Evidence map›Paper›PMID 25048377›Full record

ArticleThe American journal of tropical medicine and hygiene2014

PGMS: a case study of collecting PDA-based geo-tagged malaria-related survey data.

Ying Zhou, Neil F Lobo, Adam Wolkon, John E Gimnig, Alpha Malishee, Jennifer Stevenson, Sulistyawati, Frank H Collins, Greg Madey

Open access · bronzeAbstract read
In one paragraph

Article in The American journal of tropical medicine and hygiene, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.6field-weighted citation impact, top 12% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

9 authors at 4 institutions in 3 countries.

Ying Zhou
Neil F Lobo
Adam Wolkon
John E Gimnig
Alpha Malishee
Jennifer Stevenson
Sulistyawati
Frank H Collins
Greg Madey
University of Notre Dame · USIfakara Health Institute · TZJohns Hopkins University · USUniversitas Ahmad Dahlan · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using mobile devices, such as personal digital assistants (PDAs), smartphones, tablet computers, etc., to electronically collect malaria-related field data is the way for the field questionnaires in the future. This case study seeks to design a generic survey framework PDA-based geo-tagged malaria-related data collection tool (PGMS) that can be used not only for large-scale community-level geo-tagged electronic malaria-related surveys, but also for a wide variety of electronic data collections of other infectious diseases. The framework includes two parts: the database designed for subsequent cross-sectional data analysis and the customized programs for the six study sites (two in Kenya, three in Indonesia, and one in Tanzania). In addition to the framework development, we also present our methods used when configuring and deploying the PDAs to 1) reduce data entry errors, 2) conserve battery power, 3) field install the programs onto dozens of handheld devices, 4) translate electronic questionnaires into local languages, 5) prevent data loss, and 6) transfer data from PDAs to computers for future analysis and storage. Since 2008, PGMS has successfully accomplished quite a few surveys that recorded 10,871 compounds and households, 52,126 persons, and 17,100 bed nets from the six sites. These numbers are still growing.

Indexed as

Computers, HandheldCross-Sectional StudiesDatabases, FactualData CollectionFamily CharacteristicsGeographyIndonesiaKenyaMalariaSoftwareSurveys and QuestionnairesTanzania

Identifiers

PMID25048377
PMCPMC4155550
OpenAlexW2010911426

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.