The Road to Reintegration: Status and Continuing Support of the U.S. Air Force's Wounded, Ill, and Injured
Bibliographic record
Abstract
The U.S. Air Force asked RAND Project AIR FORCE (PAF) to help assess the well-being of its wounded members and the quality of services provided to facilitate their recovery and reintegration. RAND PAF fielded a survey in the fall of 2016 to assess wounded airmen's functioning in the domains of physical health, mental health, interpersonal relationships, unemployment, and financial status, as well as their utilization and perceptions of Air Force nonmedical programs for wounded airmen. The authors of this study invited all 713 wounded airmen enrolled in the Air Force Wounded Warrior program to complete the survey, and 270 airmen (38 percent) completed it. One-third of airmen reported difficulty obtaining care for physical or mental health conditions, and one-quarter expressed dissatisfaction with coordination of care. Similar proportions of airmen reported barriers to care for physical and mental health conditions. Difficulty scheduling appointments was the most commonly endorsed barrier for both types of conditions. Small but notable proportions of airmen reported potential social support deficits, unemployment, and financial problems. For many of the Air Force's programs for wounded airmen, over 80 percent of program users reported overall program satisfaction. The authors recommend that the Air Force consider focusing on improving care coordination, increasing health care system capacity, continuing employment assistance, and improving marketing of programs with low uptake.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".