Implementation and Evaluation of a Mobile-Based Exercise Intervention for Knee Osteoarthritis in Rural Communities: A Mixed-Methods Study

Implementation and Evaluation of a Mobile-Based Exercise Intervention for Knee Osteoarthritis in Rural Communities: A Mixed-Methods Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Implementation and Evaluation of a Mobile-Based Exercise Intervention for Knee Osteoarthritis in Rural Communities: A Mixed-Methods Study Subasri R, Abishek J R, Manju Bashini Manoharan, Vadivelan Kanniappan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8299400/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Osteoarthritis (OA) is a common and disabling joint disorder, particularly in rural areas where access to healthcare is limited. Digital health interventions, including mobile applications, offer a potential approach to support self-management, improve mobility, and reduce pain. This study aimed to evaluate the effectiveness, acceptability, and user experiences of a mobile-based exercise intervention for individuals with knee OA in rural communities. Methods A community-based mixed-methods study was conducted in Mangalore Village and M. Puthur, Tamil Nadu. Fifty adults (≥ 40 years) with mild knee OA were recruited. Participants underwent a one-week orientation and performed app-guided exercises thrice weekly for twelve weeks. Pain and functional mobility were assessed pre- and post-intervention using the Numerical Pain Rating Scale (NPRS) and Timed Up and Go (TUG) test. A subset of ten participants was selected for in-depth qualitative interviews exploring perceptions, challenges, and suggestions for improvement. Quantitative data were analyzed using paired t-tests and Wilcoxon Signed Rank tests. Qualitative data underwent thematic analysis with open, axial, and selective coding. Results TUG scores improved significantly from 17.62 ± 1.29 s to 16.50 ± 1.36 s (mean difference = 1.12 s, p < 0.001), and NPRS scores decreased from 8.1 ± 1.45 to 5.9 ± 1.3 (p < 0.001). Three qualitative themes emerged: ( 1 ) insights and perceived benefits, including flexibility and reduced hospital visits; ( 2 ) challenges such as language barriers, limited digital literacy, and network issues; and ( 3 ) suggestions for improvement, including local language support, video demonstrations, and reminders. Conclusion Mobile-based exercise interventions can improve pain and mobility in rural adults with knee OA. Future adaptations should address cultural, linguistic, and infrastructural barriers to enhance usability and adherence. Osteoarthritis Digital health Exercise NPRS scale Rural communities BACKGROUND Osteoarthritis (OA) is a widespread and debilitating joint disorder affecting millions of people globally, particularly in rural areas where healthcare access may be limited. OA involves the gradual wear and tear of the protective cartilage at the ends of bones in the joints, resulting in pain, stiffness, and decreased mobility( 1 , 2 ). Beyond physical symptoms, OA can lead to psychological and social challenges, including depression, anxiety, fatigue, and social isolation ( 3 ). These challenges are often intensified in rural communities due to geographic isolation, limited healthcare infrastructure, and financial constraints( 2 ). Digital health solutions offer a promising approach to address these challenges by leveraging technologies such as mobile applications, telemedicine, and remote monitoring devices. These solutions provide personalized, accessible, and cost-effective care, empowering patients to actively manage their condition and improve overall quality of life ( 3 ). By exploring the potential of digital health interventions for remote OA management, this study aims to examine an innovative approach to enhancing access to care, promoting self-management, and improving well-being among individuals with OA in rural areas( 4 ). Globally, OA affects over 500 million people, representing approximately 7–8% of the world population( 2 – 4 ). In 2019, the age-standardized global prevalence of total OA was 6,348.25 per 100,000 people, reflecting a gradual increase of 0.12% per year from 1990 onwards( 1 ). In 2020, OA affected an estimated 595 million individuals worldwide (95% uncertainty interval 535–656 million), accounting for 7.6% (95% UI 6.8–8.4) of the global population( 3 , 4 ). OA is a major contributor to disability, with the global age-standardized rate of years lived with disability (YLDs) for total OA reaching 255.0 YLDs per 100,000 people in 2020, representing a 9.5% increase since 1990( 3 – 6 ) . In India, the age-standardized prevalence of OA increased from 4,895 per 100,000 in 1990 to 5,313 per 100,000 in 2019, with the total number of affected individuals rising from 23.46 million to 62.35 million during the same period( 1 , 3 , 5 , 7 ). OA accounted for 1.48% of all YLDs in India in 2019, ranking as the 20th most common cause, up from the 23rd most common in 1990( 1 , 3 ). Prevalence, incidence, and disability-adjusted life years (DALYs) for OA, particularly knee OA, are consistently higher among females, and certain states, including Goa, Rajasthan, and Kerala, exhibit the highest age-standardised prevalence( 8 – 10 ). Clinically, OA presents with joint pain and stiffness that worsen with activity and improve with rest. Prolonged disease can result in reduced range of motion, joint deformity, bony enlargement, crepitus, effusions, and tenderness on palpation, with characteristic hand findings such as Bouchard and Heberden nodes( 1 – 4 , 8 , 10 , 11 ). Digital health interventions have shown potential in improving outcomes for individuals with OA, particularly in rural communities where in-person care is limited( 12 – 14 ). Such interventions often include mobile applications, telemedicine, remote monitoring devices, and SMS-based programs to support self-management through personalized guidance, education, and social support( 13 , 14 ). Holistic, activity-focused digital interventions can promote higher adherence and lower attrition compared to usual care, empowering patients to take an active role in managing their condition( 11 , 12 ). Telemedicine enables real-time communication with healthcare professionals, expanding access to treatment for those in remote areas( 2 , 15 ). Addressing these challenges, the present study explores the implementation of mobile-based digital health solutions for OA management in a rural context, evaluating their potential to enhance self-management, accessibility, and overall outcomes( 16 ). The study aimed to evaluate the effectiveness and acceptability of a mobile-based exercise intervention for adults with mild knee osteoarthritis in rural communities and to explore participants’ experiences, perceptions, and challenges in using a digital health tool for self-directed exercise. The objectives were to assess changes in functional mobility and pain intensity following a 12-week exercise program and to understand participants’ perspectives on the usability, perceived benefits, and barriers associated with the mobile application. METHODS Study Design This was a community-based mixed-methods study combining quantitative pre-post evaluation with qualitative inquiry. The study aimed to assess the feasibility, acceptability, and preliminary effectiveness of a mobile-based exercise intervention for individuals with knee osteoarthritis in rural communities. Study Setting and Duration The study was conducted in Mangalore Village and M. Puthur, Cuddalore District, Tamil Nadu. The total study period was four months, including one week of participant sensitisation and twelve weeks of intervention. Once recruited, participants underwent a one-week orientation programme before starting the intervention. Participants Recruitment Participants were identified using the community registry maintained by the physiotherapy department of the primary health centre, which included residents with musculoskeletal complaints. Sixty-eight individuals who met the eligibilty criteria were approached, and fifty participants consented to participate. Two were excluded for lack of smartphone access, and sixteen declined due to time constraints, reluctance to exercise, or discomfort with mobile applications. Eligibility Criteria Intervention Mobile Application The intervention utilized the “Knee Osteoarthritis Exercises App for Android” ( https://share.google/Ic8QXryTaHVpxBtUh ), a freely available English-language mobile app containing pictorial demonstrations of fifteen exercises suitable for mild knee osteoarthritis. No modifications were made to the app; Because the app did not provide regional language instructions or audio guidance, the research team explained how to interpret each image and how to navigate the application interface. Exercise Program, Adherence and Monitoring Participants performed exercises three times per week on alternate days, three sessions per day, with two sets of ten repetitions per exercise, for twelve weeks. Weekly investigator phone calls assessed adherence, difficulties, and symptom aggravation. No objective app usage logs were available; adherence was monitored via participant self-report during calls. Sample adherence questions included: “Have you performed exercises three times this week?”, “On each day, did you perform three sessions?”, “For each session, were you able to complete all 10 repetitions per set?”, “Did you experience any difficulty or aggravation of symptoms?”