Journal of Developmental and Behavioral Pediatrics最新文献

Objective: Attention deficit disorder with or without hyperactivity (ADHD) has negative consequences for children. The effectiveness of medical interventions and educational outcomes are strongly influenced by expectations, which can be modulated by nocebo effects. The aims of this study were to compare the nocebo effect on pain perception and attention in children with and without ADHD as well as to characterize the associations of the nocebo effect with personal variables, such as anxiety, sleep, and pain catastrophizing.

Methods: Data were collected from 30 children with and without ADHD. The nocebo effect was induced using an inactive pill, "increasing" pain perception and attention deficits. Experimental thermal pain was evoked using a thermode and recorded using a computerized visual analog scale. Attention abilities were measured with the Stop-Signal Task. We also used questionnaires to measure personal variables.

Results: When combining groups, the nocebo treatment led to comparable nocebo effects for pain (increased pain perception) and attention (increased time needed for inhibition). When comparing groups, the nocebo effect on pain perception was similar for children with and without ADHD. Inattention, learning problems, anxiety, and sleep problems were associated with the nocebo response for pain and attention.

Conclusion: This exploratory study conducted in an experimental setting emphasizes the importance of managing children's expectations for pain perception and attention as well as the potentially deleterious impact of negative suggestions on elementary school children.

Objective: Suboptimal sleep is associated with disruptive behaviors in childhood. We evaluate associations of mean and variability (SD) of sleep duration, quality, and timing with emotion regulation, impulsivity, and prosocial and antisocial behavior in children.

Methods: Intervention Nurses Start Infants Growing on Healthy Trajectories, a randomized controlled trial designed for obesity prevention, compared a responsive parenting intervention delivered in the first 2.5 years after birth with a home safety control group. At age 6 years, children wore an actigraphy device for 7 days and participated in behavioral tasks evaluating behavioral control, emotion regulation, and prosocial and antisocial behaviors. Separate linear regression models examined associations between sleep and behavioral variables, adjusting for study group, child sex, and household income. Moderation analysis investigated whether the study group moderated relationships between sleep and positive age-appropriate behavior.

Results: Children (N = 143, age 6.7 ± 0.3 years) were predominantly non-Hispanic White (95%). Mean actigraphic sleep duration, quality, and timing were not associated with behavioral variables. By contrast, greater variability in sleep onset timing was associated with greater impulsivity (B = 0.85, p = 0.004) and poorer emotion regulation (B = -0.65, p = 0.01). Greater variability in sleep midpoint timing was associated with greater impulsivity (B = 0.80, p = 0.03). The study group moderated the effect of sleep onset variability on behavior; only the home safety control group exhibited a significant negative relationship between variability in sleep onset timing and emotion regulation (B = -1.28, p = 0.0002).

Conclusion: Findings support the importance of consistency in sleep timing and how this may play a greater role in children's behavioral and emotional outcomes than mean actigraphic sleep duration and quality.

Case: Leo is a 28-month-old boy from a monolingual Spanish-speaking family who was referred to a developmental-behavioral pediatrics (DBP) clinic for concerns regarding autism. His parents migrated to the United States 8 years ago and currently live and work on a farm. He was born in a US hospital after an uncomplicated pregnancy and has been generally healthy. His parents first became concerned about his development when he was 16 months old. He stopped saying mama/dada in Spanish and started lining up random objects. He had frequent temper tantrums and was difficult to console during unexpected changes in his routine. He screened positive on the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) at his 18-month well-child visit, and his pediatrician referred him to the local early intervention program. Calls from the early intervention program to his parents were unanswered. At his 24-month well-child visit, he again screened positive on the M-CHAT-R/F, and his pediatrician placed a referral for a DBP consultation. During the DBP visit at 28 months of age, developmental testing indicated his receptive and expressive language skills to be in the extremely low range, with significant scatter in his cognitive and adaptive skills. Behavioral observations were consistent with parental history and showed differences in social communication and interaction, the presence of repetitive behaviors, and extreme distress with transitions. He was diagnosed with autism spectrum disorder. Recommendations, including referral to early intervention, applied behavior analysis therapy, speech and language therapy, audiology evaluation, and genetic testing, were discussed with his parents through an interpreter. An autism packet, written in Spanish, with detailed information about autism and community resources was given to the family. By the time of a follow-up DBP visit 6 months later, Leo had not started on any early intervention or therapeutic services. Where do you go from here?

