Measuring strengths and weaknesses in dimensional psychiatry

Alexander, Lindsay; Salum, Giovanni Abrahão; Swanson, James M.; Milham, Michael P.

doi:10.1111/jcpp.13104

Cited by 38 publications

(28 citation statements)

References 31 publications

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“…It uses items from the Swanson Nolan And Pelham IV (SNAP IV; Swanson, 2003). The SNAP-IV teacher and parent rating scale is often used to assess ADHD symptoms, but the SWAN rephrases the symptoms into strength-based statements making them follow a normal distribution instead of a skewed distribution (Alexander, Salum, Swanson, & Milham, 2019).…”

Section: Methodsmentioning

confidence: 99%

Probing the overarching continuum theory: Data-driven phenotypic clustering of children with ASD or ADHD

Deserno¹,

Bathelt²,

Groenman³

et al. 2021

Preprint

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The clinical validity of the distinction between ADHD and ASD is a longstanding discussion. Recent advances in the realm of data-driven analytic techniques now enable us to formally investigate theories aiming to explain the frequent co-occurrence of these neurodevelopmental conditions. In this study, we probe different theoretical positions by means of a pre-registered integrative approach of novel classification, subgrouping and taxometric techniques in a representative sample (N=434) and replicate the results in an independent sample (N=219) of children (ADHD, ASD, and typically developing) aged 7 to 14 years. First, Random Forest Classification could predict diagnostic groups based on questionnaire data with limited accuracy - suggesting some remaining overlap in behavioural symptoms between them. Second, community detection identified four distinct groups, but none of them showed a symptom profile clearly related to either ADHD or ASD in neither the original sample nor the replication sample. Third, taxometric analyses showed evidence for a categorical distinction between ASD and typically developing children, a dimensional characterization of the difference between ADHD and typically developing children and mixed results for the distinction between the diagnostic groups. We present a novel framework of cutting-edge statistical techniques which represent recent advances in both the models and the data used for research in psychiatric nosology. Our results suggest that that ASD and ADHD cannot be unambiguously characterised as either two separate clinical entities or opposite ends of a spectrum and highlight the need to study ADHD and ASD traits in tandem.

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Section: Methodsmentioning

confidence: 99%

Probing the overarching continuum theory: Data-driven phenotypic clustering of children with ASD or ADHD

Deserno¹,

Bathelt²,

Groenman³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Alternatively, it may reflect the fact the effects for the psychiatric factors were notably smaller than those observed for the cognitive -possibly due to the fact that the HCP samples are largely neurotypical subjects. Related to this point, recent work has highlighted the suboptimal nature of psychiatric tools such as the Adult Self Report in non-psychiatric samples (Alexander et al, 2020).…”

Section: Figure 6 Comparisons Of Prediction Accuracy Between Functiomentioning

confidence: 99%

Toward a Connectivity Gradient-Based Framework for Reproducible Biomarker Discovery

Hong

Nikolaidis

et al. 2020

Preprint

Self Cite

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Despite myriad demonstrations of feasibility, the high dimensionality of fMRI data remains a critical barrier to its utility for reproducible biomarker discovery. Recent studies applying dimensionality reduction techniques to resting-state fMRI (R-fMRI) have unveiled neurocognitively meaningful connectivity gradients that are present in both human and primate brains, and appear to differ meaningfully among individuals and clinical populations. Here, we provide a critical assessment of the suitability of connectivity gradients for biomarker discovery.Using the Human Connectome Project (discovery subsample=209; two replication subsamples= 209×2) and the Midnight scan club (n=9), we tested the following key biomarker traits -reliability, reproducibility and predictive validity -of functional gradients. In doing so, we systematically assessed the effects of three analytical settings, including i) dimensionality reduction algorithms (i.e., linear vs. non-linear methods), ii) input data types (i.e., raw time series, [un-]thresholded functional connectivity), and iii) amount of the data (R-fMRI time-series lengths). We found that the reproducibility of functional gradients across algorithms and subsamples is generally higher for those explaining more variances of whole-brain connectivity data, as well as those having higher reliability. Notably, among different analytical settings, a linear dimensionality reduction (principal component analysis in our study), more conservatively thresholded functional connectivity (e.g., 95-97%) and longer time-series data (at least ≥20mins) was found to be preferential conditions to obtain higher reliability. Those gradients with higher reliability were able to predict unseen phenotypic scores with a higher accuracy, highlighting reliability as a critical prerequisite for validity. Importantly, prediction accuracy with connectivity gradients exceeded that observed with more traditional edge-based connectivity measures, suggesting the added value of a low-dimensional gradient approach. Finally, the present work highlights the importance and benefits of systematically exploring the parameter space for new imaging methods before widespread deployment.

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“…Tasks on Prolific mostly consist of study participation. However, studies conducted on this platform are very diverse and from multiple disciplines such as clinical psychology (Alexander, Salum, Swanson, & Milham, 2020), cognitive psychology (e.g., Ensor, Surprenant, & Neath, 2019), health psychology (e.g., Todd, Aspell, Barron, & Swami, 2019), social psychology (e.g., Jolley, Douglas, Leite, & Schrader, 2019), and economics (e.g., Teubner, Hawlitschek, & Adam, 2019). Tasks on MTurk do also include study participation but do largely consist of business requests such as classification tasks, product reviews, or transcriptions (e.g., Ipeirotis, 2010).…”

Section: The Present Investigationmentioning

confidence: 99%

Behavior in cheating paradigms is linked to overall approval rates of crowdworkers

Schild

Lilleholt

Zettler

2020

Behavioral Decision Making

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Dishonest and fraudulent behavior poses a serious threat to both individuals and societies. Many studies investigating dishonesty rely on (one of) a few well‐established lab and online cheating paradigms. Quite surprisingly, though, the external validity of these paradigms has only been investigated in a small number of studies, raising the question of whether behavior in these paradigms is related to real‐life dishonesty or, more broadly, socially questionable behavior. Tackling this gap, we link observed behavior in two widely used cheating paradigms to approval rates on two crowdworking platforms (namely, Prolific and Amazon Mechanical Turk) using data from four studies (overall N = 5,183). Results indicate that lower approval rates are associated with higher proportions of dishonest individuals. Importantly, this relation also holds for crowdworkers who exceed commonly used thresholds for study inclusion. The results thus support the external validity of (two widely used) cheating paradigms. Further, the study identifies approval rates as a variable that explains dishonesty on crowdworking platforms.

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Measuring strengths and weaknesses in dimensional psychiatry

Cited by 38 publications

References 31 publications

Probing the overarching continuum theory: Data-driven phenotypic clustering of children with ASD or ADHD

Probing the overarching continuum theory: Data-driven phenotypic clustering of children with ASD or ADHD

Toward a Connectivity Gradient-Based Framework for Reproducible Biomarker Discovery

Behavior in cheating paradigms is linked to overall approval rates of crowdworkers

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