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DOI: 10.1055/a-2267-1727
Human-Centered Design and Development of a Fall Prevention Exercise App for Older Adults in Primary Care Settings
Authors
- Abstract
- Background and Significance
- Objective
- Methods
- Results
- Discussion
- Conclusion
- Clinical Relevance Statement
- Multiple-Choice Questions
- References
Abstract
Background Falls in older adults are a serious public health problem that can lead to reduced quality of life or death. Patients often do not receive fall prevention guidance from primary care providers (PCPs), despite evidence that falls can be prevented. Mobile health technologies may help to address this disparity and promote evidence-based fall prevention.
Objective Our main objective was to use human-centered design to develop a user-friendly, fall prevention exercise app using validated user requirements. The app features evidence-based behavior change strategies and exercise content to support older people initiating and adhering to a progressive fall prevention exercise program.
Methods We organized our multistage, iterative design process into three phases: gathering user requirements, usability evaluation, and refining app features. Our methods include focus groups, usability testing, and subject-matter expert meetings.
Results Focus groups (total n = 6), usability testing (n = 30) including a posttest questionnaire [Health-ITUES score: mean (standard deviation [SD]) = 4.2 (0.9)], and subject-matter expert meetings demonstrate participant satisfaction with the app concept and design. Overall, participants saw value in receiving exercise prescriptions from the app that would be recommended by their PCP and reported satisfaction with the content of the app.
Conclusion This study demonstrates the development, refinement, and usability testing of a fall prevention exercise app and corresponding tools that PCPs may use to prescribe tailored exercise recommendations to their older patients as an evidence-based fall prevention strategy accessible in the context of busy clinical workflows.
Keywords
exercise - mobile apps - geriatrics - primary care - evidence-based behavior change strategiesBackground and Significance
Falls among older adults are a growing public health issue, as they are the leading cause of fatal and nonfatal injuries in this population.[1] Every hour, three older Americans die because of a fall,[2] and it is estimated that 30% of the adults aged 65 years and older fall each year.[1] [3] Fear of falling alone leads to activity restrictions, is associated with poorer physical and cognitive functions,[4] and can have a negative impact on quality of life.
To be effective, fall prevention programs must be patient-centered meaning that the exercise program is tailored to patient-specific abilities and preferences. Tailored fall prevention exercises have been shown to greatly reduce the incidence of falls.[5] A recent meta-analysis found that participation in an appropriate fall-prevention exercise program for an older adult reduces the risk of falls by 23% in relative terms, for an absolute reduction of 0.20 falls per person per year.[6] Many guidelines, including the U.S. Preventive Service Task Force, recommend that older adults at risk of falls are referred to appropriate fall-prevention exercise programs such as the Otago program that improves strength and balance.[7] As most adults aged 65 years and more receive some form of medical care annually,[8] primary care visits present an ideal opportunity to screen patients and prescribe appropriate fall prevention strategies.[9] Unfortunately, fall prevention is inadequately addressed in outpatient settings[10] as primary care providers (PCPs) often lack the time, resources, and/or knowledge to develop a tailored exercise plan.[10] Referrals for physical therapy or fall prevention programs may be effective yet inaccessible due to financial, social, geographic, and language barriers.[11] [12]
During the coronavirus disease 2019 (COVID-19) pandemic,[13] mobile health (mHealth) became more prevalent in addressing these barriers.[14] Currently, there are several mobile apps and websites designed to promote fall prevention.[15] [16] [17] [18] [19] In our prior research aiming to develop a clinical decision support (CDS) tool to help providers prescribe tailored, actionable fall prevention recommendations for their patients, we identified a preliminary set of end-user requirements including for apps and websites that could be integrated into PCPs' care: no additional workflow burden for providers, tools to support behavior change in patients, built-in support networks to encourage adherence, individualized fall prevention resources, and evidence-based safe exercises with expert guidance.[20] To our knowledge, no apps exist that address all of these user requirements while targeting older patients seen in primary care settings.
Objective
Our main objective was to use human-centered design (HCD) to develop a user-friendly, fall prevention exercise app (eSTEPS app), featuring evidence-based behavior change strategies and exercise content[21] to support older people initiating and adhering to a progressive fall prevention exercise program. The purpose of HCD is to “make systems usable and useful” by focusing on “end-user” needs and requirements at every stage of development,[22] [23] ultimately producing systems with a higher likelihood of adoption.[24] [25] [26] We aimed to leverage mHealth by designing tools (e.g., an app with corresponding website and printable handouts) meant to be prescribed by PCPs while making evidence-based and tailored fall prevention strategies more accessible for older adults. The exercise content is based on the Otago program which is an individually tailored, home-based, fall prevention program that has been shown to improve strength and balance and reduce falls and fall-related injuries among older adults.[27] The exercises were selected and modified so that they could be safely completed by older people at risk for falls without direct supervision. This article describes the iterative, HCD process using a series of focus groups and usability testing sessions to develop wireframes, prototypes, and a final fall prevention exercise app which is currently being evaluated in the eSTEPS clinical trial.
