Evidence mapPaperPMID 39334286Full record

ReviewBMC medicine2024

Unleashing the full potential of digital outcome measures in clinical trials: eight questions that need attention.

Mia S Tackney, James R Carpenter, Sofía S Villar

Abstract readReview
In one paragraph

Review in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026
    Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mia S TackneyMRC-Biostatistics Unit, University of Cambridge, East Forvie Building, Forvie, Robinson Way, Cambridge, CB2 0SR, UK. mst35@cam.ac.uk.
James R CarpenterMRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, 90 High Holborn, London, WC1V 6LJ, UK.
Sofía S VillarMRC-Biostatistics Unit, University of Cambridge, East Forvie Building, Forvie, Robinson Way, Cambridge, CB2 0SR, UK.

Funding

Medical Research Council MC UU 00002/15Medical Research Council MC UU 00004/07
6 · The paper itself

Abstract

The use of digital health technologies to measure outcomes in clinical trials opens new opportunities as well as methodological challenges. Digital outcome measures may provide more sensitive and higher-frequency measurements but pose vital statistical challenges around how such outcomes should be defined and validated and how trials incorporating digital outcome measures should be designed and analysed. This article presents eight methodological questions, exploring issues such as the length of measurement period, choice of summary statistic and definition and handling of missing data as well as the potential for new estimands and new analyses to leverage the time series data from digital devices. The impact of key issues highlighted by the eight questions on a primary analysis of a trial are illustrated through a simulation study based on the 2019 Bellerophon INOPulse trial which had time spent in MVPA as a digital outcome measure. These eight questions present broad areas where methodological guidance is needed to enable wider uptake of digital outcome measures in trials.

Indexed as

Clinical Trials as TopicOutcome Assessment, Health CareDigital TechnologyHumansResearch DesignClinical trialDigital endpointsDigital health technologyDigital outcome measuresValidation

Identifiers

PMID39334286
PMCPMC11438362

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.