Evidence map›Paper›PMID 30664491›Full record

ArticleJMIR research protocols2019

Accelerating Research With Technology: Rapid Recruitment for a Large-Scale Web-Based Sleep Study.

Sean Deering, Madeline M Grade, Jaspreet K Uppal, Luca Foschini, Jessie L Juusola, Adam M Amdur, Carl J Stepnowsky

Abstract read
In one paragraph

Article in JMIR research protocols, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Precision recruitment for high-risk participants in a COVID-19 cohort study.Contemporary clinical trials communications · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

7 authors.

Sean DeeringVeterans Affairs San Diego Healthcare System, Health Services Research & Development Unit, La Jolla, CA, United States.ORCID http://orcid.org/0000-0001-9369-1282
Madeline M GradeEvidation Health, San Mateo, CA, United States.ORCID http://orcid.org/0000-0003-4888-360X
Jaspreet K UppalEvidation Health, San Mateo, CA, United States.ORCID http://orcid.org/0000-0002-9611-0671
Luca FoschiniEvidation Health, San Mateo, CA, United States.ORCID http://orcid.org/0000-0003-1409-3570
Jessie L JuusolaEvidation Health, San Mateo, CA, United States.ORCID http://orcid.org/0000-0002-2885-2008
Adam M AmdurAmerican Sleep Apnea Association, Washington, DC, United States.ORCID http://orcid.org/0000-0002-8095-4458
Carl J StepnowskyVeterans Affairs San Diego Healthcare System, Health Services Research & Development Unit, La Jolla, CA, United States.ORCID http://orcid.org/0000-0002-4633-3228

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParticipant recruitment can be a significant bottleneck in carrying out research studies. Connected health and mobile health platforms allow for the development of Web-based studies that can offer improvement in this domain. Sleep is of vital importance to the mental and physical health of all individuals, yet is understudied on a large scale or beyond the focus of sleep disorders. For this reason and owing to the availability of digital sleep tracking tools, sleep is well suited to being studied in a Web-based environment.

objectiveThe aim of this study was to investigate a method for speeding up the recruitment process and maximizing participant engagement using a novel approach, the Achievement Studies platform (Evidation Health, Inc, San Mateo, CA, USA), while carrying out a study that examined the relationship between participant sleep and daytime function.

methodsParticipants could access the Web-based study platform at any time from any computer or Web-enabled device to complete study procedures and track study progress. Achievement community members were invited to the study and assessed for eligibility. Eligible participants completed an electronic informed consent process to enroll in the study and were subsequently invited to complete an electronic baseline questionnaire. Then, they were asked to connect a wearable device account through their study dashboard, which shared their device data with the research team. The data were used to provide objective sleep and activity metrics for the study. Participants who completed the baseline questionnaires were subsequently sent a daily single-item Sleepiness Checker activity for 7 consecutive days at baseline and every 3 months thereafter for 1 year.

resultsOverall, 1156 participants enrolled in the study within a 5-day recruitment window. In the 1st hour, the enrollment rate was 6.6 participants per minute (394 per hour). In the first 24 hours, the enrollment rate was 0.8 participants per minute (47 participants per hour). Overall, 1132 participants completed the baseline questionnaires (1132/1156, 97.9%) and 1047 participants completed the initial Sleepiness Checker activity (1047/1156, 90.6%). Furthermore, 1000 participants provided activity-specific wearable data (1000/1156, 86.5%) and 982 provided sleep-specific wearable data (982/1156, 84.9%).

conclusionsThe Achievement Studies platform allowed for rapid recruitment and high study engagement (survey completion and device data sharing). This approach to carrying out research appears promising. However, conducting research in this way requires that participants have internet access and own and use a wearable device. As such, our sample may not be representative of the general population.

Indexed as

connected healthengagementhealthmHealthmobile healthmobile phonerecruitmentsleepsleep qualitywearables

Identifiers

PMID30664491
PMCPMC6360390

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.