| Literature DB >> 25058403 |
Joseph M Currier1, Jason M Holland2, Kent D Drescher3.
Abstract
BACKGROUND: Combat-related posttraumatic stress disorder (PTSD) can be a difficult condition to treat and has been associated with serious medical and economic issues among U.S. military veterans. Distinguishing between treatment responders vs. non-responders in this population has become an important public health priority. This study was conducted to identify pre-treatment characteristics of U.S. veterans with combat-related PTSD that might contribute to favorable and unfavorable responses to high value treatments for this condition.Entities:
Mesh:
Year: 2014 PMID: 25058403 PMCID: PMC4109915 DOI: 10.1371/journal.pone.0101741
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Descriptive Statistics and Bivariate Correlations Between Study Variables.
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| PTSD at Pre-treatment | PTSD at Post-treatment | PTSD at Follow-up | |
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| 51.632 | 8.066 | −.085* | .024 | .055 |
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| 0.891 | 0.311 | .065 | .153*** | .123*** |
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| 0.595 | 0.491 | −.072* | −.050 | −.012 |
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| 21.924 | 12.272 | .158*** | .224*** | .127*** |
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| 38.809 | 10.138 | −.169*** | −.136*** | −.126*** |
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| 30.760 | 9.083 | −.336*** | −.224*** | −.197*** |
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| 32.950 | 17.690 | .218*** | .134*** | .119*** |
: ***p<.001, **p<.01, *p<.05; M = mean, SD = standard deviation, PTSD = Posttraumatic Stress Disorder. Sex was coded in such a manner that 0 = Women, 1 = Men. Ethnicity was coded such that 0 = Non-Caucasian, 1 = Caucasian persons.
Goodness of Fit Indices for Latent Class Growth Analysis Examining Posttraumatic Stress Symptoms from Pretreatment to Follow-up (N = 805).
| AIC | BIC | Entropy | VLMR-LRT | |
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| 19124.116 | 19147.570 | — | — |
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| 18533.766 | 18604.128 | .732 | <.001 |
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| 18350.847 | 18468.118 | .735 | <.001 |
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| 18339.694 | 18503.874 | .785 | .114 |
: AIC = Akaike Information Criterion, BIC = Bayesian Information Criterion, VLMR-LRT = Vuong-Lo-Mendell-Rubin Likelihood Ratio Test. Missing data was handled using multiple imputation with five imputed data sets. Mean values across these data sets are presented for AIC, BIC, and Entropy, and the median p value is presented for the VLMR-LRT.
Figure 1Graphical depiction of the 3-class solution for PCL-M scores from pre-treatment to a four-month follow-up assessment.
Solid lines represent trajectories based on estimated means. Dotted lines represent trajectories based on actual means in the sample.
Comparison of Mean PTSD Scores at Pre-treatment, Post-treatment, and Follow-up for the 3-Class Model (N = 805).
| Mean: Pre-treatment (Pre) | Mean: Post-treatment (Post) | Mean: Follow-up | Wald Test: Pre vs. Post | Pre to Post | Wald Test: Pre- vs. Follow-up | Pre to Follow-up | Wald Test: Post vs. Follow-up | Post to Follow-up | |
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| 72.594 | 69.107 | 71.442 | 26.971** | −0.42 | 2.832 | −0.15 | 8.362* | 0.26 |
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| 62.324 | 54.931 | 58.127 | 96.716** | −0.78 | 31.910** | −0.50 | 17.136** | 0.32 |
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| 45.554 | 38.404 | 44.262 | 32.497** | −0.77 | 0.934 | −0.13 | 12.021** | 0.59 |
: PTSD = Posttraumatic Stress Disorder. **p<.001, *p<.01.
Multinomial Logistic Regression Analysis Predicting Class Membership for the 3-Class Model (N = 805).
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| B | SE | Odds Ratio | p | B | SE | Odds Ratio | p | B | SE | Odds Ratio | p | |
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| 0.006 | 0.014 | 1.006 | .676 | 0.051 | 0.025 | 1.052 | .045 | −0.045 | 0.026 | 0.956 | .081 |
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| 0.200 | 0.478 | 1.221 | .677 | 0.080 | 0.554 | 1.083 | .885 | 0.120 | 0.685 | 1.127 | .862 |
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| −0.295 | 0.233 | 0.744 | .205 | 0.361 | 0.364 | 1.435 | .321 | −0.656 | 0.379 | 0.519 | .083 |
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| 0.022 | 0.011 | 1.022 | .055 | −0.053 | 0.020 | 0.948 | .007 | 0.075 | 0.022 | 1.078 | .001 |
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| −0.046 | 0.014 | 0.955 | .001 | 0.056 | 0.018 | 1.057 | .002 | −0.102 | 0.021 | 0.903 | <.001 |
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| −0.080 | 0.018 | 0.923 | <.001 | 0.089 | 0.020 | 1.093 | <.001 | −0.169 | 0.025 | 0.844 | <.001 |
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| 0.011 | 0.007 | 1.011 | .154 | −0.033 | 0.012 | 0.967 | .006 | 0.044 | 0.013 | 1.045 | <.001 |
: PTSD = Posttraumatic Stress Disorder.