Assistive devices (ADs) are defined as “any item, piece of equipment, or product system, whether commercially acquired, modified, or customized, that is used to enhance, maintain, or improve the functional capabilities of individuals with disabilities.” [1]. Among these, mobility devices, particularly prosthetics and orthotics (P&O), are the most frequently needed [2], with global demand rising due to aging populations and the increased prevalence of disabling conditions [3,4].

Estimates of the global need vary, with some reports suggesting that up to 2.4 billion people may benefit from ADs by 2050 [2,3,5,6]. However, the ability to meet this growing demand is hampered by a shortage of trained professionals [3,5].

Prosthetists and orthotists professionals play a vital role in the comprehensive assessment of patients, considering physical, functional, psychosocial, and environmental factors, as well as in the design, fitting, and adjustment of ADs [6]. Yet, the number of trained professionals is insufficient to match the growing patient population. In Canada, for example, 37% of individuals report unmet needs for ADs [7]. In Sweden, where P&O training is offered only at Jönköping University, a national shortage is acknowledged, suggesting similar challenges in service delivery [8]. This shortage is associated with delayed care, extended rehabilitation timelines, and suboptimal patient outcomes [3,6].

Beyond workforce limitations, inefficiencies in the clinical workflow also affect care delivery. The process of prescribing a prosthetic device typically involves multiple professionals across 3 stages: physician referral, prosthetist assessment and fitting, and rehabilitation therapy [4]. However, the lack of standardized decision-making protocols often results in variation in device selection and unequal patient outcomes. For instance, in Sweden, regional guidelines differ, leading to inconsistent levels of care across clinics [9], further exacerbating inconsistencies in care.

Another concern is the limited follow-up after device delivery. Patients often reconnect with their prosthetists only when problems arise, making it difficult to track long-term outcomes or ensure continuous use. This is critical, as discontinuation of AD is a common issue. Studies have found abandonment rates as high as 40% in some populations, with reasons including discomfort, poor training, and inadequate follow-up [10-12]. Discontinued use is not only associated with poorer health outcomes but also imposes additional economic strain due to the cost of unused or replacement devices [10-15].

Reimbursement models in the P&O field further compound these challenges. In many settings, including Sweden and the United States, reimbursement is based on a fee-for-service model that emphasizes device provision over patient outcomes [16]. This misalignment can lead to inefficiencies and insufficient incentives to support ongoing patient engagement. As health care systems move toward value-based models [17-19], there is an increasing demand for solutions that promote better outcomes while optimizing workflow.

One such solution is Life Lounge Clinical Workflow (LLCW), a digital platform developed by Ottobock to support prosthetists and orthotists professionals in managing patient data, monitoring progress, and enhancing interprofessional communication [20]. LLCW centralizes records, enables data transfer, and includes tools such as Smart Documentation and Custom Fabrication to streamline administrative processes and personalize care.

These features aim to reduce documentation burden, improve decision-making, and increase patient engagement, thereby addressing some of the key inefficiencies in current AD workflows.

LLCW, although not yet deployed in Sweden, has been used since 2023 in US clinics with positive feedback.

LLCW proposes to enhance the workflow by:

These key changes aim to streamline the clinical process, promote patient-centered care, and improve overall efficiency.

Despite the benefits of LLCW, immediate acceptance by Swedish prosthetists and orthotists professionals is not guaranteed. Health care technology adoption can face resistance or unintended consequences if imposed without considering user concerns [21,22]. This study aims to optimize LLCW deployment by first understanding acceptance and addressing potential barriers.

Several frameworks assess technology acceptance, particularly in health care, where new tools impact workflows. Two widely used models are the technology acceptance model (TAM) [23] and the unified theory of acceptance and use of technology (UTAUT). TAM focuses on Perceived Usefulness and Perceived Ease of Use. While TAM is foundational, it has been criticized for oversimplifying the adoption process, leading to extended versions such as TAM2 and TAM3 [23]. On the other hand, UTAUT [24] emphasizes factors including performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and behavioral intention (BI), which provides a more comprehensive framework for understanding technology acceptance.

