An eHealth Intervention to Increase Physical Activity and Healthy Eating in Older Adult Cancer Survivors: Summative Evaluation Results

Development Trends and Prospects of Technology-Based Solutions for Health Challenges in Aging Over the Past 25 Years: Bibliometric Analysis

BACKGROUND

As the global population ages, we witness a broad scientific and technological revolution tailored to meet the health challenges of older adults. Over the past 25 years, technological innovations, ranging from advanced medical devices to user-friendly mobile apps, are transforming the way we address these challenges, offering new avenues to enhance the quality of life and well-being of the aging demographic.

OBJECTIVE

This study aimed to systematically review the development trends in technology for managing and caring for the health of older adults over the past 25 years and to project future development prospects.

METHODS

We conducted a comprehensive bibliometric analysis of literatures related to technology-based solutions for health challenges in aging, published up to March 18, 2024. The search was performed using the Web of Science Core Collection, covering a span from 1999 to 2024. Our search strategy was designed to capture a broad spectrum of terms associated with aging, health challenges specific to older adults, and technological interventions.

RESULTS

A total of 1133 publications were found in the Web of Science Core Collection. The publication trend over these 25 years showed a gradual but fluctuating increase. The United States was the most productive country and participated in international collaboration most frequently. The predominant keywords identified through this analysis included "dementia," "telemedicine," "older-adults," "telehealth," and "care." The keywords with citation bursts included "telemedicine" and "digital health."

CONCLUSIONS

The scientific and technological revolution has significantly improved older adult health management, particularly in chronic disease monitoring, mobility, and social connectivity. The momentum for innovation continues to build, with future research likely to focus on predictive analytics and personalized health care solutions, further enhancing older adults' independence and quality of life.

Assessing the Effectiveness of eHealth Interventions to Manage Multiple Lifestyle Risk Behaviors Among Older Adults: Systematic Review and Meta-Analysis

BACKGROUND

Developing adverse lifestyle behaviors increases the risk of a variety of chronic age-related diseases, including cardiovascular disease, obesity, and Alzheimer disease. There is limited evidence regarding the effectiveness of eHealth-based multiple health behavior change (MHBC) interventions to manage lifestyle risk behaviors.

OBJECTIVE

The purpose of this systematic evaluation was to assess the effectiveness of eHealth MHBC interventions in changing ≥2 major lifestyle risk behaviors in people aged ≥50 years.

METHODS

The literature search was conducted in 6 electronic databases-PubMed, Embase, Web of Science, Scopus, Cochrane Library, and SPORTDiscus-from inception to May 1, 2024. Eligible studies were randomized controlled trials of eHealth interventions targeting ≥2 of 6 behaviors of interest: alcohol use, smoking, diet, physical activity (PA), sedentary behavior, and sleep.

RESULTS

A total of 34 articles with 35 studies were included. eHealth-based MHBC interventions significantly increased smoking cessation rates (odds ratio 2.09, 95% CI 1.62-2.70; P<.001), fruit intake (standardized mean difference [SMD] 0.18, 95% CI 0.04-0.32; P=.01), vegetable intake (SMD 0.17, 95% CI 0.05-0.28; P=.003), self-reported total PA (SMD 0.22, 95% CI 0.02-0.43; P=.03), and objectively measured moderate to vigorous PA (SMD 0.25, 95% CI 0.09-0.41; P=.002); in addition, the interventions decreased fat intake (SMD -0.23, 95% CI -0.33 to -0.13; P<.001). No effects were observed for alcohol use, sedentary behavior, or sleep. A sensitivity analysis was conducted to test the robustness of the pooled results. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework.

CONCLUSIONS

eHealth-based MHBC interventions may be a promising strategy to increase PA, improve diet, and reduce smoking among older adults. However, the effect sizes were small. Further high-quality, older adult-oriented research is needed to develop eHealth interventions that can change multiple behaviors.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42023444418; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023444418.

