Associations Between Mobile Health Technology use and Self-rated Quality of Life: A Cross-sectional Study on Older Adults with Cognitive Impairment

Barriers and facilitators to health technology adoption by older adults with chronic diseases: an integrative systematic review

BACKGROUND

In recent years, healthcare systems have progressively adopted several technologies enhancing access to healthcare for older adults and support the delivery of efficient and effective care for this specific population. These technologies include both assistive technologies designed to maintain or improve the independence, social participation and functionality of older people at home, as well as health information technology developed to manage long-term conditions. Examples of such technologies include telehealth, wearable devices and mobile health. However, despite the great promise that health technology holds for promoting independent living among older people, its actual implementation remains challenging.

METHODS

This study aimed to conduct an integrative systematic review of the research evidence on the factors that facilitate or hinder the adoption of different types of technology by older individuals with chronic diseases. For this purpose, four electronic databases (PsycArticles, Scopus, Web of Science and PubMed) were queried to search for indexed published studies. The methodological quality of the selected papers has been assessed using the Mixed Methods Appraisal Tool (MMAT).

RESULTS

Twenty-nine articles were selected, including 6.213 adults aged 60 or older. The studies have been synthesised considering the types of technological interventions and chronic diseases, as well as the main barriers and facilitators in technology acceptance. The results revealed that the majority of the selected articles focused on comorbid conditions and the utilisation of telemedicine tools. With regard to hindering and facilitating factors, five main domains were identified: demographic and socioeconomic, health-related, dispositional, technology-related and social factors.

CONCLUSION

The study results have practical implications not only for technology developers but also for all the social actors involved in the design and implementation of healthcare technologies, including formal and informal caregivers and policy stakeholders. These actors could use this work to enhance their understanding of the utilisation of technology by the ageing population. This review emphasises the factors that facilitate technology adoption and identifies barriers that impede it, with the ultimate goal of promoting health and independent living.

Pilot RCT examining feasibility and disability outcomes of a mobile health platform for strategy training in inpatient stroke rehabilitation (iADAPT)

BACKGROUND

Strategy training is an intervention that may reduce disability when delivered in inpatient rehabilitation following stroke. However, shorter lengths of stay and challenges with continuity of care following discharge results in difficulties in achieving adequate intervention dosage and carryover of training.

OBJECTIVE

We examined whether strategy training using a mobile health platform (iADAPT) is feasible during inpatient stroke rehabilitation and following discharge.

METHODS

In this RCT, participants were randomized to receive strategy training using either the iADAPT application (n = 16) or a workbook (n = 15). Participants in both groups received 7 in-person sessions during inpatient rehabilitation and 3 remote sessions following discharge. We calculated descriptive statistics to examine acceptance, attendance, and adherence, and within-group effect sizes on satisfaction and disability.

RESULTS

Participants in the iADAPT group attended fewer total intervention sessions (n = 5.5, workbook n = 9.0) but attempted a similar number of goals (n = 7.6, workbook n = 8.2). Both groups reported similar satisfaction with in-person intervention (Treatment Expectancy: iADAPT d = 0.60, workbook d = 0.47; Patient Provider Connection: iADAPT d = 0.18, workbook d = 0.31), but the mobile health group reported greater satisfaction with remote intervention (Treatment Expectancy: iADAPT d = -0.91, workbook d = -0.97; Patient Provider Connection: iADAPT d = 0.85, workbook d = -1.80). .

CONCLUSIONS

Considering these promising feasibility metrics and the benefits of mobile health, it is worth continuing to explore the efficacy of strategy training using a mobile health platform.

Associations of Demographic, Socioeconomic, and Cognitive Characteristics With Mobile Health Access: MESA (Multi-Ethnic Study of Atherosclerosis)

Background

Mobile health (mHealth) has an emerging role in the prevention of cardiovascular disease. This study evaluated possible inequities in mHealth access in older adults.

Methods and Results

mHealth access was assessed from 2019 to 2020 in MESA (Multi‐Ethnic Study of Atherosclerosis) telephone surveys of 2796 participants aged 62 to 102 years. A multivariable logistic regression model adjusted for general health status assessed associations of mHealth access measures with relevant demographic, socioeconomic, and cognitive characteristics. There were lower odds of all access measures with older age (odds ratios [ORs], 0.37–0.59 per 10 years) and annual income <$50 000 (versus ≥$50 000 ORs, 0.55–0.62), and higher odds with higher Cognitive Abilities Screening Instrument Score (ORs, 1.22–1.29 per 5 points). Men (versus women) had higher odds of internet access (OR, 1.32 [95% CI,1.05–1.66]) and computing device ownership (OR, 1.31 [95% CI, 1.05–1.63]) but lower fitness tracker ownership odds (OR, 0.70 [95% CI, 0.49–0.89]). For internet access and computing device ownership, we saw lower odds for Hispanic participants (versus White participants OR, 0.61 [95% CI, 0.44–0.85]; OR, 0.69 [95% CI, 0.50–0.95]) and less than a high school education (versus bachelor's degree or higher OR, 0.27 [95% CI, 0.18–0.40]; OR, 0.32 [95% CI, 0.28–0.62]). For internet access, lower odds were seen for Black participants (versus White participants OR, 0.64 [95% CI, 0.47–0.86]) and other health insurance (versus health maintenance organization/private OR, 0.59 [95% CI, 0.47–0.74]). Chinese participants (versus White participants) had lower internet access odds (OR, 0.63 [95% CI, 0.44–0.91]) but higher computing device ownership odds (OR, 1.87 [95% CI, 1.28–2.77]).

