Investigating a user-centered design driven multifactorial falls risk assessment tool in primary care: A randomized effectiveness-implementation study

Investigating a user-centered design driven multifactorial falls risk assessment tool in primary care: A randomized effectiveness-implementation study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigating a user-centered design driven multifactorial falls risk assessment tool in primary care: A randomized effectiveness-implementation study Sara Groos, Judith Kuiper, Natasja van Schoor, Julia van Weert, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6915278/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Purpose Multifactorial falls risk assessment tools (FRATs) identify and target individual falls risk factors in older adults. However, barriers can hinder their effectiveness. User-Centered Design (UCD) could improve multifactorial FRATs for both primary (HCPs) and secondary (patients) users. This study investigated a UCD developed multifactorial FRAT, the Fall Analysis 2.0. Methods A randomized effectiveness-implementation study included 19 HCPs from 15 primary care practices, randomly assigned to either the intervention or control group (usual care). The intervention involved using the Fall Analysis 2.0 and corresponding training. Participants were community-dwelling (65 + years) at high risk of falling (36 intervention, 27 control). Primary outcomes included differences in HCPs falls risk management behavior and older adults’ adherence-related motivation to falls prevention advice, analyzed using Fisher’s Exact tests and Mann Whitney U tests. Secondary outcomes of the Fall Analysis 2.0 user experience and implementation was explored through HCP interviews. Results Fully completed multifactorial falls risk assessments (86.1%) by HCPs was higher in the intervention compared to the control group (3.7%), p < .001. Use of validated tools was lower in the control group (11.1%), p < .001. HCPs rated the Fall Analysis 2.0 highly for user experience. Successful implementation is dependent on HCP reimbursement and interoperability with electronic health records. No significant differences in older adults’ adherence-related motivation were found between groups due to a ceiling effect. Conclusion UCD developed multifactorial FRATs like the Fall Analysis 2.0 show promise for enhancing falls prevention care quality by improving delivery for HCPs and older adults. Figures Figure 1 Figure 2 Key summary points Aim : The aim of this study was to examine the effectiveness, user experience, and implementation of a User-Centered Design (UCD) developed multifactorial falls risk assessment tool (FRAT), namely the Fall Analysis 2.0, in Dutch primary care. Findings : The rate of fully completed multifactorial falls risk assessments was higher among health care professionals (HCPs) using the Fall Analysis 2.0 compared to usual care. The Fall Analysis 2.0 was rated highly for user experience with implementation dependent on HCP reimbursement and interoperability with electronic health records. No significant differences in older adults’ adherence-related motivation were found. Message : UCD developed multifactorial FRATs have potential in improving the quality of falls prevention-related care. 1. Introduction Falls in older adults (65+) is a growing global health problem [ 1 , 2 ]. Falls incidences can significantly reduce the quality of life of older adults as they frequently lead to functional, psychological, and cognitive decline [ 3 ]. Falls can also result in mortality, with the falls-related mortality rate in older adults increasing worldwide [ 1 , 2 ]. The medical costs of falls are estimated to account for 1.5 percent of total health care expenditures in Western countries [ 4 , 5 ]. Effective falls prevention is crucial to reduce the burden on our rapidly ageing society [ 6 ]. Falls are a result of numerous interacting risk factors of which several are potentially modifiable, including reduced mobility, sensory function, activities of daily living, cognitive function, dizziness, disease history, medications, nutritional status and vitamin D, and environmental risk [ 7 – 10 ]. The World Guidelines for falls prevention and management recommend that health care professionals (HCPs) perform multifactorial falls risk assessments to detect and target modifiable falls risk factors in older adults at high risk of falling. Multifactorial falls risk assessment tools (FRATs) make use of evidence-based functional tests and questionnaires to support HCPs in carrying out such an assessment in these adults by (1) identifying modifiable falls risk factors, and (2) selecting interventions to effectively target two or more identified falls risk factors (hereafter a multidomain intervention) [ 10 ]. Multidomain interventions based on fully completed multifactorial falls risk assessments are more effective at reducing falls rates in older adults [ 11 – 14 ]. In the Netherlands, a multidomain intervention based on a multifactorial falls risk assessment is considered usual care for older adults at high risk of falling. Despite their effectiveness, certain limitations are hindering the optimal use of multifactorial FRATs in practice. First, given the multifactorial nature of falls, quality falls prevention care relies on multidisciplinary expertise (i.e., the collaboration between several HCPs from different disciplines) [ 10 ]. However, multifactorial FRATs are often developed for use in one particular care context, which can limit the usability of these tools in a multidisciplinary care context [ 15 ]. Second, multifactorial FRATs are perceived by HCPs as difficult to use, time consuming, and poorly integrated into workflows [ 16 ]. These barriers indicate that these tools are not adapted to the heterogeneous needs of HCPs, resulting in incomplete multifactorial falls risk assessments and, in turn, suboptimal multidomain interventions in older adults at high risk of falling One way to cater multifactorial FRATs to the needs of users is through User-Centered Design (UCD). UCD is an iterative development process in which prospective users of an intervention are involved early and continuously to inform the development of tools [ 17 – 19 ]. A UCD approach has been successfully applied in the development of several digital tools for falls prevention such as clinical decision support systems for use by HCPs and mHealth applications for use by older adults [ 20 – 26 ]. Additionally, UCD studies are increasingly thinking about the secondary user experience (here older adults at high risk of falling). In health care, the secondary user experience refers to the experience of patients during the HCP’s interaction with a tool during consultations [ 27 , 28 ]. As a result, barriers experienced by the primary user (e.g., difficulty using a multifactorial FRAT) can negatively impact the secondary user (e.g., incomplete assessment and suboptimal interventions). Thus, enhancing multifactorial FRATs for HCPs through UCD could in addition positively impact the wellbeing of older adults. However, it remains uncertain whether improving the user experience of digital clinical tools can influence behavior or determinants of behavior. Specifically, a UCD developed digital health intervention is ineffective in improving risk of falling and managing risk factors for falling in older adults if it is not used by HCPs as intended (e.g., incomplete assessments) or if patients are not motivated to adhere to the advice provided by HCPs. Lack of motivation by older adults is a commonly reported barrier in falls prevention [ 16 , 29 ]. Therefore, investigating whether UCD driven tools can improve behavior in primary users or determinants of behavior, such as motivation, in secondary users is vital for optimizing UCD further. The aim of this study is two-fold. First, we aimed to test the effectiveness of a UCD developed digital multifactorial FRAT on the falls risk management behavior of HCPs (i.e., performing fully completed assessments) and on motivation to adhere to falls prevention advice of older adults (hereafter adherence-related motivation) in primary care in the Netherlands. Second, we aimed to assess the user experience of HCPs, and the implementation of the UCD driven tool in practice. 2. Methods 2.1. Study design To evaluate our UCD developed digital multifactorial FRAT, a hybrid type 2 effectiveness-implementation study was conducted in Dutch primary care [ 30 ]. Randomization occurred at the practice level to avoid possible contamination of the intervention between HCPs working at the same practice. This resulted in an intervention group ( n older adults = 36, HCPs = 10) and a control group ( n older adults = 27, HCP = 9) across 15 practices ( n control = 6; intervention = 9). Older adults were blinded to the intervention allocation. However, blinding of the intervention allocation was not possible for researchers and HCPs as researchers had to set up the digital multifactorial FRAT prior to the consultations and HCPs had to interact with the tool during the consultations. Measurements were collected at four timepoints: T0 was a baseline questionnaire prior to the first consultation (HCPs only), T1 and T2 was a questionnaire after each consultation (HCPs and patients), and T3 was an interview after all consultations were completed (intervention HCPs only). Data was collected between May and September 2024. The study protocol was evaluated by the Medical Ethics Research Committee of the first author’s institute who declared that the Medical Research Involving Human Subjects Act did not apply to this study. The study was presented and documented at the working group meeting for the national multidomain falls prevention program on November 20th, 2023. This program is set up by the Netherlands Ministry of Health, Welfare, and Sport (VWS) and aims to improve the implementation of clinical guidelines regarding falls prevention into practice. The study was registered at OSF (hyperlink redacted for double blind peer review). 2.2. Procedure HCP practices were randomized to either the intervention or control group using a random number generator. All HCPs were briefed about the practical matters of the study such as the inclusion and exclusion criteria of older patients in an online meeting. The T0 questionnaire assessing relevant background characteristics (e.g., age, gender, falls prevention education) was sent to HCPs via mail. HCPs in the intervention group attended the full day in-person training session. The T0 questionnaires were returned to the researcher prior to this training to avoid bias. The first contact with an eligible patient was initiated by the participating HCP during which the patient received an information letter about the study. Interested patients provided consent for the HCP to share their contact details with the researcher who then initiated the second contact with the patient by telephone. During this phone call, the researcher reassessed whether the patient was eligible to participate and answered any questions from the patient about the study. Additionally, verbal consent was obtained to schedule a consultation with the HCP for the purpose of the study. Written consent was obtained from all participants prior to data collection (both HCPs and patients). Consultations occurred at the primary care practice or at the patient’s home with the researcher present. HCPs in the intervention group used the Fall Analysis 2.0 during consultations with older patients, whereas HCPs in the control group provided usual care. HCPs completed the T1 questionnaire after each consultation. This questionnaire examined the falls risk management behavior of HCPs. In turn, patients completed the T2 questionnaire within two weeks after the consultation, either in-person, at home or by telephone. This questionnaire assessed the adherence-related motivation of patients and relevant background characteristics (e.g., age, gender). The T3 interview of 30 minutes with HCPs in the intervention group occurred after all consultations were completed and T1 questionnaires were returned. 