Problem Solving, Attachment, And Anxiety In Motor Vehicle Accident Survivors With Ptsd
Bibliographic record
Abstract
The current research study examined effects of social problem-solving skills and attachment styles on anxiety levels in motor vehicle accident (MVA) survivors diagnosed with posttraumatic stress disorder (PTSD). The sample consisted of 23 clients from a private practice in a small city in Ontario, Canada. The population of this study was chosen to address limitations noted in past literature outlining the limited scope of populations examined in the context of PTSD (i.e., nature of trauma). A theoretical framework of attachment theory was outlined as well as a comprehensive literature review examining the independent effects of attachment styles and social problem solving skills on anxiety levels. The participants completed a demographic questionnaire as well as the Beck Anxiety Inventory (BAI; Beck & Steer, 1993), Social Problem-Solving Inventory-Revised Short Form (SPSI-R (SF; D’Zurilla et al., 2002), and the Adult Attachment Scale (Collins & Reed, 1990). The results of the study found that social problem solving skills did not significantly predict anxiety levels, with a negative relationship expected between social problem-solving skills and anxiety levels. In addition, attachment style did not significantly predict anxiety levels however, the negative relationship between close and dependent attachment and anxiety levels is understandable illustrating that anxiety levels are likely to be low in individuals with more secure attachment styles. Limitations of the study include the homogeneity of the sample demographics, the sample size, measures implemented, and the method of measure administration. Future research is needed to explore these variables on victims of motor vehicle accidents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".