Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at, first published .
Rehabilitation Applications Based on Behavioral Therapy for People With Knee Osteoarthritis: Systematic Review

Rehabilitation Applications Based on Behavioral Therapy for People With Knee Osteoarthritis: Systematic Review

Rehabilitation Applications Based on Behavioral Therapy for People With Knee Osteoarthritis: Systematic Review


1School of Design, Shanghai Jiao Tong University, Shanghai, China

2Department of Design, Jiangxi Science and Technology Normal University, Shanghai, China

3Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China

Corresponding Author:

Ting Han, Prof Dr

School of Design

Shanghai Jiao Tong University

No 800, Dong Chuan Rd

Shanghai, 200240


Phone: 86 18901626266


Background: The development of digital applications based on behavioral therapies to support patients with knee osteoarthritis (KOA) has attracted increasing attention in the field of rehabilitation. This paper presents a systematic review of research on digital applications based on behavioral therapies for people with KOA.

Objective: This review aims to describe the characteristics of relevant digital applications, with a special focus on the current state of behavioral therapies, digital interaction technologies, and user participation in design. The secondary aim is to summarize intervention outcomes and user evaluations of digital applications.

Methods: A systematic literature search was conducted using the keywords “Knee Osteoarthritis,” “Behavior Therapy,” and “Digitization” in the following databases (from January 2013 to July 2023): Web of Science, Embase, Science Direct, Ovid, and PubMed. The Mixed Methods Assessment Tool (MMAT) was used to assess the quality of evidence. Two researchers independently screened and extracted the data.

Results: A total of 36 studies met the inclusion criteria and were further analyzed. Behavioral change techniques (BCTs) and cognitive behavioral therapy (CBT) were frequently combined when developing digital applications. The most prevalent areas were goals and planning (n=31) and repetition and substitution (n=27), which were frequently used to develop physical activity (PA) goals and adherence. The most prevalent combination strategy was app/website plus SMS text message/telephone/email (n=12), which has tremendous potential. This area of application design offers notable advantages, primarily manifesting in pain mitigation (n=24), reduction of physical dysfunction (n=21), and augmentation of PA levels (n=12). Additionally, when formulating design strategies, it is imperative to consider the perspectives of stakeholders, especially in response to the identified shortcomings in application design elucidated within the study.

Conclusions: The results demonstrate that “goals and planning” and “repetition and substitution” are frequently used to develop PA goals and PA behavior adherence. The most prevalent combination strategy was app/website plus SMS text message/telephone/email, which has tremendous potential. Moreover, incorporating several stakeholders in the design and development stages might enhance user experience, considering the distinct variations in their requirements. To improve the efficacy and availability of digital applications, we have several proposals. First, comprehensive care for patients should be ensured by integrating multiple behavioral therapies that encompass various aspects of the rehabilitation process, such as rehabilitation exercises and status monitoring. Second, therapists could benefit from more precise recommendations by incorporating additional intelligent algorithms to analyze patient data. Third, the implementation scope should be expanded from the home environment to a broader social community rehabilitation setting.

JMIR Mhealth Uhealth 2024;12:e53798



Knee osteoarthritis (KOA) is a prevalent musculoskeletal disorder that ranks among the primary contributors to disability [1,2]. Possible long-term ramifications encompass diminished levels of physical activity (PA), the development of body dysmorphic disorder, compromised sleep patterns, depressive symptoms, and the onset of disability [3,4]. In recent times, there has been a notable shift in the approach to treating KOA, with a greater emphasis on nonpharmacologic interventions. This change is supported by evidence indicating that nonpharmacologic treatments are more effective in delivering sustained symptom alleviation and in delaying or even preventing functional deterioration [5,6]. The primary nonpharmacological interventions for KOA include educational programs, PA interventions, and weight management strategies [3]. Patient initiation and adherence to these treatments are essential factors for achieving effective symptom control [7]. Traditional nonpharmacological interventions, however, require professional guidance to achieve the desired results, which is associated with high costs and unequal health care resources [8].

Digital health interventions have the potential to offer widespread, cost-effective, readily available, and easily expandable patient education and self-management interventions for individuals with KOA [9-11]. Several research investigations have been carried out to substantiate their efficacy in rehabilitating musculoskeletal problems. For instance, digital health interventions have been found to be successful in decreasing pain, improving functionality, and promoting the self-management of musculoskeletal pain syndromes [12,13]. Significant increases in adherence have also been observed throughout the mid-term follow-up [14]. These systematic evaluations have focused on summarizing various techniques for digital health or intervention effectiveness in relation to health outcomes [15,16]. However, digital interventions do not always provide desirable outcomes. Providing guidance on the ideal dosage required to achieve significant benefits or disclosing the elements of effective digital health treatments is challenging owing to the variations in interventions and the insufficient information in interventions [15]. In recent years, it has been discovered that theory-driven interventions can help organize the content of digital interventions, resulting in improved health outcomes [17-19].

A growing number of studies have used the behavioral psychology theoretical framework in digital format [20]. Compared to generic digital interventions, behavioral therapy-based digital interventions are significantly more effective at relieving pain, improving physical dysfunction, and increasing self-efficacy in patients with KOA [21,22]. Physiotherapists use scalable interventions along with some digital tools to enhance treatment adherence [16,23]. The concept of behavioral therapy (BT) incorporates various therapeutic approaches, including behavioral change techniques (BCTs), dialectical behavioral therapy (DBT), and cognitive behavioral therapy (CBT). It has been used to aid complex intervention designs that include facilitating the adoption of behavior change, promoting behavioral compliance, sustaining behavioral change, and preventing behavioral relapse [24]. Previous studies have employed BCTs in combination with digital interventions among individuals with musculoskeletal pain [25]. These studies have reported the efficacy of such interventions in facilitating the transition of patients from a sedentary lifestyle to an active one [21,22,26]. Multiple studies have demonstrated that the integration of CBT with standard care yielded noteworthy outcomes in the management of KOA. Specifically, the implementation of CBT interventions resulted in a considerable reduction in pain levels and an improvement in insomnia symptoms when compared to the utilization of standard care alone, as indicated by previous investigations [27,28].

Currently, there are evaluations investigating the rehabilitative impacts of digitalization in KOA and highlighting the significance of behavioral theory in some applications [19]. Nevertheless, there is a shortage of thorough exposition of the behavioral theory in digital applications, as well as an absence of an assessment of the suitability of these applications from the patient’s point of view. Thus, this review offers a methodical and thorough examination of digital applications rooted in behavioral therapy. It shifts the focus of digital applications from mere practical usability to providing support for behavioral change theories. Additionally, it meticulously analyzes the functional reasoning behind various products, thereby serving as a comprehensive guide for designing future digital interventions. Hence, the objectives of this review are to (1) provide a concise overview of the existing landscape of digital behavioral therapy applications for individuals diagnosed with KOA and examine the potential of digital applications in augmenting the rehabilitation process for KOA patients, and (2) present a comprehensive analysis of the underlying psychological theories, fundamental mechanisms, design methodologies, typical attributes, efficacy of treatment outcomes, and patient preferences pertaining to this particular mode of recovery intervention.


This review has been registered in the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42023430716). Furthermore, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines have been applied (Multimedia Appendix 1) [29].

Search Strategy

Literature searches were conducted in 5 databases: Web of Science, Embase, Science Direct, Ovid, and PubMed. The selection of these databases was based on their provision of comprehensive access to full-text journals and conference proceedings pertaining to prominent conferences and meetings focused on digital technology and medicine.

To locate relevant articles, we conducted a search by filtering papers based on 3 primary categories of MeSH (Medical Subject Headings) terms: “Knee Osteoarthritis,” “Behavioral Therapies,” and “Digitization.” According to MeSH terminology, “Behavioral Therapy” is divided into “Behavioral Therapy,” “Cognitive Behavioral Therapy,” and “Dialectical Behavioral Therapy.” In this review, in order to understand the categorization of all behavioral therapies, we collected information on the subcategories of these 3 categories related to behavior. In relation to the subject of “digital” content, we gathered relevant material from the report by Safari et al [19] on digital literature, encompassing topics, such as “Telehealth,” “Email,” “Smartphone,” “Computer Systems,” “Digital Technologies,” and “Mobile Applications,” and other forms of digitization. Table 1 illustrates sample search strategies used for the PubMed digital library. The article titles, keywords, and abstracts were searched. Similar search strategies were applied to the remaining 3 databases. Relevant articles published between January 2013 and July 2023 were gathered. We included journal papers and peer-reviewed conference proceedings. Only articles written in English were considered.

Table 1. Literature search strategy.
MeSHaBoolean logic search strings
Knee Osteoarthritis“Knee Osteoarthritides” OR “Knee Osteoarthritis” OR “Osteoarthritis of Knee” OR “Osteoarthritis of the Knee”
Behavior Therapy“Behavior Therapies” OR “Behavior Treatment” OR “Conditioning Therapy” OR “Conditioning Therapies” OR “Behavior Change Techniques” OR “Behavior Change Technique” OR “Behavior Modification” OR “Behavior Modifications” OR “Dialectical Behavior Therapies” OR “Cognitive Behavioral Therapies” OR “Cognitive Therapy” OR “Cognitive Behavior Therapy” OR “Cognitive Psychotherapy” OR “Cognition Therapy” OR “Cognitive Behavior Therapies” OR “Cognitive Behavior Therapy”
Digitization“Telemedicine” OR “Mobile Health” OR “Telehealth” OR “ehealth” OR “mhealth” OR “Email” OR “E-mail” OR “Mobile” OR “Smartphone” OR “smart-phone” OR “smart telephone” OR “Tablet” OR “cell” OR “hand-held” OR “Cell Phone” OR “handheld” OR “Remote Consultation” OR “Teleradiology” OR “Telenursing” OR “Computer Systems” OR “Computer-Assisted Instruction” OR “Internet” OR “web” OR “computer” OR “Digital Technologies” OR “APP” OR “Social Media” OR “Internet-Based Intervention” OR “Mobile Application” OR “Mobile App” OR “Smartphone App” OR “Portable Software Application”

aMeSH: Medical Subject Headings.