Although TAM and its extensions have been widely used, their limited ability in capturing the full complexity of acceptance [25-27] makes UTAUT a more complete framework to assess technology acceptance.

The main aim of this study is to assess Swedish prosthetists and orthotists professionals’ acceptance of LLCW based on the UTAUT framework and to explore additional contextual factors that may support or hinder a future deployment in Sweden. To address this aim, the following research question guides the study: How do UTAUT-related factors and clinicians’ perceived benefits and shortcomings of LLCW shape their overall acceptance of the platform, and what elements should be prioritized to improve its suitability for future deployment in the Swedish P&O context?

A qualitative, exploratory approach was adopted to investigate clinicians’ perceptions of LLCW. The study was situated within a constructivist-interpretivist paradigm [28], which assumes that clinicians’ experiences and acceptance of new technologies are shaped by individual interpretations and contextual factors. This paradigm aligns with capturing subjective perceptions rather than measuring predefined outcomes.

This method was selected as the research focuses on understanding individual experiences and acceptance, which is consistent with established qualitative practices in health care technology studies [29,30]. The study aimed to evaluate immediate acceptance and perceived usability following a demonstration session, combining descriptive Likert-scale summaries with thematic analysis of open-ended responses. This approach has previously proven effective in similar studies applying frameworks such as UTAUT to assess technology acceptance [24,31-34].

The primary researcher has an academic background in P&O and experience with technology-supported clinical workflows. These professionals’ experiences informed the formulation of the research aim and contributed to an initial expectation that digital platforms such as LLCW may support clinical efficiency and documentation quality. The researcher had no prior clinical relationship with the participating clinicians, which minimized direct power dynamics; however, shared professional terminology and familiarity with P&O practice may have influenced the interpretation of participant responses.

Throughout the study, reflexive attention was given to how these professional assumptions could shape data collection and analysis. Iterative discussions within the research team were used to monitor the potential impact of researcher perspectives on coding decisions and theme development. These measures were intended to strengthen transparency and support the transferability of findings by clearly acknowledging the interpretive position from which the analysis was conducted.

The study was conducted at Ottobock Care Sweden, which in total operates 20 clinics across the country. Participants were recruited from these clinics; however, only prosthetists and orthotists professionals were included, as they are directly involved in patient care and their roles are most relevant to the use of LLCW. Clinic managers selected participants based on availability, reflecting a convenience sampling approach targeting 2‐5 clinicians per site. The inclusion criteria required participants to be actively engaged in patient care (regardless of years of experience) and to be a current employee of Ottobock Care Sweden.

Convenience sampling was chosen because it allowed the study to recruit clinicians without disrupting ongoing clinical operations and to access participants across geographically dispersed clinics. Decisions regarding whether further sampling was necessary were guided by the concept of thematic saturation at the overall dataset level. Saturation was monitored during early analysis to determine whether additional recruitment was likely to generate new themes.

All questionnaire responses in Microsoft Forms were reviewed for completeness, duplicate submissions, and formatting inconsistencies before coding began. Before analysis, each response was assigned a unique ID by the primary researcher to ensure full anonymization.

A 2-stage thematic analysis [35] was conducted using both deductive [36] and inductive [37] approaches, framed around the UTAUT model. In the deductive stage, responses were initially categorized according to the 5 UTAUT constructs. In the subsequent inductive stage, open-text responses within each UTAUT category were further analyzed to identify emerging subthemes using reflective thematic analysis [38]. Construct-specific coding was applied as follows: for PE, codes reflected perceived impact on clinical efficiency and patient care; for EE, codes addressed ease of learning, usability, and potential barriers; for SI, the analysis focused on the influence of colleagues, management, and organizational culture; for FC, coding covered availability of technical support, resources, and training; and for BI, codes captured participants’ intentions to use the system in future practice. Quantitative data from Likert-style responses were analyzed alongside qualitative findings. Relationships between constructs (eg, EE and BI) were explored. As all forms were fully completed, no missing data issues arose. PE and FCs were captured solely through open-ended qualitative responses, with no corresponding Likert-scale ratings. By triangulating quantitative and qualitative results, the study provides a comprehensive view of factors influencing LLCW acceptance and offers insight into how the platform can be better tailored for successful implementation.

