Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review.
PMID: 37966871 ·
E, m, i, l, y, , G, r, a, y, e, k, ;, , T, a, m, a, r, , K, r, i, s, h, n, a, m, u, r, t, i, ;, , L, y, d, i, a, , H, u, ;, , O, l, i, v, i, a, , B, a, b, i, c, h, ;, , K, a, t, h, e, r, i, n, e, , W, a, r, r, e, n, ;, , B, a, r, u, c, h, , F, i, s, c, h, h, o, f, f
Реклама
Аннотация
The rapid growth of digital health apps has necessitated new regulatory approaches to ensure compliance with safety and effectiveness standards. Nonadherence and heterogeneous user engagement with digital health apps can lead to trial estimates that overestimate or underestimate an app's effectiveness. However, there are no current standards for how researchers should measure adherence or address the risk of bias imposed by nonadherence through efficacy analyses. This systematic review aims to a
Реклама
Официальный источник
Открыть в PubMed →Данные получены из PubMed / NCBI. Полный текст и наиболее актуальную информацию всегда смотрите в официальной записи.