Forskningsartikler

Abstract:
Introduction: We investigated the effectiveness of the multicomponent learning, innovation, volunteer support, empowerment (LIVE) intervention on caregiver burden and care time in dyads of home-dwelling people with dementia and caregivers.

Method: A 24 month, multicenter, stepped-wedge trial, randomized dyads to receive the 6-month LIVE intervention by municipal coordinators (May 2019 to December 2021). Primary outcomes were caregiver burden assessed by Relative Stress Scale (RSS) and informal care time spent on personal activities assessed by Resource Utilization in Dementia Personal Activities of Daily Living (RUD-PADL). Analyses used an intention-to-treat.

Results: Two hundred eighty dyads were enrolled. Caregivers during the intervention period reported lower levels of RSS of 0.7 points (standard deviation [SD]: 0.8) compared to the caregivers in the control period. Caregivers during the intervention period reported more time spent on PADL of 11.7 hours/month (SD: 8.7) compared to caregivers during the control period; both were not statistically significant (P > 0.05).

Discussion: The LIVE intervention did not reduce caregiver burden or care time.

Trial registration: ClinicalTrials.gov NCT04043364.

Highlights: Two hundred eighty persons with dementia and caregivers were included in a stepped wedge randomized controlled trial. We used the learning, innovation, volunteer support, empowerment (LIVE) intervention. The LIVE intervention did not reduce caregiver burden or informal care time. The LIVE intervention improved the caregiver’s clinical global impression of change. Positive change was most pronounced for coordinator personalized support.

Line Iden Berge, Renira Corinne Angeles, Marie Hidle Gedde, Stein Erik Fæø, Janne Mannseth, Maarja Vislapuu, Natalie Genevieve Søyland Puaschitz, Eirin Hillestad, Dag Aarsland, Wilco Peter Achterberg, Heather Allore, Clive Ballard, Fan Li, Geir Selbæk, Ipsit Vihang Vahia & Bettina Sandgate Husebo

Abstract:
Background:
This study forecasts total and cause-specific health expenditures in Norway to 2050 and quantifies the contribution of four key drivers—total population growth, population aging, changes in disease prevalence, and cost per case—on future health care spending.

Methods:
We forecast spending for 116 health conditions in Norway from 2022 to 2050, using historical and forecasted data of population growth, disease prevalence, gross domestic product (GDP), health spending, and residual factors. Our analysis included a reference scenario that forecasted disease-specific health spending; two alternative scenarios examining the effects of alternative unit cost developments; and a scenario examining the consequences of improved behavioral and metabolic risk factors.

Results:
Health spending increased from 10.6% (95% uncertainty interval, 10.2–11.1) of GDP in 2022 to 14.3% (13.0–15.7) in 2050 in the reference scenario. Among the top aggregate causes of Norwegian health spending in 2022, the spending for neurological disorders rose the most, from 1.7% (1.6–1.8) to 2.7% (2.3–3.1) of GDP, surpassing mental and substance use disorders which rose from 2.2% (2.1–2.3) to 2.4% (2.2–2.6) of GDP. Of the 116 single conditions analyzed, dementias accounted for the highest spending in 2022. This expenditure was forecasted to increase considerably from 1.1% (1.09–1.2) to 1.9% (1.6–2.2) of GDP by 2050, largely due to population aging. Spending on other old-age-related conditions like falls, stroke, and diabetes, was also forecasted to increase. Increased population, aging, and spending per case contributed to increased future spending. Reduced behavioral and metabolic risks were forecasted to increase the number of elderly persons and reduce age-specific disease prevalence but had little impact on forecasted health spending.

Conclusions:
Health spending growth was forecasted regardless of the scenario, and Norway needs to plan for this. However, policymakers can curb total spending growth, while maintaining health care quality and output, by ensuring more efficient allocation and effective use of resources. While the overall impact of behavioral and metabolic risk reductions on total healthcare spending was modest, reducing risk factors is needed if countries aim to achieve a healthier, longer-living population.

Jonas Minet Kinge, Henning Øien, Joseph L. Dieleman, Bjørn-Atle Reme, Ann Kristin Skrindo Knudsen, Geir Godager, Geir Selbæk, Jan C. Frich, Enis Barış, Christopher J. L. Murray & Stein Emil Vollset

Abstract:

Introduction: Understanding factors that influence care service use is crucial for developing preventive strategies to maintain independence among older adults. In this study, we aimed to identify distinct trajectory groups of municipal care service use among community-dwelling older adults to determine whether daily physical activity is associated with future care service use.