To enhance credibility and dependability, the analysis followed a documented analytical workflow, including iterative coding, reflexive memo-writing, and repeated comparison between codes and raw data. Triangulation of qualitative themes with descriptive Likert-scale results strengthened the confirmability of interpretations. The reporting of this study followed the Standards for Reporting Qualitative Research (SRQR) guidelines (Checklist 1) to ensure methodological transparency, rigor, and completeness [39].

This study was carried out in Sweden. According to the Swedish Ethical Review Act (SFS 2003:460) [40] and the guidelines of the Swedish Ethical Review Authority [41], ethical approval was not required for this research, as it did not involve any sensitive personal data as defined under the European General Data Protection Regulation (EU 2016/679) [42]. Nevertheless, we acknowledge the importance of maintaining ethical standards and confirm that all relevant ethical principles were followed, in accordance with applicable legislation, the Declaration of Helsinki [43], and recognized research best practices. Prior to data collection, all participants received full information about the study’s purpose, scope, and voluntary nature. No incentives were offered, and participants were free to withdraw at any time without consequence. Written informed consent was obtained from all participants. Confidentiality and anonymity were maintained throughout the research: identifiable data were securely stored and accessible only to the research team. Results are reported in aggregate form to prevent identification. However, in clinics with only 2 participants, the risk of indirect identification remained despite standard deidentification. To mitigate this, additional steps were taken, such as grouping professional experience into broader intervals (eg, 10-year ranges), to strengthen anonymity without compromising data integrity.

A total of 18 participants were recruited for this study. Questionnaire data were analyzed using a deductive thematic approach guided by the 5 constructs of the UTAUT. Participant responses were organized by these constructs to identify key patterns. Irrelevant statements were excluded to maintain focus. Each UTAUT construct is presented in the following sections, supported by direct quotations to illustrate core findings. Responses are referenced by participant ID.

Background information was collected to describe the sample, including gender, age, and professional experience (summarized in Table 1). The participant group was evenly split, with 9 male and 9 female respondents (n=18). Participants represented a wide age range. Male participants ranged from 24 to 55 years of age (mean 39 years; median 36 years). Female participants ranged from 28 to 35 years (mean and median 32 years). These figures reflect the age distributions within each subgroup and are presented solely as descriptive characteristics.

Regarding professional experience, male participants reported 0‐25 years of experience (mean 12; median 11) and female participants reported 2‐15 years (mean and median 8). As with age, these values are descriptive and not used to infer subgroup differences.

Overall, the sample included both early-career and experienced professionals, providing a range of perspectives for evaluating the platform.

To assess key factors influencing acceptance of LLCW, 6 Likert-scale questions (rated from 0 to 5) were included in the survey. These questions aimed to capture perceptions related to the platform’s usefulness, usability, SI, and likelihood of adoption. The average scores for each factor are summarized in Table 2.

Table 2 shows strong positive perceptions in several areas. “Use Motivation” (Q23) had a mean score of 4.61, “Management Encouragement” (Q15) had a mean of 4.56, and both “Ease of Use” (Q10) and “Willingness to use Voluntarily” (Q5) were rated with mean scores of 4.11. “Recommendation” (Q22) with a mean score of 4.00 indicates a general openness toward adopting LLCW, though with slightly less enthusiasm than for the previously mentioned items.

In contrast, the relatively lower score for “Colleagues’ Perceptions” (Q14), a mean of 2.7, implies that peer influence may not be a strong motivating factor in this context. This might suggest that LLCW adoption is currently seen as more of an individual or management-driven initiative, rather than a socially reinforced norm.

In addition to Likert ratings, written responses were analyzed and categorized by UTAUT construct. Emerging themes reflect both perceived benefits and potential concerns (Table 3).

