Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.
Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.
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DOI：
10.1093/tbm/ibz180
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发表时间：
2021-02-11
影响因子：
3.6
通讯作者：
Dillingham R
中科院分区：
文献类型：
--
作者：
Canan CE;Flickinger TE;Waselewski M;Tabackman A;Baker L;Eger S;Waldman ALD;Ingersoll K;Dillingham R
使用移动的应用程序进行艾滋病毒自我管理和社会支持的艾滋病毒感染者根据需求和偏好以不同的模式与应用程序进行互动。PositiveLinks（PL）是一个基于智能手机的多功能平台，用于改善艾滋病毒感染者的临床护理和病毒抑制（VS）。功能包括药物提醒，情绪/压力登记，社区板和安全的提供者消息。我们的目标是检查PL用户如何与应用程序交互，并确定使用模式是否与临床结果相关。2016年6月至2017年3月，一所大学Ryan白色诊所的患者（N = 83）入组PL，并接受了长达12个月的随访。一个子集（N = 49）完成了3周后的招生采访，探讨他们的经验和意见的PL。我们使用潜在类别分析，根据应用程序功能的6个月使用情况区分PL成员。我们探讨了与类成员的特征，比较报告的需求和偏好类，并研究类和VS之间的关联。样本的83 PL成员分为四个类。“最大化者”经常使用所有应用程序功能（27%）;“签到用户”倾向于只与日常查询交互（22%）;“中等全功能用户”偶尔使用所有功能（33%）;“按需沟通者”与应用程序交互最少（19%）。6个月后，所有班级的VS都有所改善或保持较高水平。在最大化者（基线和12个月VS：100%，94%）、登记用户（82%，100%）和中等全功能用户（73%，94%）中，VS在12个月时仍然很高，但在按需沟通者中则不高（69%，60%）。这项混合方法研究根据PL使用模式确定了四类，这些模式在特征和临床结局方面截然不同。识别和表征移动医疗用户类别提供了机会，以根据患者的需求和偏好适当地定制干预措施，并提供有针对性的替代支持，以实现临床目标。
People living with HIV who use a mobile app for HIV self-management and social support interact with the app in distinct patterns based on needs and preferences. Clinical outcomes differ among the distinct usage patterns PositiveLinks (PL) is a multi-feature smartphone-based platform to improve engagement-in-care and viral suppression (VS) among clinic patients living with HIV. Features include medication reminders, mood/stress check-ins, a community board, and secure provider messaging. Our goal was to examine how PL users interact with the app and determine whether usage patterns correlate with clinical outcomes. Patients (N = 83) at a university-based Ryan White clinic enrolled in PL from June 2016 to March 2017 and were followed for up to 12 months. A subset (N = 49) completed interviews after 3 weeks of enrollment to explore their experiences with and opinions of PL. We differentiated PL members based on 6-month usage of app features using latent class analysis. We explored characteristics associated with class membership, compared reported needs and preferences by class, and examined association between class and VS. The sample of 83 PL members fell into four classes. “Maximizers” used all app features frequently (27%); “Check-in Users” tended to interact only with daily queries (22%); “Moderate All-Feature Users” used all features occasionally (33%); and “As-Needed Communicators” interacted with the app minimally (19%). VS improved or remained high among all classes after 6 months. VS remained high at 12 months among Maximizers (baseline and 12-month VS: 100%, 94%), Check-in Users (82%, 100%), and Moderate All-Feature Users (73%, 94%) but not among As-Needed Communicators (69%, 60%). This mixed-methods study identified four classes based on PL usage patterns that were distinct in characteristics and clinical outcomes. Identifying and characterizing mHealth user classes offers opportunities to tailor interventions appropriately based on patient needs and preferences as well as to provide targeted alternative support to achieve clinical goals.
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影响因子：
3.5
作者：
Collins KM;Armenta RF;Cuevas-Mota J;Liu L;Strathdee SA;Garfein RS
通讯作者：
Garfein RS
DOI：
10.2174/1874613620130812003
发表时间：
2013
期刊：
The open AIDS journal
影响因子：
--
作者：
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通讯作者：
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影响因子：
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作者：
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影响因子：
4.4
作者：
Althoff, Meghan D.;Theall, Katherine;Kissinger, Patricia
通讯作者：
Kissinger, Patricia
影响因子：
7.4
作者：
Demment, Margaret Mochon;Graham, Meredith Leigh;Olson, Christine Marie
通讯作者：
Olson, Christine Marie