Methods
Overview of Study Procedures
We organized our multistage, iterative design process into three phases: (1) gathering user requirements, (2) usability evaluation, and (3) refining app features. Our methods include focus groups, usability testing, and subject-matter expert meetings. Initial requirements gathering began in January 2022 and app refinements concluded in September 2022 ([Fig. 1]). All participants provided verbal consent to participate. Participant data were collected including age, gender, ethnicity, and race. Three questions were included to screen for fall risk[28] based on their fear of falling, history of falls, and any resulting fall injuries ([Table 1]). This study was conducted at Brigham and Women's Hospital, part of Mass General Brigham (MGB), a large, integrated health care system in the New England region of the United States. IRB approval was obtained from the MGB Human Subject Committee for all study activities.


Abbreviation: SD, standard deviation.
Data Collection
Phase I: Gathering User Requirements
Six participants were recruited to participate in a series of focus group sessions from the Patient and Family Advisory Council (PFAC) of Brigham and Women's Hospital, a committee of patients, family members, and health care professionals to integrate patient and family voices in developing projects. All participants were older adults and potential users of the app. The purpose of these small focus groups was to build upon prior user research, engage fully with a small set of users, and refine the user needs iteratively until we reached saturation.[20] [29] [30] [31] [32] Focus groups were conducted virtually over Zoom. Each session began with a presentation to introduce the research staff, obtain consent for video/audio recording, display the agenda for the session, and present the most updated version of the app. Participants were provided with $10 gift cards for participation in each focus group.
Based on our earlier project that determined end-user needs for effective electronic fall prevention strategies, we had a preliminary set of requirements[20] that would lay the groundwork for focus groups 1 and 2. These focus groups sought to identify key content and design concepts for the initial design of our patient app. Focus group guides were developed to expand on the basic user requirements for the eSTEPS app and other “lower tech” tools (i.e., a website with exercise videos and illustrated handouts), as well as questions about fear of falling, fall risk, patient–provider relationships, exercise, and mobile app use. During focus group 3, wireframes were displayed through a storyboard featuring an imaginary participant accessing and using the app. Focus group participants were asked to provide thoughts and feedback on each part of the story and the features of the wireframes. The wireframes from focus group 3 were then developed into the version 1 eSTEPS app.
Phase II: Usability Evaluation
The usability evaluation consisted of two group sessions as well as individual sessions to reach a larger number of participants. The directors of two community centers (a local YMCA and a senior center) were contacted by email and agreed to allow study staff to conduct hour-long group usability testing sessions at each site. Flyers were hung in these community spaces to advertise the sessions and recruit participants. Additionally, study staff recruited a convenience sample of older adults, who participated in individual usability sessions. We reached out to participants from previous fall prevention research that we identified as high risk for falls and potential users of this type of application. All participants received a $25 gift card to thank them for their time.
Study staff developed a guide for all sessions, including an introduction to the eSTEPS project, the purpose of the app, and a scenario to help participants imagine that they received an exercise prescription from their PCPs and could access the exercise content through the app. Participants were then provided with a device (smartphone or tablet) containing the version 1 eSTEPS app to complete certain tasks within the app, explore, and think aloud to provide feedback on its functions and features. The app's exercise content, including both exercise videos and handouts, was also displayed on a computer website (www.homestrong.net) and a physical handout that had simple illustrations for each exercise (our “lower tech” tools). Lastly, participants were asked to fill out a modified version of the Health-ITUES,[33] a 20-item questionnaire to assess app usability consisting of four subscales: (1) quality of work life, (2) perceived usefulness, (3) perceived ease of use, and (4) user control. The Health-ITUES has demonstrated high internal consistency reliability and validity through exploratory factor analysis and confirmatory factor analysis.[33] [34] For this study, the Health-ITUES was modified with permission from the author to a 14-item questionnaire that includes wording relevant to the content and functionality of our prototype. The subdomain of user control was removed as it was not relevant to our app functionality. Each question consists of a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). A higher scale value indicates higher perceived usability of the technology. All feedback was compiled and integrated to produce the version 2 eSTEPS app.
