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Sensory impairment is common in older age and is associated with intra- and interpersonal struggles, however, treatment efforts may be hampered by functional difficulties or unwillingness to seek face-to-face mental health services. The current study examined the efficacy of an online psychological intervention for older adults with sensory loss and their spouses in Denmark, using a two-arm, parallel-group, randomized controlled trial study design with a wait-list control group. The intervention consisted of four digital, sequential modules that contained psychoeducation and Acceptance and Commitment Therapy inspired therapeutic activities. Individuals (N = 662) completed online surveys (using the SurveyXact platform) at baseline, 6 weeks, and 10 weeks post-baseline, in terms of well-being, relationship satisfaction, and depressive symptoms. The data were analyzed in SAS, version 9.4, using multilevel modeling to account for non-independence of data (nesting within participant and within couple), specifying an alpha level of 0.05. Inconsistent with the hypotheses, we found that the intervention group reported poorer well-being at 6 weeks, compared to the control group, and we found no effect in terms of relationship satisfaction or depressive symptoms. As the first study of an online intervention for older adults with sensory loss and their spouses, the study highlights the need for simple login procedures, and we speculate whether a user customizable format may be better, features that might be useful for any digital intervention aimed at elderly populations. These features may be of particular importance in implementing digital interventions into standard healthcare practices.
Sensory impairment is common in older age and is associated with intra- and interpersonal struggles, however, treatment efforts may be hampered by functional difficulties or unwillingness to seek face-to-face mental health services. The current study examined the efficacy of an online psychological intervention for older adults with sensory loss and their spouses in Denmark, using a two-arm, parallel-group, randomized controlled trial study design with a wait-list control group. The intervention consisted of four digital, sequential modules that contained psychoeducation and Acceptance and Commitment Therapy inspired therapeutic activities. Individuals (N = 662) completed online surveys (using the SurveyXact platform) at baseline, 6 weeks, and 10 weeks post-baseline, in terms of well-being, relationship satisfaction, and depressive symptoms. The data were analyzed in SAS, version 9.4, using multilevel modeling to account for non-independence of data (nesting within participant and within couple), specifying an alpha level of 0.05. Inconsistent with the hypotheses, we found that the intervention group reported poorer well-being at 6 weeks, compared to the control group, and we found no effect in terms of relationship satisfaction or depressive symptoms. As the first study of an online intervention for older adults with sensory loss and their spouses, the study highlights the need for simple login procedures, and we speculate whether a user customizable format may be better, features that might be useful for any digital intervention aimed at elderly populations. These features may be of particular importance in implementing digital interventions into standard healthcare practices.
Background. Physical activity (PA) is a recognized boon for older adults, enhancing their overall well-being and mitigating health risks. Nevertheless, to encourage active lifestyles in this demographic, it is vital to understand the factors influencing PA. Conventional approaches predominantly rely on supervised cross-sectional evaluations, presuming both the stability of PA determinants over time and their isolated components. However, the complex nature of real-life dynamics often involves temporal variability in individual-level determinants. Digital phenotyping (DP), employing data recruited from personal digital devices, enables the continuous, unsupervised and real-time quantification of an individual's behavior within their natural context. This approach offers more ecological and dynamic assessments, revolutionizing our understanding of the intricacies underlying individual PA patterns in their environmental context. Objective. This paper aims to design a robust research protocol for the DP of PA behavior among healthy community-dwelling older adults aged 65 and above by employing a novel measurement approach. Methods. Observational data will be collected over a two-week period to assess various functions combining both cross-sectional and longitudinal data collection methods. Patterns of PA behavior and factors affecting PA outcomes will be detected in order to identify digital phenotypes related to PA. The measurements are based on the Behavior Change Wheel and include self-reporting and clinical assessments for cross-sectional data collection and ecological momentary assessment as well as time series collection for longitudinal data. The statistical analysis involves machine learning which will handle data complexity. Unsupervised learning will be used to uncover patterns, and supervised learning to identify variables. The analysis will be conducted in RStudio (v3.6.3) with significance set at 0.05. Discussion. A novel approach to understanding older adults' PA behavior will be used in this study. Challenges include varying technology adoption, usability, and unproven validity of health tech. Ethical considerations, representativeness, participant engagement, and machine learning expertise are also key aspects of the study's success. This study offers promise in bridging traditional and dynamic assessment methods for older adults' PA behavior to promote active lifestyles. Trial registration: Clinical Trials.gov: NCT06094374
A healthy lifestyle can be an important prerequisite to prevent or at least delay the onset of dementia. However, the large number of physically inactive adults underscores the need for developing and evaluating intervention approaches aimed at improving adherence to a physically active lifestyle. In this regard, hybrid physical training, which usually combines center- and home-based physical exercise sessions and has proven successful in rehabilitative settings, could offer a promising approach to preserving cognitive health in the aging population. Despite its potential, research in this area is limited as hybrid physical training interventions have been underused in promoting healthy cognitive aging. Furthermore, the absence of a universally accepted definition or a classification framework for hybrid physical training interventions poses a challenge to future progress in this direction. To address this gap, this article informs the reader about hybrid physical training by providing a definition and classification approach of different types, discussing their specific advantages and disadvantages, and offering recommendations for future research. Specifically, we focus on applying digital technologies to deliver home-based exercises, as their use holds significant potential for reaching underserved and marginalized groups, such as older adults with mobility impairments living in rural areas.
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