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      Smartphone Versus Pen-and-Paper Data Collection of Infant Feeding Practices in Rural China

      research-article
      , MSc 1 , , B.Sci 1 , , MSc 2 , , MSc 1 , , MD, PhD 2 , , MPH, MD, PhD, DSc 3 , , MSc 1 , , , B.Sci 1 , , MPH, MD 4
      (Reviewer)
      Journal of Medical Internet Research
      Gunther Eysenbach
      Data collection, health survey, questionnaires, infant feeding, smartphone

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          Abstract

          Background

          Maternal, Newborn, and Child Health (MNCH) household survey data are collected mainly with pen-and-paper. Smartphone data collection may have advantages over pen-and-paper, but little evidence exists on how they compare.

          Objective

          To compare smartphone data collection versus the use of pen-and-paper for infant feeding practices of the MNCH household survey. We compared the two data collection methods for differences in data quality (data recording, data entry, open-ended answers, and interrater reliability), time consumption, costs, interviewers’ perceptions, and problems encountered.

          Methods

          We recruited mothers of infants aged 0 to 23 months in four village clinics in Zhaozhou Township, Zhao County, Hebei Province, China. We randomly assigned mothers to a smartphone or a pen-and-paper questionnaire group. A pair of interviewers simultaneously questioned mothers on infant feeding practices, each using the same method (either smartphone or pen-and-paper).

          Results

          We enrolled 120 mothers, and all completed the study. Data recording errors were prevented in the smartphone questionnaire. In the 120 pen-and-paper questionnaires (60 mothers), we found 192 data recording errors in 55 questionnaires. There was no significant difference in recording variation between the groups for the questionnaire pairs ( P = .32) or variables ( P = .45). The smartphone questionnaires were automatically uploaded and no data entry errors occurred. We found that even after double data entry of the pen-and-paper questionnaires, 65.0% (78/120) of the questionnaires did not match and needed to be checked. The mean duration of an interview was 10.22 (SD 2.17) minutes for the smartphone method and 10.83 (SD 2.94) minutes for the pen-and-paper method, which was not significantly different between the methods ( P = .19). The mean costs per questionnaire were higher for the smartphone questionnaire (¥143, equal to US $23 at the exchange rate on April 24, 2012) than for the pen-and-paper questionnaire (¥83, equal to US $13). The smartphone method was acceptable to interviewers, and after a pilot test we encountered only minor problems (eg, the system halted for a few seconds or it shut off), which did not result in data loss.

          Conclusions

          This is the first study showing that smartphones can be successfully used for household data collection on infant feeding in rural China. Using smartphones for data collection, compared with pen-and-paper, eliminated data recording and entry errors, had similar interrater reliability, and took an equal amount of time per interview. While the costs for the smartphone method were higher than the pen-and-paper method in our small-scale survey, the costs for both methods would be similar for a large-scale survey. Smartphone data collection should be further evaluated for other surveys and on a larger scale to deliver maximum benefits in China and elsewhere.

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          Most cited references25

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          Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: a meta-analytic review.

          Patient-reported outcomes (PROs; self-report assessments) are increasingly important in evaluating medical care and treatment efficacy. Electronic administration of PROs via computer is becoming widespread. This article reviews the literature addressing whether computer-administered tests are equivalent to their paper-and-pencil forms. Meta-analysis was used to synthesize 65 studies that directly assessed the equivalence of computer versus paper versions of PROs used in clinical trials. A total of 46 unique studies, evaluating 278 scales, provided sufficient detail to allow quantitative analysis. Among 233 direct comparisons, the average mean difference between modes averaged 0.2% of the scale range (e.g., 0.02 points on a 10-point scale), and 93% were within +/-5% of the scale range. Among 207 correlation coefficients between paper and computer instruments (typically intraclass correlation coefficients), the average weighted correlation was 0.90; 94% of correlations were at least 0.75. Because the cross-mode correlation (paper vs. computer) is also a test-retest correlation, with potential variation because of retest, we compared it to the within-mode (paper vs. paper) test-retest correlation. In four comparisons that evaluated both, the average cross-mode paper-to-computer correlation was almost identical to the within-mode correlation for readministration of a paper measure (0.88 vs. 0.91). Extensive evidence indicates that paper- and computer-administered PROs are equivalent.
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            Challenges in using mobile phones for collection of antiretroviral therapy adherence data in a resource-limited setting.

            Frequent antiretroviral therapy adherence monitoring could detect incomplete adherence before viral rebound develops and thus potentially prevent treatment failure. Mobile phone technologies make frequent, brief adherence interviews possible in resource-limited settings; however, feasibility and acceptability are unknown. Interactive voice response (IVR) and short message service (SMS) text messaging were used to collect adherence data from 19 caregivers of HIV-infected children in Uganda. IVR calls or SMS quantifying missed doses were sent in the local language once weekly for 3-4 weeks. Qualitative interviews were conducted to assess participant impressions of the technologies. Participant interest and participation rates were high; however, weekly completion rates for adherence queries were low (0-33%), most commonly due to misunderstanding of personal identification numbers. Despite near ubiquity of mobile phone technology in resource-limited settings, individual level collection of healthcare data presents challenges. Further research is needed for effective training and incentive methods.
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              A review of randomized controlled trials comparing the effectiveness of hand held computers with paper methods for data collection

              Background Handheld computers are increasingly favoured over paper and pencil methods to capture data in clinical research. Methods This study systematically identified and reviewed randomized controlled trials (RCTs) that compared the two methods for self-recording and reporting data, and where at least one of the following outcomes was assessed: data accuracy; timeliness of data capture; and adherence to protocols for data collection. Results A comprehensive key word search of NLM Gateway's database yielded 9 studies fitting the criteria for inclusion. Data extraction was performed and checked by two of the authors. None of the studies included all outcomes. The results overall, favor handheld computers over paper and pencil for data collection among study participants but the data are not uniform for the different outcomes. Handheld computers appear superior in timeliness of receipt and data handling (four of four studies) and are preferred by most subjects (three of four studies). On the other hand, only one of the trials adequately compared adherence to instructions for recording and submission of data (handheld computers were superior), and comparisons of accuracy were inconsistent between five studies. Conclusion Handhelds are an effective alternative to paper and pencil modes of data collection; they are faster and were preferred by most users.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                Gunther Eysenbach (JMIR Publications Inc., Toronto, Canada )
                1439-4456
                1438-8871
                Sep-Oct 2012
                18 September 2012
                : 14
                : 5
                : e119
                Affiliations
                [1] 1Department of Integrated Early Childhood Development Capital Institute of Pediatrics BeijingChina
                [2] 2Global eHealth Unit Department of Primary Care and Public Health Imperial College London LondonUnited Kingdom
                [3] 3Centre for Population Health Sciences and Global Health Academy University of Edinburgh Medical School EdinburghUnited Kingdom
                [4] 4Section of Health and Nutrition, Water, Environment and Sanitation UNICEF China BeijingChina
                Article
                v14i5e119
                10.2196/jmir.2183
                3510690
                22989894
                3f6c410b-d3b5-4abe-a8ec-bfa90e5dd2fd
                ©Shuyi Zhang, Qiong Wu, Michelle HMMT van Velthoven, Li Chen, Josip Car, Igor Rudan, Yanfeng Zhang, Ye Li, Robert W Scherpbier. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.09.2012.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 23 May 2012
                : 24 July 2012
                : 07 August 2012
                : 06 August 2012
                Categories
                Original Paper

                Medicine
                data collection,health survey,questionnaires,infant feeding,smartphone
                Medicine
                data collection, health survey, questionnaires, infant feeding, smartphone

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