Evidence map›Paper›PMID 25233212›Full record

ArticlePloS one2014

Developing and validating a tablet version of an illness explanatory model interview for a public health survey in Pune, India.

Joseph G Giduthuri, Nicolas Maire, Saju Joseph, Abhay Kudale, Christian Schaetti, Neisha Sundaram, Christian Schindler, Mitchell G Weiss

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
7.7field-weighted citation impact, top 3% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

8 authors at 3 institutions in 2 countries.

Joseph G GiduthuriDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Nicolas MaireDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Saju JosephThe Maharashtra Association of Anthropological Sciences, Centre for Health Research and Development, Pune, India.
Abhay KudaleThe Maharashtra Association of Anthropological Sciences, Centre for Health Research and Development, Pune, India.
Christian SchaettiDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Neisha SundaramDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Christian SchindlerDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Mitchell G WeissDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Swiss Tropical and Public Health Institute · CHMaharashtra Association of Anthropological Sciences · INUniversity of Basel · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Research DesignSurveys and QuestionnairesComputers, HandheldHealth Care SurveysHumansIndiaInfluenza VaccinesPatient CompliancePublic HealthInfluenza Vaccines

Identifiers

PMID25233212
PMCPMC4169412
OpenAlexW2153086948

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.