Eligibility Criteria

The authors DZ and JZ were assisted in the literature search by an experienced librarian well versed in medical database searching. This literature review was guided by the question of how behavioral therapies can be integrated with digital applications in the rehabilitation of patients with KOA. On this basis, we anticipated that this review would (1) generalize and summarize the digital applications used in behavioral therapy, and (2) describe the overall research status and research trends of these digital applications.

Inclusion Criteria

The inclusion criteria were as follows: (1) adult participants (age ≥18 years) with KOA diagnosed by self-reported symptoms or imaging; (2) patients had access to digital applications; (3) any form of intervention or treatment based on the inclusion of at least one behavioral treatment was delivered through any digital application (eg, website or app) within any time frame; and (4) the described interventions were compared to waiting list control (no intervention) or alternative (standard) delivery modalities (eg, face-to-face approaches, classroom-based approaches, and printed materials or handouts), nondigital self-management interventions, and noninteractive digital interventions (eg, web pages with flat copies).

Exclusion Criteria

The exclusion criteria were as follows: (1) patients with KOA were not included; (2) nondigital interventions were assessed; (3) behavioral therapies were not included; (4) research protocols, reviews, conceptual articles, case studies or discussion papers, and conference abstracts; (5) market research; (6) digitization was not designed for the recovery process; (7) text was not written in English; and (8) duplicate reports of the same study from different sources.

Data Extraction

Data relevant to the purpose of the study were extracted independently by the authors MW, WZ, and BC, and any misunderstandings and disagreements were resolved through negotiation. Extracted data included study context details, study population, and digital application details. In more detail, the template included the following categories: (1) basic information (author, year, origin, study population, sample size, presence of a physiotherapy intervention, and duration of the intervention); (2) digital application details (digitalization of behavioral therapy, interactive device function, study outcomes, and application deficiencies); and (3) type of study (randomized controlled trial, cohort experiment, experimental protocol, and qualitative study).

Quality Assessment

The Mixed Methods Assessment Tool (MMAT) was used to evaluate the methodological quality of the included studies [30]. This tool was initially created in 2006 through a comprehensive analysis of systematic evaluations that integrated qualitative and quantitative evidence. In 2018, a revised version of the MMAT was developed by assessing its usefulness, reviewing key assessment tools in the literature, and conducting a modified e-Delphi study involving methodology experts to determine the essential criteria (Multimedia Appendix 2). The MMAT evaluates the caliber of research employing qualitative, quantitative, and mixed approaches. The primary emphasis is on methodological standards, which encompass 5 fundamental quality criteria for 5 distinct study designs: (1) qualitative, (2) randomized controlled, (3) nonrandomized, (4) quantitative descriptive, and (5) mixed methods.


Figure 1 provides a summary of the outcomes at various phases of article selection. The search results of the databases are provided in Multimedia Appendix 3. Based on the search strategy, 2975 articles were found initially, and 2507 articles remained after title and abstract screening and removal of duplicates. Next, full-text articles were chosen based on the inclusion and exclusion criteria. We included a total of 131 articles explicitly related to digital behavioral therapy for KOA. Moreover, 4 articles were identified following a manual search of the references for articles that were cited. Final consideration was given to 36 articles for systematic evaluation (Table 2).

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart. KOA: knee osteoarthritis.
Table 2. Information on the included studies.
AuthorYearCountryPopulationSample sizePhysiotherapistDurationDigital formsExperimentQuality
Bossen et al [31]2013NetherlandsKOAa/HOAb20Yes6-12 weeksInternet platform + SMS text message/telephoneNonrandomized pilot study4
Rini et al [32]2016United StatesOAc113No9-11 weeksApp + “virtual coaching”Randomized controlled trial5
Pearson et al [33]2016United KingdomKOA/HOA200NodInternet websiteMixed methods research2
Bennell et al [34]2017AustraliaKOA168Yes24 weeksInternet platform + SMS text message/telephoneRandomized clinical trial5
Bennell et al [11]2017AustraliaKOA148Yes24 weeksInternet platform + SMS text message/telephoneRandomized clinical trial5
Li et al [35]2017CanadaKOA34Yes8 weeks Electronic equipment + telephoneRandomized controlled trial4
Lawford et al [36]2018AustraliaKOA148Yes12-36 weeksPainCOACH software + emailRandomized controlled trial5
Button et al [37]2018United KingdomKOA49Yes12 weeksOnline courseQualitative research4
Mecklenburg et al [38]2018United StatesKOA162Yes12 weeksHinge Health app + wearableRandomized controlled trial5
Kline et al [39]2019United StatesTKRe100YesOnline course + wearableRandomized controlled trial protocolN/Af
Nelligan et al [40]2019AustraliaKOA12No24 weeksSMS text message application + messaging interactionsQualitative research5
Pelle et al [41]2019NetherlandsKOA/HOA427No12-24 weeksBart appRandomized controlled trial5
Bailey et al [42]2020United StatesMDg10,264Yes9 weeksHinge Health app + wearable motion sensorsCohort study4
Baker et al [43]2020United StatesKOA104Yes2 yearsTeleconferencing (remote software)Cohort study4
Bennell et al [22]2020AustraliaKOA/obesity12No24 weeksSMS text message application + messaging interactionsRandomized controlled trial5
Fitzgibbon et al [44]2020United StatesOA203Yes8 weeksF&S! and F&S! Plus + telephoneComparative effectiveness test4
Hinman et al [45]2020AustraliaKOA165Yes24 weeksInternet website + SMS text message/telephoneRandomized controlled trial5
Hinman et al [46]2020AustraliaKOA394Yes12 weeksInternet website + video consultingRandomized controlled trial protocolN/A
Li et al [47]2020CanadaKOA51Yes12 weeksElectronic device + telephone/mailRandomized controlled trial4
Nelligan et al [48]2020AustraliaKOA16YesInternet website + SMS text message/telephoneQualitative research2
Dunphy et al [49]2021United KingdomOA59Yes12 weeksInternet websiteTwo-arm parallel randomized controlled trial5
Lindberg et al [50]2021NorwayOA282Yes12 weeksiCBT application + telephoneRandomized controlled trial protocolN/A
Nelligan et al [21]2021AustraliaKOA206Yes24 weeksInternet website + SMS text message/telephoneRandomized controlled trial5
Pelle et al [51]2021NetherlandsKOA/HOA214No26 weeksBart appRandomized controlled trial4
Rognsvåg et al [52]2021United KingdomKOA/TKR4YesiCBT application + telephoneQualitative research3
Bennell et al [53]2022AustraliaKOA88Yes24 weeksWebsite + remote softwareRandomized controlled trial protocolN/A
Groves-Williams et al [54]2022ScotlandKOA90No12-36 weeksInternet website + SMS text message/telephoneRandomized controlled trial protocolN/A
Hinman et al [55]2022AustraliaKOA182Yes14 weeksApp + SMS text messageRandomized controlled trial protocolN/A
Östlind et al [56]2022SwedenKOA/HOA20Yes12 weeksApp + electronic deviceQualitative research4
Östlind et al [57]2022SwedenKOA/HOA160Yes12 weeksApp+ electronic deviceRandomized controlled trial3
Whittaker et al [58]2022CanadaOA30Yes4 weeksVideo conferencing + wearable + appRandomized trial4
Godziuk et al [59]2023CanadaKOA53Yes12 weeksWebsite + emailCohort study3
Lorbeer et al [60]2023GermanyKOA241Yes1 yearTeleconferencing (remote software)Randomized controlled trial4
Scheer et al [61]2023United StatesMD4051Yes12 weeksApp + electronic deviceCohort study4
Truong et al [62]2023CanadaOA16NoVideo conferencing + wearable + appQualitative research5
Weber et al [63]2023GermanyKOA/HOA330Yes3 weekse-Exercise + online physiotherapyRandomized controlled trial protocolN/A

aKOA: knee osteoarthritis.

bHOA: hip osteoarthritis.

cOA: osteoarthritis.

dData not available.

eTKR: total knee replacement.

fN/A: not applicable.

gMD: musculoskeletal disorder.

Methodological Quality

Among the included studies, 12 met 100% of the quality assessment criteria, 15 fulfilled 60%-80% of the quality assessment criteria, and 2 met 40% of the quality assessment criteria (Multimedia Appendix 4 [11,21,22,31-63]). The remaining 7 studies could not be evaluated for their quality owing to the absence of results. Nevertheless, the application description portion involved in the studies was highly valuable for analysis.

Digitalization of Behavioral Therapy

Behavior Change Therapy

The majority of digital applications for KOA rehabilitation are based on BCTs. BCTs (achieving objectives, setting goals, restructuring beliefs, and inducing acceptance) are applicable to addressing the central issues of initiating and maintaining PA [64]. The primary categories of BCTs used in the reviewed studies were based on the V1 Taxonomy of Behavior Change by Michie et al [65], which was devised by behavior change researchers [66]. The taxonomy comprises 93 distinct BCTs organized into 16 hierarchical structures and has been extensively used in the literature on behavior change (Table 3): (1) goals and planning; (2) feedback and monitoring; (3) social support; (4) shaping knowledge; (5) natural consequences; (6) behavioral comparisons; (7) associations; (8) repetition and substitution; (9) outcome comparisons; (10) rewards and threats; (11) regulation; (12) presuppositions; (13) identity; (14) intended consequences; (15) self-confidence; and (16) implicit learning.

