Development and Evaluation of the Telehealth in Motor Neuron Disease System: The TIME Study Protocol
Bibliographic record
Abstract
BACKGROUND: For more responsive care provision for motor neuron disease and caregivers, a digital system called Telehealth in MND-Care (TiM-C) was created. TiM-C sends regular symptom questionnaires to users; their responses are sent to health care professionals (HCPs). To enable people with motor neuron disease to participate in research studies more easily, a parallel platform was developed from TiM-C, called Telehealth in MND-Research (TiM-R). TiM-R can advertise studies, collect data, and make them available to MND researchers. OBJECTIVE: This study has 4 work packages (WPs) to facilitate service approval, codevelop the TiM systems, and evaluate the service. Each WP aims to understand (1) what helps and hinders the approval of the TiM-C system as a National Health Service; (2) what aspects of MND care and research are currently unmet and can be addressed through the TiM-C and TiM-R systems; (3) how TiM-C influences MND care, from the perspective of people with motor neuron disease, their caregivers, and HCPs; and (4) the costs and benefits associated with TiM-C. METHODS: WP1 will use semistructured interviews with 10-15 people involved in the approval of TiM-C to understand the barriers and facilitators to governance processes. WP2 will use individual and group interviews with 25-35 users (people with motor neuron disease, caregivers, HCPs, MND researchers, and industry) of TiM-C and TiM-R to understand the current unmet needs of these user groups and how TiM services can be developed to meet these needs. WP3 will use a process evaluation involving 5 elements; local context, engagement, user experiences, service impact, and mechanisms of action. A range of methods, including audits, analysis of routine data, questionnaires, interviews, and observations will be used with people with motor neuron disease, caregivers, and HCPs, both those using the system and those who declined the service when invited. WP4 will use data collected through the process evaluation and known costs to conduct a cost-consequence and budget impact analysis to explore the cost-benefit of the TiM-C service. Most data collected will be qualitative, with thematic and framework analysis used to develop themes from transcripts and observations. Descriptive statistics or t tests and chi-square tests will be used to describe and analyze quantitative data. RESULTS: This study has received ethical approval and has begun recruitment in 1 site. Further, 13 specialist MND centers will adopt TiM-C and the TIME study, beginning in July 2024. The study will conclude in November 2026 and a final report will be produced 3 months after the completion date. CONCLUSIONS: This study will facilitate the implementation and development of TiM-C and TiM-R and fully evaluate the TiM-C service, enabling informed decision-making among health care providers regarding continued involvement and contribute to the wider literature relating to how technology-enabled care services can affect clinical care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57685.
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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 | 0.075 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.046 | 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".