Conclusions

Among older‐age adults, mHealth access varied by major demographic, socioeconomic, and cognitive characteristics, suggesting a digital divide. Novel mHealth interventions should consider individual access barriers.

Registration

URL: https://www.clinicaltrials.gov/; Unique identifier: NCT00005487.

A randomized controlled trial of an mHealth application with nursing interaction to promote quality of life among community-dwelling older adults

SIGNIFICANCE

Using mHealth apps alone at home without the support of healthcare experts could mean that older adults might not fully utilize the functions of the apps, recognize their benefits, and sustain their use. Incorporating an integrated health-social partnership model to support the app usage when further help is needed by the older adults might maximize the apps' benefits in the long term.

OBJECTIVES

This study aimed to examine the benefits of adding nursing interaction supported by a health-social partnership model in the use of mHealth, and the sustained beneficial effects on psychological outcomes, including quality of life, self-efficacy, and depression, among older adults after the completion of the program.

METHODS

A three-arm, randomized controlled trial design was adopted. Community-dwelling older adults with chronic pain, hypertension, or diabetes, were randomly assigned to either the mHealth, mHealth with interactivity, or control group. Subjects in both the mHealth and the mHealth with interactivity groups received the mHealth application. In addition, the mHealth with interactivity group received support from a nurse case manager, who was supported by a health-social partnership team. mHealth apps and services from a nurse case manager were not provided to the control group. The primary outcome measure was quality of life, and secondary outcomes were self-efficacy and depression. Data were collected at pre-intervention (T1), post-intervention (T2), and at 3 months post-intervention to measure the sustained effect of the program.

RESULTS

There were 74 mHealth+I, 71 mHealth, and 76 control group subjects enrolled in the program. No statistically significant between-group, within-group, and interaction effects between group and time in both physical component summary (PCS) and mental component summary (MCS) scores were found among the three groups. The mHealth group showed an improvement in PCS and depression scores from T1 to T2, sustained at T3; while the mHealth+I group demonstrated improved self-efficacy from T1 to T2, with a decrease at T3.

CONCLUSION

Adding nurse-directed telephone calls may be of little to no benefit at all in the long term. Future studies may consider a longer intervention period to build and sustain quality of life and self-efficacy levels among community-dwelling older adults.

CLINICAL TRIAL REGISTRATION

www.ClinicalTrials.gov, identifier: NCT03878212.

Allicin, an Antioxidant and Neuroprotective Agent, Ameliorates Cognitive Impairment

Allicin (diallylthiosulfinate) is a defense molecule produced by cellular contents of garlic (Allium sativum L.). On tissue damage, the non-proteinogenic amino acid alliin (S-allylcysteine sulfoxide) is converted to allicin in an enzyme-mediated process catalysed by alliinase. Allicin is hydrophobic in nature, can efficiently cross the cellular membranes and behaves as a reactive sulfur species (RSS) inside the cells. It is physiologically active molecule with the ability to oxidise the thiol groups of glutathione and between cysteine residues in proteins. Allicin has shown anticancer, antimicrobial, antioxidant properties and also serves as an efficient therapeutic agent against cardiovascular diseases. In this context, the present review describes allicin as an antioxidant, and neuroprotective molecule that can ameliorate the cognitive abilities in case of neurodegenerative and neuropsychological disorders. As an antioxidant, allicin fights the reactive oxygen species (ROS) by downregulation of NOX (NADPH oxidizing) enzymes, it can directly interact to reduce the cellular levels of different types of ROS produced by a variety of peroxidases. Most of the neuroprotective actions of allicin are mediated via redox-dependent pathways. Allicin inhibits neuroinflammation by suppressing the ROS production, inhibition of TLR4/MyD88/NF-κB, P38 and JNK pathways. As an inhibitor of cholinesterase and (AChE) and butyrylcholinesterase (BuChE) it can be applied to manage the Alzheimer's disease, helps to maintain the balance of neurotransmitters in case of autism spectrum disorder (ASD) and attention deficit hyperactive syndrome (ADHD). In case of acute traumatic spinal cord injury (SCI) allicin protects neuron damage by regulating inflammation, apoptosis and promoting the expression levels of Nrf2 (nuclear factor erythroid 2-related factor 2). Metal induced neurodegeneration can also be attenuated and cognitive abilities of patients suffering from neurological diseases can be ameliorates by allicin administration.