Factors affecting smartphone adoption for accessing information in medical settings

Tahamtan, Iman; Pajouhanfar, Sara; Sedghi, Shahram; Azad, Mohsen; Roudbari, Masoud

doi:10.1111/hir.12174

Cited by 18 publications

(13 citation statements)

References 20 publications

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“…Geographically, 24% (12/50) of the studies were based in the United States [ 35 - 46 ], 10% (5/50) of the studies were based in the United Kingdom [ 47 - 51 ], and the rest were spread across many countries: Australia [ 52 , 53 ], Australia and the United Kingdom [ 15 ], Austria [ 54 ], Canada [ 55 - 57 ], Germany [ 58 - 60 ], Iran [ 61 ], Iraq [ 62 ], Japan [ 63 ], the Netherlands [ 64 ], the Netherlands, Spain, and the United Kingdom [ 65 ], Nigeria [ 66 ], Norway [ 67 , 68 ], South Korea [ 69 , 70 ], Spain [ 71 - 74 ], Spain Colombia and Bologna [ 75 ], Sri Lanka [ 76 ], Sweden [ 77 , 78 ], Switzerland [ 79 ], Taiwan [ 80 , 81 ], and Turkey [ 82 ].…”

Section: Resultsmentioning

confidence: 99%

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Jacob¹,

Sánchez-Vázquez²,

Ivory³

2020

JMIR Mhealth Uhealth

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Background Although there is a push toward encouraging mobile health (mHealth) adoption to harness its potential, there are many challenges that sometimes go beyond the technology to involve other elements such as social, cultural, and organizational factors. Objective This review aimed to explore which frameworks are used the most, to understand clinicians’ adoption of mHealth as well as to identify potential shortcomings in these frameworks. Highlighting these gaps and the main factors that were not specifically covered in the most frequently used frameworks will assist future researchers to include all relevant key factors. Methods This review was an in-depth subanalysis of a larger systematic review that included research papers published between 2008 and 2018 and focused on the social, organizational, and technical factors impacting clinicians’ adoption of mHealth. The initial systematic review included 171 studies, of which 50 studies used a theoretical framework. These 50 studies are the subject of this qualitative review, reflecting further on the frameworks used and how these can help future researchers design studies that investigate the topic of mHealth adoption more robustly. Results The most commonly used frameworks were different forms of extensions of the Technology Acceptance Model (TAM; 17/50, 34%), the diffusion of innovation theory (DOI; 8/50, 16%), and different forms of extensions of the unified theory of acceptance and use of technology (6/50, 12%). Some studies used a combination of the TAM and DOI frameworks (3/50, 6%), whereas others used the consolidated framework for implementation research (3/50, 6%) and sociotechnical systems (STS) theory (2/50, 4%). The factors cited by more than 20% of the studies were usefulness, output quality, ease of use, technical support, data privacy, self-efficacy, attitude, organizational inner setting, training, leadership engagement, workload, and workflow fit. Most factors could be linked to one framework or another, but there was no single framework that could adequately cover all relevant and specific factors without some expansion. Conclusions Health care technologies are generally more complex than tools that address individual user needs as they usually support patients with comorbidities who are typically treated by multidisciplinary teams who might even work in different health care organizations. This special nature of how the health care sector operates and its highly regulated nature, the usual budget deficits, and the interdependence between health care organizations necessitate some crucial expansions to existing theoretical frameworks usually used when studying adoption. We propose a shift toward theoretical frameworks that take into account implementation challenges that factor in the complexity of the sociotechnical structure of health care organizations and the interplay between the technical, social, and organizational aspects. Our consolidated framework offers recommendations on which factors to include when investigating clinicians’ adoption of mHealth, taking into account all three aspects.

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Section: Resultsmentioning

confidence: 99%

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Jacob¹,

Sánchez-Vázquez²,

Ivory³

2020

JMIR Mhealth Uhealth

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“…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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“…Dissemination of evidence, means of access and the effectiveness of that access are all explored in this quarter's issue of the Health Information and Libraries Journal.…”

Section: In This Issue…mentioning

confidence: 99%

“…The usefulness of a source or mode of access would seem an obvious criteria for determining its use and perceived usefulness was indeed the strongest factor influencing the adoption of smart phone technology in Tahamtan et al . 's mixed method study. Similarly, LaValley et al's study exploring consumer's experiences of their online search for health information found that different types of web sites shape users' online information‐seeking experiences and levels of frustration!…”

Section: In This Issue…mentioning

confidence: 99%

Knowledge Management in healthcare libraries: the current picture

Hopkins

2017

Health Info Libraries J

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Knowledge management has seen something of a resurgence in attention amongst health librarians recently. Of course it has never ceased to exist, but now many library staff are becoming more involved in organisational knowledge management, and positioning themselves as key players in the sphere. No single model of knowledge management is proliferating, but approaches that best fit the organisation's size, structure and culture, and a blending of evidence based practice and knowledge sharing. Whatever it is called and whatever models are used, it's clear that for librarians and information professionals, the importance of putting knowledge and evidence into practice, sharing knowledge well and capturing it effectively, are still what we will continue to do.

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Factors affecting smartphone adoption for accessing information in medical settings

Cited by 18 publications

References 20 publications

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

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

Knowledge Management in healthcare libraries: the current picture

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