2.3. Control comparator In the Netherlands, a multifactorial falls risk assessment can be performed by primary care-based HCPs with experience in falls prevention using validated multifactorial FRATs to perform such an assessment, for instance the Fall Analysis 1.0 [ 31 ]. Therefore, HCPs in the control group were asked to perform a multifactorial falls risk assessment as part of usual care for older adults at high risk of falling. 2.4. Intervention components The intervention components comprised a UCD developed digital multifactorial FRAT, hereafter referred to as the Fall Analysis 2.0 (in Dutch: “Valanalyse 2.0”) and attendance of a corresponding in-person training session about multifactorial falls risk assessments in general and the Fall Analysis 2.0 specifically. The Fall Analysis 2.0 is an adapted, digital version of the existing validated multifactorial FRAT (i.e., the paper-based Fall Analysis 1.0), and the content of the training is based on the content of the corresponding training for the Fall Analysis 1.0 currently available for use by primary care-based HCPs [ 32 ]. The user experience of the Fall Analysis 2.0 and corresponding training was enhanced by employing methods from UCD. The UCD driven development of the Fall Analysis 2.0 is described in detail elsewhere [ 33 , 34 ]. Prior to the start of the pilot study, the Fall Analysis 2.0 underwent a usability testing round to identify and solve usability problems that could affect both the primary and secondary user experience. This resulted in a ready-to-use Fall Analysis 2.0, as depicted in Fig. 1 . A detailed description of the Fall Analysis 2.0 and corresponding training is provided in the supplementary materials. 2.5. Recruitment of HCPs and older adults The study population consisted of primary care-based HCPs and older adults at high risk of falling. A convenience sample of HCPs was recruited with the help from several organizations who are each in direct contact with primary care-based HCPs across the Netherlands (refer to acknowledgements). Representatives from these organizations were requested to distribute a call for participants which included information about the study and an embedded link to a sign-up sheet. HCPs were eligible to participate if they were (1) general practitioners, physical therapists, occupational therapists, pharmacists, district nurses, or nurse practitioners currently working in Dutch primary care; and (2) regularly conducting multifactorial falls risk assessments in older adults at high risk of falling in current practice. A convenience sample of patients was recruited with the help of participating HCPs. Following the World Falls Guidelines algorithm for high falls risk, older adults were eligible to participate if they adhered to the inclusion and exclusion criteria as displayed in Table 1 [ 10 ]. Each HCP was instructed to include about five older patients at high risk of falling based on the inclusion and exclusion criteria. 2.6. Measurements 2.6.1. Background characteristics Table S1 in the supplementary materials provides a detailed overview of the measurements of the background characteristics. HCPs were asked to indicate their age, gender, profession, years worked in primary care, practice setting, falls prevention education, and practice patterns (measured at T0). Older adults were asked about their age, gender, level of education, and living situation at (measured at T2). 2.6.2. Primary outcomes The primary outcomes of this study was the falls risk management behavior of HCPs and the adherence-related motivation of older adults. Falls risk management behavior of HCPs was operationalized as the number of fully completed multifactorial falls risk assessments by HCPs, preferably using a validated tool (measured at T1). Based on Dutch guideline recommendations, a completed multifactorial falls risk assessment is defined as a set of assessments performed by HCPs across 13 risk factors to identify and target potentially modifiable risk factors. These risk factors are: history of falls, mobility, medication, dizziness, vision, hearing, cognition, urinary incontinence, fear of falling, activities of daily living, environmental factors, footwear and foot problems, nutritional status and vitamin D intake [ 31 ]. To measure this, HCPs were asked to write down which risk factors for falling they assessed during the consultation and whether they made use of a validated tool while performing the assessment. This behavior information was also received in the form of user data from HCPs in the intervention group (i.e., fully assessed risk factors). Assessments were considered complete when all of the 13 risk factors were assessed by HCPs during the consultation, with HCPs in the control group preferably using a validated multifactorial FRAT (e.g., the Fall Analysis 1.0). Risk assessment data from HCPs was manually coded into two separate categorical variables, namely completion of multifactorial falls risk assessments (1 = completed and 0 = not completed ) and use of validated tools (1 = use of tools and 0 = no use of tools ). The adherence-related motivation of older adults was measured using the 16-item Situational Motivation Scale by [ 35 ] and adapted to fit the context of this study (measured at T2). For example, the phrase “…engaged in this activity” in the original scale was adapted to the phrase “…follow the advice.” Participants were asked “Why would you follow the falls prevention advice from your HCP?” of which four items measured the construct of intrinsic motivation (e.g., “Because I think it is useful advice”), identified regulation (e.g., “Because the advice is for my own good”), external regulation (e.g., “Because I am supposed to follow the advice”), and amotivation (e.g., “There may be good reasons to follow the advice, but personally I do not see any.”), respectively using a three-point Likert scale (i.e., 1 = completely disagree to 3 = completely agree ). Items for identified regulation, external regulation, and amotivation were summarized into three separate mean scales where higher scores indicated higher identified regulation (M = 2.8, SD = 0.4, α = .68), external regulation (M = 2.3, SD = 0.6, α = 0.79), and amotivation (M = 1.9, SD = 0.6, α = .75), respectively. Items measuring intrinsic motivation were treated as separate items due to poor internal consistency between items ( α = .37). 2.7. Secondary outcome The secondary outcome of this study was the user experience of HCPs, and the implementation of the Fall Analysis 2.0 in practice (measured at T3). Interviews were carried out by the first author using a semi-structured interview guide developed for this study. First, HCPs were asked about the perceived usability and usefulness of the Fall Analysis 2.0 for assessing and targeting risk factors for falling in practice (e.g., “How do you find the Fall Analysis 2.0 compared to your previous method of screening?”; “When the Fall Analysis 2.0 was first introduced what benefits did you think would result?; and “To what extent did you experience these benefits?”). Afterwards, HCPs were asked about potential barriers and facilitators to implementing the Fall Analysis 2.0 (e.g., “Can you indicate what factors facilitate and hinder the implementation of the Fall Analysis 2.0 in practice?”). Each interview lasted 30 to 45 minutes. 2.8. Data analysis Fisher’s exact tests were performed to evaluate the association between the group condition (intervention versus usual care) and falls risk management behavior of HCPs, namely the completion of multifactorial falls risk assessments (completed versus not completed) and use of a validated multifactorial FRAT for these assessments (use of one or more tools versus no use of tools). Mann-Whitney U tests were used to examine differences in falls prevention-related motivation between older patients in the intervention versus usual care group using the items of intrinsic motivation, and mean scale items of identified regulation, external regulation, and amotivation as dependent variables. Lastly, differences between the group condition (intervention versus usual care) on participant characteristics were assessed using Fisher’s exact test for categorical variables and Mann-Whitney U test for continuous variables. The statistical software IBM SPSS Statistics v.28.0.1.1 (15) was used for data analysis. Interviews with HCPs were recorded and transcribed verbatim by the first author. All transcripts were analyzed in MAXQDA 2022 [ 36 ]. Each transcript was coded by the first author using both a deductive and inductive approach, and doubts were discussed with co-authors. Specifically, the predefined main category codes of user experience, barriers, and facilitators were established following the topics from the semi-structured interview guide. Additionally, predefined subcategory codes of guided assessment/treatment, enhanced efficiency, and improved adaptability were established following the results of a Fall Analysis-related needs assessment [ 33 ]. This was used to examine whether UCD was effective at addressing the previously established needs of primary care-based HCPs. Lastly, an inductive approach was used to identify specific barriers and facilitators mentioned by HCPs. 3. Results Table 2 and Table 3 display the characteristics of HCPs and older patients at baseline, respectively. Figure 2 displays a flowchart for the inclusion of HCPs and patients. The results of the primary outcomes are displayed in Table 4 . 3.1. Background characteristics of HCPs As shown in Table 2 , no statistically significant differences in characteristics were observed among HCPs in the intervention and usual care group at baseline. In short, the majority of participating HCPs were female (84.2%) and the mean age was 46.2 years old. The most reported professions were nurse practitioners (26.3%), physical therapists (21.1%), and occupational therapists (21.1%). HCPs indicated diverse practice patterns with regards to performing multifactorial falls risk assessments in older adults at high risk of falling (refer to Table 2 for details). Only a few HCPs reported using the Fall Analysis 1.0 when performing multifactorial falls risk assessments in older adults (15.8%). Among the 13 risk factors for falling that make up a recommended multifactorial falls risk assessment, medication (94.7%), mobility (78.9%), environmental factors (78.9%), vision (73.7%), and cognition (63.2%) were the risk factors most often listed by HCPs when asked about their previous knowledge about risk factors for falling. 3.2. Background characteristics of older patients As shown in Table 3 , no statistically significant differences in baseline characteristics were observed among older patients in the intervention and usual care group. The majority of patients were female (63.5%) and the mean age was 81 years. More than half of participants reported receiving secondary level of education (53.2%) indicating a completed middle school or high school degree. Furthermore, the majority of participants lived alone without a partner or child(ren) (63.5%). 