This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
Smartphone technology is ubiquitous throughout neurologic practices, and numerous apps relevant to a neurologist’s clinical practice are now available. Data from other medical specialties suggest high utilization of smartphones in routine clinical care. However, the ways in which these devices are used by neurologists for patient care–related activities are not well defined.
This paper aims to characterize current patterns of smartphone use and perceptions of the utility of smartphones for patient care–related activities among academic neurology trainees and attending physicians. We also seek to characterize areas of need for future app development.
We developed a 31-item electronic questionnaire to address these questions and invited neurology trainees and attendings of all residency programs based in the United States to participate. We summarized descriptive statistics for respondents and specifically compared responses between trainees and attending physicians.
We received 213 responses, including 112 trainee and 87 attending neurologist responses. Neurology trainees reported more frequent use of their smartphone for patient care–related activities than attending neurologists (several times per day: 84/112, 75.0% of trainees; 52/87, 59.8% of attendings;
Smartphones are used frequently and are subjectively perceived to be highly useful by academic neurologists. Trainees tended to use their devices more frequently than attendings. Our results suggest specific avenues for future technological development to improve smartphone use for patient care–related activities. They also suggest an unmet need for education on effectively using smartphone technology for clinical care.
Smartphones are a ubiquitous presence on hospital wards. Ownership among physicians is nearly universal [
There are now many neurology-specific smartphone apps, with an emphasis on everything from anatomy to localization, reference materials, education, and documentation [
The study was approved by the Johns Hopkins University School of Medicine Institutional Review Board. An initial draft questionnaire was developed by the authors and was subsequently refined and validated through 2 focus groups consisting of a total of 4 residents and 3 attendings from the Department of Neurology at the Johns Hopkins University School of Medicine. Focus group participants provided direct oral and written feedback regarding the questionnaire length and subject areas, as well as the clarity, response options, and relevance of items in the questionnaire about their experience using smartphones. Patient care–related activities were clarified to include “communication with or about patients, clinical documentation, physical examination, accessing clinical or reference information, and healthcare specific mobile applications.” The final questionnaire was distributed electronically using Qualtrics software.
A letter with an anonymous link to the final 31-item questionnaire was emailed to all program directors and coordinators of academic neurology residency training programs (154 programs in total) in the United States in the spring of 2018. Follow-up reminder emails were sent 1 and 2 months later, and data collection was closed 3 months after the initial invitation. We did not solicit or receive feedback from programs about whether they had distributed the survey to physicians at their program, and as a result, we were unable to calculate a complete response rate for the questionnaire. On the first page of the questionnaire, participants were told the purpose of the survey and the estimated length of time to complete the survey (10 minutes) and were informed that participation was completely voluntary and that participation in the survey would serve as consent to have responses included in the study. Respondents could leave questionnaire items incomplete. No personal or identifying data were collected or stored about respondents. We did not collect information about the institutions to which respondents belonged nor did we attempt to validate self-reported usage data with data logs from respondents’ smartphones.
Data were analyzed using MATLAB (MathWorks) and R (R Foundation for Statistical Computing). Questionnaires with incomplete data were included in the analysis. Results are presented with the total number of respondents for each questionnaire item. Primary analysis was done with chi-square tests. When expected counts were low (<5), response categories were binned. When response categories could not be logically binned, a Fisher exact test was used. A threshold for statistical significance of 0.05 was used. Follow-up 2 × 2 contingency tables were created for post hoc testing of individual response categories with Bonferroni correction. For matrix table items with Likert-type scales, data were compared using the Wilcoxon rank sum test with Bonferroni correction.
A total of 213 neurologists responded to the questionnaire, all of whom owned smartphones. We estimate our response rate was about 4% for trainees, based on 112 trainee responses and a total of 2797 neurology residents and fellows in 2018 [
Demographics of survey respondents.