. No real-time monitoring was embedded in the app. Weekly telephone calls were conducted by the investigator to confirm adherence and monitor safety. Participants reported full adherence, and no adverse events were noted. Outcome Measures a) Quantitative Assessments Baseline assessments were conducted following the sensitisation period. Pain intensity was measured using the Numerical Pain Rating Scale (NPRS), where participants rated their worst pain in the preceding 24 hours. Mobility was assessed using the 10-metre Timed Up and Go (TUG) test following a standardized protocol in which the participant rose from a chair, walked ten metres at a comfortable pace, returned to the chair, and sat down. A demonstration was provided, and time was recorded using a smartphone stopwatch. The same unblinded assessor performed all pre- and post-intervention assessments; given the objective nature of the TUG test and the self-reported nature of the NPRS, assessor bias was considered minimal. Post-intervention assessments were conducted twenty-four hours after the final exercise session. b) Qualitative Methods Purpose The qualitative component aimed to explore participants’ perceptions, experiences, and acceptability of using a mobile-based exercise application to manage knee osteoarthritis in a rural community. The focus was on understanding barriers and facilitators to engagement, usability of digital tools, and the perceived impact on pain management and joint function. Methodological Approach A descriptive qualitative approach was employed, guided by thematic analysis. This approach allowed an in-depth exploration of participants’ lived experiences and perspectives, emphasizing context-specific insights relevant to rural adults with limited prior exposure to digital health interventions. Participant Selection and Interviews From the cohort of fifty participants, ten were selected for qualitative interviews using simple random selection to ensure that perspectives were not intentionally biased toward more motivated or more digitally literate individuals. Interviews were conducted in Tamil by the principal investigator, a physiotherapy researcher with prior qualitative research experience. Interviews were audio-recorded, held in private spaces within participants’ homes, and lasted approximately fifteen to twenty minutes. Participants chose whether to be interviewed alone or with a family member present. Interviews were conducted in Tamil audio-recorded, and held in participants’ homes. The relatively short duration of interviews was appropriate given the focused nature of questions and participants’ limited prior experience with digital health tools, allowing efficient capture of key insights. Interview Guide A semi-structured guide specific to this study was developed and formally validated by community health care experts for the language clarity and appropriateness was used to explore key domains (a sample of the questions is attached in the supplementary file). The flow of the interview included: Initial perceptions of digital health tools for OA management, Comfort with technology and prior experience with mobile applications, Expectations and perceived benefits of the exercise app, Challenges anticipated in using the app regularly, and Suggestions for improving usability and support. This approach allowed participants to freely express their experiences while ensuring that core topics relevant to feasibility, acceptability, and engagement were addressed. Data Analysis a) Quantitative analysis Data were analyzed using IBM SPSS Statistics (Version 26.0). Participant demographics and baseline characteristics were summarized using descriptive statistics, with continuous variables such as age and TUG scores presented as mean ± standard deviation (SD), and categorical variables such as gender and side affected reported as frequencies and percentages. The normality of outcome variables was assessed using both the Kolmogorov–Smirnov and Shapiro–Wilk tests. Pre- and post-intervention TUG scores were normally distributed (p > 0.05), whereas the calculated TUG change scores (Pre – Post) were not normally distributed (p < 0.05). NPRS scores are ordinal by nature and were treated as non-parametric data. To evaluate the effect of the intervention, paired-samples t-tests were used to compare pre- and post-intervention TUG scores. Changes in pain intensity, measured using the Numerical Pain Rating Scale (NPRS), were analyzed using the Wilcoxon Signed Rank Test. For subgroup analyses, change scores for TUG and NPRS (Pre – Post) were calculated to assess whether improvements differed according to gender or side affected (unilateral vs bilateral OA). Given the non-normal distribution of the change scores, Mann–Whitney U tests were used for comparisons between groups. Across all analyses, a p-value < 0.05 was considered statistically significant. Table 1 Demographic Characteristics of the Study Participants (n = 50) Variable Category / Statistic Value Gender Men 32 (64.0%) Women 18 (36.0%) Side Affected Unilateral 27 (54.0%) Bilateral 23 (46.0%) Age (years) Mean ± SD 48.08 ± 5.02 Range 40–58 Duration of Pain (years) Mean ± SD 5.82 ± 2.16 Range 2–10 Table 1 summarizes the demographic profile of the 50 study participants. Most participants were men (64%), and 54% presented with unilateral knee involvement. The mean age of the sample was 48.08 years (SD = 5.02), with ages ranging from 40 to 58 years. The average duration of knee pain was 5.82 years (SD = 2.16), with a reported range between 2 and 10 years. Table 2 Pre- and Post-Intervention Outcomes (TUG and NPRS, n = 50) Outcome Pre-Intervention Post-Intervention Mean / Median Difference 95% CI / IQR Test Used p-value TUG Test (seconds) 17.62 ± 1.29 16.50 ± 1.36 1.12 0.92–1.33 Paired t-test < 0.001 NPRS (0–10) 8.1 ± 1.45 5.9 ± 1.3 2.2 – Wilcoxon Signed Rank Test < 0.001 Table 2 summarizes the pre- and post-intervention outcomes for functional mobility (TUG) and pain intensity (NPRS) among 50 participants. TUG scores improved significantly after the intervention, decreasing from 17.62 ± 1.29 s to 16.50 ± 1.36 s (mean difference = 1.12 s, 95% CI: 0.92–1.33, p < 0.001). NPRS scores also changed significantly (mean difference = 2.2, p < 0.001, Wilcoxon Signed Rank Test). Table 3 Subgroup Analysis of TUG and NPRS Change Scores by Gender and Side Affected (n = 50) Outcome Subgroup n Mean Rank U / Z p-value Interpretation TUG Change (seconds) Men 32 27.06 U = 238, Z = − 1.011 0.312 No significant difference Women 18 22.73 Unilateral 27 23.50 U = 364.5, Z = 1.051 0.293 No significant difference Bilateral 23 27.85 NPRS Change Men 32 26.38 U = 260, Z = − 0.609 0.542 No significant difference Women 18 23.94 Unilateral 27 24.72 U = 331.5, Z = 0.440 0.660 No significant difference Bilateral 23 26.41 TUG Change = Pre – Post TUG (seconds), NPRS Change = Pre – Post NPRS (0–10 scale). Mann–Whitney U test was used due to non-normal distribution of change scores. b) Qualitative analysis Transcription, Translation, and Analysis Interviews were transcribed verbatim in Tamil by a trained research assistant who was not involved in data collection. Translations into English were completed by a bilingual researcher, and an independent bilingual reviewer verified translation accuracy to ensure preservation of original meanings. Data analysis followed an inductive thematic analysis approach. Coding was performed manually in Microsoft Excel by two independent coders. Open, axial, and selective coding steps were applied iteratively. Coding and analysis were conducted concurrently with data collection, allowing emerging concepts to be reflected in subsequent interviews. Data saturation was considered achieved when two consecutive interviews yielded no new codes. Any discrepancies between coders were resolved through consensus, and when necessary, a third researcher adjudicated disagreements. Safety No adverse events, such as exercise-related pain flare or falls, were reported during weekly follow-up calls or at final assessment. RESULTS a) Quantitative results Participant Characteristics A total of 50 participants were included in the study, with a mean age of 48.08 ± 5.02 years (range 40–58). The majority were men (32, 64%) and 27 participants (54%) had unilateral knee osteoarthritis, while 23 participants (46%) had bilateral involvement. The mean duration of osteoarthritis was 5.82 ± 2.16 years. These demographic details are summarized in Table 1. Pre- and Post-Intervention Outcomes Functional mobility, measured by the Timed Up and Go (TUG) test, improved significantly following the intervention. Mean TUG scores decreased from 17.62 ± 1.29 s pre-intervention to 16.50 ± 1.36 s post-intervention, representing a mean improvement of 1.12 s (95% CI: 0.92–1.33), t(49) = 11.01, p < 0.001. Pain intensity, assessed using the Numerical Pain Rating Scale (NPRS), also changed significantly after the intervention. Median NPRS scores decreased from 6 [IQR: 5–7] pre-intervention to 4 [IQR: 3–5] post-intervention (Z = − 5.072, p < 0.001, Wilcoxon Signed Rank Test). These findings indicate that the intervention significantly improved mobility and reduced pain among participants (Table 2). Subgroup Analysis Subgroup analyses were performed to evaluate whether improvements differed by gender or side affected (unilateral vs bilateral OA). For TUG change scores, there was no significant difference between men (mean rank = 27.06) and women (mean rank = 22.73), U = 238, Z = − 1.011, p = 0.312, nor between participants with unilateral (mean rank = 23.50) and bilateral OA (mean rank = 27.85), U = 364.5, Z = 1.051, p = 0.293. For NPRS change scores, no significant differences were observed between men (mean rank = 26.38) and women (mean rank = 23.94), U = 260, Z = − 0.609, p = 0.542, or between unilateral (mean rank = 24.72) and bilateral OA (mean rank = 26.41), U = 331.5, Z = 0.440, p = 0.660. These results suggest that the intervention’s effects on functional mobility and pain were consistent across gender and side affected (Table 3). Qualitative Results From the in-depth interviews with ten participants, three major themes emerged: ( 1 ) Insights and Perceived Benefits, ( 2 ) Challenges in Using the Digital Tool, and ( 3 ) Suggestions for Improvement (Table 4). These themes reflected participants’ perspectives on feasibility, acceptability, usability, and engagement with the mobile-based exercise application for knee osteoarthritis in a rural community. Table 4 Coding Framework of Participants’ Perspectives on Using a Mobile-Based Exercise Application for Knee Osteoarthritis Themes Subthemes / Axial Coding Illustrative Codes / Open Coding Insights and Perceived Benefits Perception Initially thought app would be less effective; Limited awareness of digital tools; Perceived as remote consultation Advantages and Experience Performing Exercises Reduced hospital visits; Saved time; Flexible use anytime/anywhere; Felt relaxed; Reduced pain; Muscles loosened; Not effective / No pain improvement Challenges in Using the Digital Tool Personal Barriers Unfamiliar with smartphone; Reliance on family for access; English-language difficulty; Needed assistance Network and Service Interruptions Poor network in farms/outside village; Intermittent power cuts, especially in rainy season Suggestions for Improvement Technical Features Clearer exercise images; Reminders to follow schedule Cultural and Language Considerations App localized in Tamil; Reduced dependency on others for use Preferred Support Methods Video-based guidance; Live video calls for teaching and monitoring exercises Theme 1: Insights and Perceived Benefits Subtheme 1: Perception Participants initially had limited awareness of digital health tools for exercise or pain management. Many perceived the app as a form of remote consultation rather than an exercise intervention. One participant reported “It was more like consulting the doctor using mobile