Evidence map›Paper›PMID 29101091›Full record

ArticleJMIR research protocols2017

Recruiting Women to a Mobile Health Smoking Cessation Trial: Low- and No-Cost Strategies.

Kristopher J Abbate, Melanie D Hingle, Julie Armin, Peter Giacobbi, Judith S Gordon

Abstract read
In one paragraph

Article in JMIR research protocols, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Kristopher J AbbateCollege of Medicine, University of Arizona, Tucson, AZ, United States.ORCID http://orcid.org/0000-0002-5175-4756
Melanie D HingleDepartment of Nutritional Sciences, College of Agriculture & Life Sciences, University of Arizona, Tucson, AZ, United States.ORCID http://orcid.org/0000-0002-6696-5601
Julie ArminDepartment of Family and Community Medicine, University of Arizona, Tucson, AZ, United States.ORCID http://orcid.org/0000-0001-8787-9190
Peter GiacobbiDepartment of Social and Behavioral Sciences, West Virginia University, Morgantown, WV, United States.ORCID http://orcid.org/0000-0003-1978-7424
Judith S GordonCollege of Nursing, University of Arizona, Tucson, AZ, United States.ORCID http://orcid.org/0000-0002-5911-4219

Funding

Mobile Application for Guided Imagery to Address Smoking, Diet and Physical ActivR21CA174639 · NCI · UNIVERSITY OF ARIZONA · PI GORDON, JUDITH SARAH · 2014 to 2015
$366k
NCI NIH HHS R21 CA174639
6 · The paper itself

Abstract

backgroundSuccessful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers.

objectiveThe objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media.

methodsTo determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users' self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC).

resultsMedia coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study.

conclusionsResearch identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention's broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research.

Indexed as

mHealthmobile applicationssmoking cessationsocial mediawomen

Identifiers

PMID29101091
PMCPMC5695655

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.