Methods: This prospective cohort study included 981 community-dwelling older adults from the HUNT4 Trondheim 70+ study. At baseline, physical activity was assessed over seven consecutive days using two accelerometers attached to the thigh and lower back. An activity type machine learning model was used to classify the physical activity types: walking, standing, cycling, running, sitting, and lying. Municipal care service use was retrieved monthly from medical records for 3 years. Using group-based trajectory modeling, we identified distinct trajectories of care service use. Multinomial regression models adjusted for age, sex, education level, dementia, and physical performance were used to evaluate the associations between daily physical activity at baseline and care service group belonging.

Results: We identified four distinct trajectory groups of municipal care service use, labeled steady low (72.7%), low increasing (9.0%), medium increasing (12.0%), and high increasing (6.3%). Daily time spent in total physical activity was not associated with trajectory group belonging when adjusted for age, sex, education level, dementia, and physical performance. However, more time spent walking, in bouts lasting longer than a minute, was associated with a reduced relative risk of belonging to the high increasing compared to the steady low group. Furthermore, age, physical performance, and dementia were all significantly associated with trajectory group belonging, and sex differences were observed. Compared to women, men had a reduced relative risk of belonging to the low increasing, medium increasing, or high increasing trajectory groups.

Conclusion: This study identified four distinct trajectories of municipal care service use among older adults over 3 years. Total daily physical activity was not associated with trajectories of care service use, but more time spent walking in longer bouts was independently associated with lower care service use, even when adjusted for the strong predictors of physical performance, dementia diagnosis, and age.

Astrid Ustad, Trine Holt Edwin, Kjerstin Næss Melsæter, Karen Sverdrup, Gro Gujord Tangen, Øystein Døhl, Pernille Thingstad, Beatrix Vereijken and Nina Skjæret-Maroni

Abstract:
Background: With the increasing number of older adults globally, there is a constant search for new ways to organize health care services. Digital health services are promising and may reduce workload and at the same time improve patient well-being. A certain level of eHealth literacy is needed to be able to use digital health services. However, knowledge of technology readiness in this target group of older adults is unclear.

Objective: The aim of this study was to understand the technology readiness level of a group of older adults who were provided home care services in order to address the present and future needs of this group in relation to the implementation of digital health care services.

Methods: This quantitative cross-sectional study included 149 older adults from Norway receiving home care services. The participants completed the Readiness and Enablement Index for Health Technology (READHY) instrument, assessments of well-being (World Health Organization-Five Well-Being Index [WHO-5]), and assessments of demographic and clinical variables (sex, age, education, living situation, comorbidity, use of digital devices, and use of IT). Cluster analyses were used to group the users according to their technology readiness.

Results: The mean participant age was 78.6 (SD 8.0) years, and 55.7% (83/149) were women. There was good consistency within the assumed READHY scales (Cronbach α=.61-.91). The participants were grouped into 4 clusters, which differed in terms of READHY scores, demographic variables, and the use of IT in daily life. Participants in cluster 1 (n=40) had the highest scores on the READHY scales, were younger, had a larger proportion of men, had higher education, and had better access to digital devices and IT. Participants in cluster 4 (n=16) scored the lowest on eHealth literacy knowledge. Participants in cluster 1 had relatively high levels of eHealth literacy knowledge and were expected to benefit from digital health services, while participants in cluster 4 had the lowest level of eHealth literacy and would not easily be able to start using digital health services.

Conclusions: The technology readiness level varied in our cohort of Norwegian participants receiving home care. Not all elderly people have the eHealth literacy to fully benefit from digital health services. Participants in cluster 4 (n=16) had the lowest scores in the eHealth Literacy Questionnaire scales in the READHY instrument and should be offered nondigital services or would need extensive management support. The demographic differences between the 4 clusters may inform stakeholders about which older people need the most training and support to take advantage of digital health care services.

Sverre Bergh, Jūratė Šaltytė Benth, Lisbeth Dyrendal Høgset, Britt Rydjord, Lars Kayser