phones.” When first introduced to the app, some participants thought it would have minimal effects, Initially, I thought it would be less effective, but it was more effective than I thought. Subtheme 2: Advantages and Experience Performing Exercises Despite initial skepticism, participants recognized several practical benefits of mobile-based exercise. They reported that the app reduced the need for hospital visits, saved time, and allowed flexible usage without specific place or time constraints. It was easy to use the application and could be used at any place and any time. Participants’ experiences with the exercise program varied. Several reported pain relief, relaxation, and reduced knee stiffness after performing the exercises: I felt my muscles around the knee loosened and my pain reduced; I felt relaxed after performing the exercises. Conversely, some participants did not perceive any improvement in pain: I did not feel my pain reduced; it was not effective. Theme 2: Challenges in Using the Digital Tool Subtheme 1: Personal Barriers Participants identified personal barriers related to technology use and language proficiency. Some were unfamiliar with smartphones or relied on family members to access the app, while others faced difficulties due to English-language instructions. I did not know English, so it was difficult to read the instructions; I needed help to use the digital tool. My son had a smartphone. I used a button phone and needed assistance to use modern technology. Subtheme 2: Network and Service Interruptions Rural infrastructure limitations posed additional challenges. Participants reported intermittent network connectivity and power outages, especially when outside the village or during adverse weather conditions: I had poor network and could not use my phone when I went to the farm; I had to come home to use it. Sometimes there was a power cut when using my computer, especially in rainy seasons. Theme 3: Suggestions for Improvement Subtheme 1: Technical Features Participants suggested enhancements to improve usability, such as clearer exercise images and reminders to perform exercises: The pictures could be clearer, and it would have helped if the app had reminders to follow the schedule. Subtheme 2: Cultural and Language Considerations Several participants recommended localizing the app into Tamil to increase accessibility for the broader rural community: I did not know English and found it difficult to use the app. It would have helped if it were in Tamil so I would not need anyone’s help. Subtheme 3: Preferred Support Methods Participants highlighted the potential value of video-based guidance and live supervision. It would have helped if the app showed videos of exercises, so I could remember the steps even if I forgot. Live video calls to teach and monitor exercises would have been more useful than just pictures. DISCUSSION The study focused on evaluating the potential of digital health solutions for managing osteoarthritis (OA) in rural communities, where access to healthcare is often limited. Both quantitative and qualitative findings highlighted the advantages and challenges of implementing mobile-based exercise interventions in this context. Quantitative data showed that participants experienced significant improvements in functional mobility and reductions in pain following a 12-week exercise program. The Timed Up and Go Test (TUG) demonstrated a mean improvement of 1.12 seconds (p < 0.05), while pain intensity measured by the Numerical Pain Rating Scale also decreased significantly, supporting the effectiveness of the intervention in improving joint function and reducing OA-related discomfort. These findings align with previous research, including Nelligan et al. (2020), which found that telehealth-delivered exercise programs improved pain and function in individuals with knee OA, and Shah et al. (2022), who reported that digital health interventions can be as effective as traditional treatments for exercise, education, and activity promotion.( 17 , 18 ) Qualitative interviews provided context for these quantitative outcomes, revealing that participants initially had limited awareness of digital health tools and often perceived the app as a form of remote consultation rather than an exercise intervention. Despite initial skepticism, participants acknowledged practical benefits such as reduced hospital visits, time savings, and flexibility to perform exercises at their convenience. Experiences with the exercises varied, with some participants reporting relaxation, reduced knee stiffness, and pain relief, while others perceived minimal improvement. These findings resonate with Nelligan et al. (2020), who emphasized that human connection and guidance are important in e-health interventions, and highlight the challenges of digital literacy and infrastructure in rural communities.( 18 ) Participants faced personal and technical barriers while engaging with the mobile application. Limited familiarity with smartphones, English-language instructions, intermittent network connectivity, and power outages in rural areas impeded independent use. Similar issues were reported in studies by Rasekaba et al. (2022) and Shah N et al. (2022), underscoring the influence of digital literacy, social support, and infrastructure on intervention uptake. Additionally, the application’s cultural and linguistic mismatch, being designed for a Western audience, reduced engagement and adherence, reflecting recommendations by Godziuk K et al. (2023) and Hale-Gallardo JL (2020) regarding the importance of culturally tailored and co-designed digital health solutions.( 13 , 17 , 19 , 20 ) The combination of quantitative and qualitative findings indicates that mobile-based exercise interventions can effectively support self-managed care for knee OA in rural settings, but the success of such interventions is contingent on addressing contextual challenges. Participants suggested improvements including clearer visual demonstrations, video-based guidance, reminders for scheduled exercises, and localization of content into Tamil to enhance accessibility and usability. These recommendations highlight the need for culturally and linguistically appropriate adaptations and ongoing support to optimize engagement and adherence. Limitations The study had several limitations. The quantitative evaluation did not include a formal feasibility assessment or objective measurement of adherence, relying instead on participant self-report during weekly calls, which may have introduced bias. The qualitative interviews were one-time, brief encounters lasting 15–20 minutes, limiting the depth of insights into participants’ experiences and engagement over time. The study was conducted in only two villages, which may restrict generalizability to other rural settings or populations with more severe osteoarthritis. Additionally, the mobile application was in English, requiring investigator guidance, which may not reflect the independent use of the app in routine practice. The short duration of follow-up did not allow assessment of long-term sustainability of exercise adherence or outcomes. Recommendations Future iterations of mobile-based exercise interventions should integrate local language instructions, provide clear visual or video demonstrations, and include reminders to encourage adherence. Incorporating brief training sessions or live supervision could support participants with limited smartphone experience. Addressing infrastructural challenges, such as network limitations or power interruptions, and designing content for offline use would improve accessibility. Larger studies across multiple rural communities with longer follow-up periods are warranted to validate these findings, assess long-term outcomes, and optimize digital interventions for broader use. CONCLUSION The mobile-based exercise program was effective in improving functional mobility and reducing pain among rural adults with knee osteoarthritis, and participants generally accepted the intervention as a practical tool for self-directed exercise. While initial perceptions were skeptical, experiences indicated that digital health tools could support exercise engagement when adequately explained and contextualized. Incorporating culturally and linguistically appropriate adaptations, along with visual or video-based guidance, may further enhance usability and participant confidence. Declarations Human ethics and consent to participate The study was conducted in accordance to Helsinki’s guidelines and Ethical approval was obtained from the Institutional Ethics Committee of SRM Medical College Hospital and Research Centre (IEC No. SRMIEC-ST0224-1081). Written informed consent was obtained from all participants, including consent for audio recording during qualitative interviews. Data were anonymized, securely stored, and accessible only to the principal investigator. Participants were recruited to the study following their voluntary willingness to participate. No participant of this study was less than 18, hence consent was only obtained from the participant. Participants were informed about the study procedures and informed consent was obtained from after ensuring that their responses would be held confidential and their identity will not be revealed anywhere. After ensuring that the data would only be used for research purposes, written consent was obtained from them Consent for publication: Not applicable Funding statements: Nil Availability of data and materials The datasets used and/or analysed during the current study are available from the PI on reasonable request. Conflicts of interest: The Authors declare no conflict of interest Clinical trial number: Not applicable Author Contributions S R: Conceptualisation, study design, data collection, drafting the manuscript, editing the draft, approval of final version AJR: conducting interviews, data transcription, coding of data, data analysis, reweing the manuscript, approval of final version MBM: Coding of data, data analysis, reweing the manuscript, approval of final version K V: Conceptualization, framework of the study, drafting results, proof corrections, approval of final version References Hinman RS, Lawford BJ, Nelligan RK, Bennell KL. Virtual Tools to Enable Management of Knee Osteoarthritis. Curr Treatm Opt Rheumatol [Internet]. 2023 Mar 11 [cited 2025 Dec 2];1–21. