The SF-36 Offers a Strong Measure of Mental Health Symptoms in Survivors of Acute Respiratory Failure. A Tri-National Analysis
Bibliographic record
Abstract
RATIONALE: Survivors of acute respiratory failure commonly experience long-term psychological sequelae and impaired quality of life. For researchers interested in general mental health, using multiple condition-specific instruments may be unnecessary and inefficient when using the Medical Outcomes Study Short Form (SF)-36, a recommended outcome measure, may suffice. However, relationships between the SF-36 scores and commonly used measures of psychological symptoms in acute survivors of respiratory failure are unknown. OBJECTIVES: Our objective is to examine the relationship of the SF-36 mental health domain (MH) and mental health component summary (MCS) scores with symptoms of depression, anxiety, and post-traumatic stress disorder (PTSD) evaluated using validated psychological instruments. METHODS: We conducted a cross-sectional analysis of 1,229 participants at 6- and 12-month follow-up assessment using data from five studies from the United States, the United Kingdom, and Australia. MEASUREMENTS AND MAIN RESULTS: Symptoms were assessed using the Hospital Anxiety and Depression Scale (HADS), Depression Anxiety Stress Scales, the Davidson Trauma Scale, Impact of Event Scale (IES), and IES-Revised (IES-R). At 6-month assessment there were moderate to strong correlations of the SF-36 MH scores with HADS depression and anxiety symptoms (r = -0.74 and -0.79) and with IES-R PTSD symptoms (r = -0.60) in the pooled analyses. Using the normalized population mean of 50 on the SF-36 MH domain score as a cut-off, positive predictive values were 16 and 55% for substantial depression; 20 and 68% for substantial anxiety (Depression Anxiety Stress Scales and HADS, respectively); and 40, 44, and 67% for substantial PTSD symptoms (IES-R, IES, and Davidson Trauma Scale, respectively). Negative predictive values were high. The area under the receiver operating characteristics curve of the SF-36 MH score was high for depression, anxiety, and PTSD symptoms (0.88, 0.91, and 0.84, respectively). All results were consistent for the MCS, across the individual studies, and for the 12-month assessment. CONCLUSIONS: For researchers interested in general mental health status, the SF-36 MH or MCS offers a strong measure of psychological symptoms prevalent among survivors of acute respiratory failure. For researchers interested in specific conditions, validated psychological instruments should be considered.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".