Editorial: The search for knowledge: what diagnoses do and do not tell us
Bibliographic record
Abstract
In our research, we continually ask questions in order to better understand and know our world. Answers typically lead to more and more fine-grained questions, rather than to absolute knowledge and content. The same is true when we examine our nosology of clinical diagnoses. The more we know, the more we need and want to know. With the new editions of the DSM and ICD coming out in the next few years, researchers and clinicians alike are devoting considerable effort to improving their descriptions and definitions of the various clinical entities. The papers in this issue contribute to this effort. The current issue includes several contributions that question the commonly held assumption about the validity of the autistic triad of impairments described in our current diagnostic manuals. In a research review, Mandy and Skuse discuss the lack of conclusive evidence for a strong association between the social-communicative domain on the one hand, and the repetitive interests, behaviors, and activities (RIBAs) domain on the other. In their review, Mandy and Skuse correctly argue that the association between social-communication and RIBAs cannot be thoroughly examined in samples of individuals with ASD because these individuals were selected based on the very presence of the triad of impairments. Thus, one can only study the strength of the association among these groups but not whether it actually does or does not exist. This is a pivotal issue for future research and clinical practice. It is suggested that more intra-group studies are needed in which groups of individuals with autism who differ on just one aspect of the disorder are compared. Clinically, given that the new DSM-V is soon to appear, and given clinicians’ experience that some children manifest the social-communication deficits without significant impairments in RIBAs, Mandy and Skuse recommend an additional category of atypical autism for people with social-communication problems but without RIBAs or else that the requirement for impairment in RIBAs be removed from the diagnostic criteria. Boomsma and colleagues actually suggest a different triad of symptoms based on the ADI-R: 1. Impaired social communication, which includes symptoms from the original DSM impaired social interaction domain in addition to symptoms pertaining to use of gestures and failure to initiate or sustain conversion from the original DSM communication domain. 2. Stereotyped features in speech and behavior, which includes symptoms from the original DSM RIBAs domain as well as the communication domain. 3. Impaired play skills, which includes symptoms from both the DSM impaired social interaction and communication domains. This new model was found to be relatively invariant with respect to symptom severity, intelligence, and age, as it solely relied on the ADI-R and on samples of children and adolescents only. Still, it will be important to examine whether these three factors are also validated when other diagnostic procedures are used and for current diagnoses of adults with ASD. Future studies should also examine issues pertaining to continuity and/or changes in symptoms within the factors over development within the same individuals. Ben-Sasson and colleagues demonstrate that toddlers with ASD vary in their sensory profile. These researchers identified three sensory behavior clusters: (a) children who reveal a low frequency of sensory behaviors relative to other behaviors; (b) children with a mixed pattern, thus showing high frequencies of both under- and over-responsivity together with low seeking behaviors; and (c) children who manifest a high frequency of all sensory behaviors. Importantly, the three groups significantly differed in their level of affective symptoms, where children who manifested a high frequency of all sensory behaviors also scored significantly higher on affective symptoms regardless of the severity of symptoms associated with autism. These data are important in achieving a better description of the difficulties experienced by young children with ASD and for designing appropriate multidisciplinary-based interventions. Nonetheless, in the domain of repetitive and stereotyped behaviors, Morgan, Wetherby, and Barber report that repetitive and stereotyped movements are already evident in young children with ASD under the age of 2 years and, together with the observed social-communicative impairments, reliably differentiate this young sample from children with typical development and children with developmental delays. The weak association between the repetitive and stereotyped movements and the social-communication impairments in the ASD group and the fact that the repetitive and stereotyped movements at age 2 predicted ASD at age 4 only after the contribution of social and communication abilities, support the notion raised by Mandy and Skuse that the social and nonsocial impairments involved in ASD may indeed represent independent domains. Moving into a more fine-grained examination of the social deficit involved in face processing, Scherf, Behrmann, Minshew, and Luna examine whether the deficit in face processing in people with autism is attributable to a more specific deficit associated with decreased motivation to attend to social stimuli or to a more general atypical perceptual