Characteristics | All | Attending | Trainee | ||
Sex (female), n/N (%) | 93/199 (46.7) | 37/87 (42.5) | 56/112 (50.0) | .36 | |
|
30-34 | 40-49 | 30-34 | <.001 | |
|
<30, n/N (%)a | 36/198 (18.2) | 1/87 (1.1) | 35/111 (31.5) |
|
|
30-34, n/N (%)a | 66/198 (33.3) | 6/87 (6.9) | 60/111 (54.1) |
|
|
35-39, n/N (%) | 32/198 (16.2) | 17/87 (19.5) | 15/111 (13.5) |
|
|
40-49, n/N (%)a | 29/198 (14.6) | 29/87 (33.3) | 0/111 (0.0) |
|
|
50-59, n/N (%)a | 15/198 (7.6) | 14/87 (16.1) | 1/111 (0.9) |
|
|
>60, n/N (%)a | 20/198 (10.1) | 20/87 (23.0) | 0/111 (0.0) |
|
PGYb, median | N/Ac | N/A | 3 | N/A | |
Years in practice, median | N/A | 14 | N/A | N/A |
aIndividual response category was found to be significant upon post hoc testing with Bonferroni correction.
bPGY: postgraduate year.
cN/A: not applicable.
Respondents were also surveyed regarding current usage of their devices as an aid to the performance of the neurologic examination. Most respondents said they had used their smartphone as an aid to the examination, with more trainees having done so compared to attending physicians (97/108, 89.8% trainees vs 58/83, 69.9% attending physicians;
Finally, respondents were asked about their expectations regarding future smartphone use. The majority of respondents reported a high likelihood (“likely” or “very likely”) of using their devices for patient care–related activities in the future, with trainees reporting higher likelihood (
Given that we found several differences between attending physicians and trainees, we wondered how much of this effect could have been driven by age rather than training status. Therefore, we conducted a subgroup analysis for respondents in the age range with the greatest overlap between attending physicians and trainees (35-39 years). In this age range, we did not find any significant differences between groups for any of the items reported in
Patterns of current smartphone usage and predicted future usage.
Usage | All | Attending | Trainee | ||
|
Several times a day | Several times a day | Several times a day | .03 | |
|
Once a week or less, n/N (%) | 18/199 (9.0) | 13/87 (14.9) | 5/112 (4.5) | |
|
2-3 times a week, n/N (%) | 19/199 (9.5) | 11/87 (12.6) | 8/112 (7.1) | |
|
Once or twice a day, n/N (%) | 26/199 (13.1) | 11/87 (12.6) | 15/112 (13.4) | |
|
Several times a day, n/N (%) | 136/199 (68.3) | 52/87 (59.8) | 84/112 (75.0) | |
|
11-30 min | 11-30 min | 31-50 min | .02 | |
|
<10, n/N (%)a | 34/199 (17.1) | 22/87 (25.3) | 12/112 (10.7) |
|
|
11-30, n/N (%) | 69/199 (34.7) | 32/87 (36.8) | 37/112 (33.0) | |
|
31-50, n/N (%) | 29/199 (14.6) | 11/87 (12.6) | 18/112 (16.1) | |
|
>50, n/N (%) | 67/199 (33.7) | 22/87 (25.3) | 45/112 (40.2) | |
|
<5 | <5 | <5 | .03 | |
|
<5, n/N (%)a | 121/198 (61.1) | 62/86 (72.1) | 59/112 (52.7) |
|
|