Table 3. Behavioral change techniques in digital applications.
Cluster label and component behavioral change techniquesReferences
1: Goals and planning

1.1: Goal setting (behavior)[11,31-37,39-47,49-52,54,58,59,61,62]

1.2: Problem solving/coping planning[35,39,44,54,63]

1.4: Action planning[11,21,31-37,43,46,48,52,53,60,63]

1.5: Review of behavior goal(s)[11,31,33,34,39,43,52]

1.7: Review of outcome goal(s)[11,34,58,62]
2: Feedback and monitoring

2.2: Feedback on behavior[33,42,56,57]

2.3: Self-monitoring of behavior[31,32,36,39,42,44,47,55,57-59,62]

2.4: Self-monitoring of the outcome of behavior[33,47,58,61]

2.6: Biofeedback[11,33-35,37,39,42,47,56-58,61,62]

2.7: Feedback on behavioral outcomes[32,36]
3: Social support

3.2: Social support (practical)[33,59]

3.3: Social support (emotional)[43,60]
4: Shaping knowledge

4.1: Instructions on how to perform a behavior [21,32,42-44,46-50,52-54,56,59,61]

4.2: Antecedents[32,36,38]
5: Natural consequences

5.1: Health consequences[32,36,39,41,42,50,51]

5.4: Self-assessment of affective consequences[33,43]

5.5: Anticipated regret[35,39,43,63]
6: Comparison of behavior 

6.1: Modeling of behavior[42,56]

6.2: Social comparison[33,53,60]

6.3: Information about others’ approval[32,36,42-44,49,53,58,59,61-63]
7: Associations

7.1: Prompts/cues[11,21,22,31,34,37,40,43,45,48,50,54,55,59,60]
8: Repetition and substitution

8.1: Behavioral rehearsal/practice[11,21,34,35,37,39-43,46,48,49,51,56,58,59,61-63]

8.6: Generalization of a target behavior[33,38,42]

8.7: Graded tasks[31,33,45,49,63]
10: Reward and threat

10.3: Nonspecific reward[32,36]
11: Regulation 

11.2: Regulate negative emotions[33,38,42,43,50,52,59]
12: Antecedents 

12.4: Distraction[32]
13: Identity 

13.1: Identification of self as a role model[52]
15: Self-belief 

15.1: Verbal persuasion to boost self-efficacy[32,36,39]
16: Covert learning

16.2: Covert conditioningN/Aa

16.3: Vicarious reinforcement[43]

aN/A: not applicable.

In 31 studies, objectives and planning were mentioned, including goal setting (behavior), problem solving or coping planning, and reviewing behavioral or outcome goals. Among these factors, goal setting and action planning were shown to be the most prominent components within the area. A total of 26 applications included goal setting, which has a very broad definition in the taxonomy (setting goals defined according to the behavior or outcome to be accomplished) [11,31-37,39-47,49-52,54,58,59,61,62]. Applications created evidence-based, individualized, progressive home exercise plans; promoted increased general PA; and established short-term objectives. Moreover, 16 applications [11,21,31-37,43,46,48,52,53,60,66] contained action planning in which patients were asked or chose to perform activities until their pain tolerance was attained, based on which the patients prescribed their own individual therapeutic actions. Additionally, 5 applications [35,39,44,54,63] addressed problem solving and coping strategies encountered during rehabilitation by other individuals or physiotherapists. Furthermore, 9 applications contained a review of behavioral or outcome objectives [11,31,33,34,39,43,52,58,62], encouraging participants to monitor their progress and assisting them in identifying personal barriers and strategies for overcoming them.

A total of 19 investigations included various forms of feedback and monitoring, such as feedback on behavior, self-monitoring of behavior, biofeedback, self-monitoring of behavioral outcomes, and feedback on behavioral outcomes. Feedback was provided on behavior wherein activities or exercises were recorded on performance metrics through a digital application and discussed by the physiotherapist during follow-up [33,42,56,57]. Among the included studies, 12 involved self-monitoring for managing exercise reminders and records, viewing progress charts, and setting or modifying exercise objectives [31,32,36,39,42,44,47,55,57-59,62]. Moreover, 13 studies offered participants a wearable device with additional features, such as the ability to monitor activity intensity and visualize activity performance over time [11,33-35,37,39,42,47,56-58,61,62]. These features enabled individuals to monitor progress and receive real-time feedback on objective achievement.

A total of 18 studies applied shaping knowledge. They primarily incorporated videos or lectures on osteoarthritis (OA), the effects of PA, self-management, and coping strategies [21,32,42-44,46-50,52-54,56,59,61]. Three of these studies presented information about antecedents via multiple online physical therapy consultations using video phone services [32,36,38].

A limited subset of digital applications employed social support. The programs offered online platforms where individuals could engage in discussions pertaining to joint pain. Four studies documented the beneficial effects of engaging with social organizational structures on the rehabilitation of individuals with KOA [33,43,59,60].

The concept of natural consequences was addressed in 11 investigations [32,33,35,36,39,41-43,50,51,63], and it included information regarding health consequences, monitoring of emotional consequences, and anticipated misgivings. At each online meeting, the interventionist provided the patient with information about the benefits and costs of engaging in or refraining from a particular course of action. In addition, reminders regarding obstacles and facilitators were provided beforehand.

Comparison of behavior was addressed in 16 studies [32,33,36,42-44,49,53,56,58-63]. It was primarily implemented with behavior evidence, social comparisons, and information about the approbation of others. Three studies on group therapy prompted patients to establish a “buddy” system to change their behavior [33,56,59]. In some cases, a physiotherapist was included to provide the patient with assistance or instrumental social support. Twelve studies referred to information about other people’s perceptions of a person’s behavior and whether others would approve or disapprove of any proposed behavioral change to encourage people to decide to set overall goals [32,36,42-44,49,53,58,59,61-63]. For instance, making behavioral decisions was practiced more the following week, along with identifying obstacles to executing the behavior and devising strategies to overcome them.

A total of 16 studies referred to associations, particularly prompts, as reminders for the patient to perform a particular behavior [11,21,22,31,34,37,40,43,45,48,50,54,55,59,60]. The defined frequency, intensity, or duration of the specified behavior, along with a description of at least one context, location, time, and manner, was included. Of those, 12 involved primary distribution by the physiotherapist via short messages or email timed reminders. In addition, 8 studies involved prompts by the application’s included features [21,22,31,40,48,54,55,59].

Repetition and substitution, which involve behavioral practice or rehearsal, generalization of target behaviors, and grading tasks, were the most common components of the applications. In 27 studies, patients were required to rehearse and repeat KOA exercises [11,21,34,35,37,39-43,46,48,49,51,56,58,59,61-63]. Additionally, 1 study described neuromuscular exercises designed to enhance the physical function of the lower extremities, and the targeted behaviors were broken down into daily video bundles sent to patients [59]. Five studies divided the exercises into varying intensities and progressively increased the difficulty until the desired behaviors were achieved [31,33,45,49,63]. Individual progress and the patient’s perception of the capacity to exercise without aggravating discomfort were taken into account.

Rewards and threats were mentioned in 2 studies [32,36]. Mobile health apps were supplemented with motivation-enhancing techniques, such as praise, encouragement, and material rewards, for the achievement of specific goals.

The primary goal of regulation was to reduce negative emotions in patients. Seven studies trained users to recognize negative thoughts and reactions to them by relaxing mood through thoughts, emotions, and behaviors that affect pain [33,38,42,43,50,52,59]. One study adhered to the practice by revisiting pleasant imagery and distractions from the previous week [32]. In addition, 1 study discussed the potential for novel or alternative pain medications in applied implicit learning [43].


Complementary and alternative medicine therapy refers to a deliberate, intentional, and organized form of psychotherapy intervention aimed at improving psychological issues by impacting the beliefs and behaviors of patients [67,68]. CBT combines techniques to develop more adaptive cognitions and behaviors, such as psychoeducation, cognitive restructuring, relaxation therapy, and guided imagery (eg, to reduce muscle tension and autonomic arousal), as well as positive thinking training, problem-solving, and stress management [69,70].

Specifically, CBT focuses on reducing pain and distress by altering bodily sensations, catastrophic and contemplative thinking, and maladaptive behaviors, as well as enhancing self-efficacy [71,72]. Four studies addressed common CBT topics, such as catastrophizing, positive coping methods, and anxiety avoidance, through educational interactive modules and internet courses pertaining to behavior change [42,50,52,61]. The remaining 4 studies addressed common barriers to exercise (eg, pain, low confidence, weather, and relapse) and ways to overcome them (eg, increasing confidence through exercise, seeking social support, teaching proper exercise routines and postures, and promoting positive reasoning) in conjunction with programmatic elements of social cognitive theory and goal-setting strategies for exercise behaviors [32,36,43,44].

Interactive Device Function

Digital Presentation Modalities

The emergence of the internet in the health field has drastically altered the medical information available to patients and the manner in which physicians and patients communicate [73]. A significant number of digital applications involving KOA utilize information and communication technology (ICT) to facilitate behavioral therapy. The included studies covered 5 types of digitization (Table 4): (1) app, (2) website, (3) teleconferencing software/remote phone contact, (4) wearable electronic device, and (5) SMS text message/telephone/email.

