The study was conducted between April and August 2023 by a team based at Shandong University’s School of Nursing and Rehabilitation, working with colleagues at the Second Qilu Hospital of Shandong University and the Qingdao Mental Health Center. Each participating family consisted of a child with autism spectrum disorder and one parent, forming what researchers call a dyad. Parents completed the Strengths and Difficulties Questionnaire, a brief parent-report instrument developed by child psychiatrist Robert Goodman that screens for emotional symptoms, conduct problems, hyperactivity, peer relationship difficulties, and prosocial behavior. Because parents observe children across everyday settings rather than in a single clinical session, parent-report measures of this kind are often used to capture the real-world expression of a child’s difficulties.

The headline finding was the sheer prevalence of difficulty: 81.3 percent of the children were flagged as having emotional or behavioral problems according to the questionnaire. That figure is consistent with a broader literature. A 2023 systematic review and meta-analysis published in Neuroscience and Biobehavioral Reviews documented high rates of co-occurring conditions in autistic children and adults, and longitudinal work following autistic people from childhood into early adulthood has shown that emotional and behavioral problems frequently persist across development. For families, this means the challenges associated with autism rarely stop at the core diagnostic features; they extend into anxiety, dysregulation, and conduct difficulties that shape daily life at home and at school.

What sets the new study apart is its analytical approach. Rather than averaging scores across the whole sample or treating problem severity as a single continuous scale, the researchers used latent profile analysis, a person-centered statistical method that searches for unobserved subgroups within a population. The technique asks a simple but powerful question: do children cluster into recognizable patterns of emotional and behavioral difficulty, or do their scores vary smoothly along one continuum? In this sample, the answer was that three distinct latent profiles best described the data, implying that autistic children do not form one uniform group but instead occupy meaningfully different positions with respect to their emotional and behavioral adjustment.

Identifying the profiles was only the first step. The team then wanted to know what distinguished families whose children fell into the more affected profiles from those in the less affected ones. To do this, they used the R3STEP procedure in the Mplus statistical software, an automatic three-step method that has become a standard tool in latent profile research. The procedure’s key virtue is that it accounts for classification uncertainty. Latent profile analysis never assigns a child to a profile with absolute certainty; instead, each child carries a probability of belonging to each group. Older approaches that simply assigned children to their most likely profile and then ran ordinary statistical tests treat those assignments as if they were error-free, which can bias estimates. The three-step method keeps the classification uncertainty in the model, producing more honest estimates of how observed variables relate to profile membership.

The covariates the researchers examined came from two domains of family life. The first was parenting stress, measured with an instrument whose Chinese-language version has been validated in prior psychometric work. Parenting stress in this context refers to the strain a parent experiences in the parenting role, encompassing perceptions of the child as demanding, a sense of incompetence or distress in the parental role, and restrictive or disrupted interactions between parent and child. The second domain was family management, assessed with a Chinese version of the Family Management Measure, a framework originally developed by nursing scientists to describe how families organize daily life around a child’s condition. Family management spans both difficult dimensions, such as difficulty managing the child’s condition and disruption of family routines, and positive dimensions, such as family life difficulty being managed with confidence, developmental competence in parents, and the family’s ability to maintain normalcy.

The associations that emerged were directionally coherent. Higher parenting stress was positively associated with membership in the profiles characterized by more emotional and behavioral problems. Negative family management, meaning families reporting greater difficulty and disruption in handling the child’s condition, was likewise positively associated with the high-problem profiles. Positive family management, by contrast, was inversely associated with membership in the most affected groups. In other words, after the model accounted for the probabilistic nature of profile assignment, families reporting more stress and more struggle tended to have children in the more difficult profiles, while families reporting confidence and competence in managing daily life tended to have children in the less affected ones.

The authors are careful about what this pattern does and does not establish. The study is cross-sectional, meaning stress, family management, and child outcomes were measured at the same point in time. That design cannot determine whether parenting stress drives children’s emotional and behavioral problems, whether challenging child behavior drives parental stress, or whether the two reinforce each other in a bidirectional loop. There is substantial evidence that such loops exist. A 2024 meta-analysis in Jornal de Pediatria synthesized studies linking parental stress to emotional and behavioral problems in offspring, and research on Chinese families of autistic children published in Autism Research has examined how child behavior problems and parental psychological distress relate to one another, with social support and cultural values as potential moderators. Other work has traced pathways from parental social support through family functioning to child outcomes, suggesting that the family system operates as an interconnected whole rather than as a set of independent variables.

