Computer Literacy in the Elderly: A Survey Examining Real World Usability of Medical Software

Computer Literacy in the Elderly: A Survey Examining Real World Usability of Medical Software

Rasiah, S

Whitchurch, M

Journal MTM 7:2:66–67, 2018

doi:10.7309/jmtm.7.2.10

There is widespread evidence of an association between reduced health literacy and an increased risk of poor medical outcome. Patients with poor medical education experience significantly higher emergency room costs¹ and up to double the hospital admission rates compared to patients with sufficient medical education.²–⁶ Lack of medical literacy is particularly important in the ageing population, due to increased burden of chronic illness and the increasingly complex management of progressive chronic conditions. To address this, various smartphone and tablet medical applications have been developed to improve patient health literacy and monitor chronic illnesses. We propose the need to examine the technological literacy of elderly patients, who are most likely to benefit from these applications.

The efficacy of self-monitoring medical applications hinges on a patient’s ability to access and use technology to track health progress. We suspect that computer literacy in elderly patients will not be adequate for effective technological monitoring of chronic illness at this time. It has been shown that amongst doctors there is often low familiarity with basic computer applications.⁷

We have designed a study to determine the technological literacy of patients who present to a large specialist Ophthalmology hospital. This population is one of the least likely to adequately operate advanced technology due to deteriorating vision and advanced age. There has also been recent development of patient health-monitoring applications for illnesses in this field. These include applications to monitor glaucoma and macular degeneration, which have significant correlation with clinical assessment in experimental settings.^8,9

We will survey Ophthalmology patients and compare their ability to perform simple tasks on their smartphones and tablets as a screening measure for operating more advanced medical software for the purposes of health monitoring. The designed survey will enquire about the ability of patients to install, open and operate applications on a smartphone or tablet. The survey will also obtain information about the type of devices patients own and frequently use. Finally, the survey asks whether a patient has any previous experience with medical applications.

With the results of this research we aim to assess the computer literacy of an ageing patient population, and extrapolate from this data the reliability of personal medical software to accurately monitor chronic disease in this demographic. Due to potential limitations in patient language comprehension, participants will be limited to those fluent in English. While there are also potential study limitations due to visual or technological difficulties, these problems will reflect the issues in implementing personal medical applications in practice.

These findings will act as a benchmark to guide the feasibility of implementation of technology-based disease monitoring in the near future. We would expect, with time, that subsequent generations’ computer literacy will only improve from this benchmark.

References

1. Howard DH, Gazmararian J, Parker RM. The impact of low health literacy on the medical costs of Medicare managed care enrollees. The American journal of medicine [Internet]. 2005;118(4):371–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15808134

2. Baker DW, Parker RM, Williams M V., Clark WS. Health literacy and the risk of hospital admission. Journal of General Internal Medicine. 1998;13(12):791–8.

3. Levin-Zamir D, Peterburg Y. Health literacy in health systems: Perspectives on patient self-management in Israel. Vol. 16, Health Promotion International. 2001. p. 87–94.

4. Dewalt DA, Berkman ND, Sheridan S, Lohr KN, Pignone MP. Literacy and health outcomes: a systematic review of the literature. Journal of general internal medicine. United States; 2004 Dec;19(12):1228–39.

5. Williams M V, Baker DW, Parker RM, Nurss JR. Relationship of functional health literacy to patients’ knowledge of their chronic disease. A study of patients with hypertension and diabetes. Archives of internal medicine. United States; 1998 Jan;158(2):166–72.

6. Schillinger D, Grumbach K, Piette J, Wang F, Osmond D, Daher C, et al. Association of health literacy with diabetes outcomes. JAMA. United States; 2002 Jul;288(4):475–82.

7. Debehnke DJ, Valley VT. Assessment of the current computer literacy and future computer needs of emergency medicine residents and faculty. American Journal of Emergency Medicine. 1993;11(4):371–3.

8. Anderson A, Bedggood A, Kong Y, Martin K, Vingrys A. Can Home Monitoring Allow Earlier Detection of Rapid Visual Field Progression in Glaucoma? American Academy of Ophthalmology. 2017;124(12):1735–42.

9. Winther C, Frisen L. Self-Testing of Vision in Age-Related Macula Degeneration: A Longitudinal Pilot Study Using a Smartphone-Based Rarebit Test. Journal of Opthalmology. 2015;2015:285463.

A Survey of Japanese Young Adults’ Postures When Using Smartphones before Sleeping

Michitaka Yoshimura, MA¹, Momoko Kitazawa, MA¹, Taishiro Kishimoto, MD, PhD^2,3*, Masaru Mimura, MD, PhD², Kazuo Tsubota, MD, PhD¹

¹Department of Ophthalmology, Keio University School of Medicine, Tokyo, Japan; ²Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; ³Hofstra Northwell School of Medicine, Hempstead, New York, USA

^*Taishiro Kishimoto is not a recipient of a research scholarship.