Objective: Dynamic, real-time, in-home methods of data collection are increasingly common in child health research. However, these methods are rarely cocreated or used with families of youth with developmental disabilities. We aimed to determine the feasibility of codesigned methods for in-home data collection for youth across the developmental spectrum.

Methods: Sixteen youth (14-18 years) with autism spectrum disorder, cerebral palsy, and/or chronic pain completed 14 days of data collection, wearing an accelerometer, answering Ecological Momentary Assessment (EMA) questionnaires, and collecting salivary cortisol samples. Participants completed a poststudy interview regarding their experiences. Data were analyzed for feasibility, quantity, and quality.

Results: At least 1 EMA response was provided on 73% of days, with 54% of the total number of administered prompts answered before the next prompt arrived. In total, 77% of participants wore the accelerometer ≥10 hours for at least 7 days. Adherence to 8-day saliva sampling after accounting for protocol violations and dry samples was 28%. No significant adverse events were reported aside from mild emotional distress (25%). Families reported generally high satisfaction, willingness to participate again, and acceptability, with moderate burden and interference. Qualitative interviews described: (1) the research question's value to the family as a motivator of engagement; (2) in-home data collection is not a passive or neutral experience; (3) personalized approaches and context are important to families; and (4) a clear need for continued iteration and engagement.

Conclusion: In-home multimodal data collection is potentially feasible for families across the developmental spectrum but requires iteration based on family feedback to increase adherence.

Objective: The purpose of this study was to discover the care meanings of facilitators and barriers to detection and intervention for developmental delay among Head Start preschool-aged children, as viewed by parents, teachers, and primary care providers.

Methods: We used a qualitative focus group design and broad cultural lens to understand similarities and differences in family and professional care, as Head Start programs educate preschoolers living in poverty who are disproportionately from ethno-racial minoritized groups. We sought the perspectives of 15 Head Start parents equally representing Black, Latino(a), and White parents, 17 teachers, and 11 healthcare providers to discover facilitators and barriers to adherence with professional recommendations.

Results: We found that silos in professional communications, parent distrust, knowledge deficits, and stigma were barriers to obtaining developmental recommendations. Participants also identified missed opportunities to facilitate interagency coordination, parental advocacy of a child's developmental needs, and professional alliances to take collaborative actions for early identification and treatment. Furthermore, a subculture of poverty adversely influenced adherence to developmental recommendations, and ethno-racial biases affected Black and Latino(a) families' follow-through.

Conclusion: Our findings highlight how the lack of coordination between sectors resulted in the dismissal of parental concerns or denial of services by 1 system or the other, thus, at the very least reducing the child's chances for earlier intervention and treatment. We also identified potential benefits to children when the barriers of poverty and ethnoracial bias are addressed by professionals with coordinated actions, and new systems are developed for sharing developmental screening results and partnering to coordinate care across the preschool and primary healthcare settings.

Objective: To examine whether maternal cannabis use during early pregnancy is associated with offspring attention deficit hyperactivity disorder (ADHD) and disruptive behavior disorders (DBD).

Methods: We conducted a population-based retrospective birth cohort study of children (N = 141,570) born between 2011 and 2018 to pregnant individuals (N = 117,130) in Kaiser Permanente Northern California universally screened for any prenatal cannabis use at the entrance to prenatal care (at ∼8-10 wk gestation). Prenatal cannabis use was defined as (1) self-reported use and/or a positive toxicology test, (2) self-reported use, (3) a positive toxicology test, and (4) self-reported use frequency. Cox proportional hazards regression models adjusting for maternal characteristics (sociodemographics, other substance use and substance use disorders, prenatal care initiation, comorbidities) examined associations between prenatal cannabis use and offspring ADHD and DBD diagnosed by age 11 years.

