ArticleBMJ global health2021
Who do phone surveys miss, and how to reduce exclusion: recommendations from phone surveys in nine Indian states.
Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed, 15 citations in OpenAlex.
- Trial
- Understanding retention in longitudinal surveys conducted by mobile phone in lower-resource contexts: A case study from Kenya.PloS one · 2026Article
- Computer-Assisted Mobile Phone Interviews in Low- and Middle-Income Countries Through a Total Survey Error Framework.Public opinion quarterly · 2026Review
- Women's participation in mobile phone surveys in Mozambique: Findings from a qualitative study.Tropical medicine & international health : TM & IH · 2025Article
- Trends in mobile phone ownership, frequency of number changes, and implications for public health service delivery in Uganda, 2010-2020.Scientific reports · 2025Article
- Exploring barriers to IVR surveys and the effectiveness of human follow-up calls: insights from a mixed methods study in Uganda.Oxford open digital health · 2025Article
- Can I Interview Her? Gatekeeping in a Telephone Survey of Female Migrants in India.Survey practice · 2025Article
- Mobile Phone Syndromic Surveillance for Respiratory Conditions in an Emergency (COVID-19) Context in Colombia: Representative Survey Design.Journal of medical Internet research · 2024Article
- Health system utilization and perceived quality among adults in Lao PDR: evidence from a nationally representative phone survey.BMC public health · 2024Article
- Article
- Symptoms of SARS-CoV-2 infection and vaccine status of sixty-seven adult patients affected by inherited metabolic diseases: a phone survey.Orphanet journal of rare diseases · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer-assisted telephone interviews (CATI) through mobile phones are a low-cost, rapid and safe way to collect data. However, decisions for how such mobile phone surveys are designed and implemented, and their data analysed, can have implications for the sample reached, and in turn affect the generalisability of sample estimates. In this practice paper, we propose a framework for extending the use of CATI-mobile phone surveys in India, which can be applied broadly to future surveys conducted using this method. Across the stages of design, implementation and analysis, we outline challenges in ensuring that the data collected through such surveys are representative and provide recommendations for reducing non-coverage and non-response errors, thereby enabling practitioners in India to use CATI-mobile phone surveys to estimate population statistics with lower bias. We support our analysis by drawing on primary data that we collected in five mobile phone surveys across nine Indian states in 2020. Our recommendations can help practitioners in India improve the representativeness of data collected through mobile phone surveys and generate more accurate estimates.
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.