Evidence map›Paper›PMID 40789274›Full record

ArticleJMIRx med2025

Use of Mobile Forms in Low-Resource Areas for Population Health Surveys: Interview and Field Test Study.

Alexander Davis, Aidan Chen, Milton Chen, James Davis

Abstract read
In one paragraph

Article in JMIRx med, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Alexander Davis *University of California, Santa Cruz, CA, 95064, United States.ORCID http://orcid.org/0009-0001-8960-1798
Aidan Chen *University of California, Santa Cruz, CA, 95064, United States.ORCID http://orcid.org/0009-0002-6957-2122
Milton ChenVSee Health, Newton, MA, 02458, United States.ORCID http://orcid.org/0009-0008-4528-1631
James DavisDepartment of Computer Science and Engineering, University of California, 1156 High St, MS:SOE3, Santa Cruz, CA, 95064, United States, 1 (831) 459 1841.ORCID http://orcid.org/0000-0002-1413-2616

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Population health surveys are an important tool to effectively allocate limited resources in low-resource communities. In such an environment, surveys are often done by the local population with pen and paper. Data thus collected are difficult to tabulate and analyze. Objective: The objective of this study was to evaluate the viability and efficiency of mobile forms as an alternative to paper-based surveys in a specific low-resource setting. Methods: We conducted pilot interviews with 53 local surveyors in the Philippines to assess their initial attitudes toward mobile forms. We then built software that can generate mobile forms that are easy to use, capable of working offline, and able to track key metrics such as time to complete questions. Our mobile form was field-tested in 3 locations in the Philippines with 33 surveyors collecting health survey responses from 266 participants. Results: In the pilot phase, we found that 32 out of 53 (60%) of the local surveyors preferred mobile forms over paper. After field-testing, the number of surveyors preferring mobile forms increased to 25 out of 33 (76%) after just using the form a few times. The mobile forms overall demonstrated enhanced efficiency in data collection and usability over paper surveys. Conclusions: Our findings indicate that mobile forms are a viable method to conduct large-scale population health surveys in this low-resource environment.

Indexed as

designelectronic data capturehealth surveyslow-resource settingsmobile formsoffline forms

Identifiers

PMID40789274
PMCPMC12339011

What OpenQuestion holds

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LicenceCC BY
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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.