Still, the practical implications of the study are relatively clear, and the authors frame them in terms of family-based support strategies. If parenting stress and negative family management are reliably associated with children landing in the most affected profiles, then interventions that reduce parental strain and strengthen families’ capacity to organize and manage daily life may be relevant to children’s emotional and behavioral adjustment. This aligns with a growing body of intervention research. Group counseling programs for parents of autistic children have been shown to improve psychological resilience, life satisfaction, and family functioning, and studies of family-school partnerships have linked them to lower parenting stress and better parent mental health. The family management framework, adapted over the past decade to include children with a range of conditions, gives clinicians a vocabulary for identifying families who feel overwhelmed by their child’s condition and for targeting support toward routine-building and confidence rather than only toward the child’s symptoms.

For the autism research community, the study’s contribution is methodological as much as substantive. By demonstrating that emotional and behavioral problems in autistic children fall into heterogeneous latent profiles, and that family variables predict profile membership even when classification uncertainty is modeled explicitly, the work adds to a shift away from treating autistic children as a single diagnostic block. Researchers have increasingly argued for plural understandings of autism, noting differences in developmental trajectories and symptom combinations, and the profile approach offers a quantitative way to capture that heterogeneity. The study was funded by the National Natural Science Foundation of China and the Natural Science Foundation of Shandong Province, and the authors report no competing financial interests. Its limitations, including the cross-sectional design and reliance on parent report, leave open the causal questions that longitudinal and multi-informant studies will need to address. But for families and clinicians, the message is concrete: the emotional lives of autistic children are entangled with the stress levels and management capacities of the households around them, and supporting the family may be one of the most direct routes to supporting the child.

Subject of Research: Latent profile analysis of parenting stress and family management in relation to emotional and behavioral problems in children with autism spectrum disorder

Article Title: Association of Parenting Stress and Family Management With Emotional and Behavioral Problems in Children With Autism Spectrum Disorders: A Latent Profile Analysis

Article References: Association of Parenting Stress and Family Management With Emotional and Behavioral Problems in Children With Autism Spectrum Disorders: A Latent Profile Analysis. (n.d.). https://doi.org/10.1007/s10803-026-07510-1

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07510-1

Keywords: autism spectrum disorder, parenting stress, family management, emotional and behavioral problems, latent profile analysis, Strengths and Difficulties Questionnaire, R3STEP procedure, Mplus, parent-child dyads, family-based intervention, child mental health, cross-sectional study

The research team, led by Hannah Lundh of the Centre for Physical Activity in Region Västra Götaland and colleagues at the University of Gothenburg, recruited 39 children aged 6 to 12 who had been referred to outpatient paediatric clinics for obesity treatment, along with one parent each. The children, 19 of them girls, had a mean age of 9.7 years and a mean body mass index standard deviation score of 3.0, indicating severe obesity relative to Swedish reference populations. Their parents, 20 of them mothers, averaged 42.2 years of age. Fifty-seven percent of the parents were born in Sweden, 16 percent in other European countries, and 27 percent outside Europe, giving the sample a broadly diverse socioeconomic and cultural profile.

Each child-parent pair wore a small Axivity AX3 accelerometer on an elastic belt around the waist, positioned over the right hip close to the body’s centre of mass, for seven consecutive days and nights. The devices sampled movement at 50 Hz with an acceleration range of plus or minus 8 g, and participants kept diaries of bedtime, waking time, cycling, water activities and strength training to help researchers identify sleep and non-wear periods. A valid day required at least 10 hours of wear time, and a valid week required at least two such days — a deliberately lenient threshold that sensitivity analyses showed made no difference compared with the traditional four-day requirement, but which maximised the number of pairs that could be included.

The data processing was where the study distinguished itself technically. Rather than applying conventional low-pass filters that can misclassify vigorous movement as noise, the team used the 10 Hz Frequency Extended Method, which has been shown in calibration work to capture higher-intensity activity more faithfully. Data were reduced into 3-second epochs, a window short enough to register the brief, sporadic bursts that characterise children’s movement. Perhaps most notably, the researchers set the cut-point for moderate-to-vigorous physical activity at 4 metabolic equivalents rather than the traditional 3 METs, arguing that 3 METs corresponds to a slow walking pace of just 3 to 4 kilometres per hour and shows minimal association with cardiometabolic health, whereas clinically meaningful benefits begin around 4 METs, roughly a brisk walk of 4 to 5 kilometres per hour. Cut-points of 52 mg and 388 mg for children and 39 mg and 331 mg for adults marked the boundaries between light activity and moderate-to-vigorous activity.

