NCT03768934

Brief Summary

This study evaluates the effect of four different airtime incentive amounts on short message service (SMS) survey cooperation, response, refusal and contact rates, as compared to control group, in Colombia and Tanzania.

Trial Health

90
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
2,151

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Feb 2019

Shorter than P25 for not_applicable

Geographic Reach
2 countries

2 active sites

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

December 5, 2018

Completed
2 days until next milestone

First Posted

Study publicly available on registry

December 7, 2018

Completed
2 months until next milestone

Study Start

First participant enrolled

February 19, 2019

Completed
2 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 26, 2019

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 26, 2019

Completed
Last Updated

August 11, 2020

Status Verified

August 1, 2020

Enrollment Period

2 months

First QC Date

December 5, 2018

Last Update Submit

August 7, 2020

Conditions

Keywords

mobile phone surveysshort message serviceincentive

Outcome Measures

Primary Outcomes (2)

  • Cooperate Rate #1

    As defined by American Association for Public Opinion Research, cooperation rate is defined as I/(I+P+R) where I is complete interviews, P is partial interviews, and R is refusals and breakoffs.

    Through study completion, an average of one month

  • Response Rate #4

    As defined by American Association for Public Opinion Research, response rate is defined as (I+P)/(I+P+R+eU) where I is complete interviews, P is partial interviews, R is refusals and breakoffs, and eU is the estimated eligible proportion of unknowns.

    Through study completion, an average of one month

Secondary Outcomes (2)

  • Refusal Rate #2

    Through study completion, an average of one month

  • Contact Rate #2

    Through study completion, an average of one month

Study Arms (4)

Control

NO INTERVENTION

No airtime incentive for completing the survey

1X Incentive

EXPERIMENTAL

1X airtime incentive

Other: 1X airtime incentive

2X incentive

EXPERIMENTAL

2X airtime incentive

Other: 2X airtime Incentive

Lottery Incentive

EXPERIMENTAL

Lottery airtime incentive where odds of winning lottery are 1 out of 20

Other: Lottery airtime incentive

Interventions

An incentive given in the form of airtime.

1X Incentive

An incentive given in the form of airtime.

2X incentive

An incentive given in the form of airtime.

Lottery Incentive

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Access to a mobile phone
  • Greater or equal to 18 years of age
  • In Colombia, conversant in the Spanish language. In Tanzania, conversant in the Swahili language.

You may not qualify if:

  • Less than 18 years of age

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

Instituto de Salud Publica Pontificia Universidad Javeriana

Bogotá, D.C., Colombia

Location

Ifakara Health Institute

Dar es Salaam, Tanzania

Location

Related Publications (4)

  • Gibson DG, Pariyo GW, Wosu AC, Greenleaf AR, Ali J, Ahmed S, Labrique AB, Islam K, Masanja H, Rutebemberwa E, Hyder AA. Evaluation of Mechanisms to Improve Performance of Mobile Phone Surveys in Low- and Middle-Income Countries: Research Protocol. JMIR Res Protoc. 2017 May 5;6(5):e81. doi: 10.2196/resprot.7534.

    PMID: 28476729BACKGROUND
  • Gibson DG, Pereira A, Farrenkopf BA, Labrique AB, Pariyo GW, Hyder AA. Mobile Phone Surveys for Collecting Population-Level Estimates in Low- and Middle-Income Countries: A Literature Review. J Med Internet Res. 2017 May 5;19(5):e139. doi: 10.2196/jmir.7428.

    PMID: 28476725BACKGROUND
  • Gibson DG, Farrenkopf BA, Pereira A, Labrique AB, Pariyo GW. The Development of an Interactive Voice Response Survey for Noncommunicable Disease Risk Factor Estimation: Technical Assessment and Cognitive Testing. J Med Internet Res. 2017 May 5;19(5):e112. doi: 10.2196/jmir.7340.

    PMID: 28476724BACKGROUND
  • Hyder AA, Wosu AC, Gibson DG, Labrique AB, Ali J, Pariyo GW. Noncommunicable Disease Risk Factors and Mobile Phones: A Proposed Research Agenda. J Med Internet Res. 2017 May 5;19(5):e133. doi: 10.2196/jmir.7246.

    PMID: 28476722BACKGROUND

MeSH Terms

Conditions

Noncommunicable Diseases

Condition Hierarchy (Ancestors)

Disease AttributesPathologic ProcessesPathological Conditions, Signs and Symptoms

Study Officials

  • Adnan A Hyder, PhD, MBBS

    Johns Hopkins University Bloomberg School of Public Health

    PRINCIPAL INVESTIGATOR
  • George W Pariyo, PhD

    Johns Hopkins University Bloomberg School of Public Health

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
OUTCOMES ASSESSOR
Purpose
OTHER
Intervention Model
PARALLEL
Model Details: Participants will be randomized to one of four airtime amounts: 1) no incentive; 2) 1X incentive; 3) 2X incentive or 4) a lottery incentive, in which one out of every 20 participants will receive the incentive.
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

December 5, 2018

First Posted

December 7, 2018

Study Start

February 19, 2019

Primary Completion

April 26, 2019

Study Completion

April 26, 2019

Last Updated

August 11, 2020

Record last verified: 2020-08

Data Sharing

IPD Sharing
Will not share

Locations