3.3. Primary outcomes Regarding the falls risk management behavior of HCPs, the Fisher’s exact test showed a statistically significant association, p < .001, with higher rates of fully completed multifactorial falls risk assessments in older adults observed among HCPs using the Fall Analysis 2.0 (86.1%) versus usual care (3.7%). For the use of validated instruments, Fisher’s exact test revealed a statistically significant association, p < .001, in which the use of validated tools was lower among HCPs in the usual care group (11.1%). Specifically, HCPs (n = 2) in the usual care group used the Fall Analysis 1.0. Other functional assessments and questionnaires used by HCPs (n = 2) in the usual care group were the Timed Chair Stand Test, Berg Balance Scale, or a self-built assessment questionnaire. In usual care, the most commonly assessed risk factors by HCPs were reduced mobility (74.1%) and medication use (63%). The least commonly assessed risk factors were vision problems (18.5%) and hearing (11.1%). Thus, while HCPs in usual care assessed several falls risk factors, it did not constitute a fully completed multifactorial falls risk assessment per the guidelines. Mann-Whitney U tests were performed to assess differences in adherence-related motivation between older patients in the Fall Analysis 2.0 versus usual care group. As illustrated in Table 4 , identified regulation, external regulation, amotivation, and intrinsic motivation did not significantly differ between older patients being administered the Fall Analysis 2.0 versus usual care. 3.4. Secondary outcomes Table S2 in supplementary materials displays quotes from the interviews with HCPs. The user experience of the Fall Analysis 2.0 was positively assessed by HCPs. HCPs found that the Fall Analysis 2.0 guided users in assessing risk factors for falling and subsequent treatment-related decision making for detected risk factors. For example, one HCP mentioned that the tool “organizes everything very clearly” and “[the risk factor] stays highlighted in a different color” if it is not yet assessed “so you end up filling everything in [P3].” Other HCPs mentioned how the tool guides you “through everything [P5]” , provides immediate results and advice, and allows you to look “much deeper into someone’s situation [P2].” Additionally, the Fall Analysis 2.0 was found to enhance the efficiency of multifactorial falls risk assessments. Specifically, HCPs stated that a “digital and easy to fill in” tool can save HCPs “a lot of time [P7]” with the biggest advantage being “that the advice comes out immediately [P5].” Despite the Fall Analysis 2.0 allowing HCPs to go “through [the assessment of risk factors] the way [they] want to [P6],” some HCPs highlighted issues with the tool’s adaptability in a patient’s home. Specifically, HCPs mentioned that not all functional assessments, such as the Short Physical Performance Battery, are suitable for being conducted at a home and highlighted the need for a digital tool that also works offline (e.g., no access to Wi-Fi). The main barrier for successful implementation that was mentioned by HCPs was the lack of reimbursement of the Fall Analysis 2.0 by health insurers. One HCP also saw having to attend the in-person training day as a barrier suggesting that those who already attended the training can explain the Fall Analysis 2.0 to their colleagues. Other HCPs recognized the training as a facilitator for successful implementation. For instance, one HCP highlighted that the training provided them with the “extra depth” needed to ask “certain questions” and that this was something “helpful to have explained again [P4].” Alongside the training, HCPs also mentioned that ensuring interoperability between the Fall Analysis 2.0 and electronic health records would facilitate the sustainable implementation of the tool in practice as it enhances communication between HCPs, specifically with the general practitioner (GP). 4. Discussion The aim of this hybrid type 2 effectiveness-implementation study was to investigate the effectiveness, user experience, and implementation of a UCD developed multifactorial FRAT among HCPs and older patients in Dutch primary care. The findings of this study suggest that the barriers experienced by HCPs can be reduced if multifactorial FRATs are developed following the principles of UCD. Specifically, despite multifactorial FRATs providing a structured approach for assessing, identifying, and effectively targeting individual falls risk factors in older adults at high risk falling, their successful implementation into real-world practice settings is perceived by HCPs as difficult, time consuming, and poorly integrated into workflows [ 16 , 37 ]. Additionally, systematic reviews have shown that the incorporation of clinical guidelines for falls prevention into routine practice is low among HCPs in primary care, which can result in a suboptimal multidomain falls prevention intervention in older adults at high risk of falling [ 38 ]. Such falls risk management behavior by HCPs was also observed among participants providing usual care in this study, whereby the carrying out of multifactorial falls risk assessments in older adults was not per the recommended national and international guidelines for falls prevention [ 10 , 31 ]. In turn, we found the Fall Analysis 2.0 positively influenced the falls risk management behavior of HCPs whereby use of this validated tool was associated with a significantly higher rate of fully completed multifactorial falls risk assessments. In other words, the Fall Analysis 2.0 intervention facilitated improved multifactorial falls risk assessments in older adults at high risk of falling, which can be expected to result in more optimum multidomain falls prevention interventions in these adults. This likely occurred due to the continuous involvement of prospective users in the development of the Fall Analysis 2.0 and corresponding training, which ensured that the intervention components met the previously determined needs of HCPs (e.g., guided assessment/treatment and enhanced assessment efficiency) [ 33 ]. As a result, the Fall Analysis 2.0 and corresponding training supported HCPs in delivering improved falls prevention care to older adults in practice. Additionally, HCPs suggested minor improvements for further enhancing the tool’s fit in a home care contexts (e.g., ability to conduct assessments offline), which could be examined in future implementation research. HCPs also emphasized the need for insurance reimbursement, which is recognized as an important barrier hindering the successful implementation of multifactorial falls risk assessments in practice [ 16 ]. While ensuring interoperability between systems is recognized as a challenge in health care, the findings of this suggest that the sustainability of the Fall Analysis 2.0 is dependent on its integration into existing electronic health records [ 39 ]. We are working together with the Netherlands Ministry of Health, Welfare, and Sport and the Dutch National Expert Center on Injury Prevention to address these needs and ensure sustainable long-term implementation of the Fall Analysis 2.0 into practice. With regards to older adults at high risk of falling, motivation to adhere to the falls prevention advice received by HCPs did not differ between patients being administered the Fall Analysis 2.0 versus usual care, probably due to a ceiling effect. In other words, older patients in this study displayed high levels of motivation to adhere to the falls prevention advice provided by HCPs irrespective of their group condition. This finding is surprising given that motivating older patients to adhere to the advice received by HCPs is a well-established challenge in falls prevention [ 16 , 40 , 41 ]. There are two reasons that could explain why adherence-related motivation was high among older adults in both groups. First, the majority of older adults who participated in this study were existing patients of participating HCPs with good provider-patient relationships. Good provider-patient relationships have been shown to facilitate therapeutic adherence in older adults [ 42 ]. Therefore, older adults in the usual group may have displayed high levels of motivation to adhere to advice because of the existing provider-patient relationship. Second, from a methodological perspective, the Situational Motivational Scale used to measure adherence-related motivation in this study was adapted from a five-point Likert scale to a three-point Likert scale to enhance scale comprehension among older adults [ 35 ]. This decreased the likelihood of identifying differences between group conditions (i.e., Fall Analysis 2.0 versus usual care) as a five-point Likert scale would have possibly resulted in more variability in the data. A major strength of this study is that it highlighted the potential promising effects of UCD developed digital tools in clinical practice, specifically within the context of falls prevention. However, the findings of this study should also be interpreted in the context of their limitations. First, the validated multifactorial FRAT (i.e., the Fall Analysis 1.0) used by HCPs in usual care was paper-based. Given that digital clinical tools have been shown to improve to efficiency and quality of care, we cannot determine with certainty whether the positive change in behavior among HCPs occurred due to the digitalization of the Fall Analysis 1.0 or due to its UCD development into version 2.0 [ 43 ]. Additionally, the intervention described in this study consisted of the use of the Fall Analysis 2.0 and the attendance of a corresponding in-person training session among a small sample of HCPs. While both the digital multifactorial FRAT and training were developed following UCD, a randomized controlled trial (RCT) with more conditions and bigger sample size is necessary to untangle which components of the intervention contributed to which effects in HCPs (e.g., full intervention, tool only, training only, versus usual care). Such an RCT would also allow to examine differences between HCPs from different disciplines, as well as differences in advice adherence between older adults in the long term. 5. Conclusion This pilot randomized study explored the effectiveness, user experience, and implementation of a UCD developed digital multifactorial FRAT, called the Fall Analysis 2.0, among HCPs and older patients in Dutch primary care. The Fall Analysis 2.0 facilitated more fully completed multifactorial falls risk assessments in older adults compared to usual care. Additionally, the user experience of the Fall Analysis 2.0 was perceived as high among HCPs by reducing barriers. Sustainable implementation of the Fall Analysis 2.0 is contingent upon providing the corresponding training, providing HCP reimbursement, and ensuring interoperability with electronic health records. These findings suggest that UCD developed multifactorial FRATs have the potential to improve the quality of falls prevention care, provided they are implemented sustainably in practice. Declarations Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest. Funding This work was supported by GGD Amsterdam; VeiligheidNL; and the Ministerie van Volksgezondheid, Welzijn en Sport [333322]. Consent to participate Informed consent was obtained from all health professional and older adult participants included in the study. Acknowledgments We thank VeiligheidNL, Koninklijk Nederlands Genootschap voor Fysiotherapie, Landelijke Huisartsen Vereniging, Ergotherapie Nederland, Nederlandse Vereniging voor Geriatrie Fysiotherapie, Verpleegkundigen en Verzorgenden Nederland, Nederlandse Vereniging van Praktijkondersteuners en Praktijkverpleegkundigen, Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie, and Nederlands Huisartsen Genootschap for assisting with participant recruitment. We thank GGD Amsterdam, VeiligheidNL, and the Ministerie van Volksgezondheid, Welzijn en Sport for supporting this work. We thank Stefanie Tan for assistance with the effectiveness-implementation study. We thank Uselab for assistance with the development of the Fall Analysis 2.0. References Centers for Disease Control and Prevention (CDC). Older adult falls data. Older Adult Fall Prevention. 