Cook and Move for Your Life, an eHealth intervention for women with breast cancer

We tested the feasibility and preliminary efficacy of an online diet and physical activity program for women with early-stage breast cancer who had completed surgery, chemotherapy, and radiation therapy (ongoing endocrine therapy allowed). Participants with low fruit and vegetable (F/V) consumption and/or low moderate-to-vigorous physical activity (MVPA) levels were randomized to one of two doses - low (one Zoom group session) or high (12 Zoom group sessions) - of an online lifestyle program with the goal of improving F/V intake and MVPA. All participants received eHealth communications (text messages, study website access), a Fitbit, and a WiFi-enabled scale. Primary objectives evaluated feasibility. Secondary objectives compared the 6-month change in F/V intake and MVPA between the two dose groups. Seventy-four women (mean age = 58.4 years; 87% non-Hispanic White; mean time since diagnosis = 4.6 years) were accrued. Among women in the low dose group, 94% attended the single session; among women in the high dose group, 84% attended at least 8 of the 12 sessions. Retention at 6 months was 93%. High relative to low dose participants consumed 1.5 more servings/day of F/V at 6 months (P = 0.007) but MVPA levels did not differ between groups. We successfully implemented an online lifestyle program for early-stage breast cancer survivors. The high dose intervention demonstrated preliminary efficacy in improving F/V consumption in early-stage breast cancer survivors. Future trials can test the intervention in a larger and more diverse population of breast cancer survivors.

The effectiveness of E-health interventions promoting physical activity in cancer survivors: a systematic review and meta-analysis of randomized controlled trials

PURPOSE

This systematic review and meta-analysis aimed to identify whether E-health interventions effectively improve physical activity (PA) in cancer survivors.

METHODS

PubMed, Web of Science, and Cochrane Library databases were searched from inception to October 21, 2023. Randomized controlled trials reporting the effect of E-health interventions on PA among cancer survivors were included. Random-effect models were used to calculate standardized mean differences (SMD) and the 95% confidence interval (CI).

RESULTS

In total, 15 trials with 2,291 cancer survivors were included in this meta-analysis. The results showed that E-health interventions improved moderate to vigorous physical activity (MVPA) among cancer survivors (SMD = 0.26, 95% CI 0.08, 0.43, N = 8, p < 0.001, I2 = 37%), as well as moderate physical activity (MPA) (SMD = 0.22, 95% CI 0.05, 0.38, N = 9, p < 0.001, I2 = 28%) and vigorous physical activity (VPA) (SMD = 0.34, 95% CI 0.15, 0.54, N = 6, p < 0.001, I2 = 11%).

CONCLUSION

E-health interventions are effective at promoting PA among cancer survivors. As current research primarily focuses on immediate post-intervention measurements with limited follow-up data, further investigation is required to explore the long-term effects of E-health interventions on PA.

What is the effect of a brief intervention to promote physical activity when delivered in a health care setting? A systematic review

ISSUE ADDRESSED

What are the effects of a brief intervention to promote physical activity (PA) delivered in a health care setting other than primary care?

METHODS

MEDLINE, EMBASE, CINAHL and PsycINFO were used to identify randomised controlled trials which evaluated the effect of brief interventions to increase PA, delivered in a health care setting. Review outcomes included subjectively or objectively measured PA, adherence to prescribed interventions, adverse events, health-related quality of life, self-efficacy and stage of change in relation to PA. Where possible, clinically homogenous studies were combined in a meta-analysis.

RESULTS

Twenty-five eligible papers were included. Brief counselling interventions were associated with increased PA compared to control, for both self-reported PA (mean difference 34 minutes/week, 95% confidence intervals [95% CI] 9-60 minutes), and pedometer (MD 1541 steps/day, 95% CI 433-2649) at medium term follow up.

CONCLUSION

Our findings suggest that some brief interventions to increase PA, delivered in the health care setting, are effective at increasing PA in the medium term. There is limited evidence for the long-term efficacy of such interventions. The wide variation in types of interventions makes it difficult to determine which intervention features optimize outcomes. SO WHAT?: Brief counselling interventions delivered in a health care setting may support improved PA. Clinicians working in health care settings should consider the implementation of brief interventions to increase PA in vulnerable patient groups, including older adults and those with chronic illness.

Telerehabilitation and Monitoring Physical Activity in Patient with Breast Cancer: Systematic Review

Background

Timely rehabilitation in patients with Breast Cancer (BC) has a great impact on improving their physical and mental conditions. Thus, the appropriate follow-up method is essential especially during the Covid-19 pandemic. The aim of this study was to review the different technology-assisted interventions for improving physical activity in BC patients.

Materials And Methods

In this systematic review, the original studies were extracted from the beginning of indexing in databases including PubMed, Scopus, Google Scholar, and Web of Science until 2019. Finally, 45 papers were included in this study based on the inclusion criteria for before the Covid-19 pandemic and 3 articles extracted for the Covid-19 period.

Results

The most widely used technologies for BC patients were in the United States (46.67%). Telephone, mobile application, and web with 28.89%, 15.56%, and 8.89% frequencies were the most common technologies, respectively. Although the majority of the participants were satisfied with the intervention method, in some cases, the patients were unsatisfied due to the complexity of the technology. These technologies were used for various purposes, such as physical activity and functions, control of pain severity, fitness, quality of life, diet behavior, fatigue, muscle strength, cardio-respiratory capacity, as well as arm and shoulder exercises.

