Literature DB >> 29037297

Innovative approach to the design and evaluation of treatment adherence interventions for drug-resistant TB.

K Alegria-Flores1, B J Weiner2, C A Wiesen3, K L H Lich1, A Van Rie4, J E Paul1, M A Tovar5.   

Abstract

BACKGROUND: Drug-resistant tuberculosis (DR-TB) treatment is expensive, lengthy, and can cause severe side effects. Patients face socio-economic, psychosocial, and systemic barriers to adherence; poor adherence results in poor treatment outcomes.
OBJECTIVE: To estimate the effects of the components of the information-motivation-behavioral skills model on DR-TB treatment adherence.
DESIGN: We recruited 326 adults receiving DR-TB treatment and 86 of their health care service providers from 40 health centers in Lima, Peru. The main outcome was adherence (i.e., the proportion of prescribed doses taken by a patient). Exposure measures were adherence information, motivation, and behavioral skills; loss to follow-up during previous TB treatment(s); providers' work engagement; and patient-perceived support from his/her social network.
RESULTS: Structural equation modeling revealed that adherence information and motivation had positive effects on adherence, but only if mediated through behavioral skills (β = 0.02, P < 0.01 and β = 0.07, P < 0.001, respectively). Behavioral skills had a direct positive effect on adherence (β = 0.27, P < 0.001). Loss to follow-up during previous treatment had a direct negative effect, providers' work engagement had a direct positive effect, and perceived support had indirect positive effects on adherence. The model's overall R2 was 0.76.
CONCLUSION: The components of the information-motivation-behavioral skills model were associated with adherence and could be used to design, monitor, and evaluate interventions targeting adherence to DR-TB treatment.

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Year:  2017        PMID: 29037297     DOI: 10.5588/ijtld.17.0296

Source DB:  PubMed          Journal:  Int J Tuberc Lung Dis        ISSN: 1027-3719            Impact factor:   2.373


  2 in total

Review 1.  All nonadherence is equal but is some more equal than others? Tuberculosis in the digital era.

Authors:  Helen R Stagg; Mary Flook; Antal Martinecz; Karina Kielmann; Pia Abel Zur Wiesch; Aaron S Karat; Marc C I Lipman; Derek J Sloan; Elizabeth F Walker; Katherine L Fielding
Journal:  ERJ Open Res       Date:  2020-11-02

2.  Temporal Factors and Missed Doses of Tuberculosis Treatment. A Causal Associations Approach to Analyses of Digital Adherence Data.

Authors:  Helen R Stagg; James J Lewis; Xiaoqiu Liu; Shitong Huan; Shiwen Jiang; Daniel P Chin; Katherine L Fielding
Journal:  Ann Am Thorac Soc       Date:  2020-04
  2 in total

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