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10006574/ Brundisini F, Giacomini M, DeJean D, Vanstone M, Winsor S, Smith A. Chronic disease patients’ experiences with accessing health care in rural and remote areas: a systematic review and qualitative meta-synthesis. Ont Health Technol Assess Ser. 2013;13(15):1–33. McHugh CG, Kostic AM, Katz JN, Losina E. Effectiveness of remote exercise programs in reducing pain for patients with knee osteoarthritis: A systematic review of randomized trials. Osteoarthr Cartil Open. 2022 Sept;4(3):100264. Campos L, Costa D, Donato H, Nunes B, Cruz EB. Implementation of digital health in rural populations with chronic musculoskeletal conditions: A scoping review protocol. PLOS ONE [Internet]. 2023 Dec 22 [cited 2025 Dec 2];18(12):e0291638. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0291638 Chen T, Or CK, Chen J. Effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain: A systematic review and meta-analysis of randomized controlled trials. J Am Med Inf Assoc. 2021;28(2):414–23. Yang Y, Li S, Cai Y, Zhang Q, Ge P, Shang S, et al. Effectiveness of telehealth-based exercise interventions on pain, physical function and quality of life in patients with knee osteoarthritis: A meta-analysis. J Clin Nurs. 2023 June;32(11–12):2505–20. Campos L, Cardoso B, Galego M, Machado AT, Marques D, Santos C. Sou +: Reducing health inequities in rural populations with knee osteoarthritis. Procedia Comput Sci [Internet]. 2023 Jan 1 [cited 2025 Dec 2];219(C):1470–7. Available from: https://doi.org/10.1016/j.procs.2023.01.437 Cronström A, Dahlberg LE, Nero H, Ericson J, Hammarlund CS. I would never have done it if it hadn’t been digital: a qualitative study on patients’ experiences of a digital management programme for hip and knee osteoarthritis in Sweden. BMJ Open. 2019;9(5):e028388. Lawford BJ, Hinman RS, Kasza J, Nelligan R, Keefe F, Rini C, et al. Moderators of Effects of Internet-Delivered Exercise and Pain Coping Skills Training for People With Knee Osteoarthritis: Exploratory Analysis of the IMPACT Randomized Controlled Trial. J Med Internet Res. 2018;20(5):e10021. Kim J, Foucher K. Fall experiences from the perspectives of people with osteoarthritis: in their own words. Disabil Rehabil. 2024;46(1):77–85. Naeemabadi Mr, Fazlali H, Najafi S, Dinesen B, Hansen J. Telerehabilitation for Patients With Knee Osteoarthritis: A Focused Review of Technologies and Teleservices. JMIR Biomedical Engineering [Internet]. 2020 July 21 [cited 2025 Dec 2];5(1):e16991. Available from: https://biomedeng.jmir.org/2020/1/e16991 Patel KV, Hoffman EV, Phelan EA, Gell NM. Remotely Delivered Exercise to Rural Older Adults With Knee Osteoarthritis: A Pilot Study. ACR Open Rheumatol. 2022;4(8):735–44. Hale-Gallardo JL, Kreider CM, Jia H, Castaneda G, Freytes IM, Cowper Ripley DC, et al. Telerehabilitation for Rural Veterans: A Qualitative Assessment of Barriers and Facilitators to Implementation. J Multidiscip Healthc. 2020;13:559–70. Rose MJ, Costello KE, Eigenbrot S, Torabian K, Kumar D. Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review. JMIR Rehabil Assist Technol [Internet]. 2022 June 2 [cited 2025 Dec 2];9(2):e33521. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9204569/ Dahlberg LE, Dell’Isola A, Lohmander LS, Nero H. Improving osteoarthritis care by digital means - Effects of a digital self-management program after 24- or 48-weeks of treatment. PLOS ONE [Internet]. 2020 Mar 4 [cited 2025 Dec 2];15(3):e0229783. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229783 Moore MR, Galetta MS, Schwarzkopf R, Slover JD, Force Writing Committee. Patient Satisfaction and Interest in Telemedicine Visits Following Total Knee and Hip Replacement Surgery. Telemed J E Health. 2022 Sept;28(9):1309–16. Shah N, Costello K, Mehta A, Kumar D. Applications of Digital Health Technologies in Knee Osteoarthritis: Narrative Review. JMIR Rehabil Assist Technol. 2022 June 8;9(2):e33489. Nelligan RK, Hinman RS, Teo PL, Bennell KL. Exploring Attitudes and Experiences of People With Knee Osteoarthritis Toward a Self-Directed eHealth Intervention to Support Exercise: Qualitative Study. JMIR Rehabil Assist Technol. 2020;7(2):e18860. Rasekaba TM, Pereira P, Rani GV, Johnson R, McKechnie R, Blackberry I. Exploring Telehealth Readiness in a Resource Limited Setting: Digital and Health Literacy among Older People in Rural India (DAHLIA). Geriatr (Basel). 2022;7(2):28. Godziuk K, Prado CM, Quintanilha M, Forhan M. Acceptability and preliminary effectiveness of a single-arm 12-week digital behavioral health intervention in patients with knee osteoarthritis. BMC Musculoskelet Disord. 2023;24(1):129. Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8299400","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":563725969,"identity":"d082be37-e40b-4fd1-b216-35aeb219fdc3","order_by":0,"name":"Subasri R","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Subasri","middleName":"","lastName":"R","suffix":""},{"id":563725970,"identity":"2040d85d-1648-49fa-90fa-1c41f04d5ac1","order_by":1,"name":"Abishek J 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12:59:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1201427,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8299400/v1/97d96a1f-f3ac-42c9-93c2-6c7b91943f6e.pdf"},{"id":99309638,"identity":"38bf9926-4537-40e7-afcd-65285c6ae9c6","added_by":"auto","created_at":"2025-12-31 16:10:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15086,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299400/v1/b703e1261455b0f5e76dd663.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Implementation and Evaluation of a Mobile-Based Exercise Intervention for Knee Osteoarthritis in Rural Communities: A Mixed-Methods Study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eOsteoarthritis (OA) is a widespread and debilitating joint disorder affecting millions of people globally, particularly in rural areas where healthcare access may be limited. OA involves the gradual wear and tear of the protective cartilage at the ends of bones in the joints, resulting in pain, stiffness, and decreased mobility(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Beyond physical symptoms, OA can lead to psychological and social challenges, including depression, anxiety, fatigue, and social isolation (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). These challenges are often intensified in rural communities due to geographic isolation, limited healthcare infrastructure, and financial constraints(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDigital health solutions offer a promising approach to address these challenges by leveraging technologies such as mobile applications, telemedicine, and remote monitoring devices. These solutions provide personalized, accessible, and cost-effective care, empowering patients to actively manage their condition and improve overall quality of life (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). By exploring the potential of digital health interventions for remote OA management, this study aims to examine an innovative approach to enhancing access to care, promoting self-management, and improving well-being among individuals with OA in rural areas(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlobally, OA affects over 500\u0026nbsp;million people, representing approximately 7\u0026ndash;8% of the world population(\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In 2019, the age-standardized global prevalence of total OA was 6,348.25 per 100,000 people, reflecting a gradual increase of 0.12% per year from 1990 onwards(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2020, OA affected an estimated 595\u0026nbsp;million individuals worldwide (95% uncertainty interval 535\u0026ndash;656\u0026nbsp;million), accounting for 7.6% (95% UI 6.8\u0026ndash;8.4) of the global population(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). OA is a major contributor to disability, with the global age-standardized rate of years lived with disability (YLDs) for total OA reaching 255.0 YLDs per 100,000 people in 2020, representing a 9.5% increase since 1990(\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eIn India, the age-standardized prevalence of OA increased from 4,895 per 100,000 in 1990 to 5,313 per 100,000 in 2019, with the total number of affected individuals rising from 23.46\u0026nbsp;million to 62.35\u0026nbsp;million during the same period(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). OA accounted for 1.48% of all YLDs in India in 2019, ranking as the 20th most common cause, up from the 23rd most common in 1990(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Prevalence, incidence, and disability-adjusted life years (DALYs) for OA, particularly knee OA, are consistently higher among females, and certain states, including Goa, Rajasthan, and Kerala, exhibit the highest age-standardised prevalence(\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eClinically, OA presents with joint pain and stiffness that worsen with activity and improve with rest. Prolonged disease can result in reduced range of motion, joint deformity, bony enlargement, crepitus, effusions, and tenderness on palpation, with characteristic hand findings such as Bouchard and Heberden nodes(\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDigital health interventions have shown potential in improving outcomes for individuals with OA, particularly in rural communities where in-person care is limited(\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Such interventions often include mobile applications, telemedicine, remote monitoring devices, and SMS-based programs to support self-management through personalized guidance, education, and social support(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Holistic, activity-focused digital interventions can promote higher adherence and lower attrition compared to usual care, empowering patients to take an active role in managing their condition(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Telemedicine enables real-time communication with healthcare professionals, expanding access to treatment for those in remote areas(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAddressing these challenges, the present study explores the implementation of mobile-based digital health solutions for OA management in a rural context, evaluating their potential to enhance self-management, accessibility, and overall outcomes(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study aimed to evaluate the effectiveness and acceptability of a mobile-based exercise intervention for adults with mild knee osteoarthritis in rural communities and to explore participants\u0026rsquo; experiences, perceptions, and challenges in using a digital health tool for self-directed exercise. The objectives were to assess changes in functional mobility and pain intensity following a 12-week exercise program and to understand participants\u0026rsquo; perspectives on the usability, perceived benefits, and barriers associated with the mobile application.