This study investigated the differences between clinically-ascertained individuals with ASD and individuals recruited online based on self-reported autistic traits. Key findings include a lack of significant relationship between self-reported and clinician-rated autistic traits in the ASD group (b = 0.025, P = 0.251), and differences in social behavior, with the ASD group showing reduced ability to exert social influence in the social controllability task and less affiliative behavior in the social navigation task. The online high-trait group reported significantly higher levels of social anxiety (F(2,163) = 59.80, P = 3.33 x 10^-20) and AVPD symptoms (F(2,163) = 107.84, P = 1.46 x 10^-30) compared to both the ASD and low-trait groups.
The study provides valuable insights into the differences between clinically-ascertained individuals with ASD and individuals recruited online based on self-reported autistic traits. It clearly demonstrates that while self-reported traits can be informative, they do not always align with clinician-administered assessments and may not accurately reflect observable social behavior. The study makes a strong case for caution when using online self-report measures for autism research, particularly when drawing conclusions about the ASD population as a whole.
The study's findings have practical implications for both research and clinical practice. For researchers, it highlights the need to carefully consider the limitations of online recruitment and self-report measures, particularly in the context of ASD. It suggests that online studies should be used in conjunction with, rather than as a replacement for, traditional lab-based research. For clinicians, the study reinforces the importance of using a multi-faceted approach to assessment, incorporating both self-report and observational measures, and being aware that high self-reported autistic traits may be indicative of other conditions, such as social anxiety or AVPD.
While the study provides valuable guidance, it also acknowledges key uncertainties. The reliance on a single self-report measure (BAPQ) and the lack of a direct measure of insight are limitations that need to be addressed in future research. The study also suggests that future research should explore the use of additional trait measures and self-reported diagnoses in online studies, as well as investigate potential platform differences in social profiles.
Critical unanswered questions remain, such as the extent to which the findings generalize to other populations and the specific mechanisms underlying the observed discrepancies between self-report and behavior. The methodological limitations, particularly the reliance on a single self-report measure and the lack of a direct measure of insight, do not fundamentally undermine the study's conclusions, but they do highlight the need for further research to replicate and extend these findings. The high range of IQ scores in the in-person sample is another limitation that affects the generalizability of the conclusions.
The abstract clearly states the research question, comparing in-person recruited, clinically-assessed individuals with autism to online-recruited individuals with high and low autistic traits.
The abstract concisely summarizes the key findings, highlighting the differences between the groups in social anxiety, avoidant symptoms, and social tendencies during decision-making tasks.
The abstract succinctly states the main conclusion and its implication for autism research, emphasizing the need for differentiation between clinically ascertained and trait-defined samples.
High impact. This would enhance the reader's understanding of the study's scope and the specific context of the findings. It is appropriate for the abstract as it provides a concise overview of the methods used.
Implementation: Include a brief phrase indicating the types of self-report surveys used (e.g., '...evaluated via self-reported surveys on autistic traits, social anxiety, and avoidant personality.').
Medium impact. This would improve the abstract's completeness by providing a more comprehensive overview of the study's findings, impacting reader understanding. It is appropriate for the abstract as it gives a quick overview of the findings.
Implementation: Add a sentence briefly summarizing the finding regarding the lack of relationship between self-rated and clinician-rated autistic traits within the in-person sample. For example: 'Notably, within the clinically-assessed ASD group, self-reported and clinician-rated autistic traits were not correlated.'
The introduction clearly establishes the motivation for the study by highlighting the increasing use of online platforms for data collection in human-participant research and the associated concerns about data quality and validity, particularly in the context of neuropsychiatric disorders.
The introduction effectively introduces the core problem of relying on self-report measures for autism spectrum disorder (ASD) research in online settings, where clinical characterizations are typically absent. It points out the potential limitations of self-report due to altered insight and diagnostic specificity issues.
The introduction logically connects the general problem of online research validity to the specific context of ASD, highlighting the known discrepancies between self- and caregiver-reported traits and the potential impact of altered theory of mind (ToM) on self-report accuracy in individuals with ASD.
The introduction clearly states the study's objective, which is to systematically examine the differences between adults with high autistic traits recruited online via self-report and adults with ASD defined via in-person clinical characterization.
The introduction provides a concise overview of the study's approach, mentioning the use of dynamic social interaction tasks to compare the online and in-person samples. It also states the hypothesis.
Medium impact. This would strengthen the rationale for the study by providing context. This belongs in the introduction to set the stage for the research.
Implementation: Include a sentence or two summarizing the prevalence of ASD and the importance of accurate diagnosis and research in this area. For example: 'Given the increasing prevalence of ASD and the significant impact it has on individuals' lives, rigorous research is crucial for developing effective interventions and supports. However, the challenges of traditional, in-person research have led to a growing reliance on online data collection methods.'
Low impact. This would help readers understand the specific aspects of social interaction being investigated. This belongs in the introduction to provide a more complete picture of the research focus.
Implementation: Expand slightly on the description of the dynamic social interaction tasks, providing a brief, non-technical explanation of what they involve. For example: 'These tasks involved simulated social scenarios where participants made decisions that influenced their relationships with virtual characters, allowing us to assess their social navigation and influence strategies.'
High Impact. This would enhance the flow of the introduction. It is important to establish this connection early in the paper.
