ArticlePloS one2014
Developing and validating a tablet version of an illness explanatory model interview for a public health survey in Pune, India.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: Randomized Controlled Crossover Health Care Information Technology Evaluation.JMIR mHealth and uHealth · 2019Trial
- Development of a Novel Tablet-based Approach to Reduce HIV Stigma among Healthcare Staff in India.Perspectives in health information managemen · 2017Trial
- Paper Versus Digital Data Collection Methods for Road Safety Observations: Comparative Efficiency Analysis of Cost, Timeliness, Reliability, and Results.Journal of medical Internet research · 2020Article
- Current Status and Future Directions of mHealth Interventions for Health System Strengthening in India: Systematic Review.JMIR mHealth and uHealth · 2018Review
- Do surveys with paper and electronic devices differ in quality and cost? Experience from the Rufiji Health and demographic surveillance system in Tanzania.Global health action · 2017Article
- Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi.Global health action · 2017Article
- Integrating community-based verbal autopsy into civil registration and vital statistics (CRVS): system-level considerations.Global health action · 2017Article
- Compliance of Specific Provisions of Tobacco Control Law around Educational Institutions in Delhi, India.International journal of preventive medicine · 2017Article
- Feasibility of the collection of patient-reported outcomes in an ambulatory neurology clinic.Neurology · 2016Article
- Managing research and surveillance projects in real-time with a novel open-source eManagement tool designed for under-resourced countries.Journal of the American Medical Informatics Association : JAMIA · 2016Article
- Development of the TabacoQuest app for computerization of data collection on smoking in psychiatric nursing.Revista latino-americana de enfermagem · 2016Article
- Measuring population health: costs of alternative survey approaches in the Nouna Health and Demographic Surveillance System in rural Burkina Faso.Global health action · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile electronic devices are replacing paper-based instruments and questionnaires for epidemiological and public health research. The elimination of a data-entry step after an interview is a notable advantage over paper, saving investigator time, decreasing the time lags in managing and analyzing data, and potentially improving the data quality by removing the error-prone data-entry step. Research has not yet provided adequate evidence, however, to substantiate the claim of fewer errors for computerized interviews. METHODOLOGY: We developed an Android-based illness explanatory interview for influenza vaccine acceptance and tested the instrument in a field study in Pune, India, for feasibility and acceptability. Error rates for tablet and paper were compared with reference to the voice recording of the interview as gold standard to assess discrepancies. We also examined the preference of interviewers for the classical paper-based or the electronic version of the interview and compared the costs of research with both data collection devices.
resultsIn 95 interviews with household respondents, total error rates with paper and tablet devices were nearly the same (2.01% and 1.99% respectively). Most interviewers indicated no preference for a particular device; but those with a preference opted for tablets. The initial investment in tablet-based interviews was higher compared to paper, while the recurring costs per interview were lower with the use of tablets.
conclusionAn Android-based tablet version of a complex interview was developed and successfully validated. Advantages were not compromised by increased errors, and field research assistants with a preference preferred the Android device. Use of tablets may be more costly than paper for small samples and less costly for large studies.
Indexed as
Identifiers
What OpenQuestion holds
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.