Based on feedback from participants, several areas for improvement in LLCW were identified. While the general sentiment towards the platform’s potential was positive, there are clear opportunities for enhancing its functionality and usability.

One of the pressing areas for improvement identified by participants was the usability of LLCW on mobile devices. Respondents mentioned that the platform’s layout and functionality on smartphones were not optimized, leading to issues like form resets when editing responses.

This was particularly frustrating for older patients, who might struggle to navigate the mobile interface.

These issues indicate that mobile optimization should be a priority in future updates. To make the platform more accessible, especially for older patients and those with limited technical skills, adjustments need to be made to ensure smoother navigation and fewer disruptions when completing forms.

Another gap identified in LLCW was the lack of clinical data fields within patient profiles. Participants noted that the platform currently does not capture crucial clinical information, such as strength scales, test results, or other relevant health data that clinicians routinely use to monitor and compare patient progress.

The absence of customizable clinical fields limits the platform’s ability to fully support health care workflows, as clinicians often rely on detailed patient histories to make informed decisions.

The length and complexity of the questionnaires were flagged as another area for improvement, particularly for older patients, who represent a substantial segment of those treated. Several participants pointed out that lengthy forms can lead to patient fatigue, causing some individuals to rush through responses or abandon the process altogether. To improve this aspect, there is a strong call for simplifying the questionnaires and reducing their length, as participants recommended multiple times during demo sessions.

Additionally, during demo sessions, participants recommended introducing adaptive questioning—where the number of questions changes based on the patient’s responses—could make the process more efficient and less overwhelming.

Several participants emphasized the need for improved support tools for clinicians within the platform. A suggestion was made to incorporate a forum or chat function, which would allow clinicians to access real-time support for troubleshooting or specific queries. As one respondent noted:

In addition to improving support, there were calls to integrate AI tools into LLCW to assist clinicians, especially when dealing with rare or complex cases. AI-driven assistance could help clinicians by providing real-time decision support, making it easier for them to access relevant information, identify patterns, and make more informed decisions.

By incorporating AI and enhanced support systems, LLCW could provide clinicians with more advanced tools, enabling them to handle challenging cases with greater efficiency and confidence.

This study examined acceptance of LLCW among Swedish prosthetists and orthotists professionals using the UTAUT framework. Overall, participants expressed strong BI to adopt the platform, primarily driven by high PE and EE. LLCW was perceived as intuitive and capable of improving workflow efficiency and patient care. However, concerns were raised regarding patient digital engagement, data accuracy, training needs, and long-term technical support, highlighting important considerations for successful implementation. Participants generally expressed positive acceptance of LLCW, highlighting its potential to improve job efficiency, enhance patient care, and simplify routine tasks. However, concerns about patient participation were raised, which need to be addressed for smoother implementation. Qualitative feedback on PE showed alignment between the platform’s expected benefits and users’ perceptions. Participants’ open-ended responses consistently described PE-related aspects most positively, suggesting perceived support for LLCW’s impact on efficiency and effectiveness.

Descriptive ratings indicated consistently positive perceptions of the platform, with high mean scores for motivation to use (4.61), management encouragement (4.56), willingness to use voluntarily (4.11), ease of use (4.11), and likelihood of recommending LLCW (4.00). These results reflect generally favorable user impressions and perceived value of the platform for supporting workflow and future engagement.

In line with our objective to assess factors influencing acceptance of LLCW, findings indicate that while the platform was perceived as intuitive and valuable, workflow integration may present important challenges. The introduction of LLCW could require workflow adjustments, which may pose a significant barrier to its acceptance [44-46]. While the platform aims to improve workflows, such changes may inadvertently increase errors and clinician workload [47]. Concerns about patient participation, especially in submitting data independently, could complicate this. If patients feel unsure about or struggle to complete data submissions before in-person visits, they may delay or avoid the process, negating efficiency gains and increasing clinician workload. To address this, preimplementation efforts should assess patient behavior, like response rates to current postdelivery surveys, and develop strategies to promote active patient engagement in their new roles.

