Evidence map›Paper›PMID 27613084›Full record

ArticleJMIR mHealth and uHealth2016

Beyond the Randomized Controlled Trial: A Review of Alternatives in mHealth Clinical Trial Methods.

Quynh Pham, David Wiljer, Joseph A Cafazzo

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
95citing papers in PubMed, 11 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

95 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  10. The use of eHealth to promote physical activity in cancer survivors: a systematic review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2018
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35 more citing papers are in PubMed but not listed here.

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.

Quynh PhamInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. q.pham@mail.utoronto.ca.ORCID http://orcid.org/0000-0002-0540-4181

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRandomized controlled trials (RCTs) have long been considered the primary research study design capable of eliciting causal relationships between health interventions and consequent outcomes. However, with a prolonged duration from recruitment to publication, high-cost trial implementation, and a rigid trial protocol, RCTs are perceived as an impractical evaluation methodology for most mHealth apps.

objectiveGiven the recent development of alternative evaluation methodologies and tools to automate mHealth research, we sought to determine the breadth of these methods and the extent that they were being used in clinical trials.

methodsWe conducted a review of the ClinicalTrials.gov registry to identify and examine current clinical trials involving mHealth apps and retrieved relevant trials registered between November 2014 and November 2015.

resultsOf the 137 trials identified, 71 were found to meet inclusion criteria. The majority used a randomized controlled trial design (80%, 57/71). Study designs included 36 two-group pretest-posttest control group comparisons (51%, 36/71), 16 posttest-only control group comparisons (23%, 16/71), 7 one-group pretest-posttest designs (10%, 7/71), 2 one-shot case study designs (3%, 2/71), and 2 static-group comparisons (3%, 2/71). A total of 17 trials included a qualitative component to their methodology (24%, 17/71). Complete trial data collection required 20 months on average to complete (mean 21, SD 12). For trials with a total duration of 2 years or more (31%, 22/71), the average time from recruitment to complete data collection (mean 35 months, SD 10) was 2 years longer than the average time required to collect primary data (mean 11, SD 8). Trials had a moderate sample size of 112 participants. Two trials were conducted online (3%, 2/71) and 7 trials collected data continuously (10%, 7/68). Onsite study implementation was heavily favored (97%, 69/71). Trials with four data collection points had a longer study duration than trials with two data collection points: F4,56=3.2, P=.021, η(2)=0.18. Single-blinded trials had a longer data collection period compared to open trials: F2,58=3.8, P=.028, η(2)=0.12. Academic sponsorship was the most common form of trial funding (73%, 52/71). Trials with academic sponsorship had a longer study duration compared to industry sponsorship: F2,61=3.7, P=.030, η(2)=0.11. Combined, data collection frequency, study masking, sample size, and study sponsorship accounted for 32.6% of the variance in study duration: F4,55=6.6, P<.01, adjusted r(2)=.33. Only 7 trials had been completed at the time this retrospective review was conducted (10%, 7/71).

conclusionsmHealth evaluation methodology has not deviated from common methods, despite the need for more relevant and timely evaluations. There is a need for clinical evaluation to keep pace with the level of innovation of mHealth if it is to have meaningful impact in informing payers, providers, policy makers, and patients.

Indexed as

clinical trialsmedical informaticsmobile applicationsmobile healthresearch designsmartphones

Identifiers

PMID27613084
PMCPMC5035379

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.