6-10, n/N (%)a | 50/198 (25.3) | 13/86 (15.1) | 37/112 (33.0) |
|
|
11-15, n/N (%) | 15/198 (7.6) | 6/86 (7.0) | 9/112 (8.0) | |
|
>15, n/N (%) | 12/198 (6.1) | 5/86 (5.8) | 7/112 (6.3) | |
Ever used for examination (yes), n/N (%) | 155/191 (81.2) | 58/83 (69.9) | 97/108 (89.8) | <.001 | |
|
2-3 times a month | 2-3 times a month | 2-3 times a month | .03 | |
|
Less than once a month, n/N (%) | 40/154 (26.0) | 18/58 (31.0) | 22/96 (22.9) | |
|
Once a month, n/N (%) | 19/154 (12.3) | 8/58 (13.8) | 11/96 (11.5) | |
|
2-3 times a month, n/N (%) | 32/154 (20.8) | 13/58 (22.4) | 19/96 (19.8) | |
|
Once a week, n/N (%) | 20/154 (13.0) | 11/58 (19.0) | 9/96 (9.4) | |
|
2-3 times a week, n/N (%) | 27/154 (17.5) | 7/58 (12.1) | 20/96 (20.8) | |
|
Daily, n/N (%) | 16/154 (10.4) | 1/58 (1.7) | 15/96 (15.6) | |
|
Very useful | Very useful | Very useful | .12 | |
|
Not useful at all, n/N (%) | 12/191 (6.3) | 8/83 (9.6) | 4/108 (3.7) | |
|
Minimally useful, n/N (%) | 48/191 (25.1) | 25/83 (30.1) | 23/108 (21.3) | |
|
Very useful, n/N (%) | 85/191 (44.5) | 34/83 (41.0) | 51/108 (47.2) | |
|
Essential, n/N (%) | 46/191 (24.1) | 16/83 (19.3) | 30/108 (27.8) | |
Ever received instruction (yes), n/N (%) | 12/184 (6.5) | 2/82 (2.4) | 10/102 (9.8) | .09 | |
|
Very likely | Likely | Very likely | .005 | |
|
Very unlikely, n/N (%) | 2/184 (1.1) | 2/82 (2.4) | 0/102 (0.0) |
|
|
Unlikely, n/N (%) | 1/184 (0.5) | 1/82 (1.2) | 0/102 (0.0) | |
|
Somewhat unlikely, n/N (%) | 3/184 (1.6) | 3/82 (3.7) | 0/102 (0.0) | |
|
Undecided, n/N (%) | 9/184 (4.9) | 7/82 (8.5) | 2/102 (2.0) | |
|
Somewhat likely, n/N (%) | 14/184 (7.6) | 8/82 (9.8) | 6/102 (5.9) | |
|
Likely, n/N (%) | 42/184 (22.8) | 21/82 (25.6) | 21/102 (20.6) | |
|
Very likely, n/N (%) | 113/184 (61.4) | 40/82 (48.8) | 73/102 (71.6) | |
|
Likely | Somewhat likely | Likely | .05 | |
|
Very unlikely, n/N (%) | 8/184 (4.3) | 6/82 (7.3) | 2/102 (2.0) |
|
|
Unlikely, n/N (%) | 6/184 (3.3) | 4/82 (4.9) | 2/102 (2.0) | |
|
Somewhat unlikely, n/N (%) | 9/184 (4.9) | 7/82 (8.5) | 2/102 (2.0) | |
|
Undecided, n/N (%) | 25/184 (13.6) | 14/82 (17.1) | 11/102 (10.8) | |
|
Somewhat likely, n/N (%) | 27/184 (14.7) | 11/82 (13.4) | 16/102 (15.7) | |
|
Likely, n/N (%) | 44/184 (23.9) | 17/82 (20.7) | 27/102 (26.5) | |
|
Very likely, n/N (%) | 65/184 (35.3) | 23/82 (28.0) | 42/102 (41.2) | |
|
More | More | Same or more | .37 | |
|
Never, n/N (%) | 2/184 (1.1) | 1/82 (1.2) | 1/102 (1.0) |
|
|
Less than current usage, n/N (%) | 1/184 (0.5) | 0/82 (0.0) | 1/102 (1.0) | |
|
The same as current usage, n/N (%) | 80/184 (43.5) | 31/82 (37.8) | 49/102 (48.0) | |
|
More than current usage, n/N (%) | 101/184 (54.9) | 50/82 (61.0) | 51/102 (50.0) |
aIndividual response category was found to be significant upon post hoc testing with Bonferroni correction.
