Evidence map›Paper›PMID 40917701›Full record

ArticleOxford open digital health2025

Exploring barriers to IVR surveys and the effectiveness of human follow-up calls: insights from a mixed methods study in Uganda.

Raymond Tweheyo, Dustin Gibson, Helen Kuo, Joe Ali, Michelle Kaufman, Andres Vecino Ortiz, Elizeus Rutebemberwa

Abstract read
In one paragraph

Article in Oxford open digital health, 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

7 authors.

Raymond TweheyoDepartment of Health Policy Planning and Management, Makerere University College of Health Sciences, School of Public Health, Mulago Hill-Road. P.O.Box, 7072, Kampala, Uganda.ORCID https://orcid.org/0000-0002-8347-9699
Dustin GibsonDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, United States.
Helen KuoDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, United States.
Joe AliDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, United States.
Michelle KaufmanDepartment of Population, Family, and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, United States.
Andres Vecino OrtizDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, United States.
Elizeus RutebemberwaDepartment of Health Policy Planning and Management, Makerere University College of Health Sciences, School of Public Health, Mulago Hill-Road. P.O.Box, 7072, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study explored reasons why respondents neither initiate nor complete an interactive voice response (IVR) survey and whether call-backs by a human can increase subsequent IVR survey participation. Methods: We conducted a mixed methods study. Using random digit dialing (RDD), participants were sent an IVR survey (IVR-RDD) to their mobile phone. Participants from the IVR-RDD who either did not pick the phone or terminated the survey within two questions were contacted for a computer-assisted telephone interview (CATI) survey to assess reasons for non-participation. Following CATI completion, a similar IVR survey was sent (post-CATI IVR). Descriptive statistics and adjusted logistic regression models were conducted to assess differences in survey outcomes between the IVR-RDD and the post-CATI IVR groups. Results: A total of 23 288 IVR-RDD, 9740 CATI and 1000 post CATI IVR calls were made to yield 1.9%, 11.8% and 44.9% response rates, respectively. The most common reasons for non-response or drop-off to the IVR-RDD were being busy, misunderstanding IVR instructions and mistrust of the IVR caller. Compared to the IVR-RDD, the post-CATI IVR increased both contact rate, from [(2.9%; 669/23062) to (7.74%; 1758/22704); adjusted odds ratio (AOR) 2.81, 95% confidence interval (95%CI) 2.56, 3.08, Conclusions: Understanding reasons for survey non-response can allow for interventions to improve survey response. Introducing a human interviewer to those who did not complete the IVR survey improves subsequent IVR survey participation rates.

Indexed as

computer-assisted telephone interviewinteractive voice responsemixed methodsmobile phone surveysnon-responseUganda

Identifiers

PMID40917701
PMCPMC12413760

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.