Mobile Health Technology for Improving Symptom Management in Low Income Persons Living with HIV

Schnall, Rebecca; Cho, Hwayoung; Mangone, Alexander; Pichon, Adrienne; Jia, Haomiao

doi:10.1007/s10461-017-2014-0

Cited by 59 publications

(85 citation statements)

References 35 publications

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“…Table 3 illustrates a strong preference for the use of surveys (73.0%, 49/67), independently of the timeline, with a prevalence of custom questionnaires (55.0%, 37/67). Almost all studies assessing system usability (which is a frequent interpretation of acceptability, see Table 2 ), made use of standardized surveys, which reflects the range of reliable tools available to evaluate this concept [ 72 , 74 ].…”

Section: Resultsmentioning

confidence: 99%

Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

Nadal¹,

Sas²,

Doherty³

2020

J Med Internet Res

210

132

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Background Designing technologies that users will be interested in, start using, and keep using has long been a challenge. In the health domain, the question of technology acceptance is even more important, as the possible intrusiveness of technologies could lead to patients refusing to even try them. Developers and researchers must address this question not only in the design and evaluation of new health care technologies but also across the different stages of the user’s journey. Although a range of definitions for these stages exists, many researchers conflate related terms, and the field would benefit from a coherent set of definitions and associated measurement approaches. Objective This review aims to explore how technology acceptance is interpreted and measured in mobile health (mHealth) literature. We seek to compare the treatment of acceptance in mHealth research with existing definitions and models, identify potential gaps, and contribute to the clarification of the process of technology acceptance. Methods We searched the PubMed database for publications indexed under the Medical Subject Headings terms “Patient Acceptance of Health Care” and “Mobile Applications.” We included publications that (1) contained at least one of the terms “acceptability,” “acceptance,” “adoption,” “accept,” or “adopt”; and (2) defined the term. The final corpus included 68 relevant studies. Results Several interpretations are associated with technology acceptance, few consistent with existing definitions. Although the literature has influenced the interpretation of the concept, usage is not homogeneous, and models are not adapted to populations with particular needs. The prevalence of measurement by custom surveys suggests a lack of standardized measurement tools. Conclusions Definitions from the literature were published separately, which may contribute to inconsistent usage. A definition framework would bring coherence to the reporting of results, facilitating the replication and comparison of studies. We propose the Technology Acceptance Lifecycle, consolidating existing definitions, articulating the different stages of technology acceptance, and providing an explicit terminology. Our findings illustrate the need for a common definition and measurement framework and the importance of viewing technology acceptance as a staged process, with adapted measurement methods for each stage.

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Section: Resultsmentioning

confidence: 99%

Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

Nadal¹,

Sas²,

Doherty³

2020

J Med Internet Res

210

132

View full text Add to dashboard Cite

show abstract

“…Smartphone use has definite benefits for everyday life. The smartphone technology not only has been adopted by health professionals to facilitate high-quality care (29,30), but also has shown promising results to improve the self-management of chronic conditions (31)(32)(33) including substance use disorders (SUDs) (34,35) through smartphone applications.…”

Section: Discussionmentioning

confidence: 99%

Internal Consistency and Confirmatory Factor Analysis of Smartphone Addiction Inventory (SPAI)

Imani

Goradel

Mousavi

et al. 2019

Iran J Psychiatry Behav Sci

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Background: Parallel with the rapid growth of smartphone users among the youth, its problematic use has received attention due to adverse outcomes. The psychometric properties of smartphone addiction inventory (SPAI) have been studied among Italian and Taiwanese university students. Objectives: The aim of this study was to investigate the psychometric properties of the SPAI among Iranian university students. Methods: We recruited 402 undergraduate university students in the study from February to March 2017. The SPAI and young's Internet addiction test (IAT) were completed for them. The AMOS statistical software (version 21) was used to test the five-factor model proposed in the original SPAI. The results of the goodness-of-fit index showed an ambiguous solution. For more appropriate trimming of the SPAI factorial structure, an exploratory-confirmatory cross-validation strategy was followed. Results: The SPAI showed excellent internal consistency (Cronbach's α = 0.92). Cronbach's α values of the five subscales varied from 0.53 to 0.84. The results supported a five-factor solution consisting of sleep interference, craving, daily life inference, compulsivity, and time spent (chi-square = 1105.445; P < 0.000; CFI = 0.902; TLI = 0.91; RMSEA = 0.09), which showed good convergent validity with the IAT scores. Moreover, the SPAI showed high factor correlations. Conclusions: Given the increasing trend of smartphone users in the country, the Persian version of the SAPI could be a useful tool for further investigation of smartphone problematic use among Iranian university students.

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“…diabetes, cardiovascular disease) (6). A recent study testing a symptom self-management mHealth app demonstrated that the intervention group receiving self-care strategies had a significant improvement in symptom burden and medication adherence compared with those in the control group (p=0.017) (7). However, medication adherence was a secondary measure in the study and was limited to a self-report measure (8).…”

Section: Background 11 the Importance Of Medication Adherence In Hivmentioning

confidence: 98%

A Multi-step Usability Evaluation of a Self-Management App to Support Medication Adherence in Persons Living with HIV

Beauchemin

Gradilla

Baik

et al. 2019

International Journal of Medical Informatics

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Adherence to antiretroviral therapy is essential to HIV management and sustaining viral suppression. Despite simplified regimens, adherence remains difficult for certain persons living with HIV (PLWH). There is evidence to support the use of mHealth apps for effective selfmanagement in PLWH; however, a medication adherence app with real-time monitoring for this population has not been developed and rigorously evaluated by PLWH. We developed a mHealth app (WiseApp) for HIV self-management to help PLWH self-manage their health. The purpose of this study was to evaluate the usability of the WiseApp. Methods: We conducted a three-step usability evaluation using 1) a traditional think-aloud protocol with end-users, 2) a heuristic evaluation with experts in informatics, and 3) a cognitive walkthrough with end-users. During the cognitive walkthrough, we tested two devices (fitness tracker and medication tracking bottle) that were linked to the WiseApp. Results: The think-aloud protocol informed iterative updates to the app, specifically to make it easier to see different sections of the app. The heuristic evaluation confirmed the necessity of these design changes. The cognitive walkthrough informed additional updates and confirmed that overall, the app and the linked devices were usable for the end-users. Conclusion: The results of the cognitive walkthrough with both experts and end-users informed iterative refinements to the WiseApp and finalization of a mHealth app for PLWH to better selfmanage their health.

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Mobile Health Technology for Improving Symptom Management in Low Income Persons Living with HIV

Cited by 59 publications

References 35 publications

Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

Internal Consistency and Confirmatory Factor Analysis of Smartphone Addiction Inventory (SPAI)

A Multi-step Usability Evaluation of a Self-Management App to Support Medication Adherence in Persons Living with HIV

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