Frailty discrimination: a scoping review
Bibliographic record
Abstract
Frailty, a concept which defies consensus definition is nevertheless widely acknowledged to be an important and growing public health issue facing our ageing population [1]. It has become the focus of much research aiming to mitigate its costly adverse outcomes; falls and increased fracture risk, hospitalisation, institutionalisation, dependency and death [2]. Individuals living with frailty are living in an increasingly precarious situation, where insults or shocks (events such as an infection or a sudden bereavement) become harder for their bodies’ physiology and social support networks to withstand. In the UK, the 2010 Equalities Act enshrines in law the right to protection from discrimination because of certain protected characteristics, including age and disability [3]. Frailty is not specified as a protected characteristic. However, frailty can be thought of as aligned with disability; given that physical dependency is a common outcome, and overlapping with age; given that frailty, while not an inevitable consequence, becomes more common as we age [4]. In our attempt to offer appropriate healthcare for older people, frailty screening has become the norm in UK primary and secondary healthcare [5, 6]. Particularly ubiquitous is Rockwood’s Clinical Frailty scale, a pictorial and vignette grading system developed from the Canadian Study of Health and Aging’s frailty index [7]. Guidelines now recommend screening based on our electronic healthcare records and for unplanned hospital admissions [8-10]. This recognition of frailty, suggests a recognition of differential care needs, based on frailty’s association with increased risk. However, balancing an assessment of population risk with individualised care is challenging, and frailty-based discrimination could result from both system-level or individual-level problems getting this right. Objectives The aim of this scoping review is to explore frailty-based discrimination, or ‘frailism’, in order to better characterise the phenomenon and its effects, to examine the extent of its inclusion in any text, and identify gaps for future investigation [10]. Findings may suggest a literature base for a narrower population systematic review. 1. Hoogendijk EO, Afilalo J, Ensrud KE, Kowal P, Onder G, Fried LP. Frailty: implications for clinical practice and public health. Lancet. 2019 Oct 12;394(10206):1365-75. 2. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013 Mar 02;381(9868):752-62. 3. Equality and Human Rights Commission. Equality Act 2010. 2018 [cited 2022 11th March]; Available from: https://www.equalityhumanrights.com/en/equality-act/equality-act-2010. 4. Junius-Walker U, Onder G, Soleymani D, Wiese B, Albaina O, Bernabei R, et al. The essence of frailty: A systematic review and qualitative synthesis on frailty concepts and definitions. Eur J Intern Med. 2018 Oct;56:3-10. 5. Church S, Rogers E, Rockwood K, Theou O. A scoping review of the Clinical Frailty Scale. BMC Geriatr. 2020 Oct 7;20(1):393. 6. Clegg A, Bates C, Young J, Ryan R, Nichols L, Ann Teale E, et al. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing. 2016 May;45(3):353-60. 7. Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005 Aug 30;173(5):489-95. 8. National Institute for Health and Care Excellence. Multimorbidity: clinical assessment and management. NICE; 2016 [cited 2022 11th March]; Available from: https://www.nice.org.uk/guidance/ng56. 9. NHS England. NHS RightCare: Frailty Toolkit Optimising a frailty system. https://www.england.nhs.uk/rightcare/products/pathways/frailty/: NHS England; 2019 [cited 2022 11th March]; Available from: https://www.england.nhs.uk/rightcare/wp-content/uploads/sites/40/2019/07/frailty-toolkit-june-2019-v1.pdf. 10. Clegg A, Rockwood K, Romero-Ortuno R, Cunningham C. Silver Book II: Frailty. In: Rockwood K, editor. Silver Book II Quality care for older people with urgent care needs2021.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.012 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.308 | 0.013 |
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".