The Smartphone App haMSter for Tracking Patient-Reported Outcomes in People With Multiple Sclerosis: Protocol for a Pilot Study
Bibliographic record
Abstract
BACKGROUND: Treatment and monitoring decisions in people with multiple sclerosis (MS) are based commonly on clinician-reported outcomes. These reflect physical and radiological disease activity and are the most relevant endpoints in clinical trials. Over the past few years, the number of studies evaluating so-called patient-reported outcomes (PROs) has been increasing. PROs are reports from patients concerning their own health perception. They are typically obtained by means of questionnaires and aim to quantify symptoms such as fatigue, depression, and sexual dysfunction. The emergence of PROs has made a tremendous contribution to understanding the individual impact of disease in people with MS and their health-related quality of life. However, the assessment of PROs consumes resources, including time and personnel. Thus, useful ways to conveniently introduce PROs into clinical practice are needed. OBJECTIVE: We aim to provide a rationale and pilot study protocol for a mobile health (mHealth) solution named "haMSter" that allows for remote monitoring of PROs in people with MS. METHODS: The core function of haMSter is to provide three scientifically validated PRO questionnaires relevant to MS for patients to fill out at home once a month. Thereby, longitudinal and remote documentation of PROs is enabled. A scoring algorithm graphically plots PRO scores over time and makes them available at the next visit. RESULTS: The pilot study is currently ongoing and will evaluate adherence to this mHealth solution in 50 patients over a period of 6 months. Results from the haMSter pilot study are expected in 2021. CONCLUSIONS: haMSter is a novel mHealth-based solution for modern PRO research, which may constitute the first step in achieving the ability to integrate PROs in clinical practice. This allows for a more problem-oriented approach in monitoring visits, which addresses patient needs and ultimately saves time. TRIAL REGISTRATION: ClinicalTrials.gov NCT04555863; https://clinicaltrials.gov/ct2/show/NCT04555863. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/25011.
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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 | 0.032 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.049 | 0.012 |
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".