Phase III: Refining App Features
Screenshots of the version 2 App were displayed during focus group 4, following the same procedures as in the first three focus groups. Participants were encouraged to provide feedback on each function, feature, and tab. Based on feedback from past focus groups and usability sessions, and the evidence suggesting that fall prevention exercise programs must be progressive and continued over time,[6] [7] [35] the research team also met with a motivational subject-matter expert who recommended new content and features to improve motivation and adherence to the app. Feedback received from focus group 4 and recommendations from the subject matter expert resulted in changes to produce our final app, the version 3 eSTEPS app.
Data Analysis
Content analysis was performed for all focus groups and usability sessions. We used a modified, rapid qualitative analysis framework, a method that balances efficiency and quality[36] [37] and is less resource-intensive and time-consuming than traditional methods.[38] All sessions requiring the collection of feedback from participants were guided by our user experience specialist (P.M.G.). During these sessions, another research team member (H.R.) took preliminary notes on emergent themes, recommendations, and direct quotes by participants. In addition, the audio recordings of the focus groups and usability sessions were reviewed by P.M.G. and H.R. to ensure that all feedback was extracted. Recurring or critical issues were identified and prioritized by reported frequency and impact on app usability. Themes and issues were discussed at weekly research team meetings as they emerged to iteratively translate into user requirements and developed into solutions to improve the next app version. After each focus group and usability session, study staff developed a series of PowerPoint mock-ups displaying the app that iteratively incorporated end-user feedback; these mock-ups were then provided to the app developer to create the next app version.
Results
Phase I: Gathering User Requirements
In this phase, we completed three focus groups. From the pool of six patients recruited to participate in one or more of the focus groups, five patient participants attended each of the first three focus groups. [Table 1] summarizes PFAC members' demographics and answers to the self-reported fall risk screening questions. After focus groups 1 and 2, we achieved saturation and summarized participant feedback into five user requirements and brainstormed design solutions to meet those requirements, included in [Table 2].
These requirements were used to create the wireframes with corresponding design elements and features, and the wireframes were shared via storyboard presentation during focus group 3. Overall, participants saw value in receiving exercise prescriptions from the app that would be recommended by their PCP. [Table 3] (Phase 1) describes a summary of participant feedback from focus group 3 regarding the wireframes and the resulting changes, which were implemented to produce the first mobile-ready app, version 1, displayed in [Fig. 2A–D]. For clarity, [Table 4] provides an overview of the evolution of every app version's main menu and tab layout, beginning with the wireframes and concluding with app version 3.
Phase/app version |
Feedback category |
Feedback summary |
Major changes |
Resulting prototype |
---|---|---|---|---|
Phase I feedback on wireframes (with corresponding changes resulting in app version 1) |
Exercises |
Want to know which exercise levels are next and which ones they have completed |
Current exercise levels listed first; completed exercise levels in gray color |
Version 1—see [Fig. 2A–D] |
Motivation |
Past, current, and future goals are unclear |
Gold stars indicate status of goal (filled in = complete) |
||
Resources |
Want additional information about falls in app |
Added tab dedicated to fall prevention resources |
||
Accessibility |
Difficulty seeing the text |
Option to adjust text size |
||
Accessibility |
Want other methods to view materials beyond app |
Developed Web site with exercise videos (Homestrong.net) and printable handouts to accommodate all user abilities |
||
Phase 2 feedback on app version 1 (with corresponding changes resulting in app version 2) |
Exercises |
Unclear where to view written exercise directions |
“Tap to View” button with every set of written directions |
Version 2—see [Fig. 3A–D] |
Exercises |
Unclear what happens after completing certain exercises and how they will progress |
Each exercise level made visible as a “preview” |
||
Motivation |
Completed goals unclear based on gold stars |
Remove the goals tab with “stars.” Explore “Your Journey” tab using “locks” that will depict “unlocking” when graduating to next exercise level |
||
Motivation |
Purpose of the Matches tab is unclear |
Matches tab becomes “Build My Support Network” under Main Menu for clarity |
||
Motivation |
Unnecessary to message support network (i.e., friends) within the app |
Remove feature to direct message friends; add “ask a question” to a physical therapist |
||
Resources |
Make fall prevention resources more prominent |
Fall Prevention Resources page becomes own “Resources” tab |
||
Phase 3 feedback on app version 2 (with corresponding changes resulting in app version 3 |
Motivation |
Locks on “Your Journey” tab are unclear |
“Your Journey” tab deleted; Exercises tab previews each exercise level |
Version 3—see [Fig. 4A–D] |
Exercises |
Include a more diverse array of exercise demonstrators |
Videos redone; feature more diverse demonstrators |
||
Motivation |
Include more motivational content for exercise adherence |
Motivational quotes added; “Progress Check” feature added to provide objective feedback about progress |


Abbreviation: FAQ, frequently asked questions.