Although patient-reported data offers valuable insights, its quality may vary. The subjectivity involved in interpreting questions could compromise data accuracy [48], leading to potential treatment errors if clinicians rely too heavily on it. To optimize the value of patient-reported data, LLCW should implement mechanisms for verifying its accuracy. Automated approaches for data verification, as explored in existing literature [49], could be incorporated into the system to ensure data reliability and maximize its potential benefits. These findings suggest that although LLCW shows promise for improving efficiency and clinical preparation, successful implementation will depend on addressing workflow adaptation and ensuring data accuracy.

Participants’ positive outlook on PE aligns with previous literature, which consistently supports the significance of PE in the acceptance of health care technology. Studies by Ljubičić et al [24], De Mesa et al [31], and Klappe et al [32] identify PE as a key adoption driver within the UTAUT framework. The benefits of LLCW align closely with this construct, particularly in its ability to reduce documentation burdens and increase patient involvement. Since documentation is often regarded as a time-consuming task by clinicians [50], tools like LLCW that streamline such processes are well-received.

Participants generally had positive impressions of LLCW’s EE, with a mean of 4.11, reflecting its user-friendly design and aligning with earlier findings that EE significantly affects technology adoption [51]. However, concerns were raised about the ability of older patients, a significant portion of the caseload, to engage with the platform. Literature supports this, as older adults often have lower digital literacy in health apps [52,53]. This could hinder the expected benefits of LLCW in clinical practice and impact long-term acceptance. Since this study didn’t focus on patients, it is not possible to make definitive claims about their expected reaction; however, since older patients are known to have lower confidence and self-perceived tech skills [53], a patient introduction strategy similar to the one used with clinicians is essential to ensure proper support and reduce potential digital barriers.

Additionally, participants expressed concerns about the ability of their older colleagues to navigate LLCW, especially those who might have less comfort with technology. This was particularly voiced by older participants themselves, highlighting how age can influence perceptions of digital competence. This concern aligns with findings in the literature [54,55], but in this case, it was framed as an issue for colleagues rather than a personal one. Regardless, these concerns underline the importance of offering thorough training [33,51,56] to all health care providers, regardless of age (even though a trend among younger participants seeing training as unnecessary has been identified) or digital proficiency.

When it comes to SI, this construct seemed to be the least emphasized by participants in their feedback about LLCW, mirroring previous research where SI was found to be the weakest predictor of technology acceptance [34]. As shown in Table 2, SI received the lowest mean score of 2.72, which, while not negative, suggests it played a relatively neutral role in shaping participants’ intentions to adopt LLCW in the future. This indicates that the influence of peers, supervisors, or colleagues may not be a significant driving factor in their decision-making process. Participants reported strong (expected) managerial support for the adoption of LLCW, reinforced by expectations of operational gains. Although peer influence appeared limited in the previously mentioned findings, managerial endorsement seemed to play a greater role in shaping acceptance decisions. Despite assurances of anonymity, this discrepancy may reflect organizational pressure. The lack of expressed concerns about peer opinion may also indicate, however, confidence in the tool rather than disregard for social dynamics. If negative feedback were anticipated, SI might have played a larger role.

When it comes to FC, participants generally felt that their workplace infrastructure could support LLCW’s implementation, which might justify the expected acceptance, as strong infrastructure has been positively associated with technology acceptance [24,34,57]. However, concerns about existing IT support, such as slow response times and inefficiency, were raised. These issues could impact the platform’s long-term acceptance, as effective IT support is crucial for a smooth rollout [58,59]. If LLCW addresses these support issues, it could positively influence perceptions and adoption.

If LLCW fails to meet expectations, professionals may reassess their views, leading to frustration and reduced trust, which could hinder adoption [60,61]. Therefore, it’s important for LLCW to deliver on its promises to maintain positive engagement and long-term acceptance. Setting up strategies to follow up on this specific factor is then extremely important to consider postimplementation.