Table 4. Forms of digital applications.
Digital application typeReferences
App/website + SMS text message/telephone/email[11,21,31,34,36,44,48,50,52-54,59]
Teleconferencing software/remote messaging[22,40,43,45,55,60]
Wearable electronic device + SMS text message/telephone/email + app/website[35,38,39,42,47,56,57,61]
Teleconferencing software + wearable electronic device + app/website[58,62]

Twelve studies adopted the combination of app/website plus SMS text message/telephone/email. Physiotherapists in 2 studies provided verbal and written education or information about OA, benefits of PA or exercise, and strategies to increase adherence [11,44]. In addition, a progressive individualized home exercise program based on scientific evidence was devised, which included several lower extremity exercises and was accessible through an app or website. In 2 studies, weekly emails containing OA-specific content and resources were sent directly to patients. The emails included (1) nutritional advice; (2) an instructional video on exercise; and (3) a video on positive thinking and advice on self-care, motivation, and stress management [36,59]. Nine studies supported general health and wellness behavior change through free website support [11,21,31,34,36,48,53,54,59]. To increase patient compliance, physiotherapists conducted regular telephone counseling sessions to determine if the use of optional sessions should be based on participant preference, confidence, and success in achieving the desired behavior change. In 3 other investigations, the aforementioned functions were implemented in their entirety within a single application [44,50,52].

Eight studies used apps or websites for self-management and coping with arthritis pain through exercise [32,33,37,41,46,49,51,63]. The websites included information on PA or exercise, goal setting, action plans, pacing, medication management, diet, home exercise, understanding pain, pain management, and relaxation modules. One study explained how individuals can input data and view graphical feedback regarding the amount of exercise they have performed, their activity levels, and their mood [33].

Five investigations [22,40,43,45,60] applied teleconferencing software or telemessaging, and 3 programs provided patients with complimentary access to online webinars featuring “expert advice” [43,45,60]. Participants could ask the facilitator queries about nutrition, exercise, or positive thinking. Registered dietitians, registered psychologists, and kinesiologists led the sessions in pairs according to a rotating schedule. Two other studies addressed recommendations for the development of health behavior interventions utilizing only SMS text messaging on mobile phones [22,40].

Eight studies used the combination of wearable electronic devices plus SMS text message/telephone/email plus app/website to guide participants in setting specific, measurable, achievable, pertinent, and time-bound PA goals [35,38,39,42,47,56,57,61]. Self-monitoring is typically assessed using commercially available wrist-worn wearable activity trackers (such as Fitbit) or other similar devices. These devices collect measures and communicate them through Bluetooth to a smartphone, tablet, or computer application. Subsequently, the application transmits the data to the Fitbit server. Individuals who possess apprehensions over engaging in PA have the option to communicate their concerns via electronic mail to their physiotherapists.

Two studies [58,62] employed teleconferencing plus electronic devices plus apps. The program comprised 3 elements: (1) a 1-time knee boot camp where participants worked at home on their exercise therapy and PA goals; (2) weekly personalized in-home exercise therapy, PA, and tracking where participants received a Fitbit Inspire activity tracker; and (3) weekly physiotherapist-guided exercise therapy and activity action plans via videoconference on Zoom, optional group exercise classes, and exercise therapy and PA goal setting. In the TeleHab app, exercise therapy objective completion levels, target rating of perceived effort, and any associated pain were recorded, and Fitbit data were synchronized with the Fitbit online dashboard.

Design Methodology

Although researchers and developers typically validate their digital applications with end users, it is uncommon for relevant studies to include end-user participation in the design phase. Of the 36 studies in our review, 8 (22%) reported end-user participation in the design phase [31,33,37,40,41,48,50,56], and 6 (75%) of these 8 studies also reported the participation of stakeholders other than end users [33,37,40,41,50,56]. These stakeholders also included caregivers, coaches, physiotherapists, and other individuals who provide care or services to the target population.

Heuristic assessments were used in a study to explore usability of the intervention for patients with KOA. Based on the outcomes of the interviews and heuristic evaluations, the program’s time structure was modified to be more flexible. In the most recent iteration, users had the option of repeating modules and adjusting module difficulty. The strategy also addressed improper website design and placement of multiple icons [31]. In addition, a study involved 3 patients with KOA who provided feedback on the prototype to inform the final design. Regarding how participants perceived interventions used outside the study setting, the majority suggested that health professionals, particularly general practitioners or physiotherapists, could deliver interventions to enhance or improve care [48].

Additional stakeholders were included in the qualitative study analysis. One study referred to experimental websites where patients with KOA and physiotherapists provided feedback on prototypes to inform the final design [40,41,50]. In a separate study, the app was also developed in collaboration with physiotherapists, physicians, and patient representatives. Named members of the project team submitted a list of 30 SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) objectives related to OA treatment [41].

Study Outcomes

A total of 23 experimental studies, 7 experimental protocols, and 6 qualitative studies were included in this literature review. The primary outcomes of using digital behavioral therapy for rehabilitation of patients with KOA were (1) pain, (2) symptoms, (3) physical functioning, and (4) PA. Moreover, the secondary outcomes included (1) self-efficacy, (2) usability and user needs, (3) health-related quality of life, (4) satisfaction, (5) negative emotions, (6) quality of sleep, (7) adherence, (8) surgical intent, and (9) understanding of the condition (Table 5).

Table 5. Rehabilitation outcomes for patients with knee osteoarthritis.
Outcome of the interventionReferences
Physical function[11,21,22,31,32,34,36,38,39,41,44-46,49,50,52-55,59,63]
Physical activity[21,22,31,34,35,39,41,44,46,47,49-51,53-56,58,60,61]
Usability and user requirements[33,37,40,42,48,49,54,56,58,62]
Health-related quality of life[11,21,22,34,36,46,48-51,53-55,59,63]
Negative emotions[22,32,42,44,52,53,61]
Quality of sleep[42,61]
Surgical intention[38,55,59]
Understanding of the condition[38,51]

A total of 24 studies that aimed to reduce pain in patients with KOA were ultimately identified in this review [11,21,22,31,32,34,36,38,41,42,45,46,49-56,59-61,63]. Moreover, 12 studies reported statistically significant decreases in pain [11,21,31,32,36,38,41,42,49,59-61]. Of the 12 studies that did not demonstrate improvement, 6 involved randomized controlled trial protocols and 2 involved qualitative studies. In the studies that showed improvement, intervention durations ranged from 9 weeks to 9 months, and in those that did not show positive results, intervention durations ranged from 8 weeks to 6 months.

Overall, 21 studies assessed physical dysfunction [11,21,22,31,32,34,36,38,39,41,44-46,49,50,52-55,59,63], and of these, 6 reported statistically significant improvements [21,34,41,44,45,59]. Among the 15 studies that did not demonstrate improvement, 7 were randomized controlled trial protocols and 2 involved qualitative research. In studies that demonstrated improvement, intervention durations ranged from 3 weeks to 9 months, while in studies that demonstrated no improvement, intervention durations ranged from 4 weeks to 4 months.

A total of 12 studies measured PA outcomes [21,22,31,34,35,39,41,44,46,47,49-51,53-56,58], and 5 of them reported statistically significant improvements [34,41,47,49,60]. Among the 15 studies that did not demonstrate improvement, 6 were randomized controlled trial protocols and 2 involved qualitative research. In studies that demonstrated improvement, intervention durations ranged from 3 weeks to 9 months, while in studies that demonstrated no improvement, intervention durations ranged from 4 weeks to 12 months.

Physical symptoms were assessed in 11 studies [31,35,36,41,44,47,49-52,60], and of these, 4 studies reported statistically significant improvements [31,35,44,49]. In studies that demonstrated improvement, the intervention duration was 2 months, while in studies that demonstrated no improvement, intervention durations ranged from 2 to 9 months.

Self-efficacy was examined in 11 studies [11,21,22,32,36,46,52,55,58-60], and of these, 3 studies reported statistically significant improvements [11,36,58]. A total of 15 studies reported health-related quality of life [11,21,22,34,36,46,48-51,53-55,59,63], and of these, 3 studies reported statistically significant improvements [11,49,59]. Satisfaction was assessed in 8 studies [21,42,45,46,55,59,61,63], and of these, 1 study reported significant improvements [61]. Seven studies reported improvements in self-reported negative affect after the intervention [22,32,42,44,52,53,61]. Adherence was evaluated in 7 studies [22,36,42,43,49,55,58], and of these, 2 studies reported statistically significant improvements [22,58]. Sleep quality was assessed in 2 studies [42,61], and of these, 1 study [61] reported significant improvements. Three studies examined surgical intent [38,55,59]; however, none of the studies reported significant changes in patients’ surgical intent. Patients’ understanding of their condition was examined in 2 studies [38,51]; however, no improvement was identified.

Application Deficiencies

The design recommendations of users and stakeholders for the app were reported at different stages of the final app study design. Two studies identified the negative emotions associated with the app [31,56]. For instance, Östlind et al [56] found that a wearable activity tracker facilitated PA in various ways and increased the awareness of the optimal number of steps to treat OA symptoms. However, not all participants found the wearable activity tracker to be motivating, and in some cases, if they missed a weekly PA, the app’s prompts about PA caused them to feel anxious and frustrated [31].

Two studies examined the efficacy of applying various characteristics. For instance, the study by Lindberg et al [50] demonstrated the combined efficacy of education, exercise therapy, and internet-based CBT, but was unable to distinguish between these interventions individually. Moreover, Dunphy et al [49] suggested that some participants viewed the physiotherapist’s participation as positive, customizing the digital program and monitoring their progress. Others described it as restrictive, particularly if the physiotherapist did not understand how the digital program operated.

In terms of how to promote PA, the studies suggested various potential solutions. For instance, setting and achieving a daily step objective would motivate individuals to walk more than usual [56]. In addition, there was a strong desire for support from health care professionals who could monitor and guide progress; reinforce health messages; and offer reassurance, motivation, and encouragement. In the interviews, peer support through online communities (eg, forums and blogs) was also mentioned as a positive feature where people could share their experiences and learn from and support others experiencing joint pain, although users felt that it needed to be supervised to prevent inaccurate and inappropriate posts [37].


