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Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods

Overview of attention for article published in Cochrane database of systematic reviews, July 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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21 tweeters
2 Facebook pages


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Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods
Published in
Cochrane database of systematic reviews, July 2015
DOI 10.1002/14651858.mr000042.pub2
Pubmed ID

José S Marcano Belisario, Jan Jamsek, Kit Huckvale, John O'Donoghue, Cecily P Morrison, Josip Car


Self-administered survey questionnaires are an important data collection tool in clinical practice, public health research and epidemiology. They are ideal for achieving a wide geographic coverage of the target population, dealing with sensitive topics and are less resource-intensive than other data collection methods. These survey questionnaires can be delivered electronically, which can maximise the scalability and speed of data collection while reducing cost. In recent years, the use of apps running on consumer smart devices (i.e., smartphones and tablets) for this purpose has received considerable attention. However, variation in the mode of delivering a survey questionnaire could affect the quality of the responses collected. To assess the impact that smartphone and tablet apps as a delivery mode have on the quality of survey questionnaire responses compared to any other alternative delivery mode: paper, laptop computer, tablet computer (manufactured before 2007), short message service (SMS) and plastic objects. We searched MEDLINE, EMBASE, PsycINFO, IEEEXplore, Web of Science, CABI: CAB Abstracts, Current Contents Connect, ACM Digital, ERIC, Sociological Abstracts, Health Management Information Consortium, the Campbell Library and CENTRAL. We also searched registers of current and ongoing clinical trials such as ClinicalTrials.gov and the World Health Organization (WHO) International Clinical Trials Registry Platform. We also searched the grey literature in OpenGrey, Mobile Active and ProQuest Dissertation & Theses. Lastly, we searched Google Scholar and the reference lists of included studies and relevant systematic reviews. We performed all searches up to 12 and 13 April 2015. We included parallel randomised controlled trials (RCTs), crossover trials and paired repeated measures studies that compared the electronic delivery of self-administered survey questionnaires via a smartphone or tablet app with any other delivery mode. We included data obtained from participants completing health-related self-administered survey questionnaire, both validated and non-validated. We also included data offered by both healthy volunteers and by those with any clinical diagnosis. We included studies that reported any of the following outcomes: data equivalence; data accuracy; data completeness; response rates; differences in the time taken to complete a survey questionnaire; differences in respondent's adherence to the original sampling protocol; and acceptability to respondents of the delivery mode. We included studies that were published in 2007 or after, as devices that became available during this time are compatible with the mobile operating system (OS) framework that focuses on apps. Two review authors independently extracted data from the included studies using a standardised form created for this systematic review in REDCap. They then compared their forms to reach consensus. Through an initial systematic mapping on the included studies, we identified two settings in which survey completion took place: controlled and uncontrolled. These settings differed in terms of (i) the location where surveys were completed, (ii) the frequency and intensity of sampling protocols, and (iii) the level of control over potential confounders (e.g., type of technology, level of help offered to respondents). We conducted a narrative synthesis of the evidence because a meta-analysis was not appropriate due to high levels of clinical and methodological diversity. We reported our findings for each outcome according to the setting in which the studies were conducted. We included 14 studies (15 records) with a total of 2275 participants; although we included only 2272 participants in the final analyses as there were missing data for three participants from one included study.Regarding data equivalence, in both controlled and uncontrolled settings, the included studies found no significant differences in the mean overall scores between apps and other delivery modes, and that all correlation coefficients exceeded the recommended thresholds for data equivalence. Concerning the time taken to complete a survey questionnaire in a controlled setting, one study found that an app was faster than paper, whereas the other study did not find a significant difference between the two delivery modes. In an uncontrolled setting, one study found that an app was faster than SMS. Data completeness and adherence to sampling protocols were only reported in uncontrolled settings. Regarding the former, an app was found to result in more complete records than paper, and in significantly more data entries than an SMS-based survey questionnaire. Regarding adherence to the sampling protocol, apps may be better than paper but no different from SMS. We identified multiple definitions of acceptability to respondents, with inconclusive results: preference; ease of use; willingness to use a delivery mode; satisfaction; effectiveness of the system informativeness; perceived time taken to complete the survey questionnaire; perceived benefit of a delivery mode; perceived usefulness of a delivery mode; perceived ability to complete a survey questionnaire; maximum length of time that participants would be willing to use a delivery mode; and reactivity to the delivery mode and its successful integration into respondents' daily routine. Finally, regardless of the study setting, none of the included studies reported data accuracy or response rates. Our results, based on a narrative synthesis of the evidence, suggest that apps might not affect data equivalence as long as the intended clinical application of the survey questionnaire, its intended frequency of administration and the setting in which it was validated remain unchanged. There were no data on data accuracy or response rates, and findings on the time taken to complete a self-administered survey questionnaire were contradictory. Furthermore, although apps might improve data completeness, there is not enough evidence to assess their impact on adherence to sampling protocols. None of the included studies assessed how elements of user interaction design, survey questionnaire design and intervention design might influence mode effects. Those conducting research in public health and epidemiology should not assume that mode effects relevant to other delivery modes apply to apps running on consumer smart devices. Those conducting methodological research might wish to explore the issues highlighted by this systematic review.

Twitter Demographics

The data shown below were collected from the profiles of 21 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 425 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
South Africa 1 <1%
Brazil 1 <1%
Indonesia 1 <1%
Canada 1 <1%
United States 1 <1%
Unknown 418 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 77 18%
Student > Ph. D. Student 55 13%
Researcher 54 13%
Student > Bachelor 49 12%
Student > Doctoral Student 31 7%
Other 90 21%
Unknown 69 16%
Readers by discipline Count As %
Medicine and Dentistry 118 28%
Nursing and Health Professions 51 12%
Psychology 41 10%
Social Sciences 28 7%
Computer Science 19 4%
Other 76 18%
Unknown 92 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 May 2020.
All research outputs
of 16,164,081 outputs
Outputs from Cochrane database of systematic reviews
of 11,416 outputs
Outputs of similar age
of 236,781 outputs
Outputs of similar age from Cochrane database of systematic reviews
of 255 outputs
Altmetric has tracked 16,164,081 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,416 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.9. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 236,781 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 255 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.