The informal and hidden curricula of mobile device use in medical education

2013 ◽  
Vol 36 (1) ◽  
pp. 89-91 ◽  
Author(s):  
Rachel Ellaway
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khutsafalo Kadimo ◽  
Athulang Mutshewa ◽  
Masego B. Kebaetse

Purpose Seeking to leverage on benefits of personal mobile device use, medical schools and healthcare facilities are increasingly embracing the use of personal mobile devices for medical education and healthcare delivery through bring-your-own-device (BYOD) policies. However, empirical research findings that could guide the development of BYOD policies are scarce. Available research is dominated by studies that were guided by technocentric approaches, hence seemingly overlooking the complexities of the interactions of actors in mobile device technologies implementation. The purpose of this study was to use the actor–network theory to explore the potential role of a BYOD policy at the University of Botswana’s Faculty of Medicine. Design/methodology/approach Purposive sampling was used to select the participants and interviews, focus group discussions, observations and document analysis were used to collect data. Data were collected from 27 participants and analysed using grounded theory techniques. Emerging themes were continually compared and contrasted with incoming data to create broad themes and sub-themes and to establish relationships or patterns from the data. Findings The results suggest that the potential roles for BYOD policy include promoting appropriate mobile device use, promoting equitable access to mobile devices and content, and integrating mobile devices into medical education, healthcare delivery and other institutional processes. Research limitations/implications BYOD policy could be conceptualized and researched as a “script” that binds actors/actants into a “network” of constituents (with shared interests) such as medical schools and healthcare facilities, mobile devices, internet/WiFi, computers, software, computer systems, medical students, clinical teachers or doctors, nurses, information technology technicians, patients, curriculum, information sources or content, classrooms, computer labs and infections. Practical implications BYOD is a policy that seeks to represent the interests (presents as a solution to their problems) of the key stakeholders such as medical schools, healthcare facilities and mobile device users. BYOD is introduced in medical schools and healthcare facilities to promote equitable access to mobile devices and content, appropriate mobile device use and ensure distribution of liability between the mobile device users and the institution and address the implication of mobile device use in teaching and learning. Originality/value The BYOD policy is a comprehensive solution that transcends other institutional policies and regulations to fully integrate mobile devices in medical education and healthcare delivery.


SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A5-A5
Author(s):  
A Gozar ◽  
A Seixas ◽  
L Hale ◽  
C Branas ◽  
M Barrett ◽  
...  

Abstract Introduction Mobile phone use at night is associated with worse sleep quality. It may also be associated with daytime productivity, possibly via anxiety. Methods Data were obtained from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) study, including N=1007 adults age 22–60. Mobile device use in bed was assessed as the frequency that participants reported: a device in the bedroom, use of the device in bed, texting, emails, internet browsing, calls, and/or social networking in bed, being woken up by the device in a planned (alarm) or unplanned (alert/call/message) way, and checking the phone at night. Each of these were coded as “never,” “rarely,” or “often.” Work productivity was assessed with the Well-Being Assessment of Productivity (WBA-P; scores 0–22 measure productivity loss). Regressions with WBA-P score as outcome and mobile phone variables as predictors were adjusted for age, sex, race/ethnicity, education, and income level. Post-hoc analyses included GAD7 score to examine the mediating role of anxiety. Results The presence of a device was not associated with productivity loss, but frequent use (“often”) was (B=1.26,p=0.01). Increased productivity loss was also seen in those who frequently (“often”) sent texts (B=1.20,p=0.008), browsed internet (B=1.14,p=0.01), emailed (B=2.09,p<0.0005), called (B=1.42,p=0.004), and used social media (B=1.26,p=0.004). Productivity loss was associated with being woken by a call/alert “rarely” (B=1.20,p=0.001) or “often” (B=1.72,p=0.005), but not by alarm. Checking the phone at night “rarely” (B=0.89,p=0.01) and “often” (B=1.73,p<0.0005) were also associated with productivity loss. When anxiety was entered into the model, all relationships except those with frequent emails and calls in bed became nonsignificant. Conclusion Anxiety may be the underlying cause for both increased mobile phone usage and reduced productivity. Reducing anxiety levels may indirectly aid in decreasing nighttime mobile phone use and increasing daytime productivity. Support The SHADES study was funded by R21ES022931 Dr. Grandner is supported by R01MD011600


2019 ◽  
Vol 22 (5) ◽  
pp. 517-531
Author(s):  
Marieke Haan ◽  
Peter Lugtig ◽  
Vera Toepoel
Keyword(s):  

2021 ◽  
Author(s):  
Tarja Heponiemi ◽  
Anu Kaihlanen ◽  
Kia Gluschkoff ◽  
Kaija Saranto ◽  
Sari Nissinen ◽  
...  