2024; https://www.cdc.gov/falls/data-research/index.html. Wang Z, Hu Y, Peng F. 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The Cochrane Database of Systematic Reviews, Chichester, UK: John Wiley & Sons, Ltd. 2003; https://doi.org/10.1002/14651858.CD000340. Hopewell S, Adedire O, Copsey BJ, Boniface GJ, Sherrington C, Clemson L, et al. Multifactorial and multiple component interventions for preventing falls in older people living in the community. Cochrane Database of Systematic Reviews 2018. 2018; https://doi.org/10.1002/14651858.CD012221.pub2. Hopewell S, Copsey B, Nicolson P, Adedire B, Boniface G, Lamb S. Multifactorial interventions for preventing falls in older people living in the community: a systematic review and meta-analysis of 41 trials and almost 20 000 participants. Br J Sports Med. 2020; https://doi.org/10.1136/bjsports-2019-100732. Lee SH, Yu S. Effectiveness of multifactorial interventions in preventing falls among older adults in the community: A systematic review and meta-analysis. International Journal of Nursing Studies. 2020; https://doi.org/10.1016/j.ijnurstu.2020.103564. McKay C, Anderson KE. How to manage falls in community dwelling older adults: a review of the evidence. Postgraduate Medical Journal. 2010; https://doi.org/10.1136/pgmj.2009.093468. Vandervelde S, Van Den Bosch N, Vlaeyen E, Dierckx De Casterlé B, Flamaing J, Belaen G, et al. Determinants influencing the implementation of multifactorial falls risk assessment and multidomain interventions in community- dwelling older people: a systematic review. Age and Ageing. 2024; https://doi.org/10.1093/ageing/afae123. Abras C, Maloney-Krichmar, Preece. User-centered design. Encyclopedia of Human-Computer Interaction. Brainbridge, W., Ed., Thousand Oaks, CA: Sage Publications. 2005; p. 445–56. Kujala S. User involvement: A review of the benefits and challenges. Behaviour & Information Technology. 2003; https://doi.org/10.1080/01449290301782. Norman DA, Draper, SW. User centered system design: new perspectives on human-computer interaction. 1986. Czuber NK, Garabedian PM, Rice H, Tejeda CJ, Dykes PC, Latham NK. Human-centered design and development of a fall prevention exercise app for older adults in primary care settings. Appl Clin Inform. 2024; https://doi.org/10.1055/a-2267-1727. Groos SS, De Wildt KK, Van De Loo B, Linn AJ, Medlock S, Shaw KM, et al. Development of the ADFICE_IT clinical decision support system to assist deprescribing of fall-risk increasing drugs: a user-centered design approach. PLoS ONE. 2024; https://doi.org/10.1371/journal.pone.0297703. Harte R, Quinlan LR, Glynn L, Rodríguez-Molinero A, Baker PM, Scharf T, et al. Human-centered design study: enhancing the usability of a mobile phone app in an integrated falls risk detection system for use by older adult users. JMIR Mhealth Uhealth. 2017; https://doi.org/10.2196/mhealth.7046. Hsieh K, Fanning J, Frechette M, Sosnoff J. Usability of a fall risk mHealth app for people with multiple sclerosis: mixed methods study. JMIR Hum Factors. 2021; https://doi.org/10.2196/25604. Nimmanterdwong Z, Boonviriya S, Tangkijvanich P. Human-centered design of mobile health apps for older adults: systematic review and narrative synthesis. JMIR Mhealth Uhealth. 2022; https://doi.org/10.2196/29512. Rice H, Garabedian PM, Shear K, Bjarnadottir RI, Burns Z, Latham NK, et al. Clinical decision support for fall prevention: defining end-user needs. Appl Clin Inform. 2022; https://doi.org/10.1055/s-0042-1750360. Tejeda CJ, Garabedian PM, Rice H, Samal L, Latham NK, Dykes PC. Development and usability testing of an exercise-based primary care fall prevention clinical decision support tool. AMIA Annu Symp Proc 2023. 2023; 699–708. Alsos OA, Svanæs D. Designing for the secondary user experience. Human-Computer Interaction – INTERACT 2011: 13th IFIP TC 13 International Conference, Lisbon, Portugal, September 5-9, 2011, Proceedings, Part IV, vol. 6949, Berlin, Heidelberg: Springer Berlin Heidelberg. 2011; https://doi.org/10.1007/978-3-642-23768-3. Angell SK, Keitsch M, Sigurjónsson J. The significance of the secondary user experience when designing for medical diagnostics. Proceedings of NordDesign 2016: August 10-12, 2016, Trondheim, Norway, Bristol, United Kingdom: The Design Society. 2016. Dos Santos RB, Lago GN, Jencius MC, Barbosa BA, Lima CA, Paschoal SM, et al. Older adults’ views on barriers and facilitators to participate in a multifactorial falls prevention program: Results from Prevquedas Brasil. Archives of Gerontology and Geriatrics. 2021; https://doi.org/10.1016/j.archger.2020.104287. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Medical Care. 2012; https://doi.org/10.1097/MLR.0b013e3182408812. Federatie Medisch Specialisten. Preventie van valincidenten bij ouderen. Richtlijnendatabase. n.d.; https://richtlijnendatabase.nl/richtlijn/preventie_van_valincidenten_bij_ouderen/valrisicobeoordeling_thuiswonende_ouderen.html VeiligheidNL. De Valanalyse. n.d.; https://www.veiligheid.nl/kennisaanbod/interventie/de-valanalyse. Groos SS, Linn AJ, Kuiper JI, Van Schoor NM, Van Der Velde N, Van Weert JCM. Combining user-centered design and behavioral theory to enhance health technologies: a personas-based approach for a primary-care based multifactorial falls risk assessment tool. International Journal of Medical Informatics. 2024; https://doi.org/10.1016/j.ijmedinf.2024.105420. Groos SS, Tan SM, Linn AJ, Kuiper JI, Van Schoor NM, Van Weert JCM, et al. Multidisciplinary care pathways for falls prevention in older adults: visualizing the needs of primary care-based health care professionals. Eur Geriatr Med. 2025; https://doi.org/10.1007/s41999-024-01142-3. Guay F, Vallerand RJ, Blanchard C. On the assessment of situational intrinsic and extrinsic motivation: the situational motivation scale (SIMS). Motivation and Emotion. 2000; https://doi.org/10.1023/A:1005614228250. Verbi Software. MAXQDA. MAXQDA. n.d. Alvarado N, McVey L, Wright J, Healey F, Dowding D, Cheong V-L, et al. Exploring variation in implementation of multifactorial falls risk assessment and tailored interventions: a realist review. BMC Geriatr. 2023; https://doi.org/10.1186/s12877-023-04045-3. McConville A, Hooven K. Factors influencing the implementation of falls prevention practice in primary care. J Am Assoc Nurse Pract. 2021; https://doi.org/10.1097/JXX.0000000000000360. Olaronke, Soriyan, Gambo, Olaleke. Interoperability in healthcare: benefits, challenges and resolutions. International Journal of Innovation and Applied Studies; 2013. Meekes WM, Leemrijse CJ, Korevaar JC, Stanmore EK, Van De Goor L (Ien) A. Implementing falls prevention in primary care: barriers and facilitators. CIA. 2022; https://doi.org/10.2147/CIA.S354911. Barmentloo LM, Dontje ML, Koopman MY, Olij BF, Oudshoorn C, Mackenbach JP, et al. Barriers and facilitators for screening older adults on fall risk in a hospital setting: perspectives from patients and healthcare professionals. IJERPH. 2020; https://doi.org/10.3390/ijerph17051461. Ruksakulpiwat S, Benjasirisan C, Ding K, Phianhasin L, Thorngthip S, Ajibade A, et al. Utilizing social determinants of health model to understand barriers to medication adherence in patients with ischemic stroke: a systematic review. PPA. 2023; https://doi.org/10.2147/PPA.S420059. Gentili A, Failla G, Melnyk A, Puleo V, Tanna GLD, Ricciardi W, et al. The cost-effectiveness of digital health interventions: A systematic review of the literature. Front Public Health. 2022; https://doi.org/10.3389/fpubh.2022.787135. Table 2 and 4 Table 2 and 4 are available in the Supplementary Files section. Supplementary Files Table2to4.docx Supplementarymaterialspilot.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 12 Aug, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers invited by journal 01 Jul, 2025 Editor assigned by journal 20 Jun, 2025 First submitted to journal 19 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6915278","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":478885435,"identity":"2868b282-b5d3-4aef-a58a-a5e165b53f72","order_by":0,"name":"Sara Groos","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYFAD9gYo4wCU5iOohQekNAFJCxtBLRIJRGqRb2B/wPh1j42c/MzHTzf+/GGTz3f8dJrUjRqGPFxaDA7wGDDLPEszNridZnabJyHNcuaZ3G3SOccYinFqYeBhYJY4cDhxg3SC2W2GhMMGBgeAWnIbGBLb8DgMrGX+zOPfbv5I+G9gcP4tfi1AzxowfgBqabjBY3aDJ+GAgcENArYYHOYxOMxwAOiXMzllt3nSkg0kb7zdbJ1zTAK3w9rbHz78cQAYYu3Ht938YWNnwHc+d+PtnBqbxH5cDmNmYDjMg0VcApcGMGD8gVd6FIyCUTAKRjwAADF9XSjlQYm1AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-3641-6425","institution":"Amsterdam UMC Location AMC: Amsterdam UMC Locatie AMC","correspondingAuthor":true,"prefix":"","firstName":"Sara","middleName":"","lastName":"Groos","suffix":""},{"id":478885436,"identity":"0e07b462-e033-45c0-9a6c-66b30cac5c04","order_by":1,"name":"Judith Kuiper","email":"","orcid":"","institution":"VeiligheidNL","correspondingAuthor":false,"prefix":"","firstName":"Judith","middleName":"","lastName":"Kuiper","suffix":""},{"id":478885437,"identity":"f89d96f2-7133-4701-806e-ccac7763fcae","order_by":2,"name":"Natasja van Schoor","email":"","orcid":"https://orcid.org/0000-0002-0870-0795","institution":"Amsterdam UMC - Locatie VUMC: Amsterdam UMC Locatie VUmc","correspondingAuthor":false,"prefix":"","firstName":"Natasja","middleName":"van","lastName":"Schoor","suffix":""},{"id":478885438,"identity":"787553b1-daf1-4e6f-be4f-2d689f32e0aa","order_by":3,"name":"Julia van Weert","email":"","orcid":"https://orcid.org/0000-0002-2259-5864","institution":"University of Amsterdam Amsterdam School of Communications Research: Universiteit van Amsterdam Amsterdam School of Communications Research","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"van","lastName":"Weert","suffix":""},{"id":478885439,"identity":"77536e21-a3aa-409f-b0cf-4b5a454a6e09","order_by":4,"name":"Annemiek Linn","email":"","orcid":"https://orcid.org/0000-0003-0912-3712","institution":"University of Amsterdam Amsterdam School of Communications Research: Universiteit van Amsterdam Amsterdam School of Communications Research","correspondingAuthor":false,"prefix":"","firstName":"Annemiek","middleName":"","lastName":"Linn","suffix":""},{"id":478885440,"identity":"ddb3e0f0-7b54-443f-b9b7-f750b4330d00","order_by":5,"name":"Nathalie van der Velde","email":"","orcid":"https://orcid.org/0000-0002-6477-6209","institution":"Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC","correspondingAuthor":false,"prefix":"","firstName":"Nathalie","middleName":"van der","lastName":"Velde","suffix":""}],"badges":[],"createdAt":"2025-06-17 14:18:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6915278/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6915278/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85993301,"identity":"46c7fb53-7b77-461f-82d5-c527f2092def","added_by":"auto","created_at":"2025-07-04 05:38:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":252773,"visible":true,"origin":"","legend":"\u003cp\u003eScreenshot of the Fall Analysis 2.0 tool.