Results: The sample of pregnant individuals was 27.2% Asian/Pacific Islander, 5.7% Black, 24.5% Hispanic, and 38.8% non-Hispanic White, with a mean (SD) age of 30.9 (5.2) years; 4.6% screened positive for any cannabis use (0.4% daily, 0.5% weekly, 1.1% monthly or less, 2.7% unknown frequency); 3.92% had a positive toxicology test and 1.8% self-reported use; 7.7% of offspring had ADHD and 6.8% had DBD. Maternal prenatal cannabis use was not associated with ADHD (adjusted hazard ratio [aHR]: 0.84, 95% CI, 0.70-1.01), and there was an inverse association with DBD (aHR: 0.83, 95% CI, 0.71-0.97), which remained when cannabis was defined by toxicology testing but not by self-report. Frequency of use was not associated with outcomes.

Conclusion: Maternal prenatal cannabis use was not associated with an increased risk of offspring ADHD or DBD.

Objective: Little is known about the prevalence of positive childhood experiences (PCEs), a counter to adverse childhood experiences, in children with an attention-deficit hyperactivity disorder (ADHD) diagnosis. The purpose of this study was to examine the relationship between PCEs and ADHD diagnosis and severity, adjusting for child, family, and household characteristics, using a nationally representative data set.

Methods: Using the 2020 to 2021 National Survey of Children's Health, our sample included children 6 years of age or older, as this is the age at which PCE questions are asked (n = 56,224). Multivariable logistic regression was used to examine the association between PCE type and ADHD diagnosis and severity, controlling for child and household characteristics.

Results: In multivariable regression analyses, children who had volunteered in their community had lower odds of a reported ADHD diagnosis than children who had not volunteered in their community (adjusted odds ratio [aOR] 0.83; 95% confidence interval [CI], 0.73-0.95). Children with a connected caregiver had a lower likelihood of ADHD diagnosis than children without a connected caregiver (aOR 0.66; 95% CI, 0.58-0.74). Children reporting moderate to severe ADHD were less likely to report exposure to any of the 7 PCEs examined, when compared with children reporting mild ADHD.

Conclusion: The findings from this study can be important for clinicians and families to mitigate the negative social and academic outcomes that children with ADHD may face.

Objective: This study examined (1) whether different types of mobile device use are associated with quantity/quality of parent-child interactions and (2) moment-to-moment changes in quantity/quality of parent-child interactions when devices are used.

Method: In 47 videorecorded home mealtimes conducted in 2011 to 2013, we conducted detailed coding of maternal device use (talking, texting/scrolling, having device on table), frequency of mother and child verbalizations, child bids for attention, and maternal response to bids (contingent, no response, negative response) in 5-second intervals. We examined between-mother differences in parent-child interaction variables for a 10-percentage point increase in each type of device use comparisons using negative binomial or logistic regression. We then compared intervals when there was active mobile device use to nonuse intervals using generalized estimating equation logistic regression, predicting the odds of each parent-child interaction variable.

Results: Mothers averaged 29.8 years (SD 6.10), child age 5.97 years (SD 0.56), and 55% had completed at least some college. Higher percentage of time spent texting/scrolling was associated with a lower rate of maternal verbalization (adjusted rate ratio 0.89 [95% confidence interval, 0.84-0.95]) and contingent response (adjusted rate ratio 0.92 [0.84-1.00]) and higher odds of nonresponse (adjusted odds ratio 1.13 [1.04-1.22]). In each 5-second interval of active device use, there was decreased odds of maternal verbalizations (adjusted odds ratio 0.48 [0.34-0.69]), child verbalizations (0.62 [0.44-0.88]), contingent response (0.45 [0.28-0.74]), and higher odds of maternal nonresponse (2.36 [1.40-4.00]).

Conclusion: These results demonstrate decreased parent-child verbal interaction and lower parent responsiveness during mobile device use, particularly with texting and scrolling.