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Autism spectrum conditions were once seen as a predominantly male condition. This has caused a paucity of information on common events in the lives of women, such as menstruation and menopause. Some smaller studies indicate that autistic women might suffer from increased difficulties surrounding these events. This study aims to investigate whether autistic women experience more frequent premenstrual dysphoric disorder, and increased complaints surrounding menopause. In partly overlapping samples (premenstrual dysphoric disorder, n = 70, n[subscript ASC] = 28, n[subscript comparisons] = 42; menopause, n = 65, n[subscript ASC] = 30, n[subscript comparisons] = 35), we investigated premenstrual dysphoric disorder prevalence and menopausal complaints. In 70 individuals, we did not find an increased prevalence of premenstrual dysphoric disorder in autistic women (14.3%) compared with non-autistic women (9.5%). In 65 women aged 40 years and above, we found that autistic women did experience higher levels of menopausal complaints. In autistic women, higher menopausal complaints were associated with higher levels of depression and autistic traits. In non-autistic women, menopausal complaints were associated with increased inattention, hyperactivity/impulsivity (i.e. attention deficit hyperactivity disorder traits), and depression. With this work, we show the important role that major reproductive milestones can have in an autistic woman's life.

Prospective memory helps us to remember to perform tasks in the future. Prospective memory can be either time or event based. The goal of this study was to determine time- and event-based prospective memory in autistic adults across the life span. Autistic (n = 82) and non-autistic (n = 111) adults, aged between 30 and 86 years, performed the lab-based Amsterdam Breakfast Task, and several naturalistic prospective memory tasks. Preregistered analyses (AsPredicted #34249) were performed using classical frequentist as well as Bayesian statistics. On none of the prospective memory tasks, group differences were observed. Our results show no effect of age on naturalistic tasks, but age did affect our lab-based measure, indicative of the age paradox often described in non-autistic adults. Moreover, we found evidence for a parallel age-related effect of lab-based and naturalistic prospective memory in autistic and non-autistic individuals. What is already known : Prospective memory is an important function for daily living. It is the cognitive function that helps you remember that you are meeting your friend for coffee at 2 pm tomorrow, or that you need to take your vitamins after breakfast. This cognitive function is particularly important in autistic adults, but how prospective memory is associated with increasing age, we currently do not know. What this paper adds : Although performance on experimental tasks that measure prospective memory decreases with age, this pattern is similar in autistic and non-autistic adults. No age effects were found for tasks that were performed outside the lab. Autistic adults and non-autistic adults perform similarly on prospective memory, and this performance remains similar when autistic and non-autistic adults age. Implications for practice, research, or policy : While our results show that prospective memory decreased with increasing age, our results do point to parallel development of prospective memory in autistic and non-autistic adults. This finding serves as a reassurance for those individuals concerned that older autistic individuals might show quicker cognitive decline. [ABSTRACT FROM AUTHOR]

Differences in (autism) characteristics are often reported between autistic and non-autistic adults but also between autistic adults. We aimed to determine whether mean differences correspond to differences in network structure of these characteristics in (1) autistic and non-autistic adults and (2) two previously identified autism subgroups. A total of 16 network variables related to demographic and psychological characteristics were included. First, Gaussian Graphical Models (GGMs) were used for network estimation in 261 autistic adults and 384 non-autistic comparisons aged 30–85 years. Second, we repeated this step within two previously identified autism subgroups (N 1 = 124, N 2 = 130). Third, sex differences were explored in the networks of the autism subgroups. The networks of the autism and comparison groups differed on individual edges and visual inspection, although the Network Comparison Test (NCT) showed no overall differences. The networks of autism subgroups were similar based on visual inspection and statistical comparisons. Sex did not impact the subgroup networks differently. Networks were more similar than different, but observed edge differences could be informative for targeted support. Focusing on mean differences is not sufficient to determine which factors (and associations) are important for autistic people. Thus, network analysis provides a valuable tool beyond assessing mean differences for autistic adults. There are large differences in the level of demographic, psychological, and lifestyle characteristics between autistic and non-autistic adults but also among autistic people. Our goal was to test whether these differences correspond to differences in underlying relationships between these characteristics—also referred to as network structure—to determine which characteristics (and relationships between them) are important. We tested differences in network structure in (1) autistic and non-autistic adults and (2) two previously identified subgroups of autistic adults. We showed that comparing networks of autistic and non-autistic adults provides subtle differences, whereas networks of the autism subgroups were similar. There were also no sex differences in the networks of the autism subgroups. Thus, the previously observed differences in the level of characteristics did not correspond to differences across subgroups in how these characteristics relate to one another (i.e. network structure). Consequently, a focus on differences in characteristics is not sufficient to determine which characteristics (and relationships between them) are of importance. Hence, network analysis provides a valuable tool beyond looking at (sub)group level differences. These results could provide hints for clinical practice, to eventually determine whether psychological distress, cognitive failures, and reduced quality of life in autistic adults can be addressed by tailored support. However, it is important that these results are first replicated before we move toward intervention or support. [ABSTRACT FROM AUTHOR]

