Tonic immobility does not uniquely predict posttraumatic stress symptom severity.
Bibliographic record
Abstract
Tonic immobility (TI) is an involuntary state of temporary motor inhibition believed to occur in response to events that provoke extreme fear and the perception of inescapability. Human TI has been documented in a range of traumatic events and several researchers have reported associations between TI and posttraumatic stress symptoms (PTSS); however, it remains unclear if TI is a unique predictor of PTSS. This study was designed to determine whether TI severity would account for variance in PTSS severity over and above the influence of peritraumatic dissociation and trait anxiety. Participants were community members (n 75; 88% women; ages 18–65, Mage 31.49, SD 12.21) who reported TI during a traumatic event. TI, peritraumatic dissociation, and trait anxiety were assessed as part of a larger investigation. Results of hierarchical regression analyses indicated trait anxiety and peritraumatic dissociation, but not TI, were significant and substantive predictors of PTSS scores. In all analyses TI scores failed to account for significant variance in PTSS scores (all ps .05). Results suggest the TI construct may add little to understanding PTSS beyond what can be ascertained by assessing peritraumatic dissociation and trait anxiety. Given mixed findings to date, further investigation is required to disentangle what is shared and what is distinct among these constructs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".