Phase II: Usability Evaluation
We completed one group session at the YMCA (n = 10), one group session at the senior center (n = 10), and 10 individual usability testing sessions, totaling 30 participants. [Table 1] summarizes the demographics of the usability testing participants and responses to the fall risk screening questions. Overall, participants reported satisfaction with the content of the app, but several participants felt that they were not the right users for the app. This feedback was especially pronounced with several YMCA members who were already very active and did not think these exercises would enhance their existing exercise routines. Regarding technology preference, some participants said they would prefer using the app on an iPad for the larger screen and a few preferred navigating the homestrong.net website or printable handout of the exercise instructions instead of using the app. [Table 3] (Phase 2) describes a summary of participant feedback regarding app version 1 from all usability sessions ([Fig. 2E, F]), which was implemented to develop app version 2.
Across the 30 Health-ITUES Surveys completed by participants ([Table 5]), only 2 of the 14 survey items received an average score below 4.0. Item 4 in the subdomain of perceived usefulness received the lowest average score at 3.8, stating “Using eSTEPS [app] would make it easier to exercise regularly.” Item 12 in the subdomain of ease of use received the highest average score at 4.6, stating, “It would be easy for me to become good at using the eSTEPS [app].”
Note: Bold font used in this table is to indicate a summary score for each subdomain or for the overall score.
The usability testing feedback ([Table 3], Phase 2) and survey results ([Table 5]) regarding app version 1 were incorporated in designs for version 2 of the app, displayed in [Fig. 3A–D].


Phase III: Refining App Features
In general, participants of focus group 4 (n = 3) were pleased with the version 2 features of the app, as well as our website content and printable handouts. [Table 3] (Phase 3) summarizes the feedback from focus group 4 regarding app version 2 and describes the additional motivational content developed by our motivational subject-matter expert which was incorporated to produce the final app, version 3, displayed in [Fig. 4A–D].


The final app version included (1) an outline of each exercise level that includes videos and illustrations for each exercise (chair, level 1, level 2, and level 3) and that clearly coincides with the preidentified exercise goals, (2) fall prevention resources within the app such as a link to the CDC STEADI Toolkit,[9] (3) features such as support networks with friends and/or health professionals, and (4) motivational and educational messages designed to increase exercise adherence and provide tips to help prevent falls.
Discussion
Using an HCD process to involve older adults (our target end-users) in developing an exercise app allowed us to more successfully build an accessible, user-friendly app that can promote patient adherence to a tailored exercise plan. Importantly, this app can serve as a unique resource to deliver fall-prevention exercises to patients at high risk of falls while minimizing PCP burden. Our version 1 App demonstrated a high level of usability (surpassing our goal score of a median of 4 on the Health-iTUES), which is likely due to incorporating user feedback during each phase of the design process; participants generally maintained and highlighted the same user requirements that were identified in focus groups 1 and 2 throughout the app development process. The recurrent themes resulted in four major aspects of the design: (1) displaying an outline of each exercise level that clearly coincides with the preidentified exercise goals, (2) providing other fall prevention resources within the app, (3) promoting motivation and adherence through several design features such as support networks with friends and/or health professionals, and (4) making exercise content available outside of the app (other “high tech to low tech” resources). Overall, we received positive feedback on the app, which is significant given the gap in accessible fall prevention management strategies available for older adults. However, some participants felt strongly that they were not the “right user” for this app, whether it be technology preferences (irrespective of “user-friendliness”) or having little use for the app due to an advanced physical fitness level and regular participation in a fall prevention exercise program.