This review presents an analysis of 36 papers that examined the use of digital behavioral therapies for patients with KOA. The analysis provides insights into 3 key areas: (1) the effectiveness of digital and behavioral therapies, (2) the role of digital technologies in these treatments, and (3) the importance of involving users and stakeholders throughout the design phase.

Digitalization and Behavioral Therapy

Several digital applications designed to provide behavioral therapy–based approaches for KOA were reviewed. Various theories of behavior modification and cognition were incorporated into these applications to increase their applicability and efficacy. In this review, we discuss behavioral therapy elements that are frequently combined to form applications.

Physiotherapists or applications, goal setting based on the user’s current physical status, and BCTs derived from a control theory framework can enhance long-term sustained exercise in patients with KOA [74]. Positive reinforcement of progressive PA is the most essential element of goals and planning [75]. Gradual increases in PA alter the perception that PA is associated with pain and increase confidence in improving PA performance, resulting in favorable physical (eg, physical ability, muscle strength, and joint flexibility) and psychological (eg, self-esteem, pain perception, and anxiety) changes. Repetition and substitution are intended to boost application engagement and health-related behaviors. A “severe” to “extremely severe” program and specific dosages are designed to stimulate strength gains, resulting in enhanced function. Physiotherapists assisted participants in devising a PA program intended to increase PA, with exercises targeting the hips, knees, and ankles, including sit-to-stand exercises and seated knee extensions. Our findings indicate that the aforementioned 2 BCTs were covered in virtually all of the applications we reviewed.

It has been demonstrated that reminders increase adherence to unsupervised home strengthening exercises [76]. This feature provides personalized behavior change messages to help patients with KOA surmount barriers to exercise participation. The physiotherapist or the application sends reminder messages based on completion to assist and remind the user to reach their exercise objectives. In the mobile app or wearable device, graphical displays were used to monitor workout adherence and provide feedback. These approaches provided the ability to register the completion of weekly workout sessions and send regular messages to encourage weekly workout participation. Despite the prevalence of wearable devices, their effectiveness in enhancing PA has been questioned. These devices frequently incorporate motivational techniques, such as self-monitoring and real-time feedback, but rarely address skills such as action planning and problem solving, which are essential for altering PA behaviors. Some studies also examined common CBT topics, such as catastrophizing, positive coping strategies, and fear avoidance [42]. Specifically, supervised exercise therapy through patient education enables users to access information regarding OA treatment modalities as well as topics such as the advantages of a healthy lifestyle, PA, vitality, and nutrition.

Our analysis revealed that OA digital management applications may be an alternative to traditional therapy and may further assist with the implementation of OA standards in the wider community [77,78]. However, the engagement of a physiotherapist is a vital aspect. Most participants had favorable experiences with their assigned physiotherapist and were motivated by the daily contact and the support and encouragement provided [79].

Insights From Technology

The use of digital technologies in communication by the patient care team can contribute to the enhancement of information flow, facilitation of patient information retention, improvement of information accessibility and portability, customization of information based on individual needs, and provision of tools for patients to actively participate in their health care [75,80]. In our analysis, the process of digitization manifested through a convergence of several technological mediums, including apps and websites, text messaging, phone calls, emails, and wearable gadgets.

New patient self-management programs have emerged in recent years, demonstrating the importance and efficacy of eHealth interventions such as websites and mobile apps. Current topics include PA, exercise, goal setting, action plans, pacing, medication management, nutrition, at-home exercise, pain comprehension, pain management, and relaxation. They may be combined with multimedia technologies to facilitate the sharing of content and with human-computer interface technologies to enhance accessibility.

Most health and medical apps fail to retain users beyond 90 days. This is due to their missing potential for facilitating disease management and provider-patient communication. The development of teleconferencing software or telematic messaging technology is supported by reminders and distinct objectives [81]. The development of text messaging program functionality and message libraries (including message types, message frequency, and program interaction levels) has the potential to increase adherence to unsupervised home exercise.

Wearable electronic devices aid in tracking the user’s daily activities and offer continuous visualization support. However, such devices typically carry a greater risk of privacy invasion and social stigmatization. Our findings indicate that none of the studies specifically addressed privacy concerns. Therefore, designers of pertinent systems should be encouraged to consider these factors more thoroughly. In addition, current wearable electronic devices collect limited data, and their primary function is still to provide feedback on physiological signals (steps, consumption, asymmetry, etc), lacking the accumulation of electrical signals unique to KOA. In the future, machine learning can be introduced into ubiquitous devices to predict patient activity in order to improve patient care.

In the reviewed studies, the combination of app/website plus SMS text message/telephone/email was the most common. It has been shown that text messaging programs combined with unsupervised web-based exercise can reduce pain and dysfunction in patients with KOA [22,40]. Although the addition of wearable electronic devices would improve the intervention process by providing more accurate monitoring data, the experience would not be enhanced. However, the cost of ubiquitous electronic devices and the complexity of their operation continue to prevent their widespread adoption.

Insights From the User or Stakeholder Experience

Less than half of the reviewed studies reported structured user or stakeholder participation in the design phase of their systems, according to our analysis. Nonetheless, there is a distinct trend indicating that an increasing number of studies are emphasizing the significance of involving users in the design and development phases (and not just the validation or deployment phases). Specifically, we summarize a set of emerging user or stakeholder involvement design trends in emerging research on the application of digital behavioral therapy for KOA. Based on the interviews conducted for the qualitative study, issues were identified with the digital app user experience of KOA patients [52,56,62].

First, direct patient feedback was not taken into account when developing the content of the apps, and the content was based solely on the knowledge and experience of hospital staff. In future studies, patients should play a more important role in the development of the content of patient-specific apps, evaluating and further optimizing the preferable mode of information for outcomes [26]. Moreover, there is a need for a structured collaborative design involving patients, physicians, and researchers in order to establish multiple collaborative processes based on shared concepts, mutual learning, and respect for diversity and divergent opinions [82].

Second, digital support is regarded as an integral component of OA care. An ideal approach would be one that combines traditional OA care with digital OA care to offer solutions for personalized, comprehensive, straightforward, dependable, and continuous hybrid care [56,81]. The experience of digital applications is divided into 4 subcategories [79]: (1) simplicity of implementation, (2) flexibility in choosing time and location, (3) significance of interaction with health care professionals, and (4) additional motivating factors. Consequently, our research contends that digital applications must incorporate and differentiate between various user experience stages.

The functional requirements of apps that patients, physicians, and researchers deemed most essential, convenient, desirable, and actionable differed significantly. Participants in the studies agreed, despite their differences, that minimum viable products should be electronic, should monitor patients’ symptoms and activities, and should include features tailored to factors identified by patients and physicians as well as self-management strategies based on international guidelines. Over the course of the study, participants came to a consensus regarding the order of their functional requirements. Visual symptom mapping, goal setting, exercise programs, daily monitoring, and self-management strategies had the highest priorities.

Future Work

After conducting a thorough study, a set of recommendations were summarized to improve the quality of applications. These recommendations are focused on making the process more efficient and improving future design and development endeavors. Suggestions for future studies are presented below.

Digital Applications that Provide Comprehensive Monitoring of the Entire Treatment Process

To enhance the rehabilitation of patients, it is necessary to thoroughly investigate the efficacy and impact of different behavioral therapies. This will enable the development of more precise application strategies. Multiple behavioral therapies should be integrated to cover all aspects of the rehabilitation process, including rehabilitation exercises, status monitoring, and self-screening, in order to ensure that patients receive comprehensive care. Simultaneously, by promptly understanding the wants of patients, we can bolster their trust in the process of recuperation. This customized service model can enhance patient happiness and confidence, while also facilitating the seamless advancement of the rehabilitation process. Further investigation can enhance our comprehension by examining particular facets of digital health care platforms, such as network effects and the strategic management of platform ecosystem innovation [83].

Data Analysis Requirements of Patients Based on Intelligent Algorithms

Artificial intelligence algorithms are crucial for extracting important insights from vast quantities of data and offering therapists precise recommendations. As an illustration, the algorithm may examine a patient’s exercise data while they are undergoing rehabilitation and detect tiny modifications. This helps the therapist in fine-tuning the intensity and substance of the training. Furthermore, through the comparison of data from many patients, the algorithm can investigate the efficacy of different treatments for specific patient groups, thereby establishing a strategic foundation for later treatment decisions. Significantly, these data serve the dual purposes of enhancing the precision and pertinence of treatment and evaluating the impact of different behavioral interventions. In conventional rehabilitation programs, this procedure is frequently based on subjective criteria. By employing a data-driven methodology, we can impartially evaluate the true efficacy of each technique, establishing a strong basis for further research and applications.

Community-Based Rehabilitation Scenarios With Digital Technology Integration

In order to enhance the adoption of digital behavioral therapy in rehabilitation, our objective is to extend its implementation from the domestic setting to the broader social community rehabilitation setting. The community rehabilitation setting offers a platform for patients to engage and assist one another, and fosters patients’ motivation and assurance in their recovery process. For instance, an internet-based community can be established to facilitate patients in exchanging their recovery experiences, offering reciprocal motivation and assistance, and deliberating the obstacles and remedies related to the recovery journey. Additionally, offline activities, including rehabilitation lectures, group seminars, and interactive games, can be arranged to augment patients’ social interaction and foster a sense of team camaraderie. Strong partnerships can be fostered with medical organizations and rehabilitation professionals in the community to offer comprehensive assistance for patient recovery. This not only enhances patient rehabilitation outcomes and quality of life, but also fosters the integration and optimization of community rehabilitation resources and promotes overall progress in the field of patient recovery.