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. “Valgeschiedenis” = History of falls, “Mobiliteit” = Mobility, “Medicijngebruik” = Medication, “Valangst” = Fear of falling, “Cognitie en stemming” = Cognition, “Gezichtsvermogen” = Vision, “Duizeligheid” = Dizziness/vestibular, “Incontinentie” = Urinary incontinence, “Gehoorproblemen” = Hearing, “Algemene dagelijkse levensverrichtingen” = Activities of daily living, “Omgevingsfactoren” = Environmental factors, “Voetproblemen en schoeisel” = Footwear and foot problems, “Voedingstoestand en vitamine D” = Nutritional status and vitamin D intake.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6915278/v1/a44b5e0ea608ea20ab9e83c1.png"},{"id":85993292,"identity":"4969283f-fb0e-450a-aa48-2f7f73997eaa","added_by":"auto","created_at":"2025-07-04 05:38:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":229845,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for the inclusion of HCPs and patients.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6915278/v1/bad272cd327da450bad9bda1.png"},{"id":85993906,"identity":"2810638b-3cf8-4de7-ac31-f8329257a2ef","added_by":"auto","created_at":"2025-07-04 05:46:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1153003,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6915278/v1/967d9bce-a696-409d-84eb-632b1ab7b5a6.pdf"},{"id":85993300,"identity":"f8744698-2ac4-4626-a41a-da7016f40ac1","added_by":"auto","created_at":"2025-07-04 05:38:44","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22502,"visible":true,"origin":"","legend":"","description":"","filename":"Table2to4.docx","url":"https://assets-eu.researchsquare.com/files/rs-6915278/v1/a364042f69b9ec38fcd86c0b.docx"},{"id":85993295,"identity":"7e55f3c6-5cb3-4009-a27b-aa965a1a46a2","added_by":"auto","created_at":"2025-07-04 05:38:44","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":33086,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterialspilot.docx","url":"https://assets-eu.researchsquare.com/files/rs-6915278/v1/af42d6d8bd6c35d8f810c711.docx"}],"financialInterests":"","formattedTitle":"Investigating a user-centered design driven multifactorial falls risk assessment tool in primary care: A randomized effectiveness-implementation study","fulltext":[{"header":"Key summary points ","content":"\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e: The aim of this study was to examine the effectiveness, user experience, and implementation of a User-Centered Design (UCD) developed multifactorial falls risk assessment tool (FRAT), namely the Fall Analysis 2.0, in Dutch primary care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings\u003c/strong\u003e: The rate of fully completed multifactorial falls risk assessments was higher among health care professionals (HCPs) using the Fall Analysis 2.0 compared to usual care. The Fall Analysis 2.0 was rated highly for user experience with implementation dependent on HCP reimbursement and interoperability with electronic health records. No significant differences in older adults\u0026rsquo; adherence-related motivation were found.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMessage\u003c/strong\u003e: UCD developed multifactorial FRATs have potential in improving the quality of falls prevention-related care.\u0026nbsp;\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eFalls in older adults (65+) is a growing global health problem [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Falls incidences can significantly reduce the quality of life of older adults as they frequently lead to functional, psychological, and cognitive decline [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Falls can also result in mortality, with the falls-related mortality rate in older adults increasing worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The medical costs of falls are estimated to account for 1.5 percent of total health care expenditures in Western countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Effective falls prevention is crucial to reduce the burden on our rapidly ageing society [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFalls are a result of numerous interacting risk factors of which several are potentially modifiable, including reduced mobility, sensory function, activities of daily living, cognitive function, dizziness, disease history, medications, nutritional status and vitamin D, and environmental risk [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The World Guidelines for falls prevention and management recommend that health care professionals (HCPs) perform multifactorial falls risk assessments to detect and target modifiable falls risk factors in older adults at high risk of falling. Multifactorial falls risk assessment tools (FRATs) make use of evidence-based functional tests and questionnaires to support HCPs in carrying out such an assessment in these adults by (1) identifying modifiable falls risk factors, and (2) selecting interventions to effectively target two or more identified falls risk factors (hereafter a multidomain intervention) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Multidomain interventions based on fully completed multifactorial falls risk assessments are more effective at reducing falls rates in older adults [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the Netherlands, a multidomain intervention based on a multifactorial falls risk assessment is considered usual care for older adults at high risk of falling.\u003c/p\u003e \u003cp\u003eDespite their effectiveness, certain limitations are hindering the optimal use of multifactorial FRATs in practice. First, given the multifactorial nature of falls, quality falls prevention care relies on multidisciplinary expertise (i.e., the collaboration between several HCPs from different disciplines) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, multifactorial FRATs are often developed for use in one particular care context, which can limit the usability of these tools in a multidisciplinary care context [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Second, multifactorial FRATs are perceived by HCPs as difficult to use, time consuming, and poorly integrated into workflows [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These barriers indicate that these tools are not adapted to the heterogeneous needs of HCPs, resulting in incomplete multifactorial falls risk assessments and, in turn, suboptimal multidomain interventions in older adults at high risk of falling\u003c/p\u003e \u003cp\u003eOne way to cater multifactorial FRATs to the needs of users is through User-Centered Design (UCD). UCD is an iterative development process in which prospective users of an intervention are involved early and continuously to inform the development of tools [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A UCD approach has been successfully applied in the development of several digital tools for falls prevention such as clinical decision support systems for use by HCPs and mHealth applications for use by older adults [\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24 CR25\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Additionally, UCD studies are increasingly thinking about the secondary user experience (here older adults at high risk of falling). In health care, the secondary user experience refers to the experience of patients during the HCP\u0026rsquo;s interaction with a tool during consultations [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. As a result, barriers experienced by the primary user (e.g., difficulty using a multifactorial FRAT) can negatively impact the secondary user (e.g., incomplete assessment and suboptimal interventions). Thus, enhancing multifactorial FRATs for HCPs through UCD could in addition positively impact the wellbeing of older adults. However, it remains uncertain whether improving the user experience of digital clinical tools can influence behavior or determinants of behavior. Specifically, a UCD developed digital health intervention is ineffective in improving risk of falling and managing risk factors for falling in older adults if it is not used by HCPs as intended (e.g., incomplete assessments) or if patients are not motivated to adhere to the advice provided by HCPs. Lack of motivation by older adults is a commonly reported barrier in falls prevention [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Therefore, investigating whether UCD driven tools can improve behavior in primary users or determinants of behavior, such as motivation, in secondary users is vital for optimizing UCD further.\u003c/p\u003e \u003cp\u003eThe aim of this study is two-fold. First, we aimed to test the effectiveness of a UCD developed digital multifactorial FRAT on the falls risk management behavior of HCPs (i.e., performing fully completed assessments) and on motivation to adhere to falls prevention advice of older adults (hereafter adherence-related motivation) in primary care in the Netherlands. Second, we aimed to assess the user experience of HCPs, and the implementation of the UCD driven tool in practice.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Study design\u003c/h2\u003e\n \u003cp\u003eTo evaluate our UCD developed digital multifactorial FRAT, a hybrid type 2 effectiveness-implementation study was conducted in Dutch primary care [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Randomization occurred at the practice level to avoid possible contamination of the intervention between HCPs working at the same practice. This resulted in an intervention group (\u003cem\u003en\u003c/em\u003e older adults\u0026thinsp;=\u0026thinsp;36, HCPs\u0026thinsp;=\u0026thinsp;10) and a control group (\u003cem\u003en\u003c/em\u003e older adults\u0026thinsp;=\u0026thinsp;27, HCP\u0026thinsp;=\u0026thinsp;9) across 15 practices (\u003cem\u003en\u003c/em\u003e control\u0026thinsp;=\u0026thinsp;6; intervention\u0026thinsp;=\u0026thinsp;9). Older adults were blinded to the intervention allocation. However, blinding of the intervention allocation was not possible for researchers and HCPs as researchers had to set up the digital multifactorial FRAT prior to the consultations and HCPs had to interact with the tool during the consultations. Measurements were collected at four timepoints: T0 was a baseline questionnaire prior to the first consultation (HCPs only), T1 and T2 was a questionnaire after each consultation (HCPs and patients), and T3 was an interview after all consultations were completed (intervention HCPs only). Data was collected between May and September 2024. The study protocol was evaluated by the Medical Ethics Research Committee of the first author\u0026rsquo;s institute who declared that the Medical Research Involving Human Subjects Act did not apply to this study. The study was presented and documented at the working group meeting for the national multidomain falls prevention program on November 20th, 2023. This program is set up by the Netherlands Ministry of Health, Welfare, and Sport (VWS) and aims to improve the implementation of clinical guidelines regarding falls prevention into practice. The study was registered at OSF (hyperlink redacted for double blind peer review).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Procedure\u003c/h2\u003e\n \u003cp\u003eHCP practices were randomized to either the intervention or control group using a random number generator. All HCPs were briefed about the practical matters of the study such as the inclusion and exclusion criteria of older patients in an online meeting. The T0 questionnaire assessing relevant background characteristics (e.g., age, gender, falls prevention education) was sent to HCPs via mail. HCPs in the intervention group attended the full day in-person training session. The T0 questionnaires were returned to the researcher prior to this training to avoid bias.