Conclusions

In conclusion, virtual communication can improve the health of BC patients and also increases patients' desire and hope to continue treatment. It is worth noting that in the Covid-19 pandemic, with the strengthening of virtual communication infrastructure, more attention was paid to BC patients due to their sensitive conditions.

One view of the next decade of research on behavioral and biobehavioral approaches to cancer prevention and control: intervention optimization

As a new decade begins, we propose that the time is right to reexamine current methods and procedures and look for opportunities to accelerate progress in cancer prevention and control. In this article we offer our view of the next decade of research on behavioral and biobehavioral interventions for cancer prevention and control. We begin by discussing and questioning several implicit conventions. We then briefly introduce an alternative research framework: the multiphase optimization strategy (MOST). MOST, a principled framework for intervention development, optimization, and evaluation, stresses not only intervention effectiveness, but also intervention affordability, scalability, and efficiency. We review some current limitations of MOST along with future directions for methodological work in this area, and suggest some changes in the scientific environment we believe would permit wider adoption of intervention optimization. We propose that wider adoption of intervention optimization would have a positive impact on development and successful implementation of interventions for cancer prevention and control and on intervention science more broadly, including accumulation of a coherent base of knowledge about what works and what does not; establishment of an empirical basis for adaptation of interventions to different settings with different levels and types of resources; and, in the long run, acceleration of progress from Stage 0 to Stage V in the National Institutes of Health Model of Stages of Intervention Development.

"You're Going to Have to Think a Little Bit Different" Barriers and Facilitators to Using mHealth to Increase Physical Activity among Older, Rural Cancer Survivors

Wearable activity trackers (WATs) hold great promise in increasing physical activity among older cancer survivors. However, older cancer survivors who reside in rural regions are at increased risk of being digitally marginalized. The goal of this study was to learn about WATs adoption motivation and needs of rural older cancer survivors who live in New Mexico, one of the most rural states with the lowest broadband Internet connectivity in the United States. We conducted six key informant interviews and recruited 31 older cancer survivors from rural counties statewide who participated in interviews and focus groups. Our results show great interest in using WATs as part of an intervention to alleviate barriers associated with the digital divide. Participants were offered diverse modalities to support them in adoption of the trackers. These results will be used to inform future interventions and policies focusing on increasing physical activity in older cancer survivors who reside in rural communities.

Digitally Supported Dietary Protein Counseling Changes Dietary Protein Intake, Sources and Distribution in Community-Dwelling Older Adults

Digitally supported dietary counselling may be helpful in increasing the protein intake in combined exercise and nutritional interventions in community-dwelling older adults. To study the effect of this approach, 212 older adults (72.2 ± 6.3 years) were randomised in three groups: control, exercise, or exercise plus dietary counselling. The dietary counselling during the 6-month intervention was a blended approach of face-to-face contacts and videoconferencing, and it was discontinued for a 6-month follow-up. Dietary protein intake, sources, product groups, resulting amino acid intake, and intake per eating occasion were assessed by a 3-day dietary record. The dietary counselling group was able to increase the protein intake by 32% at 6 months, and the intake remained 16% increased at 12 months. Protein intake mainly consisted of animal protein sources: dairy products, followed by fish and meat. This resulted in significantly more intake of essential amino acids, including leucine. The protein intake was distributed evenly over the day, resulting in more meals that reached the protein and leucine targets. Digitally supported dietary counselling was effective in increasing protein intake both per meal and per day in a lifestyle intervention in community-dwelling older adults. This was predominantly achieved by consuming more animal protein sources, particularly dairy products, and especially during breakfast and lunch.

eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study

Background

eHealth technologies have been found to facilitate health-promoting practices among cancer survivors with BMI in overweight or obese categories; however, little is known about their engagement with eHealth to promote weight management and facilitate patient-clinician communication.

Objective

The objective of this study was to determine whether eHealth use was associated with sociodemographic characteristics, as well as medical history and experiences (ie, patient-related factors) among cancer survivors with BMI in overweight or obese categories.

Methods

Data were analyzed from a nationally representative cross-sectional survey (National Cancer Institute’s Health Information National Trends Survey). Latent class analysis was used to derive distinct classes among cancer survivors based on sociodemographic characteristics, medical attributes, and medical experiences. Logistic regression was used to examine whether class membership was associated with different eHealth practices.

