Autistic Traits in the General NT Population

 I'm somewhat conflicted on this research. We have hardly gotten around to understanding and finding solutions for the vast heterogeneity that is autism today. Frankly its one hot mess right now.

Are we adding to the confusion with studies like this which are going about investigating the general NT population to see if they too have "autistic traits." Its almost like trying to prove, everyone has some autistic traits which is all nice for a coffee chit chat, but is distracting us from focus on research based solutions that many of the more impacted autistics desperately need. Because if everyone has autism, then no further action is needed.

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Article 1

Palmer CJ, Paton B, Enticott PG, Hohwy J. 2015. “Subtypes” in the presentation of autistic traits in the general adult population. J. Autism Dev. Disord. 45:1291–301 

Key Takeaways.

• The study examined the presentation of autistic traits in a large adult population sample using the Autism-Spectrum Quotient (AQ).
• Cluster analysis was used to identify two subgroups with distinguishable trait profiles related to autism.
• The first subgroup (n = 1,059) reported significantly higher scores on the AQ subscales related to social difficulties (Social Skills and Communication) and significantly lower scores on the Detail Orientation subscale.
• The second subgroup (n = 1,284) reported significantly higher scores on the Detail Orientation subscale and significantly lower scores on the Social Skills subscale.
• The study also found that the AQ had a three-factor solution, with two related social-themed factors (Sociability and Mentalising) and a third non-social factor that varied independently (Detail Orientation).
• These findings suggest that there is significant variability in the presentation of autistic traits in the general adult population, and that different profiles of autistic characteristics tend to occur in nonclinical populations.

Article 2

Austin EJ. 2005. Personality correlates of the broader autism phenotype as assessed by the Autism Spectrum Quotient (AQ). Personal. Individ. Differ. 38:451–60

Key Takeaways

• There is evidence to suggest the existence of a broader autism phenotype, with non-autistic relatives of autistic individuals showing similar traits and characteristics.
• The study aimed to characterize the five-factor personality model profile of the broader autism phenotype as assessed by the Autism Spectrum Quotient (AQ) which has shown to be a valid tool for assessing autism traits in the general population. 
• The AQ and personality scale were completed by 201 undergraduates and a second group of 136 adults completed the personality scale and the Asperger screening measure.
• High scores on both 'autism' measures were associated with high neuroticism and low extraversion and agreeableness.
• Three of the five proposed sub-scales of the AQ emerged from the factor analysis.
• Males had higher AQ scores than females, 'hard' science students had higher scores than other students, and students with parent(s) in a scientific occupation had higher scores.
• The AQ and sub-scales had satisfactory or near-satisfactory reliabilities.
• Male participants, science students, and individuals from a scientific family background tend to have higher scores on the AQ, indicating a higher likelihood of autistic traits.

This study explored the broader autism phenotype and its association with personality traits using the Autism Spectrum Quotient (AQ). The study found correlations between AQ scores and personality traits, suggesting that the broader autism phenotype is associated with high Neuroticism and possibly Conscientiousness, as well as low Extraversion. The factor structure of the AQ was also examined, and group differences in AQ scores were observed. The study also compared the results from the student group with a screening instrument for Asperger syndrome in an older adult group. Overall, the AQ was found to have good psychometric properties and provided valuable insights into the broader autism phenotype.

Article 3: 

Ruzich E, Allison C, Smith P, Watson P, Auyeung B, et al. 2015. Measuring autistic traits in the general population: a systematic review of the Autism-Spectrum Quotient.  

Key Takeaways:

• The study reports a comprehensive systematic review of the literature to estimate a reliable mean AQ score in individuals without a diagnosis of an autism, in order to establish a reference norm for future studies.
• Mean AQ score for the nonclinical population was 16.94 (95% CI 11.6, 20.0), while mean AQ score for the clinical population with ASC was found to be 35.19 (95% CI 27.6, 41.1).
• In the nonclinical population, a sex difference in autistic traits was found, although no sex difference in AQ score was seen in the clinical ASC population.

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Attention Check Questions

In my grad school journey or learning to do research, I come across many interesting concepts. Here's one.

Attention check questions, sometimes called validity checks or instructional manipulation checks, are typically included in a survey or questionnaire to ensure that respondents are reading and fully understanding the questions. They serve as a way to assess whether participants are paying attention and not just rushing through or randomly answering questions in order to collect payment. They help improve the reliability and validity of the data collected in a survey.

An example of a simple attention check question could be "Please select 'Somewhat agree' for this question." If a respondent doesn't select 'Somewhat agree,' it can be inferred that they aren't reading the questions carefully, which could invalidate their other responses.

More complex attention check questions might be embedded within the content of the questionnaire. For instance, you might ask a question where the correct answer is obvious or already stated in the questionnaire, or where the answer should be logically consistent with previous responses.