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis was a community-based mixed-methods study combining quantitative pre-post evaluation with qualitative inquiry. The study aimed to assess the feasibility, acceptability, and preliminary effectiveness of a mobile-based exercise intervention for individuals with knee osteoarthritis in rural communities.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Setting and Duration\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in Mangalore Village and M. Puthur, Cuddalore District, Tamil Nadu. The total study period was four months, including one week of participant sensitisation and twelve weeks of intervention. Once recruited, participants underwent a one-week orientation programme before starting the intervention.\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eRecruitment\u003c/h2\u003e \u003cp\u003eParticipants were identified using the community registry maintained by the physiotherapy department of the primary health centre, which included residents with musculoskeletal complaints. Sixty-eight individuals who met the eligibilty criteria were approached, and fifty participants consented to participate. Two were excluded for lack of smartphone access, and sixteen declined due to time constraints, reluctance to exercise, or discomfort with mobile applications.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEligibility Criteria\u003c/h3\u003e\n\n\u003ch3\u003eIntervention\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMobile Application\u003c/h2\u003e \u003cp\u003eThe intervention utilized the \u003cb\u003e\u0026ldquo;Knee Osteoarthritis Exercises App for Android\u0026rdquo;\u003c/b\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://share.google/Ic8QXryTaHVpxBtUh\u003c/span\u003e\u003cspan address=\"https://share.google/Ic8QXryTaHVpxBtUh\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ), a freely available English-language mobile app containing pictorial demonstrations of fifteen exercises suitable for mild knee osteoarthritis. No modifications were made to the app; Because the app did not provide regional language instructions or audio guidance, the research team explained how to interpret each image and how to navigate the application interface.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eExercise Program, Adherence and Monitoring\u003c/h2\u003e \u003cp\u003eParticipants performed exercises three times per week on alternate days, three sessions per day, with two sets of ten repetitions per exercise, for twelve weeks. Weekly investigator phone calls assessed adherence, difficulties, and symptom aggravation. No objective app usage logs were available; adherence was monitored via participant self-report during calls. Sample adherence questions included: \u0026ldquo;Have you performed exercises three times this week?\u0026rdquo;, \u0026ldquo;On each day, did you perform three sessions?\u0026rdquo;, \u0026ldquo;For each session, were you able to complete all 10 repetitions per set?\u0026rdquo;, \u0026ldquo;Did you experience any difficulty or aggravation of symptoms?\u0026rdquo;.\u003c/p\u003e \u003cp\u003eNo real-time monitoring was embedded in the app. Weekly telephone calls were conducted by the investigator to confirm adherence and monitor safety. Participants reported full adherence, and no adverse events were noted.\u003c/p\u003e \u003cp\u003e \u003cb\u003eOutcome Measures\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ea) Quantitative Assessments\u003c/h2\u003e \u003cp\u003eBaseline assessments were conducted following the sensitisation period. Pain intensity was measured using the Numerical Pain Rating Scale (NPRS), where participants rated their worst pain in the preceding 24 hours. Mobility was assessed using the 10-metre Timed Up and Go (TUG) test following a standardized protocol in which the participant rose from a chair, walked ten metres at a comfortable pace, returned to the chair, and sat down. A demonstration was provided, and time was recorded using a smartphone stopwatch. The same unblinded assessor performed all pre- and post-intervention assessments; given the objective nature of the TUG test and the self-reported nature of the NPRS, assessor bias was considered minimal. Post-intervention assessments were conducted twenty-four hours after the final exercise session.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eb) Qualitative Methods\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe qualitative component aimed to explore participants\u0026rsquo; perceptions, experiences, and acceptability of using a mobile-based exercise application to manage knee osteoarthritis in a rural community. The focus was on understanding barriers and facilitators to engagement, usability of digital tools, and the perceived impact on pain management and joint function.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMethodological Approach\u003c/h2\u003e \u003cp\u003eA descriptive qualitative approach was employed, guided by thematic analysis. This approach allowed an in-depth exploration of participants\u0026rsquo; lived experiences and perspectives, emphasizing context-specific insights relevant to rural adults with limited prior exposure to digital health interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Selection and Interviews\u003c/h2\u003e \u003cp\u003eFrom the cohort of fifty participants, ten were selected for qualitative interviews using simple random selection to ensure that perspectives were not intentionally biased toward more motivated or more digitally literate individuals. Interviews were conducted in Tamil by the principal investigator, a physiotherapy researcher with prior qualitative research experience. Interviews were audio-recorded, held in private spaces within participants\u0026rsquo; homes, and lasted approximately fifteen to twenty minutes. Participants chose whether to be interviewed alone or with a family member present. Interviews were conducted in Tamil audio-recorded, and held in participants\u0026rsquo; homes. The relatively short duration of interviews was appropriate given the focused nature of questions and participants\u0026rsquo; limited prior experience with digital health tools, allowing efficient capture of key insights.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eInterview Guide\u003c/h2\u003e \u003cp\u003eA semi-structured guide specific to this study was developed and formally validated by community health care experts for the language clarity and appropriateness was used to explore key domains (a sample of the questions is attached in the supplementary file). The flow of the interview included: Initial perceptions of digital health tools for OA management, Comfort with technology and prior experience with mobile applications, Expectations and perceived benefits of the exercise app, Challenges anticipated in using the app regularly, and Suggestions for improving usability and support.\u003c/p\u003e \u003cp\u003e This approach allowed participants to freely express their experiences while ensuring that core topics relevant to feasibility, acceptability, and engagement were addressed.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Analysis\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ea) Quantitative analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using IBM SPSS Statistics (Version 26.0). Participant demographics and baseline characteristics were summarized using descriptive statistics, with continuous variables such as age and TUG scores presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and categorical variables such as gender and side affected reported as frequencies and percentages.\u003c/p\u003e \u003cp\u003eThe normality of outcome variables was assessed using both the Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests. Pre- and post-intervention TUG scores were normally distributed (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), whereas the calculated TUG change scores (Pre \u0026ndash; Post) were not normally distributed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). NPRS scores are ordinal by nature and were treated as non-parametric data.\u003c/p\u003e \u003cp\u003eTo evaluate the effect of the intervention, paired-samples t-tests were used to compare pre- and post-intervention TUG scores. Changes in pain intensity, measured using the Numerical Pain Rating Scale (NPRS), were analyzed using the Wilcoxon Signed Rank Test.\u003c/p\u003e \u003cp\u003eFor subgroup analyses, change scores for TUG and NPRS (Pre \u0026ndash; Post) were calculated to assess whether improvements differed according to gender or side affected (unilateral vs bilateral OA). Given the non-normal distribution of the change scores, Mann\u0026ndash;Whitney U tests were used for comparisons between groups. Across all analyses, a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Study Participants (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory / Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (64.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (36.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSide Affected\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (54.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.08\u0026thinsp;\u0026plusmn;\u0026thinsp;5.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026ndash;58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDuration of Pain (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.82\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e summarizes the demographic profile of the 50 study participants. Most participants were men (64%), and 54% presented with unilateral knee involvement. The mean age of the sample was 48.08 years (SD\u0026thinsp;=\u0026thinsp;5.02), with ages ranging from 40 to 58 years. The average duration of knee pain was 5.82 years (SD\u0026thinsp;=\u0026thinsp;2.16), with a reported range between 2 and 10 years.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePre- and Post-Intervention Outcomes (TUG and NPRS, n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Intervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost-Intervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean / Median Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI / IQR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTest Used\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTUG Test (seconds)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePaired t-test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNPRS (0\u0026ndash;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWilcoxon Signed Rank Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e summarizes the pre- and post-intervention outcomes for functional mobility (TUG) and pain intensity (NPRS) among 50 participants. TUG scores improved significantly after the intervention, decreasing from 17.