This research has some limitations. Initially, our evaluation thoroughly examined the present state of digital behavioral therapy applications using qualitative analysis. However, it is indisputable that quantitative analysis yields more robust clinical value. Hence, a complete quantitative meta-analysis will be conducted to assess the efficacy of digital behavioral therapy applications. Future research will integrate both qualitative and quantitative analyses to provide a more thorough evaluation. In addition, our search was limited to English-language research publications, and it is possible that there are significant findings in other languages. The search for research papers was restricted to 5 databases (Web of Science, ScienceDirect, PubMed, Ovid, and Embase). As algorithms are added to digital intervention tools, additional computer science databases, such as IEEE and ACM, could be added to increase the comprehensiveness of the assessment. Furthermore, this review was limited by the search criteria employed and the time period during which the papers were published. However, a focus on the last 10 years went a long way in ensuring that this systematic review includes the most recent research.


This review provides an overview of digital behavioral therapy applications for patients with KOA. In this systematic review, 36 studies were examined. The results demonstrate 14 BCTs and show that behavioral cognitive therapies are frequently combined when developing digital applications. The most prevalent areas were “goals and planning” and “repetition and substitution,” which were frequently used to develop PA goals and PA behavior adherence. The most prevalent combination strategy was app/website plus SMS text message/telephone/email, which has tremendous potential. Consequently, this research provided results for digital applications in terms of pain relief, physical function improvement, self-confidence, and improvement in health-related quality of life among patients with KOA. Nevertheless, there was a shortage of evidence indicating enhanced surgical intention, compliance, and disease knowledge. Subsequent quantitative analysis of this phenomenon is required in the future. Moreover, the incorporation of several stakeholders in the design and development stages might enhance the user experience, considering the distinct variations in their requirements. Based on the findings, digital applications should incorporate various stages of user experience and should include a combination of traditional and digital solutions for OA care.

Conflicts of Interest

None declared.

Multimedia Appendix 1

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.

PDF File (Adobe PDF File), 748 KB

Multimedia Appendix 2

Mixed Methods Appraisal Tool (MMAT), version 2018.

PDF File (Adobe PDF File), 62 KB

Multimedia Appendix 3

The literature search results.

PDF File (Adobe PDF File), 82 KB

Multimedia Appendix 4

Methodological quality assessment using the Mixed Methods Appraisal Tool (MMAT).