\u003c/p\u003e\n \u003cp\u003eThe first contact with an eligible patient was initiated by the participating HCP during which the patient received an information letter about the study. Interested patients provided consent for the HCP to share their contact details with the researcher who then initiated the second contact with the patient by telephone. During this phone call, the researcher reassessed whether the patient was eligible to participate and answered any questions from the patient about the study. Additionally, verbal consent was obtained to schedule a consultation with the HCP for the purpose of the study. Written consent was obtained from all participants prior to data collection (both HCPs and patients).\u003c/p\u003e\n \u003cp\u003eConsultations occurred at the primary care practice or at the patient\u0026rsquo;s home with the researcher present. HCPs in the intervention group used the Fall Analysis 2.0 during consultations with older patients, whereas HCPs in the control group provided usual care. HCPs completed the T1 questionnaire after each consultation. This questionnaire examined the falls risk management behavior of HCPs. In turn, patients completed the T2 questionnaire within two weeks after the consultation, either in-person, at home or by telephone. This questionnaire assessed the adherence-related motivation of patients and relevant background characteristics (e.g., age, gender). The T3 interview of 30 minutes with HCPs in the intervention group occurred after all consultations were completed and T1 questionnaires were returned.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. Control comparator\u003c/h2\u003e\n \u003cp\u003eIn the Netherlands, a multifactorial falls risk assessment can be performed by primary care-based HCPs with experience in falls prevention using validated multifactorial FRATs to perform such an assessment, for instance the Fall Analysis 1.0 [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, HCPs in the control group were asked to perform a multifactorial falls risk assessment as part of usual care for older adults at high risk of falling.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. Intervention components\u003c/h2\u003e\n \u003cp\u003eThe intervention components comprised a UCD developed digital multifactorial FRAT, hereafter referred to as the Fall Analysis 2.0 (in Dutch: \u0026ldquo;Valanalyse 2.0\u0026rdquo;) and attendance of a corresponding in-person training session about multifactorial falls risk assessments in general and the Fall Analysis 2.0 specifically. The Fall Analysis 2.0 is an adapted, digital version of the existing validated multifactorial FRAT (i.e., the paper-based Fall Analysis 1.0), and the content of the training is based on the content of the corresponding training for the Fall Analysis 1.0 currently available for use by primary care-based HCPs [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. The user experience of the Fall Analysis 2.0 and corresponding training was enhanced by employing methods from UCD. The UCD driven development of the Fall Analysis 2.0 is described in detail elsewhere [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. Prior to the start of the pilot study, the Fall Analysis 2.0 underwent a usability testing round to identify and solve usability problems that could affect both the primary and secondary user experience. This resulted in a ready-to-use Fall Analysis 2.0, as depicted in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. A detailed description of the Fall Analysis 2.0 and corresponding training is provided in the supplementary materials.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5. Recruitment of HCPs and older adults\u003c/h2\u003e\n \u003cp\u003eThe study population consisted of primary care-based HCPs and older adults at high risk of falling. A convenience sample of HCPs was recruited with the help from several organizations who are each in direct contact with primary care-based HCPs across the Netherlands (refer to acknowledgements). Representatives from these organizations were requested to distribute a call for participants which included information about the study and an embedded link to a sign-up sheet. HCPs were eligible to participate if they were (1) general practitioners, physical therapists, occupational therapists, pharmacists, district nurses, or nurse practitioners currently working in Dutch primary care; and (2) regularly conducting multifactorial falls risk assessments in older adults at high risk of falling in current practice.\u003c/p\u003e\n \u003cp\u003eA convenience sample of patients was recruited with the help of participating HCPs. Following the World Falls Guidelines algorithm for high falls risk, older adults were eligible to participate if they adhered to the inclusion and exclusion criteria as displayed in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]. Each HCP was instructed to include about five older patients at high risk of falling based on the inclusion and exclusion criteria.\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6. Measurements\u003c/h2\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e2.6.1. Background characteristics\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e in the supplementary materials provides a detailed overview of the measurements of the background characteristics. HCPs were asked to indicate their age, gender, profession, years worked in primary care, practice setting, falls prevention education, and practice patterns (measured at T0). Older adults were asked about their age, gender, level of education, and living situation at (measured at T2).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e2.6.2. Primary outcomes\u003c/h2\u003e\n \u003cp\u003eThe primary outcomes of this study was the falls risk management behavior of HCPs and the adherence-related motivation of older adults. Falls risk management behavior of HCPs was operationalized as the number of fully completed multifactorial falls risk assessments by HCPs, preferably using a validated tool (measured at T1). Based on Dutch guideline recommendations, a completed multifactorial falls risk assessment is defined as a set of assessments performed by HCPs across 13 risk factors to identify and target potentially modifiable risk factors. These risk factors are: history of falls, mobility, medication, dizziness, vision, hearing, cognition, urinary incontinence, fear of falling, activities of daily living, environmental factors, footwear and foot problems, nutritional status and vitamin D intake [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. To measure this, HCPs were asked to write down which risk factors for falling they assessed during the consultation and whether they made use of a validated tool while performing the assessment. This behavior information was also received in the form of user data from HCPs in the intervention group (i.e., fully assessed risk factors). Assessments were considered complete when all of the 13 risk factors were assessed by HCPs during the consultation, with HCPs in the control group preferably using a validated multifactorial FRAT (e.g., the Fall Analysis 1.0). Risk assessment data from HCPs was manually coded into two separate categorical variables, namely completion of multifactorial falls risk assessments (1\u0026thinsp;=\u0026thinsp;\u003cem\u003ecompleted\u003c/em\u003e and 0\u0026thinsp;=\u0026thinsp;\u003cem\u003enot completed\u003c/em\u003e) and use of validated tools (1\u0026thinsp;=\u0026thinsp;\u003cem\u003euse of tools\u003c/em\u003e and 0\u0026thinsp;=\u0026thinsp;\u003cem\u003eno use of tools\u003c/em\u003e).\u003c/p\u003e\n \u003cp\u003eThe adherence-related motivation of older adults was measured using the 16-item Situational Motivation Scale by [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e] and adapted to fit the context of this study (measured at T2). For example, the phrase \u0026ldquo;\u0026hellip;engaged in this activity\u0026rdquo; in the original scale was adapted to the phrase \u0026ldquo;\u0026hellip;follow the advice.\u0026rdquo; Participants were asked \u0026ldquo;Why would you follow the falls prevention advice from your HCP?\u0026rdquo; of which four items measured the construct of intrinsic motivation (e.g., \u0026ldquo;Because I think it is useful advice\u0026rdquo;), identified regulation (e.g., \u0026ldquo;Because the advice is for my own good\u0026rdquo;), external regulation (e.g., \u0026ldquo;Because I am supposed to follow the advice\u0026rdquo;), and amotivation (e.g., \u0026ldquo;There may be good reasons to follow the advice, but personally I do not see any.\u0026rdquo;), respectively using a three-point Likert scale (i.e., 1\u0026thinsp;=\u0026thinsp;\u003cem\u003ecompletely disagree\u003c/em\u003e to 3\u0026thinsp;=\u0026thinsp;\u003cem\u003ecompletely agree\u003c/em\u003e). Items for identified regulation, external regulation, and amotivation were summarized into three separate mean scales where higher scores indicated higher identified regulation (M\u0026thinsp;=\u0026thinsp;2.8, SD\u0026thinsp;=\u0026thinsp;0.4, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.68), external regulation (M\u0026thinsp;=\u0026thinsp;2.3, SD\u0026thinsp;=\u0026thinsp;0.6, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.79), and amotivation (M\u0026thinsp;=\u0026thinsp;1.9, SD\u0026thinsp;=\u0026thinsp;0.6, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.75), respectively. Items measuring intrinsic motivation were treated as separate items due to poor internal consistency between items (\u003cem\u003e\u0026alpha;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.37).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7. Secondary outcome\u003c/h2\u003e\n \u003cp\u003eThe secondary outcome of this study was the user experience of HCPs, and the implementation of the Fall Analysis 2.0 in practice (measured at T3). Interviews were carried out by the first author using a semi-structured interview guide developed for this study. First, HCPs were asked about the perceived usability and usefulness of the Fall Analysis 2.0 for assessing and targeting risk factors for falling in practice (e.g., \u0026ldquo;How do you find the Fall Analysis 2.0 compared to your previous method of screening?\u0026rdquo;; \u0026ldquo;When the Fall Analysis 2.0 was first introduced what benefits did you think would result?; and \u0026ldquo;To what extent did you experience these benefits?\u0026rdquo;). Afterwards, HCPs were asked about potential barriers and facilitators to implementing the Fall Analysis 2.0 (e.g., \u0026ldquo;Can you indicate what factors facilitate and hinder the implementation of the Fall Analysis 2.0 in practice?\u0026rdquo;). Each interview lasted 30 to 45 minutes.