Such checks are important when you're conducting research that relies on self-reported data, as they can help you filter out unreliable responses. However, they should be used judiciously. If used excessively or inappropriately, they can frustrate participants or create bias in your results. They should not be designed to trick respondents or make them feel foolish, and respondents should be informed at the start of the survey that their responses will be checked for consistency and attentiveness

There's no hard and fast rule about where attention check questions should be placed in a questionnaire, as it often depends on the specifics of the questionnaire and the goals of the researcher. 

Some general guidelines

• Spacing: For a lengthy survey, it may be good to sprinkle several attention checks throughout the survey. They shouldn't be too close together, as that might be annoying or confusing for the respondents. The goal is to check for consistent attention throughout the survey, so they might be placed at regular intervals. For example, if you have a 50-question survey, you could place an attention check question after every 10 or 15 questions.
• Variety: of attention check question types means participants can't easily identify them and respond correctly without paying attention to the rest of the survey.
• Placement in Context: The questions can sometimes be related to the subject matter of the survey. In this case, they should be placed where they make the most sense in the context of the other questions.
• Randomization: If possible, randomizing the order of questions, including attention checks, can help avoid bias that might result from their position in the survey.
• Placement in Important Sections: If there are certain sections of the survey where it is particularly important that respondents are paying attention (e.g., complex questions or key measures), it might make sense to include an attention check question immediately before or after that section.
• Avoiding End or Start: At the start, respondents are usually more attentive, and at the end, they may be rushing to finish. Hence, these locations may not accurately capture the participant's overall level of attention.

 Peace is the language of love that all can understand - Hari Srinivasan 

Kindness is contagious lets spread it like wildfire

 Peace is the whisper of hope that echoes through the ages. - Hari Srinivasan 

Peace is the power that transforms hate into love - Hari Srinivasan 

Joy is the energy that fuels our passion and purpose

 Contemplation, one line a Day. 

 

Peace is the voice of reason that rises above the noise.

 Peace is the voice of reason that rises above the noise.

Optimism is the force that keeps us moving forward, even when the path is unclear. 

 

A Simple Guide to the DSM and Autism

Lexicon [Measures] - DSM

PlainSpeak. In Plain Language for the Lay Reader

The Diagnostic and Statistical Manual of Mental Disorders (DSM) is a big book that doctors and mental health professionals use to diagnose and understand mental health conditions. 

Here’s a quick history of the DSM, focusing on how it has changed its understanding of autism over the years.

The Early Years: DSM-I and DSM-II

• DSM-I (1952): The first edition of the DSM didn’t include autism. Back then, people didn’t really know about autism.
• DSM-II (1968): The second edition mentioned “schizophrenic reaction, childhood type,” because people thought autism was related to childhood schizophrenia.

Autism Emerges: DSM-III and DSM-III-R

• DSM-III (1980): This edition was a big deal because it introduced "Infantile Autism" as its own category. This was the first time autism was seen as different from schizophrenia.
• DSM-III-R (1987): The revised edition changed the name to "Autistic Disorder" and provided more detailed criteria for diagnosing it, recognizing a wider range of symptoms.

Refining the Diagnosis: DSM-IV and DSM-IV-TR

• DSM-IV (1994): This edition added more details. Autism was now part of a group called Pervasive Developmental Disorders (PDD), which included:

  • Autistic Disorder
  • Asperger’s Disorder
  • Rett’s Disorder
  • Childhood Disintegrative Disorder
  • Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS)

  This allowed doctors to better identify different types of autism.

• DSM-IV-TR (2000): This version didn’t change much but updated and clarified the existing information.

The Modern Era: DSM-5

• DSM-5 (2013): The most recent edition made major changes to how autism is diagnosed:
  • Autism Spectrum Disorder (ASD): The DSM-5 combined all the previous types of autism into one diagnosis called Autism Spectrum Disorder (ASD). This reflects the idea that autism is a single condition with different levels of severity.
  • Two Domains: The criteria for diagnosing ASD are now based on two main areas:
    1. Social Communication and Interaction: Problems with social communication and interaction in different situations.
    2. Restricted, Repetitive Behaviors: Repetitive movements, strict routines, very focused interests, and unusual reactions to sensory experiences.
  • Severity Levels: The DSM-5 includes levels to show how much support someone with ASD might need:
    • Level 1: Requires support
    • Level 2: Requires substantial support
    • Level 3: Requires very substantial support
  • Specifiers and Comorbidities: Doctors can add more details about a person’s ASD, like if they have intellectual or language difficulties. The DSM-5 also recognizes that people with ASD often have other conditions like anxiety, depression, or ADHD.

Summary

The DSM has changed a lot over the years to better understand and diagnose autism. From not recognizing autism at all to seeing it as a broad spectrum of conditions, these updates help doctors and families understand and support people with autism better.

Related Posts: [DSM], [Diagnosis],[Measures]

Equanimity is the surrender to what is and what we cannot change

Towards a more humane society. #MentalHealth. Contemplation, one line a day.