Corresponding Author: t-kishimoto@keio.jp

Journal MTM 5:2:51–53, 2016

doi:10.7309/jmtm.5.2.8

Although mobile technologies, devices and software have enriched our lives in many ways, including medical applications, the potential negative effects are often overlooked. A growing amount of evidence suggests that there are potential negative impacts of smartphones on biophysiological processes, especially on sleep.^1–6 Studies have shown that blue lights, especially the short-wavelength light (380 ~ 495 nm) emitted from smartphone monitors, disrupts circadian rhythm by retarding nocturnal melatonin production.⁷

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Medical Students’ Perceptions Regarding the Impact of Mobile Medical Applications on their Clinical Practice (RE: JMTM 2014, 3(1):46-53)

Ahmad Fayaz-Bakhsh, MD, MSc, PhD¹, Sara Geravandi, BSc²

¹Health Information Management Research Center, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran; and School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; ²School of Public Health, Teharn University of Medical Science, Tehran, Iran

Corresponding Author: fayaz@tums.ac.ir

Journal MTM 4:2:51–52, 2015

doi:10.7309/jmtm.4.2.8

In February 2014, an original article, titled, “Medical Students’ Perceptions Regarding the Impact of Mobile Medical Applications on their Clinical Practice” was released in Journal MTM. The survey was conducted on all 169 medical students in their first clinical year of the International Medical University (IMU) in the city of Seremban, State of Negeri Sembilan, Malaysia. Data was collected by using a self-administered questionnare. The questions were formulated from a list of desired qualities in medical applications (apps) which has been published by Visser BJ and Bouman J. The students’ perceptions regarding medical apps, the impact of medical apps on clinical practice and the characteristics of an ideal medical app were explored. It was found that the prevalence of medical students who owned a smart device was about 88% and 87.5% had medical apps installed on their smart devices. Data was analysed by using SPSS software version 20. The results showed most students had positive perception towards smart devices and medical apps and agreed they have positive impact on their studies and clinical practice.¹

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Beyond the Hype: Mobile Technologies and Opportunities to Address Health Disparities

Yulin Hswen, MPH^1,2, Kasisomayajula Viswanath, PhD^1,3

¹Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, MA, USA; ²Center on Media and Child Health, Boston Children’s Hospital, Boston, MA, USA; ³Health Communication Core, Dana-Farber/Harvard Cancer Center, Boston, MA, USA

Corresponding Author: yhswen@gmail.com

Journal MTM 4:1:39–40, 2015

doi:10.7309/jmtm.4.1.9

In recent years, countless news stories, blog posts, and academic commentaries have highlighted the growing excitement surrounding the potential of mobile health (mHealth) technologies. Whether it is for treatment, diagnosis, illness monitoring or promoting healthy lifestyle behaviors, mHealth refers to the use of mobile and wireless devices such as smartphones or tablet computers for health or medical purposes, and as regularly illustrated in the Journal of Mobile Technology in Medicine, these emerging technologies offer innovative approaches to addressing complex medical and population health concerns.^1,2 For example, leaders in medicine, government, and industry have championed mHealth as a strategy for treating acute and chronic illnesses, more efficiently conducting clinical and population-based health research, and addressing healthcare workforce shortages.^3–5 In a recent commentary published in the Journal of the American Medical Association, Steinhubl and colleagues discussed the potential for emerging mobile technologies to transform health care.⁶ While we entirely agree that mHealth holds tremendous potential, we caution readers that these benefits may be differentially experienced across diverse groups, and may exacerbate as opposed to close health disparities.

The Internet revolution is a case in point. It was championed as a means to overcome socioeconomic, demographic and geographic barriers, yet considerable evidence shows a digital divide and fewer opportunities for disadvantaged individuals. It is possible that mHealth may be different given the rapid worldwide penetration of mobile telecommunication technologies; however, despite the decreasing costs of owning the actual devices, continuing access to data services through subscription represents a considerable expense for low-income individuals⁷ and limits access and use of these services.⁸ This creates challenges for many people to maintain a continuous and reliable wireless connection to the Internet, which would severely limit their ability to benefit from mHealth applications requiring continual illness monitoring, real-time data collection, or remote syncing to the virtual cloud. A recent survey conducted in the United States highlighted that expense was the single greatest barrier to owning a mobile device among a predominantly African American sample of low-income individuals with serious mental health concerns.⁹

Access, however, does not guarantee benefit from mHealth technologies. Difficult or unfamiliar user-interface may deter people from lower socioeconomic status to make effective use of mobile technologies for their health. Significant gaps in trust of health information from Internet sources has also been observed across low-income and ethnic groups.⁷ It is likely that such digital inequalities and lack of trust of health information may significantly limit the potential for mHealth to enable minority and low-income individuals to benefit through self-diagnosing acute symptoms, or tracking and managing chronic health conditions. This is of particular concern given the disproportionately elevated chronic disease burden impacting these individuals.¹⁰