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8. Data analysis\u003c/h2\u003e\n \u003cp\u003eFisher\u0026rsquo;s exact tests were performed to evaluate the association between the group condition (intervention versus usual care) and falls risk management behavior of HCPs, namely the completion of multifactorial falls risk assessments (completed versus not completed) and use of a validated multifactorial FRAT for these assessments (use of one or more tools versus no use of tools). Mann-Whitney U tests were used to examine differences in falls prevention-related motivation between older patients in the intervention versus usual care group using the items of intrinsic motivation, and mean scale items of identified regulation, external regulation, and amotivation as dependent variables. Lastly, differences between the group condition (intervention versus usual care) on participant characteristics were assessed using Fisher\u0026rsquo;s exact test for categorical variables and Mann-Whitney U test for continuous variables. The statistical software IBM SPSS Statistics v.28.0.1.1 (15) was used for data analysis. Interviews with HCPs were recorded and transcribed verbatim by the first author. All transcripts were analyzed in MAXQDA 2022 [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. Each transcript was coded by the first author using both a deductive and inductive approach, and doubts were discussed with co-authors. Specifically, the predefined main category codes of user experience, barriers, and facilitators were established following the topics from the semi-structured interview guide. Additionally, predefined subcategory codes of guided assessment/treatment, enhanced efficiency, and improved adaptability were established following the results of a Fall Analysis-related needs assessment [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. This was used to examine whether UCD was effective at addressing the previously established needs of primary care-based HCPs. Lastly, an inductive approach was used to identify specific barriers and facilitators mentioned by HCPs.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e display the characteristics of HCPs and older patients at baseline, respectively. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e displays a flowchart for the inclusion of HCPs and patients. The results of the primary outcomes are displayed in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Background characteristics of HCPs\u003c/h2\u003e\n \u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, no statistically significant differences in characteristics were observed among HCPs in the intervention and usual care group at baseline. In short, the majority of participating HCPs were female (84.2%) and the mean age was 46.2 years old. The most reported professions were nurse practitioners (26.3%), physical therapists (21.1%), and occupational therapists (21.1%). HCPs indicated diverse practice patterns with regards to performing multifactorial falls risk assessments in older adults at high risk of falling (refer to Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for details). Only a few HCPs reported using the Fall Analysis 1.0 when performing multifactorial falls risk assessments in older adults (15.8%). Among the 13 risk factors for falling that make up a recommended multifactorial falls risk assessment, medication (94.7%), mobility (78.9%), environmental factors (78.9%), vision (73.7%), and cognition (63.2%) were the risk factors most often listed by HCPs when asked about their previous knowledge about risk factors for falling.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Background characteristics of older patients\u003c/h2\u003e\n \u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, no statistically significant differences in baseline characteristics were observed among older patients in the intervention and usual care group. The majority of patients were female (63.5%) and the mean age was 81 years. More than half of participants reported receiving secondary level of education (53.2%) indicating a completed middle school or high school degree. Furthermore, the majority of participants lived alone without a partner or child(ren) (63.5%).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Primary outcomes\u003c/h2\u003e\n \u003cp\u003eRegarding the falls risk management behavior of HCPs, the Fisher\u0026rsquo;s exact test showed a statistically significant association, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, with higher rates of fully completed multifactorial falls risk assessments in older adults observed among HCPs using the Fall Analysis 2.0 (86.1%) versus usual care (3.7%). For the use of validated instruments, Fisher\u0026rsquo;s exact test revealed a statistically significant association, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, in which the use of validated tools was lower among HCPs in the usual care group (11.1%). Specifically, HCPs (n\u0026thinsp;=\u0026thinsp;2) in the usual care group used the Fall Analysis 1.0. Other functional assessments and questionnaires used by HCPs (n\u0026thinsp;=\u0026thinsp;2) in the usual care group were the Timed Chair Stand Test, Berg Balance Scale, or a self-built assessment questionnaire. In usual care, the most commonly assessed risk factors by HCPs were reduced mobility (74.1%) and medication use (63%). The least commonly assessed risk factors were vision problems (18.5%) and hearing (11.1%). Thus, while HCPs in usual care assessed several falls risk factors, it did not constitute a fully completed multifactorial falls risk assessment per the guidelines.\u003c/p\u003e\n \u003cp\u003eMann-Whitney U tests were performed to assess differences in adherence-related motivation between older patients in the Fall Analysis 2.0 versus usual care group. As illustrated in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, identified regulation, external regulation, amotivation, and intrinsic motivation did not significantly differ between older patients being administered the Fall Analysis 2.0 versus usual care.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Secondary outcomes\u003c/h2\u003e\n \u003cp\u003eTable S2 in supplementary materials displays quotes from the interviews with HCPs. The user experience of the Fall Analysis 2.0 was positively assessed by HCPs. HCPs found that the Fall Analysis 2.0 guided users in assessing risk factors for falling and subsequent treatment-related decision making for detected risk factors. For example, one HCP mentioned that the tool \u003cem\u003e\u0026ldquo;organizes everything very clearly\u0026rdquo;\u003c/em\u003e and \u003cem\u003e\u0026ldquo;[the risk factor] stays highlighted in a different color\u0026rdquo;\u003c/em\u003e if it is not yet assessed \u003cem\u003e\u0026ldquo;so you end up filling everything in [P3].\u0026rdquo;\u003c/em\u003e Other HCPs mentioned how the tool guides you \u003cem\u003e\u0026ldquo;through everything [P5]\u0026rdquo;\u003c/em\u003e, provides immediate results and advice, and allows you to look \u003cem\u003e\u0026ldquo;much deeper into someone\u0026rsquo;s situation [P2].\u0026rdquo;\u003c/em\u003e Additionally, the Fall Analysis 2.0 was found to enhance the efficiency of multifactorial falls risk assessments. Specifically, HCPs stated that a \u003cem\u003e\u0026ldquo;digital and easy to fill in\u0026rdquo;\u003c/em\u003e tool can save HCPs \u003cem\u003e\u0026ldquo;a lot of time [P7]\u0026rdquo;\u003c/em\u003e with the biggest advantage being \u003cem\u003e\u0026ldquo;that the advice comes out immediately [P5].\u0026rdquo;\u003c/em\u003e Despite the Fall Analysis 2.0 allowing HCPs to go \u003cem\u003e\u0026ldquo;through [the assessment of risk factors] the way [they] want to [P6],\u0026rdquo;\u003c/em\u003e some HCPs highlighted issues with the tool\u0026rsquo;s adaptability in a patient\u0026rsquo;s home. Specifically, HCPs mentioned that not all functional assessments, such as the Short Physical Performance Battery, are suitable for being conducted at a home and highlighted the need for a digital tool that also works offline (e.g., no access to Wi-Fi). The main barrier for successful implementation that was mentioned by HCPs was the lack of reimbursement of the Fall Analysis 2.0 by health insurers. One HCP also saw having to attend the in-person training day as a barrier suggesting that those who already attended the training can explain the Fall Analysis 2.0 to their colleagues. Other HCPs recognized the training as a facilitator for successful implementation. For instance, one HCP highlighted that the training provided them with the \u003cem\u003e\u0026ldquo;extra depth\u0026rdquo;\u003c/em\u003e needed to ask \u003cem\u003e\u0026ldquo;certain questions\u0026rdquo;\u003c/em\u003e and that this was something \u003cem\u003e\u0026ldquo;helpful to have explained again [P4].\u0026rdquo;\u003c/em\u003e Alongside the training, HCPs also mentioned that ensuring interoperability between the Fall Analysis 2.0 and electronic health records would facilitate the sustainable implementation of the tool in practice as it enhances communication between HCPs, specifically with the general practitioner (GP).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe aim of this hybrid type 2 effectiveness-implementation study was to investigate the effectiveness, user experience, and implementation of a UCD developed multifactorial FRAT among HCPs and older patients in Dutch primary care. The findings of this study suggest that the barriers experienced by HCPs can be reduced if multifactorial FRATs are developed following the principles of UCD. Specifically, despite multifactorial FRATs providing a structured approach for assessing, identifying, and effectively targeting individual falls risk factors in older adults at high risk falling, their successful implementation into real-world practice settings is perceived by HCPs as difficult, time consuming, and poorly integrated into workflows [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Additionally, systematic reviews have shown that the incorporation of clinical guidelines for falls prevention into routine practice is low among HCPs in primary care, which can result in a suboptimal multidomain falls prevention intervention in older adults at high risk of falling [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Such falls risk management behavior by HCPs was also observed among participants providing usual care in this study, whereby the carrying out of multifactorial falls risk assessments in older adults was not per the recommended national and international guidelines for falls prevention [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In turn, we found the Fall Analysis 2.0 positively influenced the falls risk management behavior of HCPs whereby use of this validated tool was associated with a significantly higher rate of fully completed multifactorial falls risk assessments. In other words, the Fall Analysis 2.0 intervention facilitated improved multifactorial falls risk assessments in older adults at high risk of falling, which can be expected to result in more optimum multidomain falls prevention interventions in these adults. This likely occurred due to the continuous involvement of prospective users in the development of the Fall Analysis 2.0 and corresponding training, which ensured that the intervention components met the previously determined needs of HCPs (e.g., guided assessment/treatment and enhanced assessment efficiency) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. As a result, the Fall Analysis 2.0 and corresponding training supported HCPs in delivering improved falls prevention care to older adults in practice. Additionally, HCPs suggested minor improvements for further enhancing the tool\u0026rsquo;s fit in a home care contexts (e.g., ability to conduct assessments offline), which could be examined in future implementation research. HCPs also emphasized the need for insurance reimbursement, which is recognized as an important barrier hindering the successful implementation of multifactorial falls risk assessments in practice [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. While ensuring interoperability between systems is recognized as a challenge in health care, the findings of this suggest that the sustainability of the Fall Analysis 2.0 is dependent on its integration into existing electronic health records [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. We are working together with the Netherlands Ministry of Health, Welfare, and Sport and the Dutch National Expert Center on Injury Prevention to address these needs and ensure sustainable long-term implementation of the Fall Analysis 2.0 into practice.