Hikaru Kondo

BACKGROUND: Japan faces a shortage of care workers due to its rapidly aging population. Although nursing care technologies can reduce caregiver burden and improve care quality, their long-term feasibility remains unclear. We investigated the implementation of these technologies and associated challenges in long-term care facilities. METHODS: A cross-sectional questionnaire survey of all long-term care facilities in Aichi Prefecture, Japan (total population, approximately 7.5 million), was conducted between February and March 2024. RESULTS: Of 2,514 eligible facilities, 497 participated (a 19.8% response rate), and 477 were included in the final analysis. The overall implementation rate was 22.0%. Implementing facilities reported a lack of information on available devices (55.2%) and challenges with subsidy application processes (52.4%). Among non-implementing facilities, 63.2% expressed a willingness to adopt devices, primarily to reduce staff workload (95.7%). Key barriers included financial constraints (91.1%), cost-effectiveness concerns (62.1%), and limited information (55.7%). The results indicate significant interest in nursing-care technologies and identify key implementation difficulties and adoption barriers. CONCLUSION: Improving information accessibility and simplifying subsidy-application procedures could facilitate the adoption of nursing care technologies. These results may also benefit countries facing similar demographic challenges.

PURPOSE: Adjusting the tilt and recline angles of a wheelchair is recommended as one of the approaches for preventing pressure injuries associated with mechanical loading in wheelchair users. However, maintaining a fixed inclination may increase pressure on other body areas, raising concerns about the time-dependent risk of ulcers. To address this issue, we proposed an electrically powered wheelchair equipped with a mechanism that continuously changes the tilt angle, similar to the motion of a rocking chair, and developed a prototype as a proof of concept. This cross‑sectional study aimed to evaluate the effectiveness of the prototype wheelchair in reducing and redistributing interface pressure. MATERIALS AND METHODS: Eight healthy participants were enrolled in this study. The electrically controlled tilt angle was programmed to cycle from 0° to 30° in 50 s. Reclining angles were set at 0°, 10°, 20°, and 30°. The pressure at the head, back, and buttocks was recorded. RESULTS: The peak pressure in these areas changed dynamically with tilt variation; increasing the tilt angle raised the peak pressure at the head and back while reducing it at the buttocks. Increasing the reclining angle amplified these changes in the head and buttocks but had no effect on the back. CONCLUSION: Our findings suggest that continuous tilt variation may reduce prolonged exposure to excessive pressure, potentially reducing the risk of ulcers in the buttocks associated with mechanical loading in wheelchair users.

BACKGROUND: Although smart insoles have emerged as promising tools for long-term gait analysis, these devices face a trade-off between wearability (where sensor modules are fully accommodated within a compact insole) and data quality (where sensor modules cannot be accommodated within the insole). Integrating an inertial measurement unit (IMU) with pressure sensors and fully embedding all modules may resolve this trade-off; however, the reliability and validity of such a smart insole remain unverified. RESEARCH QUESTION: Can a smart insole with an IMU and pressure sensors provide reliable and valid spatiotemporal gait parameters comparable to an instrumented walkway? METHODS: Twenty-six healthy volunteers (mean age 26.0 ± 5.6 years) performed walking tasks while wearing the smart insole. Reliability was assessed by comparing spatiotemporal parameters between two sessions of walking trials. Validity was evaluated against a gold-standard instrumented walkway positioned along the path. Data were analyzed using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. RESULTS: ICC values indicated good to excellent reliability (0.93-0.95) and validity against the instrumented walkway (0.70-0.99). Although Bland-Altman analysis revealed systematic differences, these deviations were acceptable (<4% of mean difference), with 95% limits of agreement ratios under 8% for all parameters. SIGNIFICANCE: The smart insole incorporating IMU and pressure sensors, characterized by a highly wearable and cable-free design, provides reliable and valid spatiotemporal gait parameters. Future studies involving broader populations and real-world settings are warranted to further validate its applicability.

BACKGROUND: Gait-a frequently performed activity of daily living-is thought to reflect multiple dimensions of an individual's physical and cognitive status. Individuals with frailty or mild cognitive impairment (MCI) show decreased gait speed. However, previous studies have not simultaneously considered both statuses, although they frequently co-occur and may act as confounders. The direct association between frailty and gait is well-understood. In contrast, the association between cognitive decline-independent of physical function-and decreased gait speed, as well as the relationship among these three factors (frailty, cognitive decline, and gait speed), is not fully understood. METHODS: This study examined the effect of MCI on gait speed after accounting for frailty. Older individuals were categorized as (1) frailty with MCI, (2) frailty without MCI, (3) pre-frailty with MCI, (4) pre-frailty without MCI, (5) non-frailty with MCI, and (6) non-frailty without MCI. Frailty was assessed using the Kihon checklist and MCI using the Montreal Cognitive Assessment. Participants completed a 10-m walk test under two conditions: comfortable walking and fast walking. Two types of analyses were conducted: mediation analysis and two-way analysis of covariance (ANCOVA). RESULTS: Mediation analysis supported independent relationships between frailty and MCI status and gait speed, suggesting a direct association between MCI and gait speed, even when accounting for frailty. In addition, two-way analysis of covariance indicated significant main effects of both frailty and MCI on gait speed, with no significant interaction between them under the two walking conditions. CONCLUSIONS: These findings suggest that the observed association between MCI and gait speed is largely independent from frailty status, providing additional evidence supporting the association between cognitive function and gait performance.