Self-Selection of Bathroom-Assistive Technology: Development of an Electronic Decision Support System (Hygiene 2.0)

Abstract

Background A clinical algorithm (Algo) in paper form is used in Quebec, Canada, to allow health care workers other than occupational therapists (OTs) to make bathroom adaptation recommendations for older adults. An integrated knowledge transfer process around Algo suggested an electronic version of this decision support system (electronic decision support system [e-DSS]) to be used by older adults and their caregivers in search of information and solutions for their autonomy and safety in the bathroom. Objective This study aims to (1) create an e-DSS for the self-selection of bathroom-assistive technology by community-dwelling older adults and their caregivers and (2) assess usability with lay users and experts to improve the design accordingly. Methods On the basis of a user-centered design approach, the process started with content identification for the prototype through 7 semistructured interviews with key informants of various backgrounds (health care providers, assistive technology providers, and community services) and 4 focus groups (2 with older adults and 2 with caregivers). A thematic content transcript analysis was carried out and used during the creation of the prototype. The prototype was refined iteratively using think-aloud and observation methods with a clinical expert (n=1), researchers (n=3), OTs (n=3), older adults (n=3), and caregivers (n=3), who provided information on the usability of the e-DSS. Results Overall, 4 themes served as the criteria for the prototype of the electronic Algo (Hygiene 2.0 [H2.0]): focus (safety, confidentiality, well-being, and autonomy), engage, facilitate (simplify, clarify, and illustrate), and access. For example, users first pay attention to the images (engage and illustrate) that can be used to depict safe postures (safety), illustrate questions embedded in the decision support tool (clarify and illustrate), and demonstrate the context of the use of assistive technology (safety and clarify). Conclusions The user-centered design of H2.0 allowed the cocreation of an e-DSS in the form of a website, in line with the needs of community-dwelling older adults and their caregivers seeking bathroom-assistive technology that enables personal hygiene. Each iteration improved usability and brought more insight into the users’ realities, tailoring the e-DSS to the implementation context.

Efficacy of Installation of Temporary Bathing Transfer Aids by Older Adults

“…While some guidance documents regarding grab bar locations do exist ( CSA Group, 2018 ; Ontario Building Code, 2013 ), these are not designed for a lay audience. Development of knowledge translation and guidance strategies for the installation of, and evaluation of the installation of grab bars, such as pamphlets with suggested locations and objective testing techniques, or selection algorithms ( Guay, Latulippe et al, 2020 ) may be helpful for improving installation success. The importance of clear and interpretable indicating tools can be extended to other assistive devices, such as brakes on walkers and wheelchairs.…”

Usability evaluation of mHealth apps for elderly individuals: a scoping review

“…Test participants were the target users of the apps, and they were all elderly. Some studies (n = 52) investigated the experiences of evaluators with mobile devices or their level of eHealth literacy to obtain the testing results for experts, intermediates, and novices [41,47,73]. The number of participants varied according to the stage and purpose of the evaluation.…”

“…Thirty-four studies presented objective performance The extent to which the user's physical, cognitive and emotional responses that result from the use of an app meet the user's needs and expectations and can be expressed as interest in the app, willingness to continue using it, and initiative to share it The operational flow of the app should be easy to remember, which can be embodied by reducing the demand on working memory through supporting recognition rather than recall 11 (18.0) 4 (13.3) 3 (15.8) . 94 data that came from observations of operational behavior, body movements and facial expressions and could be collected by performance metrics, behavioral observation logs, screen recordings, and eye tracking [47,72,80,81]. Eighty-five studies gathered the subjective opinions of the participants, which involved the users' experience with the app and their design preferences for each part of the interface and could be investigated by means of concurrent thinking aloud, retrospective thinking aloud, questionnaires, interviews, and feedback logs [37,41,52,73,82].…”

“…In the wellness management category, mHealth apps were used to improve the general health of older adults rather than focusing on specific diseases, which contained a variety of solutions, including fall prevention [41,42], fitness [43,44], lifestyle modification [45,46], medication adherence [47,48], health monitoring [40,49], nutrition [50,51], and cognitive stimulation [52,53]. In the category of disease management, mHealth apps played a role in different stages of disease development, such as disease screening during diagnosis [54], decision support during treatment [33], and self-management during rehabilitation [55,56].…”

Towards Robot-Assisted Therapy for Children With Autism—The Ontological Knowledge Models and Reinforcement Learning-Based Algorithms

“…Specialized assistance systems (e.g., vision, hearing, cognition, and communication) ( Bubar, 2020 ; Desideri et al, 2020 ; Kisanga and Kisanga, 2020 ; Nganji et al, 2011 ), as well as hardware and software resources that are software and hardware, that facilitate access to information technology (e.g., computers, mobile devices). Environmental modifications or so-called Assistive environments (e.g., automatic door openers, walk-in entrances, and accessible bathrooms) ( Guay et al, 2020 ; Martinez-Martin et al, 2020 ; Hu and Hu, 2021 ), which reduce or eliminate restrictions on participation, are also considered types of assistive technology.…”