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 s to 16.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36 s (mean difference\u0026thinsp;=\u0026thinsp;1.12 s, 95% CI: 0.92\u0026ndash;1.33, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). NPRS scores also changed significantly (mean difference\u0026thinsp;=\u0026thinsp;2.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Wilcoxon Signed Rank Test).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup Analysis of TUG and NPRS Change Scores by Gender and Side Affected (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubgroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Rank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU / Z\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTUG Change (seconds)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;238, Z = \u0026minus;\u0026thinsp;1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo significant difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;364.5, Z\u0026thinsp;=\u0026thinsp;1.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo significant difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eNPRS Change\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;260, Z = \u0026minus;\u0026thinsp;0.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo significant difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;331.5, Z\u0026thinsp;=\u0026thinsp;0.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo significant difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTUG Change\u0026thinsp;=\u0026thinsp;Pre \u0026ndash; Post TUG (seconds), NPRS Change\u0026thinsp;=\u0026thinsp;Pre \u0026ndash; Post NPRS (0\u0026ndash;10 scale). Mann\u0026ndash;Whitney U test was used due to non-normal distribution of change scores.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eb) Qualitative analysis\u003c/h2\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003eTranscription, Translation, and Analysis\u003c/h2\u003e \u003cp\u003eInterviews were transcribed verbatim in Tamil by a trained research assistant who was not involved in data collection. Translations into English were completed by a bilingual researcher, and an independent bilingual reviewer verified translation accuracy to ensure preservation of original meanings. Data analysis followed an inductive thematic analysis approach. Coding was performed manually in Microsoft Excel by two independent coders. Open, axial, and selective coding steps were applied iteratively. Coding and analysis were conducted concurrently with data collection, allowing emerging concepts to be reflected in subsequent interviews. Data saturation was considered achieved when two consecutive interviews yielded no new codes. Any discrepancies between coders were resolved through consensus, and when necessary, a third researcher adjudicated disagreements.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSafety\u003c/h2\u003e \u003cp\u003eNo adverse events, such as exercise-related pain flare or falls, were reported during weekly follow-up calls or at final assessment.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003ea) Quantitative results\u003c/h2\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e \u003cp\u003eA total of 50 participants were included in the study, with a mean age of 48.08\u0026thinsp;\u0026plusmn;\u0026thinsp;5.02 years (range 40\u0026ndash;58). The majority were men (32, 64%) and 27 participants (54%) had unilateral knee osteoarthritis, while 23 participants (46%) had bilateral involvement. The mean duration of osteoarthritis was 5.82\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16 years. These demographic details are summarized in Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003ePre- and Post-Intervention Outcomes\u003c/h2\u003e \u003cp\u003eFunctional mobility, measured by the Timed Up and Go (TUG) test, improved significantly following the intervention. Mean TUG scores decreased from 17.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 s pre-intervention to 16.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36 s post-intervention, representing a mean improvement of 1.12 s (95% CI: 0.92\u0026ndash;1.33), t(49)\u0026thinsp;=\u0026thinsp;11.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Pain intensity, assessed using the Numerical Pain Rating Scale (NPRS), also changed significantly after the intervention. Median NPRS scores decreased from 6 [IQR: 5\u0026ndash;7] pre-intervention to 4 [IQR: 3\u0026ndash;5] post-intervention (Z = \u0026minus;\u0026thinsp;5.072, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Wilcoxon Signed Rank Test). These findings indicate that the intervention significantly improved mobility and reduced pain among participants (Table\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eSubgroup Analysis\u003c/h2\u003e \u003cp\u003eSubgroup analyses were performed to evaluate whether improvements differed by gender or side affected (unilateral vs bilateral OA).\u003c/p\u003e \u003cp\u003eFor TUG change scores, there was no significant difference between men (mean rank\u0026thinsp;=\u0026thinsp;27.06) and women (mean rank\u0026thinsp;=\u0026thinsp;22.73), U\u0026thinsp;=\u0026thinsp;238, Z = \u0026minus;\u0026thinsp;1.011, p\u0026thinsp;=\u0026thinsp;0.312, nor between participants with unilateral (mean rank\u0026thinsp;=\u0026thinsp;23.50) and bilateral OA (mean rank\u0026thinsp;=\u0026thinsp;27.85), U\u0026thinsp;=\u0026thinsp;364.5, Z\u0026thinsp;=\u0026thinsp;1.051, p\u0026thinsp;=\u0026thinsp;0.293.\u003c/p\u003e \u003cp\u003eFor NPRS change scores, no significant differences were observed between men (mean rank\u0026thinsp;=\u0026thinsp;26.38) and women (mean rank\u0026thinsp;=\u0026thinsp;23.94), U\u0026thinsp;=\u0026thinsp;260, Z = \u0026minus;\u0026thinsp;0.609, p\u0026thinsp;=\u0026thinsp;0.542, or between unilateral (mean rank\u0026thinsp;=\u0026thinsp;24.72) and bilateral OA (mean rank\u0026thinsp;=\u0026thinsp;26.41), U\u0026thinsp;=\u0026thinsp;331.5, Z\u0026thinsp;=\u0026thinsp;0.440, p\u0026thinsp;=\u0026thinsp;0.660.\u003c/p\u003e \u003cp\u003eThese results suggest that the intervention\u0026rsquo;s effects on functional mobility and pain were consistent across gender and side affected (Table\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eQualitative Results\u003c/h2\u003e \u003cp\u003eFrom the in-depth interviews with ten participants, three major themes emerged: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Insights and Perceived Benefits, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Challenges in Using the Digital Tool, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Suggestions for Improvement (Table\u0026nbsp;4). These themes reflected participants\u0026rsquo; perspectives on feasibility, acceptability, usability, and engagement with the mobile-based exercise application for knee osteoarthritis in a rural community.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoding Framework of Participants\u0026rsquo; Perspectives on Using a Mobile-Based Exercise Application for Knee Osteoarthritis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThemes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubthemes / Axial Coding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIllustrative Codes / Open Coding\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eInsights and Perceived Benefits\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInitially thought app would be less effective; Limited awareness of digital tools; Perceived as remote consultation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdvantages and Experience Performing Exercises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReduced hospital visits; Saved time; Flexible use anytime/anywhere; Felt relaxed; Reduced pain; Muscles loosened; Not effective / No pain improvement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eChallenges in Using the Digital Tool\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonal Barriers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnfamiliar with smartphone; Reliance on family for access; English-language difficulty; Needed assistance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNetwork and Service Interruptions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoor network in farms/outside village; Intermittent power cuts, especially in rainy season\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSuggestions for Improvement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTechnical Features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClearer exercise images; Reminders to follow schedule\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCultural and Language Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eApp localized in Tamil; Reduced dependency on others for use\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreferred Support Methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVideo-based guidance; Live video calls for teaching and monitoring exercises\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eTheme 1: Insights and Perceived Benefits\u003c/h2\u003e \u003cdiv id=\"Sec29\" class=\"Section3\"\u003e \u003ch2\u003eSubtheme 1: Perception\u003c/h2\u003e \u003cp\u003eParticipants initially had limited awareness of digital health tools for exercise or pain management. Many perceived the app as a form of remote consultation rather than an exercise intervention. One participant reported \u0026ldquo;It was more like consulting the doctor using mobile phones.\u0026rdquo;\u003c/p\u003e \u003cp\u003eWhen first introduced to the app, some participants thought it would have minimal effects,\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eInitially, I thought it would be less effective, but it was more effective than I thought.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eSubtheme 2: Advantages and Experience Performing Exercises\u003c/h3\u003e\n\u003cp\u003eDespite initial skepticism, participants recognized several practical benefits of mobile-based exercise. They reported that the app reduced the need for hospital visits, saved time, and allowed flexible usage without specific place or time constraints.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIt was easy to use the application and could be used at any place and any time.