T1. CLINICAL PROFILE AND PREVALENCE OF POSTTRAUMATIC STRESS SYMPTOMS AMONG SERVICE-USERS REFERRED FOR PSYCHOLOGICAL FOLLOW-UP: UTILITY OF ASSESSING SYMPTOMS SEVERITY RANGE
Bibliographic record
Abstract
Abstract Background Individuals with psychosis and comorbid posttraumatic stress disorder (PTSD) typically present with more severe forms of illness. Subthreshold posttraumatic stress symptoms (PTSS) are also likely to cause significant distress. There is a need to enhance screening processes for distressing PTSS to encourage appropriate referral to specialized services. The PTSD checklist for DSM-5 (PCL-5) is a widely used self-report to assess PTSS, though there is concern regarding its validity for use in psychosis. If people scoring in the severe PTSS range on the PCL-5 also present with clinical profiles similar to those typically meeting diagnosis for PTSD, it will justify considering a broader range of PTSS and support the use of the PCL-5 as a brief screener. A severe range will arguably capture a wider array of individuals, including those with subthreshold PTSS who also likely require trauma-focused intervention. Methods One hundred and two individuals with psychosis completed the PCL-5 and a battery of clinical scales as part of an intake evaluation following referral for psychological follow-up at a clinic specializing in psychosocial interventions for psychosis. Prevalence and type of DSM-5 criterion A event were explored in conjunction with PTSS severity and referral-type. Pearson correlations identified clinical variables associated with PCL-5 total scores and were subsequently entered into a multivariate analysis of variance (MANOVA) with dichotomized PTSS severity categories (low, moderate, severe). Post hoc analyses explored significant interactions. Results Of the 102 participants, 21.6% reported no prior trauma and 14.7% reported non-valid events. Sixty-five participants were included in the analysis; 6.2% of which were referred for trauma. 81.5% reported criterion A events, 10.8% reported psychosis-related events, and 7.7% did not disclose an event. PCL-5 scores were dichotomized using the 33rd and 66th percentiles, translating into low (≤ 24), moderate (25–47), and severe (≥48) groups. Delusion severity and subjective stress, anxiety, depression, social anxiety, quality of life (QoL), and wellbeing were entered into a one-way MANOVA with PTSS severity groups. Significant main effects surviving Bonferroni correction emerged for all variables except delusion severity (F(2,40) = 3.06, p = .058) and wellbeing (F(2,56) = 1.50, p =.233). Stress (F(2,62) = 7.37, p = .001) was higher in the severe (M = 13.13, SD = 5.18) versus low group (M = 7.05, SD = 4.40, p = .001). Anxiety (F(2,62) = 8.02, p = .001) was also higher in the severe (M = 12.30, SD = 5.07) compared to low group (M = 5.85, SD = 5.06, p = .000), and depression (F(2,62) = 5.37, p = .007) was additionally higher in the severe (M = 12.61, SD = 5.73) compared to low group (M = 7.20, SD = 4.97, p = .005). Finally, social anxiety (F(2,58) = 4.25, p = .026.) was higher in the severe (M = 7.76, SD = 3.58) versus low group (M = 4.68, SD = 3.68, p = .029), while QoL (F(2,58) = 3.47, p = .038) was lower in the severe (M = 49.95, SD = 10.99) compared to low group (M = 58.95, SD = 13.76, p = .037). Discussion Due to a relatively high number of invalid questionnaires (14.7%), service users should likely complete the PCL-5 in the presence of a health-care practitioner. Findings suggest inadequate referral rates for specialized services when they may indeed benefit the service-user. Severe PTSS was associated with increased symptoms of subjective anxiety, depression, stress, social anxiety, and decreased QoL, regardless of whether diagnostic criteria for PTSD was met. A severe PTSS category likely captures a broader range of individuals requiring specialized intervention and speaks to an important need to both facilitate and increase referral rate for trauma-focused therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".