Computer-enhanced practice: The benefits of computer-assisted assessment in applied clinical practice.

Young, Stephanie; Maddocks, Danika L. S.; Caemmerer, Jacqueline M.

doi:10.1037/pro0000449

Cited by 6 publications

(14 citation statements)

References 31 publications

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“…Therefore, most researches argued that when the experiment protocol is administered and instructed by assistance of a computer is less likely that neural activity and cognitive performance get adversely affected compared to the case that the experiment is controlled and instructed by interference of a human. Hence, replication of previous experiment protocols that were controlled by a human as examiner with a computer-assisted administration provides a high-quality data with removal of the human interference affects (Vrana and Vrana, 2017;Dror, 2020;Young et al, 2022). Moreover, computer assistance in the cognitive load assessment could make it feasible to conduct the experiment at places out of the clinics and laboratories.…”

Section: Locomotive and Cognitive Demandsmentioning

confidence: 99%

“…These places (e.g., participants' home or a local clinic) are accessible to the participants and individuals are comfortable to perform the experiment with assistance of a computer without interference of an examiner. As positive side effects of the computer-assisted experiment administration, high-quality and cost-effective patient care could be provided (Porrselvi, 2022;Young et al, 2022).…”

Section: Locomotive and Cognitive Demandsmentioning

confidence: 99%

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Experiment protocols for brain-body imaging of locomotion: A systematic review

2023

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IntroductionHuman locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings.MethodsThis paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols.ResultsThe findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments.DiscussionFinally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.

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Section: Locomotive and Cognitive Demandsmentioning

confidence: 99%

Section: Locomotive and Cognitive Demandsmentioning

confidence: 99%

Experiment protocols for brain-body imaging of locomotion: A systematic review

2023

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“…Well-validated computerized screeners have the potential to improve accuracy and overcome practical obstacles to cognitive screening in primary care settings. Automation of scoring and rote administration tasks can save time and reduce common examiner-related errors [ 25 , 26 ]. In addition to the time-saving benefits, many PCCs appreciate the interpretation guidelines and recommendations offered by computerized screening reports [ 27 ], which may help improve approaches to dementia care [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…Despite their advantages, computerized screeners are not yet commonly used in routine clinical practice [ 20 , 28 ], and there are several potential barriers to their adoption [ 25 ]. Some primary care clinics may worry about the acceptability of computerized screeners among their older patients, although research suggests that testing with computers is generally well tolerated by older adults [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

“…From a logistical standpoint, most computerized screeners currently administered in clinics are designed for a tablet, laptop, or desktop computer, which the primary care clinic must purchase, maintain, and securely store. The costs of devices and software, training, data security, and technical support issues associated with computerized screeners may present practical obstacles for some clinics [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

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Remote Cognitive Screening Of Healthy Older Adults for Primary Care With the MyCog Mobile App: Iterative Design and Usability Evaluation

Young¹,

Lattie²,

Berry³

et al. 2023

JMIR Form Res

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Background Annual cognitive screening in adults aged >65 years can improve early detection of cognitive impairment, yet less than half of all cases are identified in primary care. Time constraints in primary care settings present a major barrier to routine screening. A remote cognitive screener completed on a patient’s own smartphone before a visit has the potential to save primary care clinics time, encourage broader screening practices, and increase early detection of cognitive decline. Objective We described the iterative design and proposed the implementation of a remote cognitive screening app, MyCog Mobile, to be completed on a patient’s smartphone before an annual wellness visit. The research questions were as follows: What would motivate primary care clinicians and clinic administrators to implement a remote cognitive screening process? How might we design a remote cognitive screener to fit well with existing primary care workflows? What would motivate an older adult patient to complete a cognitive screener on a smartphone before a primary care visit? How might we optimize the user experience of completing a remote cognitive screener on a smartphone for older adults? Methods To address research questions 1 and 2, we conducted individual interviews with clinicians (n=5) and clinic administrators (n=3). We also collaborated with clinic administrators to create user journey maps of their existing and proposed MyCog Mobile workflows. To address research questions 3 and 4, we conducted individual semistructured interviews with cognitively healthy older adults (n=5) and solicited feedback from a community stakeholder panel (n=11). We also tested and refined high-fidelity prototypes of the MyCog Mobile app with the older adult interview participants, who rated the usability on the Simplified System Usability Scale and After-Scenario Questionnaire. Results Clinicians and clinic administrators were motivated to adopt a remote cognitive screening process if it saved time in their workflows. Findings from interviews and user journey mapping informed the proposed implementation and core functionality of MyCog Mobile. Older adult participants were motivated to complete cognitive screeners to ensure that they were cognitively healthy and saw additional benefits to remote screening, such as saving time during their visit and privacy. Older adults also identified potential challenges to remote smartphone screening, which informed the user experience design of the MyCog Mobile app. The average rating across prototype versions was 91 (SD 5.18) on the Simplified System Usability Scale and 6.13 (SD 8.40) on the After-Scenario Questionnaire, indicating above-average usability. Conclusions Through an iterative, human-centered design process, we developed a viable remote cognitive screening app and proposed an implementation strategy for primary care settings that was optimized for multiple stakeholders. The next steps include validating the cognitive screener in clinical and healthy populations and piloting the finalized app in a community primary care clinic.

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