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eParticipants\u0026rsquo; experiences with the exercise program varied. Several reported pain relief, relaxation, and reduced knee stiffness after performing the exercises:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI felt my muscles around the knee loosened and my pain reduced; I felt relaxed after performing the exercises.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eConversely, some participants did not perceive any improvement in pain:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI did not feel my pain reduced; it was not effective.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eTheme 2: Challenges in Using the Digital Tool\u003c/h2\u003e \u003cdiv id=\"Sec32\" class=\"Section3\"\u003e \u003ch2\u003eSubtheme 1: Personal Barriers\u003c/h2\u003e \u003cp\u003e Participants identified personal barriers related to technology use and language proficiency. Some were unfamiliar with smartphones or relied on family members to access the app, while others faced difficulties due to English-language instructions.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI did not know English, so it was difficult to read the instructions; I needed help to use the digital tool.\u003c/p\u003e\u003cp\u003eMy son had a smartphone. I used a button phone and needed assistance to use modern technology.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section4\"\u003e \u003ch2\u003eSubtheme 2: Network and Service Interruptions\u003c/h2\u003e \u003cp\u003eRural infrastructure limitations posed additional challenges. Participants reported intermittent network connectivity and power outages, especially when outside the village or during adverse weather conditions:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI had poor network and could not use my phone when I went to the farm; I had to come home to use it.\u003c/p\u003e\u003cp\u003eSometimes there was a power cut when using my computer, especially in rainy seasons.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eTheme 3: Suggestions for Improvement\u003c/h2\u003e \u003cdiv id=\"Sec35\" class=\"Section4\"\u003e \u003ch2\u003eSubtheme 1: Technical Features\u003c/h2\u003e \u003cp\u003eParticipants suggested enhancements to improve usability, such as clearer exercise images and reminders to perform exercises:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe pictures could be clearer, and it would have helped if the app had reminders to follow the schedule.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eSubtheme 2: Cultural and Language Considerations\u003c/h3\u003e\n\u003cp\u003eSeveral participants recommended localizing the app into Tamil to increase accessibility for the broader rural community:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI did not know English and found it difficult to use the app. It would have helped if it were in Tamil so I would not need anyone\u0026rsquo;s help.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eSubtheme 3: Preferred Support Methods\u003c/h2\u003e \u003cp\u003eParticipants highlighted the potential value of video-based guidance and live supervision.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIt would have helped if the app showed videos of exercises, so I could remember the steps even if I forgot.\u003c/p\u003e\u003cp\u003eLive video calls to teach and monitor exercises would have been more useful than just pictures.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe study focused on evaluating the potential of digital health solutions for managing osteoarthritis (OA) in rural communities, where access to healthcare is often limited. Both quantitative and qualitative findings highlighted the advantages and challenges of implementing mobile-based exercise interventions in this context. Quantitative data showed that participants experienced significant improvements in functional mobility and reductions in pain following a 12-week exercise program. The Timed Up and Go Test (TUG) demonstrated a mean improvement of 1.12 seconds (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while pain intensity measured by the Numerical Pain Rating Scale also decreased significantly, supporting the effectiveness of the intervention in improving joint function and reducing OA-related discomfort. These findings align with previous research, including Nelligan et al. (2020), which found that telehealth-delivered exercise programs improved pain and function in individuals with knee OA, and Shah et al. (2022), who reported that digital health interventions can be as effective as traditional treatments for exercise, education, and activity promotion.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eQualitative interviews provided context for these quantitative outcomes, revealing that participants initially had limited awareness of digital health tools and often perceived the app as a form of remote consultation rather than an exercise intervention. Despite initial skepticism, participants acknowledged practical benefits such as reduced hospital visits, time savings, and flexibility to perform exercises at their convenience. Experiences with the exercises varied, with some participants reporting relaxation, reduced knee stiffness, and pain relief, while others perceived minimal improvement. These findings resonate with Nelligan et al. (2020), who emphasized that human connection and guidance are important in e-health interventions, and highlight the challenges of digital literacy and infrastructure in rural communities.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eParticipants faced personal and technical barriers while engaging with the mobile application. Limited familiarity with smartphones, English-language instructions, intermittent network connectivity, and power outages in rural areas impeded independent use. Similar issues were reported in studies by Rasekaba et al. (2022) and Shah N et al. (2022), underscoring the influence of digital literacy, social support, and infrastructure on intervention uptake. Additionally, the application\u0026rsquo;s cultural and linguistic mismatch, being designed for a Western audience, reduced engagement and adherence, reflecting recommendations by Godziuk K et al. (2023) and Hale-Gallardo JL (2020) regarding the importance of culturally tailored and co-designed digital health solutions.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe combination of quantitative and qualitative findings indicates that mobile-based exercise interventions can effectively support self-managed care for knee OA in rural settings, but the success of such interventions is contingent on addressing contextual challenges. Participants suggested improvements including clearer visual demonstrations, video-based guidance, reminders for scheduled exercises, and localization of content into Tamil to enhance accessibility and usability. These recommendations highlight the need for culturally and linguistically appropriate adaptations and ongoing support to optimize engagement and adherence.\u003c/p\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe study had several limitations. The quantitative evaluation did not include a formal feasibility assessment or objective measurement of adherence, relying instead on participant self-report during weekly calls, which may have introduced bias. The qualitative interviews were one-time, brief encounters lasting 15\u0026ndash;20 minutes, limiting the depth of insights into participants\u0026rsquo; experiences and engagement over time. The study was conducted in only two villages, which may restrict generalizability to other rural settings or populations with more severe osteoarthritis. Additionally, the mobile application was in English, requiring investigator guidance, which may not reflect the independent use of the app in routine practice. The short duration of follow-up did not allow assessment of long-term sustainability of exercise adherence or outcomes.\u003c/p\u003e \u003cdiv id=\"Sec40\" class=\"Section3\"\u003e \u003ch2\u003eRecommendations\u003c/h2\u003e \u003cp\u003eFuture iterations of mobile-based exercise interventions should integrate local language instructions, provide clear visual or video demonstrations, and include reminders to encourage adherence. Incorporating brief training sessions or live supervision could support participants with limited smartphone experience. Addressing infrastructural challenges, such as network limitations or power interruptions, and designing content for offline use would improve accessibility. Larger studies across multiple rural communities with longer follow-up periods are warranted to validate these findings, assess long-term outcomes, and optimize digital interventions for broader use.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe mobile-based exercise program was effective in improving functional mobility and reducing pain among rural adults with knee osteoarthritis, and participants generally accepted the intervention as a practical tool for self-directed exercise. While initial perceptions were skeptical, experiences indicated that digital health tools could support exercise engagement when adequately explained and contextualized. Incorporating culturally and linguistically appropriate adaptations, along with visual or video-based guidance, may further enhance usability and participant confidence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eHuman ethics and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance to Helsinki\u0026rsquo;s guidelines \u0026nbsp;and Ethical approval was obtained from the Institutional Ethics Committee of SRM Medical College Hospital and Research Centre (IEC No. SRMIEC-ST0224-1081). Written informed consent was obtained from all participants, including consent for audio recording during qualitative interviews. Data were anonymized, securely stored, and accessible only to the principal investigator.\u003c/p\u003e\n\u003cp\u003eParticipants were recruited to the study following their voluntary willingness to participate. No participant of this study was less than 18, hence consent was only obtained from the participant.