Camouflaging is hypothesized to play an important role in developing mental health difficulties. But this might not be true for everyone. It remains unclear for whom camouflaging is associated with mental health. In this preregistered study (AsPredicted #45095), we investigated whether (1) camouflaging and mental health were associated and (2) we could detect subgroups with a different association between camouflaging and mental health. For this study, 352 autistic adults aged 30–84 years filled in, among others, the Dutch Camouflaging Autistic Traits Questionnaire to measure camouflaging and the Symptom Checklist-90 Revised to measure mental health difficulties. We found a moderate correlation between camouflaging and mental health difficulties (r = 0.45). However, there was only a strong association between camouflaging and mental health in a small subgroup, while the association was small in most autistic adults. For varying levels of negative affect and (to a lesser extent) autism traits, the association between camouflaging and mental health differed, but not for biological sex, age, or educational level. Thus, while one should be careful with group-based conclusions regarding the (negative) impact of camouflaging, camouflaging can be important to consider in clinical practice, especially for people with a substantial level of negative affect. When autistic people use strategies to hide their autistic characteristics, we call this camouflaging. Autistic adults suggested that camouflaging can result in mental health difficulties. That is, people who report to camouflage also report mental health difficulties. However, since there are many differences between autistic people, this relationship may also differ between subgroups. Therefore, in this study we investigated whether camouflaging and mental health difficulties are related and whether this relationship is equal for all autistic adults. For this study, 352 autistic adults aged 30–84 years filled in the Dutch Camouflaging Autistic Traits Questionnaire to measure camouflaging and the Symptom Checklist-90 Revised to measure mental health difficulties. We found that camouflaging was moderately related to mental health difficulties. This means that people who report more camouflaging also report more mental health difficulties. When we looked closer, we found that this relationship was strong for only a small subgroup of autistic adults. In most other autistic adults, there was a small or no relationship between camouflaging and mental health difficulties. Therefore, it is important that clinicians are aware of camouflaging and its possible relationship with mental health difficulties, but that they do not generalize the negative consequences to everyone. [ABSTRACT FROM AUTHOR]

Background: This metaregression analysis examined which behavioral techniques that are commonly used in behavioral parent and teacher training programs for children with attention‐deficit/hyperactivity disorder (ADHD) were related to program effectiveness on children's behavioral outcomes. Methods: We included 32 randomized controlled trials (N = 2594 children) investigating behavioral parent training, teacher training, or a combination, in children with ADHD under 18 years. Outcomes were symptom counts of total ADHD, inattention, and hyperactivity‐impulsivity and behavioral problems. The dosage of techniques was extracted from the intervention manuals. Metaregression was used to assess which techniques and intervention characteristics (setting, delivery method, duration, and home‐school collaboration) were associated with intervention effectiveness. Results: Higher dosage of psycho‐education for parents was associated with smaller effects on behavioral problems and, only in case of parent training, also with smaller effects on ADHD symptoms. Higher dosage of teaching parents/teachers to use negative consequences was associated with larger effects on behavioral problems. Individual training compared with group training was associated with larger effects on ADHD and hyperactivity‐impulsivity symptoms. Conclusions: This study provides first insights into the specific techniques that are essential in behavioral parent and teacher training programs for children with ADHD. This knowledge can eventually be used to improve and tailor interventions. [ABSTRACT FROM AUTHOR]

Cognitive performances of autistic people vary widely. Therefore, previous group‐based comparisons on cognitive aging in autistic adults might have overlooked those autistic adults that are particularly vulnerable for cognitive decline. Multivariate normative comparisons (MNC) statistically assess individual cognitive differences on the entire cognitive profile. Cognitive deviancy as indicated by MNC accurately predicts future cognitive decline, and is therefore sensitive in detecting meaningful cognitive differences. The current study aimed to (1) investigate the applicability of MNC to assess cognitive performance in autism individually, and (2) understand heterogeneous cognitive performance in autistic adults. As pre‐registered, we performed MNC in a sample of 254 non‐autistic adults, and two independent samples of respectively 118, and 86 autistic adults (20–85 years, mean: 50 years). Cognitive performance was measured on 11 outcomes in six domains (verbal/visual memory, working memory, verbal fluency, Theory of Mind, and psychomotor speed). Using MNC, about twice as many autistic individuals had a deviant cognitive profile (i.e., deviated statistically from the multivariate normspace) as compared to non‐autistic individuals. Importantly, most autistic individuals (>80%) did not have a deviant cognitive profile. Having a deviant profile was significantly associated with higher levels of psychological distress in autistic adults specifically, showing the clinical relevance of this method. Therefore, MNC seem a useful tool to individually detect meaningful cognitive differences in autism. These results are consistent with previous cognitive studies suggesting that most autistic adults show fairly similar cognitive profiles to non‐autistic adults, yet highlight the necessity for approaches reflecting the heterogeneity observed in autistic people. Lay Summary: Aiming to understand cognitive differences between autistic adults, we applied a new statistical method that assesses cognition in a sensitive, and individual manner. Cognitive profiles of autistic adults, and non‐autistic adults were, therefore, investigated statistically. About twice as many autistic individuals showed a different cognitive profile (20%) as compared to non‐autistic individuals, yet most autistic individuals (80%) did not. Differences were, in part, explained by differences in psychological distress. [ABSTRACT FROM AUTHOR]

An important question in mental healthcare for children is whether treatments are effective and safe in the long run. Here, we comment on a recent editorial perspective by Roest et al. (2022), who argue, based on an overview of systematic reviews, 'that there is no convincing evidence that interventions for the most common childhood disorders are beneficial in the long term'. We believe that the available evidence does not justify this conclusion and express our concern regarding the harmful effects of their message. We show that there is evidence to suggest beneficial longer term treatment effects for each of the disorders and explain why evidence‐based treatment should be offered to children with mental disorders. Read the full article at doi: 10.1111/jcpp.13677. [ABSTRACT FROM AUTHOR]