Implementation: Add transition sentence. For example: 'To address the limitations of online self-report in ASD research, this study directly compares...'
The Results section clearly presents the demographic and trait characteristics of the three groups (ASD, high-trait, and low-trait), demonstrating the expected differences in self-reported autistic traits (BAPQ scores) based on the group definitions. It also effectively uses Table 1 to summarize demographic information.
The section effectively presents the findings on social anxiety and avoidant personality disorder (AVPD) symptoms, highlighting the differences between the groups and demonstrating that the high-trait group reported higher levels of these symptoms compared to both the low-trait and ASD groups.
The section clearly reports the lack of a significant relationship between self-reported ASD traits (BAPQ) and clinician-rated traits (ADOS) within the in-person ASD group, highlighting a key finding that challenges the assumption of agreement between these measures.
The section effectively presents the results of the social controllability task, showing that the ASD group rejected a smaller percentage of high offers in the controllable condition and perceived less control, indicating a reduced ability to exert social influence.
The section clearly presents the findings of the social navigation task, showing that the ASD group acted less affiliative with the characters, despite similar subjective ratings of character liking, highlighting a difference in social behavior.
The results are presented with appropriate statistical details, including F-statistics, p-values, effect sizes, and confidence intervals, allowing for a thorough evaluation of the findings.
High impact. This would improve the clarity and organization of the Results section. Currently, the section jumps between different types of results (trait comparisons, social behavior tasks) without clear subheadings to guide the reader. This makes it harder to follow the flow of the findings and understand the overall structure of the results.
Implementation: Introduce clear subheadings within the Results section to organize the findings. For example: 'Autistic and Other Social Traits', 'Social Controllability Task', 'Social Navigation Task', 'Relationship Between Self-Reported Traits and Behavior'.
Medium impact. While the Results section reports the statistical findings, it could benefit from a more explicit interpretation of these findings in the context of the study's hypotheses and research questions. This would help the reader understand the significance of the results and how they relate to the broader aims of the study.
Implementation: After presenting the statistical results for each analysis, add a sentence or two briefly interpreting the findings in plain language and relating them back to the study's hypotheses. For example, after reporting the BAPQ differences, state: 'This confirms our initial expectation that the groups would differ in self-reported autistic traits based on their recruitment criteria.'
Low impact. This would provide additional context for interpreting the results. The current presentation assumes reader familiarity with the tasks.
Implementation: Briefly describe the core concepts being measured by each task. For example, before presenting the social controllability results, add a sentence like: 'The social controllability task measures participants' ability to influence others' offers in a monetary exchange game, reflecting their capacity to exert social influence.'
Low impact. This would help readers better understand the specific measures used. It is appropriate for the Results section to briefly introduce the measures before presenting the findings.
Implementation: When first mentioning each measure (BAPQ, ADOS, etc.), briefly state what it measures. For example: '...self-reported autistic traits, as measured by the Broad Autism Phenotype Questionnaire (BAPQ), a self-report instrument assessing autistic traits...' and '...clinician-rated autistic traits measured via the Autism Diagnostic Observation Schedule (ADOS-2), a standardized diagnostic assessment...'
Medium impact. This would help readers visualize the magnitude of the differences between groups. While the statistical values are reported, adding a visual representation would make the results more accessible.
Implementation: Consider adding bar graphs or box plots to visually represent the group differences in key measures (e.g., BAPQ scores, social anxiety scores, rejection rates, affiliation tendencies). Ensure the figures are clearly labeled and referenced in the text.
Fig. 1 | Trait comparisons. a, The ASD (n = 56 participants) and high-trait (HT; n = 56 participants) groups had comparable levels of self-reported autistic traits (measured via BAPQ; two-sided pairwise comparisons using estimated marginal means, with confidence intervals and P values adjusted for multiple comparisons using the Tukey method: t(111) = -0.28, P=0.957, estimated difference = -0.026, 95% CI [-0.25, 0.19], Cohen's d = -0.05; mean ASD: 3.82, mean HT: 3.85, mean low-trait (LT): 2.11).
Fig. 1 | Trait comparisons. b, c, Investigation into traits of other disorders characterized by social impairment revealed that, compared with both other groups (n = 56 participants each), the high-trait group (n = 56 participants) self-reported a higher level of social anxiety (two-sided mixed-effects model with random intercept for matched pair ID: F(2,163) = 59.80, P = 3.33 × 10-20, Npartial2 = 0.42; mean ASD: 35.39, mean HT: 46.43, mean LT: 19.21 (b)) and avoidant personality disorder (AVPD) symptoms (two-sided mixed-effects model with random intercept for
Fig. 1 | Trait comparisons. matched pair ID: F(2,163) = 107.84, P=1.46×10-30, Npartial² = 0.57; mean ASD: 20.09, mean HT: 23.80, mean LT: 11.36 (c)).
Fig. 1 | Trait comparisons. d, In the in-person ASD group (n = 56 participants), there was no relationship between clinician-rated autistic traits measured via ADOS (mean = 13.85) and self-reported autistic traits measured via BAPQ (two-sided general linear model: b = 0.025, s.e.m. = 0.02, t(51) = 1.16, P = 0.251, 95% CI [-0.018, 0.067], Npartial² = 0.01).