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Order effects in PTSD network analysis: important implications for diagnostic conceptualization, treatment refinement, and research
- Benjamin Trachik, Toby D. Elliman, Michelle L. Ganulin, Michael N. Dretsch, Lyndon A. Riviere, Oscar A. Cabrera, Jeffrey L. Thomas, Charles W. Hoge
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- Journal:
- Psychological Medicine / Volume 52 / Issue 13 / October 2022
- Published online by Cambridge University Press:
- 02 December 2020, pp. 2492-2499
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- Article
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Background
For decades confirmatory factor analysis (CFA) has been the preeminent method to study the underlying structure of posttraumatic stress disorder (PTSD); however, methodological limitations of CFA have led to the emergence of other analytic approaches. In particular, network analysis has become a gold standard to investigate the structure and relationships between PTSD symptoms. A key methodological limitation, however, which has significant clinical implications, is the lack of data on the potential impact of item order effects on the conclusions reached through network analyses.
MethodsThe current study, involving a large sample (N = 5055) of active duty army soldiers following deployment to Iraq, assessed the vulnerability of network analyses and prevalence rate to item order effects. This was done by comparing symptom networks of the DSM-IV PTSD checklist items to these same items distributed in random order. Half of the participants rated their symptoms on traditionally ordered items and half the participants rated the same items, but in random order and interspersed between items from other validated scales. Differences in prevalence rate and network composition were examined.
ResultsThe prevalence rate differed between the ordered and random item samples. Network analyses using the ordered survey closely replicated the conclusions reached in the existing network analyses literature. However, in the random item survey, network composition differed considerably.
ConclusionOrder effects appear to have a significant impact on conclusions reached from PTSD network analysis. Prevalence rates were also impacted by order effects. These findings have important diagnostic and clinical treatment implications.
Mutation Master: Profiles of substitutions in hepatitis C virus RNA of the core, alternate reading frame, and NS2 coding regions
- JOSÉ L. WALEWSKI, JULIO A. GUTIERREZ, WESTYN BRANCH-ELLIMAN, DECHERD D. STUMP, TOBY R. KELLER, ALFREDO RODRIGUEZ, GARY BENSON, ANDREA D. BRANCH
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The RNA genome of the hepatitis C virus (HCV) undergoes rapid evolutionary change. Efforts to control this virus would benefit from the advent of facile methods to identify characteristic features of HCV RNA and proteins, and to condense the vast amount of mutational data into a readily interpretable form. Many HCV sequences are available in GenBank. To facilitate analysis, consensus sequences were constructed to eliminate the overrepresentation of certain genotypes, such as genotype 1, and a novel package of sequence analysis tools was developed. Mutation Master generates profiles of point mutations in a population of sequences and produces a set of visual displays and tables indicating the number, frequency, and character of substitutions. It can be used to analyze hundreds of sequences at a time. When applied to 255 HCV core protein sequences, Mutation Master identified variable domains and a series of mutations meriting further investigation. It flagged position 4, for example, where 90% or more of all sequences in genotypes 1, 2, 4, and 5, have N4, whereas those in genotypes 3, 6, 7, 8, 9, and 10 have L4. This pattern is noteworthy: L (hydrophobic) to N (polar) substitutions are generally rare, and genotypes 1, 2, 4, and 5 do not form a recognized super family of sequences. Thus, the L4N substitution probably arose independently several times. Moreover, not one member of genotypes 1, 2, 4, or 5 has L4 and not one member of genotypes 3, 6, 7, 8, 9, or 10 has N4. This nonoverlapping pattern suggests that coordinated changes at position 4 and a second site are required to yield a viable virus. The package generated a table of genotype-specific substitutions whose future analysis may help to identify interacting amino acids. Three substitutions were present in 100% of genotype 2 members and absent from all others: A68D, R74K, and R114H. Finally, this study revealed that ARFP, a novel protein encoded in an overlapping reading frame, is as conserved as conventional HCV proteins, a result supporting a role for ARFP in the viral life cycle. Whereas most conventional programs for phylogenetic analysis of sequences provide information about overall relatedness of genes or genomes, this program highlights and profiles point mutations. This is important because determinants of pathogenicity and drug susceptibility are likely to result from changes at only one or two key nucleotides or amino acid sites, and would not be detected by the type of pairwise comparisons that have usually been performed on HCV to date. This study is the first application of Mutation Master, which is now available upon request (http://tandem.biomath.mssm.edu/mutationmaster.html).