There are many existing apps related to fall prevention, although none meet all our user requirements for an app that could be safely provided to older primary care patients who are at risk for falls. Our earlier work had found that most PCPs do not have time or domain knowledge to demonstrate or teach exercises.[20] Our app and the exercises had to be simple and safe for older people to do at home while still providing adequate challenges to improve strength and balance. Many existing apps had barriers to use with the primary care population. For example, some existing exercise apps require a subscription, provide only written descriptions of the exercises, target populations other than community-dwelling older adults, focus on certain disease conditions where fall prevention is a secondary goal, prioritize general fitness, or require specialized exercise equipment.[15] Recent articles describe a similar HCD-based fall-prevention app development process with older adults in which many of their user requirements are consistent with those validated by our participants.[16] [18] [19] Erfani et al[19] describe conducting focus groups with community-dwelling older adults to validate their user requirements, including: building a social network through the app with other users and fall prevention educational resources. They also mention improving adherence through motivational features such as a series of games within the app.[19] In another study, Hawley-Hauge et al[16] describe the development and usability testing of two corresponding fall prevention apps (a patient and provider version) after conducting a literature review to validate their user requirements, including “behavior change techniques” (i.e., goal setting) and “app usability.” Of note, the second app version was built for providers (physical and occupational therapists) to help patients set and renew goals over time within their own app, which received generally positive feedback.[16] Due to reported time constraints from PCPs in our prior research,[20] we intentionally produced an app that can be recommended by PCPs but can also be used independently of health care professional involvement.
Our participants largely supported the concept of prescribing a fall prevention exercise app with a corresponding website and printable handouts as a standard resource for patients during a primary care visit. This is important given that to our knowledge, no app currently exists that is routinely prescribed in outpatient primary care settings to promote consistent engagement of community-dwelling older adults in a safe and evidence-based exercise program. It is interesting to note that even the CDC's “STEADI” toolkit, a widely accepted resource providing fall prevention education for PCPs to address their patients' fall risk needs, does not feature any distinct app or exercise plan to recommend to patients.[9] The website does include a brochure explaining the importance of exercise, a .pdf file of written directions for a singular “chair rise exercise,” and a link to the “coordinated care plan,” which suggests providers prescribe physical therapy referrals or community exercise programs.[9]
In addition, participants reported that the app would be helpful for their peers, even if they felt they were not the “right fit” for the app due to technology preferences or difficulty with exercise adherence. Focus group participants had mixed opinions on what would help them adhere to exercises, including app design elements (i.e., gold stars to recognize achievement) and social network involvement. A few participants explained that the app would never be useful to them because they prefer “in-person exercise classes”' or want “direct guidance from an exercise expert,” such as a physical therapist. Although exercise adherence, especially with mHealth technologies, has been a prevalent issue,[39] [40] participants rated the Health-ITUES item 4 (“Using eSTEPS [app] would make it easier to exercise regularly”) 3.8 out of 5, suggesting some level of agreement with this statement. Ultimately, further testing is needed to determine patient adherence to the app.
Some participants expressed a lack of confidence in using technology early in our design process, regardless of a “user-friendly” app interface. This prompted us to create a range of “low tech to high tech” tools, including written instructions with simple figures on the exercise handouts and a website corresponding with the app's exercise program, displayed in [Fig. 5A, B]. The results from the Health-ITUES surveys support these participants' sentiments, where subcategorical sections on “ease of use” (user-friendliness) scored an average of 4.4/5 but “perceived usefulness” (likelihood of use) scored an average of 4.0/5. These technology preferences are likely a result of inadequate support and frustration with learning to use mobile technologies.[17] It is significant to note that many app design studies prioritize developing a fall prevention app that is designed to address end-user requirements[16] [18] [19] as the only mode to deliver exercises to older people even though our results suggest that a portion of the older adult population may not be able or willing to use a mobile app for exercise. Although we addressed this issue by developing a set of “lower tech” resources, more testing is required to determine how consistently each of our tools (app, website, handouts) is used and their impact.


Our study has several limitations that may be addressed in future work. Using an HCD process allowed us to collect feedback from older adults, which helped to validate and build upon their user requirements. Most of our participants are older white women. The study was conducted during the COVID-19 public health emergency. While we advertised for participants in the community settings where we did our testing, we were limited to those who were participating in community activities at that time. During our focus groups, a minority of participants failed the fall risk screening indicating that they were at high risk for falls. This could be a limitation of using a self-reported measure versus recruiting a cohort of participants based on evidence-based risk factors. For future studies, it would be ideal to recruit a larger sample of older adult participants that have racial, ethnic, and gender diversity that screen positive for fall risk to better reflect our target users for the app. Currently, this app is designed to help community-dwelling older adults who are at risk for falls to improve their baseline strength, gait, and balance capabilities. Future work may include expanding exercise levels within the app to help users continue progressing their strength and balance beyond the four levels currently included. Lastly, evidence of the effectiveness of mHealth interventions to reduce fall outcomes is lacking.[15] This app is part of the suite of exercise tools that will be delivered using the CDS intervention for primary care in our eSTEPS (Electronic Strategies and Tailored Exercise to Prevent Fall) randomized clinical trial (NCT04993781), in which falls in older adults is the primary outcome measure. This trial is ongoing in primary care practices, where providers will screen patients for fall risk, and the eSTEPS provider-facing CDS[41] will help them to prescribe the right exercise program and provide easy access within their EHR workflows to “high tech to low tech” eSTEPS tools developed in this study for patients at risk for falls. We are also making the eSTEPS fall prevention tools available through exercise handouts and posters with QR codes in the primary care intervention clinics.
