Impact of clinical symptoms and diagnosis: the electronic Person-Specific Outcome Measure (ePSOM) development programme
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Regulatory bodies recommend that outcome measures used in Alzheimer's disease (AD) clinical trials capture clinically meaningful changes for the trial participant. However, commonly used outcome measures do not reflect the individual's views on what matters to them individually. The aim of the electronic Person-Specific Outcome Measure (ePSOM) programme is to better understand what outcomes matter to patients in early Alzheimer's disease. METHODS: As part of the ePSOM programme, we designed and ran an online study to understand what matters to individuals when developing new treatments for AD. The ePSOM survey ran Aug 2019-Dec 2019 (UK) and collected primarily free text responses which were analysed using Natural Language Processing (NLP) techniques. In this paper, we focus our analyses on individuals who reported having a neurodegenerative disease diagnosis (primarily Mild Cognitive Impairment (MCI) or AD), reporting the most frequent and most important brain health priorities for this group. Due to a small sample size, the Diagnosis group was analysed as a whole. Finally, we compared the Diagnosis group to an age and gender matched control group using chi-squared tests to look for any differences between the Diagnosis and control groups' priorities. RESULTS: The survey was completed by 5808 respondents, of whom 167 (2.9%) (women n = 91, men n = 69, other n = 7) had received one of our pre-defined neurodegenerative disease diagnosis: most commonly MCI n = 52, 1.1% (mean age 69.42, SD = 10.8); or Alzheimer's disease n = 48, 1.0% (mean age 71.24, SD = 9.79). Several thematic clusters were significantly more important for the target diagnostic group, e.g.: Expressing opinions; and less important, e.g., Cognitive Games. CONCLUSION: We conclude there are a range of outcomes which individuals consider important and what potential new treatments should help maintain or improve, suggesting that outcomes that matter shift along the preclinical, prodromal and overt dementia continuum. This has important implications for the development of outcome measures in long term prevention studies that last several years where participants may pass through different stages of disease. In the final stage of our project, we will design an electronic outcomes app which will employ the methodology tested in the large-scale survey to capture what matters to individuals about their brain health at an individual level.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it