DOC File , 67 KB

  1. Uivaraseanu B, Vesa C, Tit D, Abid A, Maghiar O, Maghiar T, et al. Therapeutic approaches in the management of knee osteoarthritis (Review). Exp Ther Med. May 15, 2022;23(5):328. [FREE Full text] [CrossRef] [Medline]
  2. Jormand H, Mohammadi N, Khani Jeihooni A, Afzali Harsini P. Self-care behaviors in older adults suffering from knee osteoarthritis: Application of theory of planned behavior. Front Public Health. Nov 4, 2022;10:958614. [FREE Full text] [CrossRef] [Medline]
  3. Sharma L. Osteoarthritis of the Knee. N Engl J Med. Jan 07, 2021;384(1):51-59. [CrossRef] [Medline]
  4. Veronese N, Honvo G, Bruyère O, Rizzoli R, Barbagallo M, Maggi S, et al. Knee osteoarthritis and adverse health outcomes: an umbrella review of meta-analyses of observational studies. Aging Clin Exp Res. Feb 04, 2023;35(2):245-252. [FREE Full text] [CrossRef] [Medline]
  5. Arden NK, Perry TA, Bannuru RR, Bruyère O, Cooper C, Haugen IK, et al. Non-surgical management of knee osteoarthritis: comparison of ESCEO and OARSI 2019 guidelines. Nat Rev Rheumatol. Jan 28, 2021;17(1):59-66. [FREE Full text] [CrossRef] [Medline]
  6. Ghomrawi H, Lee J. Commentary on the article risk scoring for time to end-stage knee osteoarthritis: data from the osteoarthritis initiative. Osteoarthritis Cartilage. Aug 2020;28(8):1001-1002. [FREE Full text] [CrossRef] [Medline]
  7. Dobson F, Bennell K, French S, Nicolson P, Klaasman R, Holden M, et al. Barriers and Facilitators to Exercise Participation in People with Hip and/or Knee Osteoarthritis: Synthesis of the Literature Using Behavior Change Theory. Am J Phys Med Rehabil. May 2016;95(5):372-389. [CrossRef] [Medline]
  8. Kampmeijer R, Pavlova M, Tambor M, Golinowska S, Groot W. The use of e-health and m-health tools in health promotion and primary prevention among older adults: a systematic literature review. BMC Health Serv Res. Sep 05, 2016;16 Suppl 5(Suppl 5):290. [FREE Full text] [CrossRef] [Medline]
  9. Wilson R, Chua J, Briggs AM, Abbott JH. The cost-effectiveness of recommended adjunctive interventions for knee osteoarthritis: Results from a computer simulation model. Osteoarthr Cartil Open. Dec 2020;2(4):100123. [FREE Full text] [CrossRef] [Medline]
  10. Kostic AM, Leifer VP, Gong Y, Robinson MK, Collins JE, Neogi T, et al. Cost-Effectiveness of Surgical Weight-Loss Interventions for Patients With Knee Osteoarthritis and Class III Obesity. Arthritis Care Res (Hoboken). Mar 17, 2023;75(3):491-500. [FREE Full text] [CrossRef] [Medline]
  11. Bennell KL, Nelligan R, Dobson F, Rini C, Keefe F, Kasza J, et al. Effectiveness of an Internet-Delivered Exercise and Pain-Coping Skills Training Intervention for Persons With Chronic Knee Pain: A Randomized Trial. Ann Intern Med. Apr 04, 2017;166(7):453-462. [CrossRef] [Medline]
  12. Valentijn PP, Tymchenko L, Jacobson T, Kromann J, Biermann CW, AlMoslemany MA, et al. Digital Health Interventions for Musculoskeletal Pain Conditions: Systematic Review and Meta-analysis of Randomized Controlled Trials. J Med Internet Res. Sep 06, 2022;24(9):e37869. [FREE Full text] [CrossRef] [Medline]
  13. Xie S, Wang Q, Wang L, Wang L, Song K, He C. Effect of Internet-Based Rehabilitation Programs on Improvement of Pain and Physical Function in Patients with Knee Osteoarthritis: Systematic Review and Meta-analysis of Randomized Controlled Trials. J Med Internet Res. Jan 05, 2021;23(1):e21542. [FREE Full text] [CrossRef] [Medline]
  14. Zhang Z, Tian L, He K, Xu L, Wang X, Huang L, et al. Digital Rehabilitation Programs Improve Therapeutic Exercise Adherence for Patients With Musculoskeletal Conditions: A Systematic Review With Meta-Analysis. J Orthop Sports Phys Ther. Nov 2022;52(11):726-739. [CrossRef] [Medline]
  15. Hewitt S, Sephton R, Yeowell G. The Effectiveness of Digital Health Interventions in the Management of Musculoskeletal Conditions: Systematic Literature Review. J Med Internet Res. Jun 05, 2020;22(6):e15617. [FREE Full text] [CrossRef] [Medline]
  16. Shah N, Costello K, Mehta A, Kumar D. Applications of Digital Health Technologies in Knee Osteoarthritis: Narrative Review. JMIR Rehabil Assist Technol. Jun 08, 2022;9(2):e33489. [FREE Full text] [CrossRef] [Medline]
  17. Durst J, Roesel I, Sudeck G, Sassenberg K, Krauss I. Effectiveness of Human Versus Computer-Based Instructions for Exercise on Physical Activity-Related Health Competence in Patients with Hip Osteoarthritis: Randomized Noninferiority Crossover Trial. J Med Internet Res. Sep 28, 2020;22(9):e18233. [FREE Full text] [CrossRef] [Medline]
  18. Wang Y, Lombard C, Hussain SM, Harrison C, Kozica S, Brady SRE, et al. Effect of a low-intensity, self-management lifestyle intervention on knee pain in community-based young to middle-aged rural women: a cluster randomised controlled trial. Arthritis Res Ther. Apr 17, 2018;20(1):74. [FREE Full text] [CrossRef] [Medline]
  19. Safari R, Jackson J, Sheffield D. Digital Self-Management Interventions for People With Osteoarthritis: Systematic Review With Meta-Analysis. J Med Internet Res. Jul 20, 2020;22(7):e15365. [FREE Full text] [CrossRef] [Medline]
  20. O'moore KA, Newby JM, Andrews G, Hunter DJ, Bennell K, Smith J, et al. Internet Cognitive-Behavioral Therapy for Depression in Older Adults With Knee Osteoarthritis: A Randomized Controlled Trial. Arthritis Care Res (Hoboken). Jan 2018;70(1):61-70. [CrossRef] [Medline]
  21. Nelligan RK, Hinman RS, Kasza J, Crofts SJC, Bennell KL. Effects of a Self-directed Web-Based Strengthening Exercise and Physical Activity Program Supported by Automated Text Messages for People With Knee Osteoarthritis: A Randomized Clinical Trial. JAMA Intern Med. Jun 01, 2021;181(6):776-785. [FREE Full text] [CrossRef] [Medline]
  22. Bennell K, Nelligan RK, Schwartz S, Kasza J, Kimp A, Crofts SJ, et al. Behavior Change Text Messages for Home Exercise Adherence in Knee Osteoarthritis: Randomized Trial. J Med Internet Res. Sep 28, 2020;22(9):e21749. [FREE Full text] [CrossRef] [Medline]
  23. Nelligan RK, Hinman RS, McManus F, Lamb KE, Bennell KL. Moderators of the Effect of a Self-directed Digitally Delivered Exercise Program for People With Knee Osteoarthritis: Exploratory Analysis of a Randomized Controlled Trial. J Med Internet Res. Oct 29, 2021;23(10):e30768. [FREE Full text] [CrossRef] [Medline]
  24. Allegrante JP, Kovar PA, MacKenzie C, Peterson MGE, Gutin B. A walking education program for patients with osteoarthritis of the knee: theory and intervention strategies. Health Educ Q. Sep 04, 1993;20(1):63-81. [CrossRef] [Medline]
  25. Ravalli S, Roggio F, Lauretta G, Di Rosa M, D'Amico AG, D'agata V, et al. Exploiting real-world data to monitor physical activity in patients with osteoarthritis: the opportunity of digital epidemiology. Heliyon. Feb 2022;8(2):e08991. [FREE Full text] [CrossRef] [Medline]
  26. Timmers T, Janssen L, van der Weegen W, Das D, Marijnissen W, Hannink G, et al. The Effect of an App for Day-to-Day Postoperative Care Education on Patients With Total Knee Replacement: Randomized Controlled Trial. JMIR Mhealth Uhealth. Oct 21, 2019;7(10):e15323. [FREE Full text] [CrossRef] [Medline]
  27. Rini C, Katz AWK, Nwadugbo A, Porter LS, Somers TJ, Keefe FJ. Changes in Identification of Possible Pain Coping Strategies by People with Osteoarthritis who Complete Web-based Pain Coping Skills Training. Int J Behav Med. Aug 10, 2021;28(4):488-498. [FREE Full text] [CrossRef] [Medline]
  28. McCurry SM, Zhu W, Von Korff M, Wellman R, Morin CM, Thakral M, et al. Effect of Telephone Cognitive Behavioral Therapy for Insomnia in Older Adults With Osteoarthritis Pain: A Randomized Clinical Trial. JAMA Intern Med. Apr 01, 2021;181(4):530-538. [FREE Full text] [CrossRef] [Medline]
  29. Moher D, Liberati A, Tetzlaff J, Altman D, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. Aug 18, 2009;151(4):264-9, W64. [FREE Full text] [CrossRef] [Medline]
  30. Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. EFI. Dec 18, 2018;34(4):285-291. [CrossRef]
  31. Bossen D, Veenhof C, Van Beek KE, Spreeuwenberg PM, Dekker J, De Bakker DH. Effectiveness of a web-based physical activity intervention in patients with knee and/or hip osteoarthritis: randomized controlled trial. J Med Internet Res. Nov 22, 2013;15(11):e257. [FREE Full text] [CrossRef] [Medline]
  32. Rini C, Porter LS, Somers TJ, McKee DC, DeVellis RF, Smith M, et al. Automated Internet-based pain coping skills training to manage osteoarthritis pain: a randomized controlled trial. Pain. May 2015;156(5):837-848. [FREE Full text] [CrossRef] [Medline]
  33. Pearson J, Walsh N, Carter D, Koskela S, Hurley M. Developing a Web-Based Version of An Exercise-Based Rehabilitation Program for People With Chronic Knee and Hip Pain: A Mixed Methods Study. JMIR Res Protoc. May 19, 2016;5(2):e67. [FREE Full text] [CrossRef] [Medline]
  34. Bennell KL, Campbell PK, Egerton T, Metcalf B, Kasza J, Forbes A, et al. Telephone Coaching to Enhance a Home-Based Physical Activity Program for Knee Osteoarthritis: A Randomized Clinical Trial. Arthritis Care Res (Hoboken). Jan 2017;69(1):84-94. [FREE Full text] [CrossRef] [Medline]
  35. Li LC, Sayre EC, Xie H, Clayton C, Feehan LM. A Community-Based Physical Activity Counselling Program for People With Knee Osteoarthritis: Feasibility and Preliminary Efficacy of the Track-OA Study. JMIR Mhealth Uhealth. Jun 26, 2017;5(6):e86. [FREE Full text] [CrossRef] [Medline]
  36. 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. May 09, 2018;20(5):e10021. [FREE Full text] [CrossRef] [Medline]
  37. Button K, Nicholas K, Busse M, Collins M, Spasić I. Integrating self-management support for knee injuries into routine clinical practice: TRAK intervention design and delivery. Musculoskelet Sci Pract. Feb 2018;33:53-60. [FREE Full text] [CrossRef] [Medline]
  38. Mecklenburg G, Smittenaar P, Erhart-Hledik JC, Perez DA, Hunter S. Effects of a 12-Week Digital Care Program for Chronic Knee Pain on Pain, Mobility, and Surgery Risk: Randomized Controlled Trial. J Med Internet Res. Apr 25, 2018;20(4):e156. [FREE Full text] [CrossRef] [Medline]
  39. Kline PW, Melanson EL, Sullivan WJ, Blatchford PJ, Miller MJ, Stevens-Lapsley JE, et al. Improving Physical Activity Through Adjunct Telerehabilitation Following Total Knee Arthroplasty: Randomized Controlled Trial Protocol. Phys Ther. Jan 01, 2019;99(1):37-45. [FREE Full text] [CrossRef] [Medline]
  40. Nelligan RK, Hinman RS, Atkins L, Bennell KL. A Short Message Service Intervention to Support Adherence to Home-Based Strengthening Exercise for People With Knee Osteoarthritis: Intervention Design Applying the Behavior Change Wheel. JMIR Mhealth Uhealth. Oct 18, 2019;7(10):e14619. [FREE Full text] [CrossRef] [Medline]
  41. Pelle T, Bevers K, van der Palen J, van den Hoogen F, van den Ende C. Effect of the dr. Bart application on healthcare use and clinical outcomes in people with osteoarthritis of the knee and/or hip in the Netherlands; a randomized controlled trial. Osteoarthritis Cartilage. Apr 2020;28(4):418-427. [FREE Full text] [CrossRef] [Medline]
  42. Bailey JF, Agarwal V, Zheng P, Smuck M, Fredericson M, Kennedy DJ, et al. Digital Care for Chronic Musculoskeletal Pain: 10,000 Participant Longitudinal Cohort Study. J Med Internet Res. May 11, 2020;22(5):e18250. [FREE Full text] [CrossRef] [Medline]
  43. Baker K, LaValley MP, Brown C, Felson DT, Ledingham A, Keysor JJ. Efficacy of Computer-Based Telephone Counseling on Long-Term Adherence to Strength Training in Elderly Patients With Knee Osteoarthritis: A Randomized Trial. Arthritis Care Res (Hoboken). Jul 2020;72(7):982-990. [FREE Full text] [CrossRef] [Medline]
