Evidence map›Paper›PMID 37079373›Full record

ArticleJMIR formative research2023

Effect of the Data Collection Method on Mobile Phone Survey Participation in Bangladesh and Tanzania: Secondary Analyses of a Randomized Crossover Trial.

George Pariyo, Ankita Meghani, Dustin Gibson, Joseph Ali, Alain Labrique, Iqbal Ansary Khan, Gulam Muhammed Al Kibria, Honorati Masanja, Adnan Ali Hyder, Saifuddin Ahmed

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Measuring childhood mortality through mobile phone interviews in Mozambique.Tropical medicine & international health : TM & IH · 2025
    Article
  5. Article
  6. 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

10 authors at 4 institutions in 4 countries.

George PariyoMakerere University School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda.ORCID https://orcid.org/0000-0002-4411-2309
Ankita MeghaniJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-4952-6017
Dustin GibsonJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-9073-3376
Joseph AliJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-4767-2512
Alain LabriqueJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0003-2502-7819
Iqbal Ansary KhanInstitute of Epidemiology, Disease Control and Research, Dhaka, Bangladesh.ORCID https://orcid.org/0000-0002-1262-9987
Gulam Muhammed Al KibriaJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-7037-6658
Honorati MasanjaIfakara Health Institute, Dar es Salam, United Republic of Tanzania.ORCID https://orcid.org/0000-0002-3860-7348
Adnan Ali HyderJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-7292-577X
Saifuddin AhmedJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-9884-4580
Johns Hopkins University · USIfakara Health Institute · TZInstitute of Epidemiology, Disease Control and Research · BDMakerere University · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile phone surveys provide a novel opportunity to collect population-based estimates of public health risk factors; however, nonresponse and low participation challenge the goal of collecting unbiased survey estimates.

objectiveThis study compares the performance of computer-assisted telephone interview (CATI) and interactive voice response (IVR) survey modalities for noncommunicable disease risk factors in Bangladesh and Tanzania.

methodsThis study used secondary data from a randomized crossover trial. Between June 2017 and August 2017, study participants were identified using the random digit dialing method. Mobile phone numbers were randomly allocated to either a CATI or IVR survey. The analysis examined survey completion, contact, response, refusal, and cooperation rates of those who received the CATI and IVR surveys. Differences in survey outcomes between modes were assessed using multilevel, multivariable logistic regression models to adjust for confounding covariates. These analyses were adjusted for clustering effects by mobile network providers.

resultsFor the CATI surveys, 7044 and 4399 phone numbers were contacted in Bangladesh and Tanzania, respectively, and 60,863 and 51,685 phone numbers, respectively, were contacted for the IVR survey. The total numbers of completed interviews in Bangladesh were 949 for CATI and 1026 for IVR and in Tanzania were 447 for CATI and 801 for IVR. Response rates for CATI were 5.4% (377/7044) in Bangladesh and 8.6% (376/4391) in Tanzania; response rates for IVR were 0.8% (498/60,377) in Bangladesh and 1.1% (586/51,483) in Tanzania. The distribution of the survey population was significantly different from the census distribution. In both countries, IVR respondents were younger, were predominantly male, and had higher education levels than CATI respondents. IVR respondents had a lower response rate than CATI respondents in Bangladesh (adjusted odds ratio [AOR]=0.73, 95% CI 0.54-0.99) and Tanzania (AOR=0.32, 95% CI 0.16-0.60). The cooperation rate was also lower with IVR than with CATI in Bangladesh (AOR=0.12, 95% CI 0.07-0.20) and Tanzania (AOR=0.28, 95% CI 0.14-0.56). Both in Bangladesh (AOR=0.33, 95% CI 0.25-0.43) and Tanzania (AOR=0.09, 95% CI 0.06-0.14), there were fewer completed interviews with IVR than with CATI; however, there were more partial interviews with IVR than with CATI in both countries.

conclusionsThere were lower completion, response, and cooperation rates with IVR than with CATI in both countries. This finding suggests that, to increase representativeness in certain settings, a selective approach may be needed to design and deploy mobile phone surveys to increase population representativeness. Overall, CATI surveys may offer a promising approach for surveying potentially under-represented groups like women, rural residents, and participants with lower levels of education in some countries.

Indexed as

cooperationcooperation ratecountriesfemaleinteractive surveyinteractive voice response surveyinterviewmobile phone surveynon-communicable diseasenon-communicable disease surveillancephonepublic healthresponseresponse rateriskruralschoolsurveillancesurveyvoicewomen

Identifiers

PMID37079373
PMCPMC10160933
OpenAlexW4366463113

What OpenQuestion holds

Textmetadata
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.