Regarding BI, participants showed overwhelmingly positive attitudes towards LLCW, with a strong inclination to adopt and recommend the system. The primary motivator for this was the expected efficiency improvements, which participants felt would streamline workflows and enhance clinical operations, making them eager to embrace the platform. This aligns with broader research showing that expected performance improvements are central to fostering adoption intent [24,31,32].

Participants also reported a sense of ease in using LLCW, with its user-centered design contributing to their confidence in its effectiveness and usability, key factors for overall satisfaction [51,62]. Many expressed satisfaction with having their opinions considered during the predeployment phase, fostering a sense of involvement and ownership. This approach sparked curiosity about seeing their feedback reflected in the platform’s development, and some participants expressed a desire to contribute to future improvements [63,64].

The appreciation for being consulted aligns with previous research, showing that involving stakeholders in the design and planning stages enhances technology acceptance and satisfaction in health care [24,31,32].

Such stakeholder engagement aligns with best practices in health care digitalization, where involving clinicians early in the design process has been shown to increase satisfaction and acceptance [21,22,62,64]. When users feel their input is valued and integrated, they are more likely to support the technology’s implementation [65,66]. While appreciation for this inclusive approach was voiced most explicitly by female participants, there is no clear evidence that gender itself influenced acceptance. Rather, the findings suggest that meaningful user involvement broadly contributes to positive adoption attitudes.

Overall, the study’s findings reinforce existing research: PE and EE are the most positively rated constructs, while SI tends to be less influential. Strong FC and a user-inclusive design further bolster BI. LLCW’s perceived ability to improve efficiency, its intuitive interface, and stakeholder engagement all contributed to the favorable reception among health care professionals.

This study evaluated the acceptance of LLCW among Swedish prosthetists and orthotists professionals by applying the constructs of UTAUT. Nevertheless, certain limitations may have influenced the results. While the primary objective, accurately capturing participants’ views on LLCW, was achieved, alternative methods of data collection could have yielded richer qualitative data. For instance, focus groups, known for fostering collaborative discussion and the emergence of new ideas, might have provided deeper insight. Likewise, in-depth interviews could have enabled more probing, allowing researchers to explore individual perspectives in greater detail [67]. These methods were not viable due to operational limitations. Another limitation is the challenge of achieving participant saturation at the clinic level. In qualitative research, saturation refers to the point at which no new information or themes emerge [68]. While saturation appeared to be reached across the broader participant sample, the inclusion of clinics with very few participants (eg, n=2) may have hindered the discovery of additional relevant insights. A larger sample in these clinics could have strengthened the study’s comprehensiveness. The study also faced limitations in achieving demographic balance, particularly regarding variables such as age, which are known to influence UTAUT constructs. Since participants were selected based on availability rather than stratified sampling, the resulting demographic imbalances, such as age distribution, could have affected the results. Moreover, the brief nature of the LLCW demonstration may have limited participants’ ability to form well-rounded opinions. The session’s short duration, combined with the fact that participants were paired during the demo due to operational constraints, may have affected the quality and independence of the feedback collected. A more in-depth or individualized demo experience might have produced more nuanced responses.

It is also important to consider the potential influence of social desirability bias. Despite generally positive feedback, participants may have modified their responses to appear favorable to supervisors or colleagues [69]. Since LLCW was developed internally by Ottobock, there may have been an implicit pressure to evaluate it positively. Finally, while participants came from multiple clinic locations, no comparative analysis was conducted to examine potential differences in acceptance across these sites. Such an analysis could have helped identify the most suitable clinic for piloting LLCW and inform a more effective implementation strategy across Sweden.

This study evaluated the factors influencing prosthetists and orthotists professionals’ acceptance of the LLCW platform. While overall feedback was positive, particularly regarding its usability and potential to enhance performance, participants emphasized that full acceptance depends on future improvements. Key among these is the integration of decision support systems tools, and strategies to support patient engagement.

Given the study’s small convenience sample and immediate postdemonstration design, these findings should be interpreted as preliminary insights. Future research with larger, more diverse samples (including secondary users such as patients) will be essential to guide broader implementation and inform strategies for long-term adoption across Ottobock Care Sweden clinics.