processing deficit associated with an inability to develop expertise with any class of visual objects. Their findings show that, compared to typically developing children and adults, children and adults with autism were less accurate on both upright and inverted faces as well as less accurate on a new set of unfamiliar perceptually homogeneous objects. Furthermore, whereas typically developing individuals seemed to develop expertise over time in their ability to develop recognition skills for perceptually homogeneous objects that need to be identified at the individual level, people with autism did not show this improvement with age. The conclusion of this unique study is that the deficit in face processing is actually a result of an underlying and more generalized deficit in fine-grained visuoperceptual processing, thus once more revealing the close ties between the social and nonsocial impairments involved in ASD. The last paper on ASD examines the effect of social motivation on interference control in boys with ASD and ADHD. Geurts, Luman, and van Meel report that children with ADHS and those with ASD are able to overcome some of their difficulties when the appropriate social motivation is available and offered. Although children with ADHD were slower overall in their speed of responding compared to typically developing children and children with ASD, the motivation of both clinical groups increased when they were told that they were competing with peers and thus their social motivation was higher. Similar to the aforementioned study, once more we can see how the cognitive and social domains are intertwined in the etiology of ASDs and how interventions should be aimed at all domains. The next three papers report on findings from longitudinal studies with children and adolescents (Adams & Bukowski; Herba et al.) and even young adults (Lansford et al.). It is essential for studies such as these to rely on data from multiple informants to avoid shared variability due to the same informant providing all information. Working in Canada, Adams and Bukowski investigated the association between peer victimization and well-being among obese adolescents. They examined both psychological measures and body mass index. Findings indicated that peer victimization predicted changes in depression and body mass over the course of 4 years. Self-perception for physical appearance was a mediator for both males and females, yet for obese females, almost half of the effect of victimization on changes in depression and body mass index was explained by how these young girls and adolescents felt about their physical appearance. Herba and colleagues examined the association between bullying and suicidal ideation in their impressive prospective longitudinal study of children and adolescents in the Netherlands. The current report is based on the first two assessment points carried out at the mean ages of 11 and 13.6 years. No direct association between victimization and suicide was found; yet, lower levels of social well-being among peers, greater feelings of rejection at home, and higher levels of parental internalizing disorders were each significantly associated with suicide ideation. Furthermore, when the researchers included potential moderating variables, it was found that the interaction between victimization and parental internalizing (but not externalizing) disorders predicted suicide ideation, as did the interaction between rejection at home and victimization for participants who were victims (but not for those who were both bullies and victims). Lansford et al. investigated the links among substance use diagnoses at age 18 on the one hand, and internalizing and behavior disorders before age 18, at age 18, and after age 18 on the other. Illicit substance use increased during adolescence but declined in early adulthood by age 21–22 years. Furthermore, at age 18 years, comorbid internalizing and behavior disorder diagnoses were associated with a higher likelihood of substance use diagnoses. One implication of these findings is that comorbidity should be taken into account when planning preventive intervention and treatment approaches. In the last paper, Liber and colleagues examined group versus individual treatment of childhood anxiety disorders and reported that the two approaches are equally effective in general, with some suggestion that children with social phobia benefit more from group treatment, whereas children with diagnoses other than social phobia tend to benefit more from individual treatment. Altogether, the papers in this issue explore in more depth the similarities and differences between children and adolescents who share a common diagnosis. The take-home lesson may be that although our DSM and ICD diagnoses are helpful in many ways in informing us about the similarities among people with the same diagnosis, there are still many intra-group or intra-diagnosis or inter-individual differences that may be important in achieving a more in-depth understanding of the etiology as well as the prognosis of these individuals and which may assist in tailoring appropriate prevention and intervention programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.063 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.024 | 0.030 |
| Insufficient payload (model declined to judge) | 0.023 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".