Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Oct 14;23(1):2006.
doi: 10.1186/s12889-023-16905-z.

Risk factors for poor engagement with a smart pillbox adherence intervention among persons on tuberculosis treatment in Ethiopia

Affiliations

Risk factors for poor engagement with a smart pillbox adherence intervention among persons on tuberculosis treatment in Ethiopia

Amare Worku Tadesse et al. BMC Public Health. .

Abstract

Background: Non-adherence to tuberculosis treatment increases the risk of poor treatment outcomes. Digital adherence technologies (DATs), including the smart pillbox (EvriMED), aim to improve treatment adherence and are being widely evaluated. As part of the Adherence Support Coalition to End TB (ASCENT) project we analysed data from a cluster-randomised trial of DATs and differentiated care in Ethiopia to examine individual-factors for poor engagement with the smart pillbox.

Methods: Data were obtained from a cohort of trial participants with drug-sensitive tuberculosis (DS-TB) whose treatment started between 1 December 2020 and 1 May 2022, and who were using the smart pillbox. Poor engagement with the pillbox was defined as (i) > 20% days with no digital confirmation and (ii) the count of days with no digital confirmation, and calculated over a two evaluation periods (56-days and 168-days). Logistic random effects regression was used to model > 20% days with no digital confirmation and negative binomial random effects regression to model counts of days with no digital confirmation, both accounting for clustering of individuals at the facility-level.

Results: Among 1262 participants, 10.8% (133/1262) over 56-days and 15.8% (200/1262) over 168-days had > 20% days with no digital confirmation. The odds of poor engagement was less among participants in the higher stratum of socio-economic position (SEP) over 56-days. Overall, 4,689/67,315 expected doses over 56-days and 18,042/199,133 expected doses over 168-days were not digitally confirmed. Compared to participants in the poorest SEP stratum, participants in the wealthiest stratum had lower rates of days not digitally confirmed over 168-days (adjusted rate ratio [RRa]:0.79; 95% confidence interval [CI]: 0.65, 0.96). In both evaluation periods (56-days and 168-days), HIV-positive status (RRa:1.29; 95%CI: 1.02, 1.63 and RRa:1.28; 95%CI: 1.07, 1.53), single/living independent (RRa:1.31; 95%CI: 1.03, 1.67 and RRa:1.38; 95%CI: 1.16, 1.64) and separated/widowed (RRa:1.40; 95%CI: 1.04, 1.90 and RRa:1.26; 95%CI: 1.00, 1.58) had higher rates of counts of days with no digital confirmation.

Conclusion: Poorest SEP stratum, HIV-positive status, single/living independent and separated/ widowed were associated with poor engagement with smart pillbox among people with DS-TB in Ethiopia. Differentiated care for these sub-groups may reduce risk of non-adherence to TB treatment.

Keywords: Digital adherence technologies; Drug-sensitive tuberculosis; Ethiopia; Poor engagement; Smart pillbox.

PubMed Disclaimer

Conflict of interest statement

All authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flow diagram for study participants

References

    1. WHO, World Health Organisation. Adherence to long-term therapies: evidence for action. Geneva: World Health Organization; 2003.
    1. Ali AOA, Prins MH. Patient characteristics associated with non-adherence to tuberculosis treatment: a systematic review. J Tuberc Res. 2020;08(02):73–92. doi: 10.4236/jtr.2020.82008. - DOI
    1. Dogah E, et al. Factors influencing adherence to tuberculosis treatment in the Ketu North District of the Volta Region. Ghana Tuberc Res Treat. 2021;2021:6685039. - PMC - PubMed
    1. Fang XH, et al. Prevalence of and factors influencing anti-tuberculosis treatment non-adherence among patients with pulmonary tuberculosis: a cross-sectional study in Anhui Province. Eastern China Med Sci Monit. 2019;25:1928–1935. doi: 10.12659/MSM.913510. - DOI - PMC - PubMed
    1. Gashu KD, Gelaye KA, Tilahun B. Adherence to TB treatment remains low during continuation phase among adult patients in Northwest Ethiopia. BMC Infect Dis. 2021;21(1):725. doi: 10.1186/s12879-021-06428-6. - DOI - PMC - PubMed

Publication types

Substances