Quality of life measures in older adults after traumatic brain injury: a systematic review
Bibliographic record
Abstract
BACKGROUND: On average older adults experiencing TBI are hospitalized four times as often, have longer hospital stays, and experience slower recovery trajectories and worse functional outcomes compared to younger populations with the same injury severity. A standard measure of Qol for older adults with TBI would facilitate accurate and reliable data across the individual patient care continuum and across clinical care settings, as well as support more rigorous research studies of metadata. PURPOSE: The aim of this systematic review was to investigate patient reported Qol measures in studies with older adults post TBI. METHOD: A systematic review was carried out focusing on the various tools to measure Qol in older adults, ≥ 65 years of age with a diagnosis of TBI. Data bases searched included Medline, Embase, PubMed, CINAHL, and PsychInfo from date of inception to September 25, 2017. RESULTS: A total of 20 articles met the inclusion criteria. Nine different tools were identified. CONCLUSIONS: Findings based on the comparison of reliability and construct validity of the Qol measures reported in this review suggest that no single instrument is superior to all others for our study population. Future research in this field should include the enrollment of larger study samples of older adults. Without these future efforts, the ability to detect an optimal Qol measure will be hindered.
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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 | 0.097 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".