  44. Fitzgibbon ML, Tussing-Humphreys L, Schiffer L, Smith-Ray R, Marquez DX, DeMott AD, et al. Fit and Strong! Plus: Twelve and eighteen month follow-up results for a comparative effectiveness trial among overweight/obese older adults with osteoarthritis. Prev Med. Dec 2020;141:106267. [FREE Full text] [CrossRef] [Medline]
  45. Hinman RS, Campbell PK, Lawford BJ, Briggs AM, Gale J, Bills C, et al. Does telephone-delivered exercise advice and support by physiotherapists improve pain and/or function in people with knee osteoarthritis? Telecare randomised controlled trial. Br J Sports Med. Jul 20, 2020;54(13):790-797. [CrossRef] [Medline]
  46. Hinman RS, Kimp AJ, Campbell PK, Russell T, Foster NE, Kasza J, et al. Technology versus tradition: a non-inferiority trial comparing video to face-to-face consultations with a physiotherapist for people with knee osteoarthritis. Protocol for the PEAK randomised controlled trial. BMC Musculoskelet Disord. Aug 07, 2020;21(1):522. [FREE Full text] [CrossRef] [Medline]
  47. Li LC, Feehan LM, Xie H, Lu N, Shaw CD, Gromala D, et al. Effects of a 12-Week Multifaceted Wearable-Based Program for People With Knee Osteoarthritis: Randomized Controlled Trial. JMIR Mhealth Uhealth. Jul 03, 2020;8(7):e19116. [FREE Full text] [CrossRef] [Medline]
  48. 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. Nov 26, 2020;7(2):e18860. [FREE Full text] [CrossRef] [Medline]
  49. Dunphy E, Button K, Hamilton F, Williams J, Spasic I, Murray E. Feasibility randomised controlled trial comparing TRAK-ACL digital rehabilitation intervention plus treatment as usual versus treatment as usual for patients following anterior cruciate ligament reconstruction. BMJ Open Sport Exerc Med. May 06, 2021;7(2):e001002. [FREE Full text] [CrossRef] [Medline]
  50. Lindberg MF, Aamodt A, Badawy M, Bergvad IB, Borchgrevink P, Furnes O, et al. The effectiveness of exercise therapy and education plus cognitive behavioral therapy, alone or in combination with total knee arthroplasty in patients with knee osteoarthritis - study protocol for the MultiKnee trial. BMC Musculoskelet Disord. Dec 20, 2021;22(1):1054. [FREE Full text] [CrossRef] [Medline]
  51. Pelle T, van der Palen J, de Graaf F, van den Hoogen FHJ, Bevers K, van den Ende CHM. Use and usability of the dr. Bart app and its relation with health care utilisation and clinical outcomes in people with knee and/or hip osteoarthritis. BMC Health Serv Res. May 10, 2021;21(1):444. [FREE Full text] [CrossRef] [Medline]
  52. Rognsvåg T, Lindberg MF, Lerdal A, Stubberud J, Furnes O, Holm I, et al. Development of an internet-delivered cognitive behavioral therapy program for use in combination with exercise therapy and education by patients at increased risk of chronic pain following total knee arthroplasty. BMC Health Serv Res. Oct 25, 2021;21(1):1151. [FREE Full text] [CrossRef] [Medline]
  53. Bennell KL, Jones SE, Hinman RS, McManus F, Lamb KE, Quicke JG, et al. Effectiveness of a telehealth physiotherapist-delivered intensive dietary weight loss program combined with exercise in people with knee osteoarthritis and overweight or obesity: study protocol for the POWER randomized controlled trial. BMC Musculoskelet Disord. Jul 30, 2022;23(1):733. [FREE Full text] [CrossRef] [Medline]
  54. Groves-Williams D, McHugh GA, Bennell KL, Comer C, Hensor EMA, Conner M, et al. Evaluation of two electronic-rehabilitation programmes for persistent knee pain: protocol for a randomised feasibility trial. BMJ Open. Jun 03, 2022;12(6):e063608. [FREE Full text] [CrossRef] [Medline]
  55. Hinman RS, Nelligan RK, Campbell PK, Kimp AJ, Graham B, Merolli M, et al. Exercise adherence Mobile app for Knee Osteoarthritis: protocol for the MappKO randomised controlled trial. BMC Musculoskelet Disord. Sep 20, 2022;23(1):874. [FREE Full text] [CrossRef] [Medline]
  56. Östlind E, Ekvall Hansson E, Eek F, Stigmar K. Experiences of activity monitoring and perceptions of digital support among working individuals with hip and knee osteoarthritis - a focus group study. BMC Public Health. Aug 30, 2022;22(1):1641. [FREE Full text] [CrossRef] [Medline]
  57. Östlind E, Eek F, Stigmar K, Sant'Anna A, Hansson EE. Promoting work ability with a wearable activity tracker in working age individuals with hip and/or knee osteoarthritis: a randomized controlled trial. BMC Musculoskelet Disord. Feb 03, 2022;23(1):112. [FREE Full text] [CrossRef] [Medline]
  58. Whittaker JL, Truong LK, Silvester-Lee T, Losciale JM, Miciak M, Pajkic A, et al. Feasibility of the SOAR (Stop OsteoARthritis) program. Osteoarthr Cartil Open. Mar 2022;4(1):100239. [FREE Full text] [CrossRef] [Medline]
  59. 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. Feb 17, 2023;24(1):129. [FREE Full text] [CrossRef] [Medline]
  60. Lorbeer N, Knoll N, Keller J, Domke A, Di Maio S, Armbrecht G, et al. Enhancing physical activity and reducing symptoms of patients with osteoarthritis of the knee: a randomized controlled trial of the PrevOP-Psychological Adherence Program. BMC Musculoskelet Disord. Jul 04, 2023;24(1):550. [FREE Full text] [CrossRef] [Medline]
  61. Scheer JK, Costa F, Janela D, Molinos M, Areias AC, Moulder RG, et al. Sleep Disturbance in Musculoskeletal Conditions: Impact of a Digital Care Program. J Pain Res. 2023;16:33-46. [FREE Full text] [CrossRef] [Medline]
  62. Truong LK, Mosewich AD, Miciak M, Pajkic A, Silvester-Lee T, Li LC, et al. "I feel I'm leading the charge." Experiences of a virtual physiotherapist-guided knee health program for persons at-risk of osteoarthritis after a sport-related knee injury. Osteoarthr Cartil Open. Mar 2023;5(1):100333. [FREE Full text] [CrossRef] [Medline]
  63. Weber F, Müller C, Bahns C, Kopkow C, Färber F, Gellert P, et al. Smartphone-assisted training with education for patients with hip and/or knee osteoarthritis (SmArt-E): study protocol for a multicentre pragmatic randomized controlled trial. BMC Musculoskelet Disord. Mar 23, 2023;24(1):221. [FREE Full text] [CrossRef] [Medline]
  64. Bouma AJ, van Wilgen P, Dijkstra A. The barrier-belief approach in the counseling of physical activity. Patient Educ Couns. Feb 2015;98(2):129-136. [CrossRef] [Medline]
  65. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. Aug 2013;46(1):81-95. [FREE Full text] [CrossRef] [Medline]
  66. Wood CE, Hardeman W, Johnston M, Francis J, Abraham C, Michie S. Reporting behaviour change interventions: do the behaviour change technique taxonomy v1, and training in its use, improve the quality of intervention descriptions? Implement Sci. Jun 07, 2016;11(1):84. [FREE Full text] [CrossRef] [Medline]
  67. Shepherd N, Parker C. Depression in adults: recognition and management. Clinical Pharmacist. 2017;9(4):1-15. [CrossRef]
  68. DiRenzo D, Finan P. Self-Efficacy and the Role of Non-Pharmacologic Treatment Strategies to Improve Pain and Affect in Arthritis. Curr Treatm Opt Rheumatol. Jun 15, 2019;5(2):168-178. [FREE Full text] [CrossRef] [Medline]
  69. Cohen E, Lee YC. A Mechanism-Based Approach to the Management of Osteoarthritis Pain. Curr Osteoporos Rep. Dec 30, 2015;13(6):399-406. [FREE Full text] [CrossRef] [Medline]
  70. Broderick JE, Keefe FJ, Schneider S, Junghaenel DU, Bruckenthal P, Schwartz JE, et al. Cognitive behavioral therapy for chronic pain is effective, but for whom? Pain. Sep 25, 2016;157(9):2115-2123. [CrossRef] [Medline]
  71. Evers A, Kraaimaat F, van Riel P, de Jong A. Tailored cognitive-behavioral therapy in early rheumatoid arthritis for patients at risk: a randomized controlled trial. Pain. Nov 2002;100(1-2):141-153. [CrossRef] [Medline]
  72. Dório M, Hunter D, Bowden J, Redman S, Redman A, Dawson G, et al. Training needs and approaches to performance improvement of musculoskeletal physiotherapists coordinating the osteoarthritis chronic care program. Osteoarthritis and Cartilage. Apr 2020;28:S451-S452. [CrossRef]
  73. Dreiser R, Schwartz P. AB0602 Influence of internet on relationships between patients and rheumatologists: specific focus on hip and knee osteoarthritis management (survey study). Ann Rheum Dis. Jan 23, 2014;72(Suppl 3):A974.2-A9A974. [CrossRef]
  74. Danbjørg D, Villadsen A, Gill E, Rothmann MJ, Clemensen J. Usage of an Exercise App in the Care for People With Osteoarthritis: User-Driven Exploratory Study. JMIR Mhealth Uhealth. Jan 11, 2018;6(1):e11. [FREE Full text] [CrossRef] [Medline]
  75. Dunphy E, Gardner EC. Telerehabilitation to Address the Rehabilitation Gap in Anterior Cruciate Ligament Care: Survey of Patients. JMIR Form Res. Sep 18, 2020;4(9):e19296. [FREE Full text] [CrossRef] [Medline]
  76. Willett M, Duda J, Fenton S, Gautrey C, Greig C, Rushton A. Effectiveness of behaviour change techniques in physiotherapy interventions to promote physical activity adherence in lower limb osteoarthritis patients: A systematic review. PLoS One. 2019;14(7):e0219482. [FREE Full text] [CrossRef] [Medline]
  77. Clarkson P, Vassilev I, Rogers A, Brooks C, Wilson N, Lawson J, et al. Integrating a Web-Based Self-Management Tool (Managing Joint Pain on the Web and Through Resources) for People With Osteoarthritis-Related Joint Pain With a Web-Based Social Network Support Tool (Generating Engagement in Network Involvement): Design, Development, and Early Evaluation. JMIR Form Res. Nov 26, 2020;4(11):e18565. [FREE Full text] [CrossRef] [Medline]
  78. Plinsinga ML, Besomi M, Maclachlan L, Melo L, Robbins S, Lawford BJ, et al. Exploring the Characteristics and Preferences for Online Support Groups: Mixed Method Study. J Med Internet Res. Dec 03, 2019;21(12):e15987. [FREE Full text] [CrossRef] [Medline]
  79. 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. May 24, 2019;9(5):e028388. [FREE Full text] [CrossRef] [Medline]
  80. van Kasteren Y, Freyne J, Hussain MS. Total Knee Replacement and the Effect of Technology on Cocreation for Improved Outcomes and Delivery: Qualitative Multi-Stakeholder Study. J Med Internet Res. Mar 20, 2018;20(3):e95. [FREE Full text] [CrossRef] [Medline]
  81. Stuhlreyer J, Roder C, Krug F, Zöllner C, Flor H, Klinger R. A digital application and augmented physician rounds reduce postoperative pain and opioid consumption after primary total knee replacement (TKR): a randomized clinical trial. BMC Med. Dec 05, 2022;20(1):469. [FREE Full text] [CrossRef] [Medline]
  82. Mrklas KJ, Barber T, Campbell-Scherer D, Green LA, Li LC, Marlett N, et al. Co-Design in the Development of a Mobile Health App for the Management of Knee Osteoarthritis by Patients and Physicians: Qualitative Study. JMIR Mhealth Uhealth. Jul 10, 2020;8(7):e17893. [FREE Full text] [CrossRef] [Medline]
  83. Cenamor J. Use of health self-management platform features: The case of a specialist ehealth app. Technological Forecasting and Social Change. Dec 2022;185:122066. [CrossRef]

BCT: behavioral change technique
CBT: cognitive behavioral therapy
KOA: knee osteoarthritis
MeSH: Medical Subject Headings
MMAT: Mixed Methods Assessment Tool
OA: osteoarthritis
PA: physical activity

Edited by L Buis; submitted 19.10.23; peer-reviewed by J Zeitlin, TAR Sure; comments to author 22.12.23; revised version received 07.02.24; accepted 14.03.24; published 02.05.24.


©Dian Zhu, Jianan Zhao, Mingxuan Wang, Bochen Cao, Wenhui Zhang, Yunlong Li, Chenqi Zhang, Ting Han. Originally published in JMIR mHealth and uHealth (, 02.05.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.