Frequency of smartphone and mobile app use. (A) Respondents were asked, “How frequently do you use your smartphone and/or tablet for the following patient care related activities?” (B) Respondents were asked, “How frequently do you use the following types of mobile applications?” A: attending physicians; T: trainees. *Significantly greater usage for the indicated group compared with the other, with Bonferroni adjusted
Frequency of smartphone use for the examination. (A) Respondents were asked, “How frequently do you utilize your smartphone and/or tablet for the following parts of the neurologic examination?” (B) Respondents were asked, “How frequently do you use your smartphone and/or tablet for each of the following functions when performing the physical examination?” A: attending physicians; OKN: optokinetic nystagmus; T: trainees. *Significantly greater usage for the indicated group compared with the other, with Bonferroni adjusted
Perceived utility of potential new smartphone apps. Respondents were asked, “Imagine that a new mobile application was developed to aid in the performance of the neurologic examination. Please rank how useful it would be to have an application that could enhance the performance of each area of testing listed below.” A: attending physicians; T: trainees. *Significantly greater usage for the indicated group compared with the other, with Bonferroni adjusted
As smartphone technologies improve, neurologists frequently use their mobile devices for patient care–related activities. Standard items from the neurologist’s tool kit, such as a wristwatch and penlight, can easily be replaced with basic smartphone functionalities. Apps supplanting more advanced testing are rapidly being incorporated as well, including apps for visual acuity and color vision testing [
These practice patterns are unlikely to be transient, as most respondents in this study predicted high likelihood of future smartphone use, including as an aid to the neurologic examination. We anticipate that the use of smartphone apps in neurologic practice will continue to grow, as trainees use their devices more frequently than attending physicians across a range of smartphone apps and functions. Indeed, neurology trainees tended to use their devices more frequently both for general patient care–related activities and as an aid to the performance of the physical examination. These trends held true when examining specific smartphone apps and functions, with trainees tending to report higher usage for most categories, with the exception of communication with patients. Trainees also reported higher likelihood of future use, though subjective usefulness was similar between trainees and attending physicians. Although not powered for a subgroup analysis, responses were similar between trainees and attending physicians aged 35 to 39 years. This suggests that age may be a significant factor in the overall differences between these groups, with younger neurologists using their devices more, which further emphasizes the likelihood that smartphone use in neurologic practice will continue to grow.
In addition to changes driven by the demographics of neurologists entering the workforce, we expect other factors may increase reliance on smartphone technologies for patient care. The SARS-CoV-2 pandemic has led to a dramatically increased reliance by neurologists on telehealth technologies for remote care delivery [
Although a large majority of neurologists use their devices, almost none have had any education on how to do so effectively for clinical practice. The development of such a curriculum could have several benefits, including greater use, increased efficiency, expanded access, improved subjective utility, and potentially, encouragement to spur the next generation of app development. On the other hand, such a curriculum could address mitigation of the negative effects of smartphones, such as impaired sleep [
This study was limited in several ways. The questionnaire was distributed to academic neurology training programs, so these findings may not be generalizable to private practice or nonacademic hospital settings. Participation was voluntary and our sample may have been biased toward neurologists with an interest in technology, who might have been more likely to respond to the questionnaire. All respondents were active smartphone users, and this might have resulted in an overestimation of the frequency of use or subjective usefulness, though based on our own experience, this seems unlikely. In addition, all smartphone use data were self-reported, and we did not validate these with objective data use logs. Finally, although our total number of respondents was large, our overall response rate was likely low. Given a total of 2797 neurology residents and fellows in 2018 [
In summary, smartphones are a valuable tool in academic neurology not only for communication but also for education and practice. These devices now feature in the neurologist’s equipment bag alongside the reflex hammer and tuning fork. Smartphone-owning neurologists expect to continue using their devices in the future. There is opportunity for further refinement of these devices for neurologic practice, limited only by our creativity in the use of features and the development of associated tools, scales, and apps. We anticipate that these ubiquitous handheld devices will in time prove invaluable to the diagnosis and treatment of patients with neurologic disease.
electroencephalography
The authors received no funding for this study and have no relevant financial disclosures to report.
WZ contributed to the study conception, design, and data acquisition and analysis and drafted and revised the manuscript. SD contributed to the study design and data acquisition and revised the manuscript. JP contributed to the study conception, design, data acquisition, and analysis and revised the manuscript.
None declared.