\u003c/p\u003e\n\u003cp\u003eParticipants were informed about the study procedures and informed consent was obtained from after ensuring that their responses would be held confidential and their identity will not be revealed anywhere. After ensuring that the data would only be used for research purposes, written consent was obtained from them\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statements:\u0026nbsp;\u003c/strong\u003eNil\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the PI on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u0026nbsp;\u003c/strong\u003eThe\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAuthors declare no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS R: Conceptualisation, study design, data collection, drafting the manuscript, editing the draft, approval of final version\u003c/p\u003e\n\u003cp\u003eAJR: conducting interviews, data transcription, coding of data, data analysis, reweing the manuscript, approval of final version\u003c/p\u003e\n\u003cp\u003eMBM: Coding of data, data analysis, reweing the manuscript, approval of final version\u003c/p\u003e\n\u003cp\u003eK V: Conceptualization, framework of the study, drafting results, proof corrections, approval of final version\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHinman RS, Lawford BJ, Nelligan RK, Bennell KL. Virtual Tools to Enable Management of Knee Osteoarthritis. Curr Treatm Opt Rheumatol [Internet]. 2023 Mar 11 [cited 2025 Dec 2];1\u0026ndash;21. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pmc.ncbi.nlm.nih.gov/articles/PMC10006574/\u003c/span\u003e\u003cspan address=\"https://pmc.ncbi.nlm.nih.gov/articles/PMC10006574/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrundisini F, Giacomini M, DeJean D, Vanstone M, Winsor S, Smith A. Chronic disease patients\u0026rsquo; experiences with accessing health care in rural and remote areas: a systematic review and qualitative meta-synthesis. Ont Health Technol Assess Ser. 2013;13(15):1\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcHugh CG, Kostic AM, Katz JN, Losina E. Effectiveness of remote exercise programs in reducing pain for patients with knee osteoarthritis: A systematic review of randomized trials. Osteoarthr Cartil Open. 2022 Sept;4(3):100264.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampos L, Costa D, Donato H, Nunes B, Cruz EB. Implementation of digital health in rural populations with chronic musculoskeletal conditions: A scoping review protocol. PLOS ONE [Internet]. 2023 Dec 22 [cited 2025 Dec 2];18(12):e0291638. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0291638\u003c/span\u003e\u003cspan address=\"https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0291638\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen T, Or CK, Chen J. Effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain: A systematic review and meta-analysis of randomized controlled trials. J Am Med Inf Assoc. 2021;28(2):414\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang Y, Li S, Cai Y, Zhang Q, Ge P, Shang S, et al. Effectiveness of telehealth-based exercise interventions on pain, physical function and quality of life in patients with knee osteoarthritis: A meta-analysis. J Clin Nurs. 2023 June;32(11\u0026ndash;12):2505\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampos L, Cardoso B, Galego M, Machado AT, Marques D, Santos C. Sou +: Reducing health inequities in rural populations with knee osteoarthritis. Procedia Comput Sci [Internet]. 2023 Jan 1 [cited 2025 Dec 2];219(C):1470\u0026ndash;7. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.procs.2023.01.437\u003c/span\u003e\u003cspan address=\"10.1016/j.procs.2023.01.437\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCronstr\u0026ouml;m A, Dahlberg LE, Nero H, Ericson J, Hammarlund CS. I would never have done it if it hadn\u0026rsquo;t been digital: a qualitative study on patients\u0026rsquo; experiences of a digital management programme for hip and knee osteoarthritis in Sweden. BMJ Open. 2019;9(5):e028388.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawford BJ, Hinman RS, Kasza J, Nelligan R, Keefe F, Rini C, et al. Moderators of Effects of Internet-Delivered Exercise and Pain Coping Skills Training for People With Knee Osteoarthritis: Exploratory Analysis of the IMPACT Randomized Controlled Trial. J Med Internet Res. 2018;20(5):e10021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim J, Foucher K. Fall experiences from the perspectives of people with osteoarthritis: in their own words. Disabil Rehabil. 2024;46(1):77\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaeemabadi Mr, Fazlali H, Najafi S, Dinesen B, Hansen J. Telerehabilitation for Patients With Knee Osteoarthritis: A Focused Review of Technologies and Teleservices. JMIR Biomedical Engineering [Internet]. 2020 July 21 [cited 2025 Dec 2];5(1):e16991. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://biomedeng.jmir.org/2020/1/e16991\u003c/span\u003e\u003cspan address=\"https://biomedeng.jmir.org/2020/1/e16991\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel KV, Hoffman EV, Phelan EA, Gell NM. Remotely Delivered Exercise to Rural Older Adults With Knee Osteoarthritis: A Pilot Study. ACR Open Rheumatol. 2022;4(8):735\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHale-Gallardo JL, Kreider CM, Jia H, Castaneda G, Freytes IM, Cowper Ripley DC, et al. Telerehabilitation for Rural Veterans: A Qualitative Assessment of Barriers and Facilitators to Implementation. J Multidiscip Healthc. 2020;13:559\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRose MJ, Costello KE, Eigenbrot S, Torabian K, Kumar D. Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review. JMIR Rehabil Assist Technol [Internet]. 2022 June 2 [cited 2025 Dec 2];9(2):e33521. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pmc.ncbi.nlm.nih.gov/articles/PMC9204569/\u003c/span\u003e\u003cspan address=\"https://pmc.ncbi.nlm.nih.gov/articles/PMC9204569/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDahlberg LE, Dell\u0026rsquo;Isola A, Lohmander LS, Nero H. Improving osteoarthritis care by digital means - Effects of a digital self-management program after 24- or 48-weeks of treatment. PLOS ONE [Internet]. 2020 Mar 4 [cited 2025 Dec 2];15(3):e0229783. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229783\u003c/span\u003e\u003cspan address=\"https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229783\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoore MR, Galetta MS, Schwarzkopf R, Slover JD, Force Writing Committee. Patient Satisfaction and Interest in Telemedicine Visits Following Total Knee and Hip Replacement Surgery. Telemed J E Health. 2022 Sept;28(9):1309\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah N, Costello K, Mehta A, Kumar D. Applications of Digital Health Technologies in Knee Osteoarthritis: Narrative Review. JMIR Rehabil Assist Technol. 2022 June 8;9(2):e33489.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNelligan RK, Hinman RS, Teo PL, Bennell KL. Exploring Attitudes and Experiences of People With Knee Osteoarthritis Toward a Self-Directed eHealth Intervention to Support Exercise: Qualitative Study. JMIR Rehabil Assist Technol. 2020;7(2):e18860.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRasekaba TM, Pereira P, Rani GV, Johnson R, McKechnie R, Blackberry I. Exploring Telehealth Readiness in a Resource Limited Setting: Digital and Health Literacy among Older People in Rural India (DAHLIA). Geriatr (Basel). 2022;7(2):28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGodziuk K, Prado CM, Quintanilha M, Forhan M. Acceptability and preliminary effectiveness of a single-arm 12-week digital behavioral health intervention in patients with knee osteoarthritis. BMC Musculoskelet Disord. 2023;24(1):129.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Osteoarthritis, Digital health, Exercise, NPRS scale, Rural communities","lastPublishedDoi":"10.21203/rs.3.rs-8299400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8299400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOsteoarthritis (OA) is a common and disabling joint disorder, particularly in rural areas where access to healthcare is limited. Digital health interventions, including mobile applications, offer a potential approach to support self-management, improve mobility, and reduce pain. This study aimed to evaluate the effectiveness, acceptability, and user experiences of a mobile-based exercise intervention for individuals with knee OA in rural communities.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA community-based mixed-methods study was conducted in Mangalore Village and M. Puthur, Tamil Nadu. Fifty adults (\u0026ge;\u0026thinsp;40 years) with mild knee OA were recruited. Participants underwent a one-week orientation and performed app-guided exercises thrice weekly for twelve weeks. Pain and functional mobility were assessed pre- and post-intervention using the Numerical Pain Rating Scale (NPRS) and Timed Up and Go (TUG) test. A subset of ten participants was selected for in-depth qualitative interviews exploring perceptions, challenges, and suggestions for improvement. Quantitative data were analyzed using paired t-tests and Wilcoxon Signed Rank tests. Qualitative data underwent thematic analysis with open, axial, and selective coding.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTUG scores improved significantly from 17.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 s to 16.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36 s (mean difference\u0026thinsp;=\u0026thinsp;1.12 s, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and NPRS scores decreased from 8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45 to 5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Three qualitative themes emerged: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) insights and perceived benefits, including flexibility and reduced hospital visits; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) challenges such as language barriers, limited digital literacy, and network issues; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) suggestions for improvement, including local language support, video demonstrations, and reminders.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMobile-based exercise interventions can improve pain and mobility in rural adults with knee OA. Future adaptations should address cultural, linguistic, and infrastructural barriers to enhance usability and adherence.\u003c/p\u003e","manuscriptTitle":"Implementation and Evaluation of a Mobile-Based Exercise Intervention for Knee Osteoarthritis in Rural Communities: A Mixed-Methods Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-23 17:33:44","doi":"10.21203/rs.3.rs-8299400/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"02f13908-2f60-4219-9d9a-792972d409ce","owner":[],"postedDate":"December 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T10:54:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-23 17:33:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8299400","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8299400","identity":"rs-8299400","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}