\u003c/p\u003e \u003cp\u003eWith regards to older adults at high risk of falling, motivation to adhere to the falls prevention advice received by HCPs did not differ between patients being administered the Fall Analysis 2.0 versus usual care, probably due to a ceiling effect. In other words, older patients in this study displayed high levels of motivation to adhere to the falls prevention advice provided by HCPs irrespective of their group condition. This finding is surprising given that motivating older patients to adhere to the advice received by HCPs is a well-established challenge in falls prevention [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. There are two reasons that could explain why adherence-related motivation was high among older adults in both groups. First, the majority of older adults who participated in this study were existing patients of participating HCPs with good provider-patient relationships. Good provider-patient relationships have been shown to facilitate therapeutic adherence in older adults [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Therefore, older adults in the usual group may have displayed high levels of motivation to adhere to advice because of the existing provider-patient relationship. Second, from a methodological perspective, the Situational Motivational Scale used to measure adherence-related motivation in this study was adapted from a five-point Likert scale to a three-point Likert scale to enhance scale comprehension among older adults [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This decreased the likelihood of identifying differences between group conditions (i.e., Fall Analysis 2.0 versus usual care) as a five-point Likert scale would have possibly resulted in more variability in the data.\u003c/p\u003e \u003cp\u003eA major strength of this study is that it highlighted the potential promising effects of UCD developed digital tools in clinical practice, specifically within the context of falls prevention. However, the findings of this study should also be interpreted in the context of their limitations. First, the validated multifactorial FRAT (i.e., the Fall Analysis 1.0) used by HCPs in usual care was paper-based. Given that digital clinical tools have been shown to improve to efficiency and quality of care, we cannot determine with certainty whether the positive change in behavior among HCPs occurred due to the digitalization of the Fall Analysis 1.0 or due to its UCD development into version 2.0 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Additionally, the intervention described in this study consisted of the use of the Fall Analysis 2.0 and the attendance of a corresponding in-person training session among a small sample of HCPs. While both the digital multifactorial FRAT and training were developed following UCD, a randomized controlled trial (RCT) with more conditions and bigger sample size is necessary to untangle which components of the intervention contributed to which effects in HCPs (e.g., full intervention, tool only, training only, versus usual care). Such an RCT would also allow to examine differences between HCPs from different disciplines, as well as differences in advice adherence between older adults in the long term.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003e This pilot randomized study explored the effectiveness, user experience, and implementation of a UCD developed digital multifactorial FRAT, called the Fall Analysis 2.0, among HCPs and older patients in Dutch primary care. The Fall Analysis 2.0 facilitated more fully completed multifactorial falls risk assessments in older adults compared to usual care. Additionally, the user experience of the Fall Analysis 2.0 was perceived as high among HCPs by reducing barriers. Sustainable implementation of the Fall Analysis 2.0 is contingent upon providing the corresponding training, providing HCP reimbursement, and ensuring interoperability with electronic health records. These findings suggest that UCD developed multifactorial FRATs have the potential to improve the quality of falls prevention care, provided they are implemented sustainably in practice.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by GGD Amsterdam; VeiligheidNL; and the Ministerie van Volksgezondheid, Welzijn en Sport [333322].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all health professional and older adult participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank VeiligheidNL, Koninklijk Nederlands Genootschap voor Fysiotherapie, Landelijke Huisartsen Vereniging, Ergotherapie Nederland, Nederlandse Vereniging voor Geriatrie Fysiotherapie, Verpleegkundigen en Verzorgenden Nederland, Nederlandse Vereniging van Praktijkondersteuners en Praktijkverpleegkundigen, Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie, and Nederlands Huisartsen Genootschap for assisting with participant recruitment. We thank GGD Amsterdam, VeiligheidNL, and the Ministerie van Volksgezondheid, Welzijn en Sport for supporting this work. We thank Stefanie Tan for assistance with the effectiveness-implementation study. We thank Uselab for assistance with the development of the Fall Analysis 2.0.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCenters for Disease Control and Prevention (CDC). Older adult falls data. Older Adult Fall Prevention. 2024; https://www.cdc.gov/falls/data-research/index.html.\u003c/li\u003e\n\u003cli\u003eWang Z, Hu Y, Peng F. Long-term trends in unintentional fall mortality in China: a population-based age-period-cohort study. Front Public Health. 2021; https://doi.org/10.3389/fpubh.2021.749295.\u003c/li\u003e\n\u003cli\u003eGiovannini S, Brau F, Galluzzo V, Santagada DA, Loreti C, Biscotti L, et al. Falls among older adults: screening, identification, rehabilitation, and management. 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Interoperability in healthcare: benefits, challenges and resolutions. International Journal of Innovation and Applied Studies; 2013.\u003c/li\u003e\n\u003cli\u003eMeekes WM, Leemrijse CJ, Korevaar JC, Stanmore EK, Van De Goor L (Ien) A. Implementing falls prevention in primary care: barriers and facilitators. CIA. 2022; https://doi.org/10.2147/CIA.S354911.\u003c/li\u003e\n\u003cli\u003eBarmentloo LM, Dontje ML, Koopman MY, Olij BF, Oudshoorn C, Mackenbach JP, et al. Barriers and facilitators for screening older adults on fall risk in a hospital setting: perspectives from patients and healthcare professionals. IJERPH. 2020; https://doi.org/10.3390/ijerph17051461.\u003c/li\u003e\n\u003cli\u003eRuksakulpiwat S, Benjasirisan C, Ding K, Phianhasin L, Thorngthip S, Ajibade A, et al. Utilizing social determinants of health model to understand barriers to medication adherence in patients with ischemic stroke: a systematic review. PPA. 2023; https://doi.org/10.2147/PPA.S420059.\u003c/li\u003e\n\u003cli\u003eGentili A, Failla G, Melnyk A, Puleo V, Tanna GLD, Ricciardi W, et al. The cost-effectiveness of digital health interventions: A systematic review of the literature. Front Public Health. 2022; https://doi.org/10.3389/fpubh.2022.787135.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 2 and 4","content":"\u003cp\u003eTable 2 and 4 are available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-geriatric-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"EGEM","sideBox":"Learn more about [European Geriatric Medicine](https://www.springer.com/journal/41999)","snPcode":"41999","submissionUrl":"https://www.editorialmanager.com/egem/default2.aspx","title":"European Geriatric Medicine","twitterHandle":"","acdcEnabled":false,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6915278/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6915278/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eMultifactorial falls risk assessment tools (FRATs) identify and target individual falls risk factors in older adults. However, barriers can hinder their effectiveness. User-Centered Design (UCD) could improve multifactorial FRATs for both primary (HCPs) and secondary (patients) users. This study investigated a UCD developed multifactorial FRAT, the Fall Analysis 2.0.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA randomized effectiveness-implementation study included 19 HCPs from 15 primary care practices, randomly assigned to either the intervention or control group (usual care). The intervention involved using the Fall Analysis 2.0 and corresponding training. Participants were community-dwelling (65\u0026thinsp;+\u0026thinsp;years) at high risk of falling (36 intervention, 27 control). Primary outcomes included differences in HCPs falls risk management behavior and older adults\u0026rsquo; adherence-related motivation to falls prevention advice, analyzed using Fisher\u0026rsquo;s Exact tests and Mann Whitney U tests. Secondary outcomes of the Fall Analysis 2.0 user experience and implementation was explored through HCP interviews.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFully completed multifactorial falls risk assessments (86.1%) by HCPs was higher in the intervention compared to the control group (3.7%), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. Use of validated tools was lower in the control group (11.1%), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. HCPs rated the Fall Analysis 2.0 highly for user experience. Successful implementation is dependent on HCP reimbursement and interoperability with electronic health records. No significant differences in older adults\u0026rsquo; adherence-related motivation were found between groups due to a ceiling effect.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e UCD developed multifactorial FRATs like the Fall Analysis 2.0 show promise for enhancing falls prevention care quality by improving delivery for HCPs and older adults.\u003c/p\u003e","manuscriptTitle":"Investigating a user-centered design driven multifactorial falls risk assessment tool in primary care: A randomized effectiveness-implementation study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-04 05:38:34","doi":"10.21203/rs.3.rs-6915278/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2025-08-13T02:43:05+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-07-01T08:47:07+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-01T07:44:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-20T07:29:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Geriatric Medicine","date":"2025-06-19T10:12:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-geriatric-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"EGEM","sideBox":"Learn more about [European Geriatric Medicine](https://www.springer.com/journal/41999)","snPcode":"41999","submissionUrl":"https://www.editorialmanager.com/egem/default2.aspx","title":"European Geriatric Medicine","twitterHandle":"","acdcEnabled":false,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"de517263-2c6a-45ef-b28b-2240b2ac078b","owner":[],"postedDate":"July 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-22T16:56:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-04 05:38:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6915278","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6915278","identity":"rs-6915278","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}