Conclusion
We used a multiphase, HCD process featuring focus groups, usability evaluation, and subject-matter expert meetings to build a fall prevention exercise app for primary care patients with a corresponding website and handouts. Involving older adult participants to validate user requirements resulted in a user-friendly and acceptable mobile app. Per recurrent themes in our feedback, we integrated the following: (1) A clear overview of the exercise plan that correlates with the preidentified exercise goals, (2) links to other fall prevention resources, (3) design elements to promote adherence and motivation to exercise such as progress checks, social network support, and motivational messaging, and (4) exercise content available outside of the app for individuals who prefer “lower tech” options. Participants' generally reported high scores on the Health ITUES, indicating greater perceived usability.
Clinical Relevance Statement
These exercise resources may be prescribed by PCPs for patients who are at risk of falls. Developing the app using a human-centered design approach, as well as providing a website and handouts, offers patients and PCPs a home-based intervention that meets their needs, increasing the likelihood of adherence and success. This app is currently being tested as part of the eSTEPS CDS intervention in primary care practices in an RCT, with the goal of reducing the incidence of falls in older adults.
Multiple-Choice Questions
-
When recommending exercise to community-dwelling older adults, which of the following is the most effective for fall prevention?
-
Walking 30 minutes several days per week.
-
Using a treadmill or elliptical machine for 30 minutes several days per week.
-
Doing gait, strength, and balance exercises several days per week.
-
Swimming laps several days per week.
Correct Answer: The correct answer is option c. Doing gait, strength, and balance exercises several days per week
Rationale: Gait, strength, and balance exercises are essential components of fall prevention programs, especially for older adults. Gait training exercises can help individuals correct irregular walking patterns and promote a more stable and efficient gait, reducing the risk of tripping or stumbling. Muscle weakness, especially in the lower body, is a common risk factor for falls. Strengthening exercises, particularly those targeting the legs and core, can help older adults improve their muscle mass and strength. This, in turn, enhances their ability to control their movements and maintain stability when walking or standing. Balance is a critical skill for maintaining stability during daily activities. Balance exercises challenge the neuromuscular system to improve proprioception and equilibrium. By regularly practicing balance exercises, individuals can better adapt to various terrains and situations, reducing the likelihood of stumbling or falling. Walking and elliptical exercise is good for cardiac health but may not be safe for people who are unsteady on their feet or for those with poor balance. There is insufficient evidence to show that yoga prevents falls.
-
-
When designing interventions for older patients, which of the following practices will result in a more successful project?
-
Conducting usability testing only right before you implement the app.
-
Engaging users during each stage of the design and development process.
-
Test the prototype with the clinicians that know the patients the best.
-
Avoid any digital interventions because older adults don't use technology.
Correct Answer: The correct answer is option b. Engaging users during each stage of the design and development process.
Rationale: A HCD process results in systems that are more usable and useful. Principles of HCD include focusing on the users, their needs and requirements, and employing multiple methods through the process to design and evaluate systems with target users.
While usability testing is an important part of identifying usability issues, it should be done early and often to avoid rework of systems at the end of the development process. Secondary users and additional stakeholders, such as clinicians, should be involved but the primary user must directly test the system. Providing a range of usable tools, including digital, that were designed based on user requirements will lead to higher levels of adoption.
-
Conflict of Interest
None declared.
Acknowledgments
We would like to thank all participants for devoting time to our study, including the BWH Patient and Family Advisory Council (PFAC), the local YMCA, and the Brookline Senior Center. We thank our app developer, Zco Corporation, for providing multiple revisions and building our app from concept to functioning prototype. We also thank Lisa Quintiliani for her contributions to the HCD process for the fall prevention exercise app as our motivational subject-matter expert. This project was funded by the National Institute on Aging (NIA; grant no.: 2022P001055).
Protection of Human and Animal Subjects
The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the Mass General Brigham Institutional Review Board.
