.55a | 0.27 | 0.04 | −0.37 | 0.20 | −0.54a |
| Difficult child | −0.49 | 0.14 | 0.15 | −0.23 | 0.25 | −0.65b |
| PSI total score | −0.46 | 0.13 | 0.13 | −0.14 | 0.24 | −0.52a |
| ADHD–HI/C | ||||||
| Parental distress | −0.16 | 0.09 | −0.06 | −0.04 | −0.02 | −0.36a |
| Parent–child dysfunctional interaction | −0.25 | 0.32 | 0.03 | 0.11 | 0.09 | −0.57c |
| Difficult child | −0.22 | 0.18 | 0.00 | 0.10 | 0.17 | −0.51b |
| PSI total score | −0.24 | 0.23 | −0.01 | 0.06 | 0.09 | −0.56c |
a p < .05.
b p < .01.
c p < .001.
| β* | SE | p | |
|---|---|---|---|
| Parental distress | |||
| High score on “Parental Distress” | −2.24 | 1.89 | .237 |
| Interaction with time (≤30 min) | −1.02 | 4.34 | .815 |
| Interaction with time (>30 min) | 0.29 | 0.19 | .128 |
| Parent–Child Dysfunctional Interaction | |||
| High score on “Parent–Child Dysfunctional Interaction” | 4.10 | 1.87 | .028 |
| Interaction with time (≤30 min) | −12.59 | 4.22 | .003 |
| Interaction with time (>30 min) | 0.36 | 0.18 | .049 |
| Difficult Child | |||
| High score on “Difficult Child” | 2.81 | 2.04 | .170 |
| Interaction with time (≤30 min) | −9.35 | 4.54 | .039 |
| Interaction with time (>30 min) | 0.22 | 0.20 | .256 |
| PSI total score | |||
| High score on “PSI total score” | 3.64 | 1.98 | .066 |
| Interaction with time (≤30 min) | –10.88 | 4.41 | .014 |
| Interaction with time (>30 min) | 0.26 | 0.19 | .179 |
β*= unstandardized regression coefficient.
Bold indicate values significant at p < .05.
| β* | SE | p | |
|---|---|---|---|
| Parental Distress | |||
| High score on “Parental Distress” | 0.98 | 1.10 | .373 |
| Interaction with time (≤30 min) | −0.80 | 2.35 | .733 |
| Interaction with time (>30 min) | −0.01 | 0.10 | .923 |
| Parent–Child Dysfunctional Interaction | |||
| High score on “Parent–Child DysfunctionalInteraction” | 2.26 | 1.06 | .034 |
| Interaction with time (≤30 min) | −7.84 | 2.23 | <.001 |
| Interaction with time (>30 min) | 0.19 | 0.10 | .067 |
| Difficult Child | |||
| High score on “Difficult Child” | 1.48 | 1.07 | .166 |
| Interaction with time (≤30 min) | −6.26 | 2.26 | .006 |
| Interaction with time (>30 min) | 0.19 | 0.10 | .062 |
| PSI total score | |||
| High score on “PSI total score” | 2.05 | 1.10 | .062 |
| Interaction with time (≤30 min) | −5.44 | 2.33 | .019 |
| Interaction with time (>30 min) | 0.11 | 0.10 | .291 |
β*= unstandardized regression coefficient.
Bold indicate values significant at p < .05.
Acknowledgements
We thank the families who participated in the study.
Disclosure statement
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.
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