Our aim is not to question the promise of mHealth, but rather to emphasize that just as stated by Steinbuhl and colleagues in their concluding remarks, “much remains to be done”.⁶ Just as clearly defined government regulations³, internationally recognized research guidelines¹¹, and robust clinical trial evidence⁶ are critically necessary for advancing this nascent field, consideration of how mHealth technologies can be adapted and strategically delivered to address the needs of the most vulnerable low-income patients is of equal value. The role of mHealth technologies for addressing health disparities has received less attention¹², though important opportunities exist. For instance, trends of increasing mobile phone penetration among low-income groups, evidence that at-risk minorities are more likely to search for health related information on their phones or on the Internet than mainstream populations, and the capacity to engage at-risk patients through greater personalization, facilitating social connections, or community outreach further support the promise of using these emerging technologies for reaching marginalized individuals.^13,14

It is imperative that efforts to address health disparities through the elimination of health communication inequalities, targeted dissemination of culturally appropriate health information to at-risk minority groups¹⁰, or incentives programs aimed at addressing gaps in affordability and access to mobile health technologies⁷, must not be overshadowed by the hype or excitement of only the newest hi-tech devices. We sit at an exciting time where patients, researchers, clinicians, entrepreneurs and policy makers can shape how emerging mobile technologies will transform health care; let’s not squander this opportunity.

Disclosures

None for any author.

References

1. Perera C. The evolution of E-Health–mobile technology and mHealth. Journal of Mobile Technology in Medicine. 2012;1:1–2.

2. Hswen Y, Murti V, Vormawor AA, Bhattacharjee R, Naslund JA. Virtual avatars, gaming, and social media: Designing a mobile health app to help children choose healthier food options. Journal of Mobile Technology in Medicine. 2013;2:8–14.

3. Cortez NG, Cohen IG, Kesselheim AS. FDA regulation of mobile health technologies. New England Journal of Medicine. 2014;371:372–9.

4. Collins F. How to fulfill the true promise of “mHealth”. Scientific American. 2012;307:16.

5. Bartels SJ, Naslund JA. The underside of the silver tsunami—older adults and mental health care. New England Journal of Medicine. 2013;368:493–6.

6. Steinhubl SR, Muse ED, Topol EJ. Can mobile health technologies transform health care? Journal of the American Medical Association. 2013;310:2395–6.

7. Viswanath K, Nagler RH, Bigman-Galimore CA, McCauley MP, Jung M, Ramanadhan S. The communications revolution and health inequalities in the 21st century: implications for cancer control. Cancer Epidemiology Biomarkers & Prevention. 2012;21:1701–8.

8. Zickuhr K, Smith A. Digital differences. Pew Research Center’s Internet & American Life Project. 2012:1–41.

9. Ben-Zeev D, Davis KE, Kaiser S, Krzsos I, Drake RE. Mobile technologies among people with serious mental illness: opportunities for future services. Administration and Policy in Mental Health and Mental Health Services Research. 2013;40:340–3.

10. Gibbons MC, Fleisher L, Slamon RE, Bass S, Kandadai V, Beck JR. Exploring the potential of Web 2.0 to address health disparities. Journal of Health Communication. 2011;16:77–89.

11. Tomlinson M, Rotheram-Borus MJ, Swartz L, Tsai AC. Scaling up mHealth: where is the evidence? PLoS Medicine. 2013;10:e1001382.

12. Horn IB, Mendoza FS. Reframing the disparities agenda: a time to rethink, a time to focus. Academic Pediatrics. 2013;14:115–6.

13. Martin T. Assessing mHealth: opportunities and barriers to patient engagement. Journal of Health Care for the Poor and Underserved. 2012;23:935–41.

14. Naslund JA, Grande SW, Aschbrenner KA, Elwyn G. Naturally occurring peer support through social media: the experiences of individuals with severe mental illness using YouTube. PLoS One. 2014;9:e110171.

Skin Health Applications: Blessing or Misdiagnosis?

Anum Wasim¹, Madiha Hassan Rizvi¹, Ayisha Farooq Khan¹

¹5th year Medical Student, Dow Medical College, Karachi, Pakistan

Corresponding Author: anum.wasim5@gmail.com

doi:10.7309/jmtm.3.1.8

There has been a global rise in skin cancer over the last few years with the rising diagnosis of 2–3 million non-melanoma and 132,000 melanoma skin cancer cases each year¹. This growing prevalence is not only attributed to the increasing ultraviolet radiation by ozone depletion but also by other major predisposing factors centred to an individual’s own responsibility controls like recreational sun exposure and sunburn¹. However despite the escalating figures, low skin screening rates and awareness levels among the general population are highly disconcerting².

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Overcoming mHealth operational challenges in Cambodia (RE: JMTM 2013, 2: 20–23)

Chris Smith, MBBCh, MSc^1,2, Uk Vannak, BN¹, Ly Sokhey, BM¹, Melissa Cockroft, BA, MA¹

¹Marie Stopes International Cambodia (MSIC); ²Department of Population Health, London School of Hygiene and Tropical Medicine (LSHTM), London, UK

Corresponding Author: chris.smith@mariestopes.org.kh

doi:10.7309/jmtm.2.3.6

We concur with the mHealth operational challenges in Cambodia identified in Bisit Bullen’s perspective piece¹. We would like to share our experiences with MOTIF (MObile Technology for Improved Family Planning); a project to design and evaluate a mobile phone-based service to support post-abortion family planning (PAFP) clients accessing services at Marie Stopes International Cambodia’s (MSIC) clinics.

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