Aging and orthopedics: how a lifespan development model can inform practice and research
Bibliographic record
Abstract
Orthopedic surgical care, like all health care today, is in flux owing to an aging population and to chronic medical conditions leading to an increased number of people with illnesses that need to be managed over the lifespan. The result is an ongoing shift from curing acute illnesses to the management and care of chronic illness and conditions. Theoretical models that provide a useful and feasible vision for the future of health care and health care research are needed. This review discusses how the lifespan development model used in some disciplines within the behavioural sciences can be seen as an extension of the biopsychosocial model. We posit that the lifespan development model provides useful perspectives for both orthopedic care and research. We present key concepts and recommendations, and we discuss how the lifespan development model can contribute to new and evolving perspectives on orthopedic outcomes and to new directions for research. We also offer practical guidelines on how to implement the model in orthopedic practice.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".