Strengthening polio vaccine demand in Ghana: Understanding the factors influencing uptake of the vaccine and the effectiveness of different message frames

Abstract

Background Ghana has experienced recent polio outbreaks. Behavioral insights can be used to understand behavior and create demand for the polio vaccine. Methods This cross-sectional study is based on an interactive mobile phone survey that explored factors influencing the uptake of the polio vaccine among Ghanaian mothers with children younger than five years old. The survey also explores the mothers’ intention to vaccinate their children in the future as well as an experiment with short polio vaccine voice message nudges to identify the most effective message frames in encouraging vaccination. The study sample was drawn from volunteers from a mobile service platform. Linear probability model regressions with Ordinary Least Squares (OLS) estimates were used to analyze the data. Results In total, data from 708 caregivers was assessed. Out of the sample, 35% (n = 250) had not vaccinated their children against polio, around 8% (n = 53) of respondents stated they did not plan to do so, while 28% expressed intent to do so during the next polio vaccination campaign. Higher vaccination of children against polio, i.e. better uptake of the polio vaccine, appeared to be associated with children’s caregivers knowing that polio causes paralysis (with a coefficient of 0.13 (95% CI: 0.02, 0.24), i.e. 13% more likely than not to have their child vaccinated). Higher vaccine uptake also appeared to be associated with the perception that the polio vaccine is safe (with a coefficient of 0.11 (95% CI: 0.01, 0.22), i.e. 11% more likely than not to have their child vaccinated). Another factor in increasing vaccine uptake is whether caregivers receive support from healthcare workers with a coefficient of 0.11 (95% CI: 0.02, 0.20), i.e. 11% more likely than not to have their child vaccinated. Crucially, difficulty accessing the polio vaccine appeared to be associate with a negative change in vaccine uptake (with a coefficient of -0.16 (95% CI: -0.23, -0.08), i.e. 16% less likely to have their child vaccinated). Satisfaction with the information provided by vaccinators was also associated with better vaccine uptake (with a coefficient of 0.12 (95% CI: 0.05, 0.20) i.e. 12% more likely than not to have their child vaccinated); and having seen or heard something negative about the polio vaccine with a coefficient of 0.10 (95% CI: 0.03, 0.17), i.e. 10% more likely than not to have their child vaccinated. The social norms message frame was statistically significant with a coefficient of 0.06 (95% CI: -0.004, 012). Conclusion The findings from this study suggest that most women with children under the age of 5 appear to have vaccinated their children against polio. Many more caregivers express an intention to vaccinate their children, never having done so before. The behavior and the intention to vaccinate are both driven by a number of factors that must be addressed to create demand for the polio vaccine. Targeted message frames appeared to be statistically significant drivers of vaccine uptake. However, more research is required to understand how they impact vaccine behavior and future intention for vaccination.

The effect of mHealth on childhood vaccination in Africa: A systematic review and meta-analysis

“…At the same time, another study in Nigeria showed an enhancement in the overall number of childhood vaccinations due to SMS reminders [ 9 ]. Furthermore, other studies showed an increased number of vaccination visits due to mHealth in Benin [ 15 ], Kenya [ 11 , 16 ], Burkina Faso [ 17 ], Nigeria [ 18 ], Ghana [ 19 ], and Zimbabwe [ 20 ]. The above evidence shows reminders and vaccination information, which can be delivered through mobile phones, can potentially improve childhood vaccination [ 21 ].…”

“…The mHealth-related challenges include poor usability, lack of system integration, poor data security and privacy, poor network access, and poor reliability [ 30 ]. In addition, other challenges such as low literacy, cultural constraints to accept mHealth, and healthcare-seeking behavior are prominent in Africa [ 15 , 19 , 31 , 32 ]. Additional challenges are related to poor standardization, a challenging regulatory framework, and poor overall health system readiness [ 33 ].…”