Evidence map›Paper›PMID 28442451›Full record

ArticleJMIR research protocols2017

Using Mobile Phones to Collect Patient Data: Lessons Learned From the SIMPle Study.

Sinead Duane, Meera Tandan, Andrew W Murphy, Akke Vellinga

Registry-linked trialAbstract 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. It is linked to trial NCT01913860 (Supporting the Improvement and Management of Prescribing for Urinary Tract Infections), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT01913860 nacompletednot on this map

Supporting the Improvement and Management of Prescribing for Urinary Tract Infections (SIMPle): Protocol for a Randomised Complex Intervention

TypeinterventionalSponsorNational University of Ireland, Galway, IrelandRan2013 to 2014Enrolled2,577ConditionsUncomplicated Urinary Tract InfectionArmsImproving GP antibiotics prescribing behaviour
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Feasibility of text message sleep assessment in African American and Latino patients with type 2 diabetes.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2021
    Article
  5. Article
  6. Article
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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

4 authors.

Sinead DuaneDiscipline of General Practice, National University of Ireland Galway, Galway, Ireland.ORCID http://orcid.org/0000-0002-9228-7322
Meera TandanDiscipline of General Practice, National University of Ireland Galway, Galway, Ireland.ORCID http://orcid.org/0000-0002-7742-7980
Andrew W MurphyDiscipline of General Practice, National University of Ireland Galway, Galway, Ireland.ORCID http://orcid.org/0000-0001-5549-8246
Akke VellingaDiscipline of General Practice, National University of Ireland Galway, Galway, Ireland.ORCID http://orcid.org/0000-0002-6583-4300

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile phones offer new opportunities to efficiently and interactively collect real-time data from patients with acute illnesses, such as urinary tract infections (UTIs). One of the main benefits of using mobile data collection methods is automated data upload, which can reduce the chance of data loss, an issue when using other data collection methods such as paper-based surveys.

objectiveThe aim was to explore differences in collecting data from patients with UTI using text messaging, a mobile phone app (UTI diary), and an online survey. This paper provides lessons learned from integrating mobile data collection into a randomized controlled trial.

methodsParticipants included UTI patients consulting in general practices that were participating in the Supporting the Improvement and Management of UTI (SIMPle) study. SIMPle was designed to improve prescribing antimicrobial therapies for UTI in the community. Patients were invited to reply to questions regarding their UTI either via a prospective text message survey, a mobile phone app (UTI diary), or a retrospective online survey. Data were collected from 329 patients who opted in to the text message survey, 71 UTI patients through the mobile phone UTI symptom diary app, and 91 online survey participants.

resultsThe age profile of UTI diary app users was younger than that of the text message and online survey users. The largest dropout for both the text message survey respondents and UTI diary app users was after the initial opt-in message; once the participants completed question 1 of the text message survey or day 2 in the UTI diary app, they were more likely to respond to the remaining questions/days.

conclusionsThis feasibility study highlights the potential of using mobile data collection methods to capture patient data. As well as improving the efficiency of data collection, these novel approaches highlight the advantage of collecting data in real time across multiple time points. There was little variation in the number of patients responding between text message survey, UTI diary, and online survey, but more patients participated in the text message survey than the UTI diary app. The choice between designing a text message survey or UTI diary app will depend on the age profile of patients and the type of information the researchers' desire.

trial registrationClinicalTrials.gov NCT01913860; https://clinicaltrials.gov/ct2/show/NCT01913860 (Archived by WebCite at http://www.webcitation.org/6pfgCztgT).

Indexed as

antimicrobial resistancemobile phone appsmobile surveyprescribingprimary carequantitativeurinary tract infection

Identifiers

PMID28442451
PMCPMC5424123

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Registered trials

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.