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- 20 Rice H, Garabedian PM, Shear K. et al. Clinical decision support for fall prevention: defining end-user needs. Appl Clin Inform 2022; 13 (03) 647-655
- 21 Yang Y, Wang K, Liu H. et al. The impact of Otago exercise programme on the prevention of falls in older adult: a systematic review. Front Public Health 2022; 10: 953593
- 22 International Organization for Standardization (ISO). Ergonomics of human-system interaction—Part 210: human-centered design for interactive systems. Published July 2019. Accessed October 2, 2023. https://www.iso.org/standard/77520.html
- 23 Melles M, Albayrak A, Goossens R. Innovating health care: key characteristics of human-centered design. Int J Qual Health Care 2021; 33 (Supplement_1): 37-44
- 24 Toni E, Pirnejad H, Makhdoomi K, Mivefroshan A, Niazkhani Z. Patient empowerment through a user-centered design of an electronic personal health record: a qualitative study of user requirements in chronic kidney disease. BMC Med Inform Decis Mak 2021; 21 (01) 329
- 25 Brunner J, Chuang E, Goldzweig C, Cain CL, Sugar C, Yano EM. User-centered design to improve clinical decision support in primary care. Int J Med Inform 2017; 104: 56-64
- 26 Garabedian PM, Gannon MP, Aaron S, Wu E, Burns Z, Samal L. Human-centered design of clinical decision support for management of hypertension with chronic kidney disease. BMC Med Inform Decis Mak 2022; 22 (01) 217
- 27 Burns ER, Kakara R, Moreland B. A CDC Compendium of Effective Fall Interventions: What Works for Community-Dwelling Older Adults. 4th ed. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; Atlanta, GA: 2022
- 28 Casey CM, Parker EM, Winkler G, Liu X, Lambert GH, Eckstrom E. Lessons learned from implementing CDC's STEADI falls prevention algorithm in primary care. Gerontologist 2017; 57 (04) 787-796
- 29 Kuniavsky M. Observing the user experience: a practitioner's guide to user research. Elsevier; 2003
- 30 Krueger RA, Casey MA. Focus Groups: A Practical Guide for Applied Research. 5th Ed.. Sage Publications; 2014: 280
- 31 van Leeuwen D, Mittelman M, Fabian L, Lomotan EA. Nothing for me or about me, without me: codesign of clinical decision support. Appl Clin Inform 2022; 13 (03) 641-646
- 32 Faulkner L. Beyond the five-user assumption: benefits of increased sample sizes in usability testing. Behav Res Methods Instrum Comput 2003; 35 (03) 379-383
- 33 Schnall R, Cho H, Liu J. Health Information Technology Usability Evaluation Scale (Health-ITUES) for usability assessment of mobile health technology: validation study. JMIR Mhealth Uhealth 2018; 6 (01) e4
- 34 Yen PY, Sousa KH, Bakken S. Examining construct and predictive validity of the Health-IT usability evaluation scale: confirmatory factor analysis and structural equation modeling results. J Am Med Inform Assoc 2014; 21 (e2): e241-e248
- 35 Panel on Prevention of Falls in Older Persons, American Geriatrics Society and British Geriatrics Society. Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. J Am Geriatr Soc 2011; 59 (01) 148-157
- 36 Nevedal AL, Reardon CM, Opra Widerquist MA. et al. Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implement Sci 2021; 16 (01) 67
- 37 Holdsworth LM, Safaeinili N, Winget M. et al. Adapting rapid assessment procedures for implementation research using a team-based approach to analysis: a case example of patient quality and safety interventions in the ICU. Implement Sci 2020; 15 (01) 12
- 38 Glasgow RE, Chambers D. Developing robust, sustainable, implementation systems using rigorous, rapid and relevant science. Clin Transl Sci 2012; 5 (01) 48-55
- 39 Yang Y, Boulton E, Todd C. Measurement of adherence to mHealth physical activity interventions and exploration of the factors that affect the adherence: scoping review and proposed framework. J Med Internet Res 2022; 24 (06) e30817
- 40 Sun RT, Han W, Chang HL, Shaw MJ. Motivating adherence to exercise plans through a personalized mobile health app: enhanced action design research approach. JMIR Mhealth Uhealth 2021; 9 (06) e19941
- 41 Tejeda CJ, Garabedian PM, Rice H. et al. Development and usability testing of an exercise-based primary care fall prevention clinical decision support tool. . AMIA Annu Symp Proc 2023
Address for correspondence
Publication History
Received: 02 October 2023
Accepted: 22 January 2024
Accepted Manuscript online:
13 February 2024
Article published online:
10 July 2024