BACKGROUND Mobile devices such as tablets and smartphones are increasingly used in health care in many developed countries. Nurses form the largest group in health care that uses electronic health records (EHRs) and their mobile versions. Mobile devices are suggested to promote nurses’ workflow, constant updating of patient information and improve the communication within the health care team. However, little is known about their effect on nurses’ wellbeing. OBJECTIVE The present study aimed to examine the association of mobile device use of the EHR with nurses’ perceived time pressure, stress related to information systems (SRIS) and self-rated stress. Moreover, we examined whether mobile device use modifies the associations of EHR usability (ease of use and technical quality), experience in using EHRs and number of systems in daily use with these wellbeing indicators. METHODS The present study was a cross-sectional population-based survey study among 3,610 Finnish registered nurses gathered in 2020. The associations were examined using analyses of covariance and logistic regression adjusted for age, gender and employment sector (hospital, primary care, social service and other). RESULTS Those who used mobile version of their EHR had higher levels of time pressure ( F(1)= 14.96, p < .001) and SRIS ( F(1)= 6.11, p = .01) compared to those who did not use mobile versions. Moreover, the interactions of mobile device use with experience in using EHRs (F(1) = 14.93, p < .001), ease of use (F(1) = 10.16, p = .001) and technical quality (F(1) = 6.45, p = .01) were significant for SRIS. Inexperience in using EHRs, low levels of ease of use and technical quality were associated with higher SRIS and this association was more pronounced among those who used mobile devices. That is, the highest levels of SRIS were perceived among those who used mobile devices and were inexperienced EHR users, perceived low levels of ease of use or low levels of technical quality of their EHR. CONCLUSIONS According to our results it seems that at the moment mobile device use is not beneficial for the nurses’ wellbeing. In addition, mobile device use seems to intensify the negative effects of usability problems of the EHRs. Especially inexperienced users of EHRs seem be at disadvantage when using mobile devices. Thus, we suggest that EHRs and their mobile versions should be improved in a manner that they would be easier to use and would better support the nurses’ workflow. For example, improvements to problems related to small display, user interface and difficult data entry of mobile versions might be useful. Moreover, more training related to EHRs, their mobile versions and workflow related to these should be provided to nurses.


Author(s):  
Imran Nizamuddin ◽  
Raveena Basra ◽  
Sai Vanam ◽  
Nurbanu Pirani

In a society dominated by the use of technology as a primary method of communication and education, it should come as no surprise that medical professionals rely heavily on its use as well. The new dominance of smartphones over cell phones and pagers in medicine is largely influenced by convenience and efficiency, and over 70% of healthcare professionals have reported using a mobile device in their workplaces. This chapter aims to highlight the transition to mobile devices in the medical realm and the benefits for both clinicians and patients. For clinicians, mobile devices and apps may serve as diagnostic aids, med calculators, and clinical references. They can also be used for medical education purposes and access of electronic medical records. For patients, mobile devices and apps are often utilized to find resources and information about diseases, to help with disease management, and to promote lifestyle modification and fitness. Nevertheless, despite the numerous benefits of mobile devices in practice, potential risks and drawbacks must also be considered.


2019 ◽  
Vol 95 (5) ◽  
pp. 95-115 ◽  
Author(s):  
Shana M Clor-Proell ◽  
Ryan D Guggenmos ◽  
Kristina Rennekamp

ABSTRACT We examine how information dissemination via mobile device applications (apps) affects nonprofessional investors' judgments. In response to the prevalence of mobile device use, the media ungroups content into smaller pieces to accommodate users, and apps use push notifications to highlight this content. These changes increase users' ability to access investment information in real time, leaving some investors feeling as if they are missing out if they are not continuously connected. We validate a scale to capture investors' fear of missing out on investment information (I-FoMO) and document that I-FoMO is distinct from traditional FoMO that occurs in social settings. Then, using an experiment, we find that receiving ungrouped content via a mobile device has a greater effect on investment allocations in the presence, rather than absence, of push notifications. Further, we find that these results hold for higher, but not for lower, I-FoMO investors. JEL Classifications: G23; M41; M48; M49. Data Availability: Contact the authors.


2020 ◽  
Vol 83 ◽  
pp. 101100 ◽  
Author(s):  
T. Brown ◽  
Stephanie M. Grant ◽  
Amanda M. Winn

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lu Lin ◽  
Xiu-Chen Jing ◽  
Shu-Jiao Lv ◽  
Jing-Hong Liang ◽  
Li Tian ◽  
...  

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