The headline numbers were sobering. Children spent an average of 9.8 hours per day in sedentary behaviour and just 0.7 hours — about 42 minutes — in moderate-to-vigorous activity, with another 3.9 hours in light activity. Their parents sat even longer, averaging 12.3 sedentary hours daily, with only 0.3 hours of moderate-to-vigorous activity and 3.4 hours of light activity. Only six of the 39 children, or 15 percent, met the World Health Organization recommendation of at least 60 minutes of moderate-to-vigorous activity per day for ages 5 to 17. Among parents, the picture was bleaker still: just two of 38, or 5 percent, achieved the adult guideline of 150 minutes of moderate activity per week.

The central analytical question was whether children’s and parents’ behaviours tracked together within each pair. Using intraclass correlation coefficients in two-way mixed-effect models, the team found a statistically significant but weak correlation for sedentary time, with an ICC of 0.14 and a p-value of 0.017. By the conventional interpretation scheme of Koo and Li, any value below 0.5 counts as weak, so the shared sitting habit was real but modest. The correlation for light activity was stronger, at 0.24, but fell just short of significance with a p-value of 0.050. For moderate-to-vigorous activity, the correlation was weaker still, at 0.11, and clearly non-significant. Bland-Altman plots visualising the within-pair differences showed enormous variability: some pairs moved in near lockstep, while others diverged dramatically.

Interestingly, the generations differed systematically in how they spent their days. Children accumulated significantly more moderate-to-vigorous activity than their parents — a mean paired difference of roughly 27 minutes per day — while parents sat significantly more than their children. This inversion of the intuitive picture, in which adults might be expected to be the more active party, underscores how deeply sedentary adult lifestyles can become even in families actively engaged with paediatric obesity services. It also suggests that children in this clinical population, despite falling far short of guidelines, remain more physically capable of spontaneous movement than their parents.

The sedentary finding carries particular weight because it contradicts much of the existing parent-child literature. Previous systematic reviews, covering predominantly healthy, non-obese children, have generally reported weak to moderate positive associations between parent and child physical activity, and a large meta-analysis found a small effect of parental modelling on children’s activity. Only one of the 65 studies across two major reviews had examined accelerometer-measured associations in an obese paediatric population. The Swedish authors suggest several reasons their results may diverge: earlier studies often relied on self-report, which is prone to bias; many used the lower 3 METs threshold, inflating apparent activity levels; and crucially, previous cohorts tended to include younger children, aged 2 to 10, who are more dependent on their parents and more likely to share their activities. Children aged 6 to 12, by contrast, increasingly move in school and peer contexts their parents never see.

The study’s limitations are candidly acknowledged. The cross-sectional design rules out any causal inference — sitting together may reflect shared environment, modelling, genetic predisposition, or all three. The sample of 39 pairs fell short of the original target of 60, partly because of pandemic-related staffing problems, and no formal power calculation was performed, so a larger sample might have detected significant correlations that here hovered near the threshold of significance, particularly for light activity. The team did not collect parents’ body mass index, which likely influenced parental activity levels given the genetic component of obesity, nor did they record living arrangements, meaning some children may have spent the measurement week with the non-participating parent. Selection bias is also possible, since families with positive attitudes toward activity may have been more willing to enrol.

Still, the implications for treatment are concrete. The WHO recommends family-based, multi-professional interventions as first-line treatment for childhood obesity, and the Swedish physical activity on prescription model places parental involvement at its core. If sedentary time is the one behaviour where parent and child genuinely mirror each other, the authors argue, then interventions for this population might profitably begin by targeting sitting time together — a change that over time could open the door to increased activity — while recognising that role modelling through parental exercise may matter more for some families than others. Facilitating access to activity opportunities, initiating outings and offering encouragement may ultimately prove more powerful levers than a parent’s own workout routine. Larger samples, other settings and longitudinal designs, the researchers conclude, are needed to untangle whether shared sedentary habits are cause, consequence or coincidence in the trajectory of childhood obesity.

Subject of Research: Parent-child associations in accelerometer-measured physical activity and sedentary behaviour among children with obesity

Article Title: Physical activity and sedentary behaviour amongst children with obesity – exploring cross-sectional associations between child and parent

Article References: Lundh, H., Arvidsson, D., Greven, C., Fridolfsson, J., Börjesson, M., Boman, C., Lauruschkus, K., Lundqvist, S., Melin, K., & Bernhardsson, S. (2025). Physical activity and sedentary behaviour amongst children with obesity – exploring cross-sectional associations between child and parent. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 2. https://doi.org/10.1186/s44167-025-00072-0

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00072-0

Keywords: childhood obesity, physical activity, sedentary behaviour, accelerometry, parent-child dyads, moderate-to-vigorous physical activity, paediatric health care, Sweden, family-based intervention, intraclass correlation, WHO guidelines, behavioural modelling