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- 19 Erfani S, Erfani SM, Ramin K. A Smartphone Health Application To Facilitate Falls Prevention Practices For Older Adults. Paper presented at: 27th European Conference on Information Systems (ECIS); June 8–14, 2019; Stockholm & Uppsala, Sweden
- 20 Rice H, Garabedian PM, Shear K. et al. Clinical decision support for fall prevention: defining end-user needs. Appl Clin Inform 2022; 13 (03) 647-655
- 21 Yang Y, Wang K, Liu H. et al. The impact of Otago exercise programme on the prevention of falls in older adult: a systematic review. Front Public Health 2022; 10: 953593
- 22 International Organization for Standardization (ISO). Ergonomics of human-system interaction—Part 210: human-centered design for interactive systems. Published July 2019. Accessed October 2, 2023. https://www.iso.org/standard/77520.html
- 23 Melles M, Albayrak A, Goossens R. Innovating health care: key characteristics of human-centered design. Int J Qual Health Care 2021; 33 (Supplement_1): 37-44
- 24 Toni E, Pirnejad H, Makhdoomi K, Mivefroshan A, Niazkhani Z. Patient empowerment through a user-centered design of an electronic personal health record: a qualitative study of user requirements in chronic kidney disease. BMC Med Inform Decis Mak 2021; 21 (01) 329
- 25 Brunner J, Chuang E, Goldzweig C, Cain CL, Sugar C, Yano EM. User-centered design to improve clinical decision support in primary care. Int J Med Inform 2017; 104: 56-64
- 26 Garabedian PM, Gannon MP, Aaron S, Wu E, Burns Z, Samal L. Human-centered design of clinical decision support for management of hypertension with chronic kidney disease. BMC Med Inform Decis Mak 2022; 22 (01) 217
- 27 Burns ER, Kakara R, Moreland B. A CDC Compendium of Effective Fall Interventions: What Works for Community-Dwelling Older Adults. 4th ed. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; Atlanta, GA: 2022
- 28 Casey CM, Parker EM, Winkler G, Liu X, Lambert GH, Eckstrom E. Lessons learned from implementing CDC's STEADI falls prevention algorithm in primary care. Gerontologist 2017; 57 (04) 787-796
- 29 Kuniavsky M. Observing the user experience: a practitioner's guide to user research. Elsevier; 2003
- 30 Krueger RA, Casey MA. Focus Groups: A Practical Guide for Applied Research. 5th Ed.. Sage Publications; 2014: 280
- 31 van Leeuwen D, Mittelman M, Fabian L, Lomotan EA. Nothing for me or about me, without me: codesign of clinical decision support. Appl Clin Inform 2022; 13 (03) 641-646
- 32 Faulkner L. Beyond the five-user assumption: benefits of increased sample sizes in usability testing. Behav Res Methods Instrum Comput 2003; 35 (03) 379-383
- 33 Schnall R, Cho H, Liu J. Health Information Technology Usability Evaluation Scale (Health-ITUES) for usability assessment of mobile health technology: validation study. JMIR Mhealth Uhealth 2018; 6 (01) e4
- 34 Yen PY, Sousa KH, Bakken S. Examining construct and predictive validity of the Health-IT usability evaluation scale: confirmatory factor analysis and structural equation modeling results. J Am Med Inform Assoc 2014; 21 (e2): e241-e248
- 35 Panel on Prevention of Falls in Older Persons, American Geriatrics Society and British Geriatrics Society. Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. J Am Geriatr Soc 2011; 59 (01) 148-157
- 36 Nevedal AL, Reardon CM, Opra Widerquist MA. et al. Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implement Sci 2021; 16 (01) 67
- 37 Holdsworth LM, Safaeinili N, Winget M. et al. Adapting rapid assessment procedures for implementation research using a team-based approach to analysis: a case example of patient quality and safety interventions in the ICU. Implement Sci 2020; 15 (01) 12
- 38 Glasgow RE, Chambers D. Developing robust, sustainable, implementation systems using rigorous, rapid and relevant science. Clin Transl Sci 2012; 5 (01) 48-55
- 39 Yang Y, Boulton E, Todd C. Measurement of adherence to mHealth physical activity interventions and exploration of the factors that affect the adherence: scoping review and proposed framework. J Med Internet Res 2022; 24 (06) e30817
- 40 Sun RT, Han W, Chang HL, Shaw MJ. Motivating adherence to exercise plans through a personalized mobile health app: enhanced action design research approach. JMIR Mhealth Uhealth 2021; 9 (06) e19941
- 41 Tejeda CJ, Garabedian PM, Rice H. et al. Development and usability testing of an exercise-based primary care fall prevention clinical decision support tool. . AMIA Annu Symp Proc 2023









