PT  - JOURNAL ARTICLE
AU  - Lindsay M. Alexander
AU  - Giovanni A. Salum
AU  - James M. Swanson
AU  - Michael P. Milham
TI  - Balancing Strengths and Weaknesses in Dimensional Psychiatry
AID  - 10.1101/207019
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 207019
4099  - http://biorxiv.org/content/early/2017/10/20/207019.short
4100  - http://biorxiv.org/content/early/2017/10/20/207019.full
AB  - Objective To evaluate the feasibility and value of creating an extensible framework for psychiatric phenotyping that indexes both strengths and weaknesses of behavioral dimensions. The Extended Strengths and Weaknesses Assessment of Normal Behavior (E-SWAN) reconceptualizes each diagnostic criterion for selected DSM-5 disorders as a behavior, which can range from high (strengths) to low (weaknesses). Initial efforts have focused on Panic Disorder, Social Anxiety, Major Depression, and Disruptive Mood Dysregulation Disorder.Methods Data were collected from 523 participants (ages: 5-21 years old) in the Child Mind Institute Healthy Brain Network − an ongoing community-referred study. Parents completed each of the four E-SWAN scales and traditional unidirectional scales addressing the same disorders. Distributional properties, Item Response Theory Analysis (IRT) and Receiver Operating Characteristic (ROC) curves (for diagnostic prediction) were used to assess and compare the performance of E-SWAN and traditional scales.Results In contrast to the traditional scales, which exhibited truncated distributions, all four E-SWAN scales were found to have near-normal distributions. IRT analyses indicate the E-SWAN subscales provided reliable information about respondents throughout the population distribution; in contrast, traditional scales only provided reliable information about respondents at the high end of the distribution. Predictive value for DSM-5 diagnoses was comparable to prior scales.Conclusion E-SWAN bidirectional scales can capture the full spectrum of the population distribution for DSM disorders. The additional information provided can better inform examination of inter-individual variation in population studies, as well as facilitate the identification of factors related to resiliency in clinical samples.