Results

Three distinct classes of cancer survivors with BMI in overweight or obese categories emerged: younger with no comorbidities, younger with comorbidities, and older with comorbidities. Compared to the other classes, the younger with comorbidities class had the highest probability of identifying as female (73%) and Hispanic (46%) and feeling that clinicians did not address their concerns (75%). The older with comorbidities class was 6.5 times more likely than the younger with comorbidities class to share eHealth data with a clinician (odds ratio [OR] 6.53, 95% CI 1.08-39.43). In contrast, the younger with no comorbidities class had a higher likelihood of using a computer to look for health information (OR 1.93, 95% CI 1.10-3.38), using an electronic device to track progress toward a health-related goal (OR 2.02, 95% CI 1.08-3.79), and using the internet to watch health-related YouTube videos (OR 2.70, 95% CI 1.52-4.81) than the older with comorbidities class.

Conclusions

Class membership was associated with different patterns of eHealth engagement, indicating the importance of tailored digital strategies for delivering effective care. Future eHealth weight loss interventions should investigate strategies to engage younger cancer survivors with comorbidities and address racial and ethnic disparities in eHealth use.

The effect of e-health interventions promoting physical activity in older people: a systematic review and meta-analysis

INTRODUCTION

The objectives of this review paper were to synthesize the data from randomized controlled trials in the literature to come to a conclusion on the effects of e-health interventions on promoting physical activity in older people.

METHODS

The Medline, CINAHL, Embase, PsycINFO, and SportDiscus databases were searched for articles about studies that 1) recruited subjects with a mean age of > 50 years, 2) tested e-health interventions, 3) employed control groups with no or less advanced e-health strategies, 4) measured physical activity as an outcome, 5) were published between 1st January 2008 and 31st May 2019, and 6) employed randomized controlled trials. The risk of bias in individual studies was assessed using the Physiotherapy Evidence Database scale. To examine the effects of the interventions, variables quantifying the amount of physical activity were extracted. The within-group effects of individual studies were summarized using Hedges g and 95% confidence intervals. Between-group effects were summarized by meta-analyses using RevMan 5.0 with a random effect model.

RESULTS

Of the 2810 identified studies, 38 were eligible, 25 were included in the meta-analyses. The within-group effect sizes (Hedges g) of physical activity in the intervention group at T1 ranged from small to large: physical activity time (0.12 to 0.84), step counts (- 0.01 to 11.19), energy expenditure (- 0.05 to 0.86), walking time (0.13 to 3.33), and sedentary time (- 0.12 to - 0.28). The delayed effects as observed in T2 and T3 also ranged from small to large: physical activity time (0.24 to 1.24) and energy expenditure (0.15 to 1.32). In the meta-analysis, the between-group effect of the e-health intervention on physical activity time measured by questionnaires, physical activity time measured by objective wearable devices, energy expenditure, and step counts were all significant with minimal heterogeneity.

CONCLUSION

E-health interventions are effective at increasing the time spent on physical activity, energy expenditure in physical activity, and the number of walking steps. It is recommended that e-health interventions be included in guidelines to enhance physical activity in older people. Further studies should be conducted to determine the most effective e-health strategies.

The emerging role of digital health in monitoring and supporting people living with cancer and the consequences of its treatments

PURPOSE OF REVIEW

As rising numbers of people are living with the long-term impact of cancer, digital health is playing an increasingly important role in the monitoring and support of survivors and their caregivers. This article reviews current evidence, practice and developments, and identifies emerging issues and opportunities.

RECENT FINDINGS

Digital health innovations, primarily using internet or smartphone-enabled applications, have been successfully developed, particularly in the areas of symptom management, decision-making, survivorship and follow-up care and palliative care. The research is characterized by much developmental activity, and evidence is accruing for efficacy and effectiveness. Opportunities afforded by digital health include timelier and patient-centred evidence-based care, offering improved clinical outcomes and independence. Barriers to implementation include lack of patient and professional engagement, perceived burden, depersonalization and missed care.

SUMMARY

There is much enthusiasm for the role of digital health in monitoring and providing support to cancer survivors, but further research is needed to establish clinical efficacy and understand the mechanisms for successful implementation in practice. The role of wearables, the internet of things and big data analytics is yet to be fully explored in supportive cancer care and may present new opportunities to enhance care and survivor experience.

The role of primary care in supporting patients living with and beyond cancer

PURPOSE OF REVIEW

The prevalence of cancer survivors is increasing. Those living with and beyond a cancer diagnosis have a range of physical, psychosocial and practical needs. This review aims to discuss the role of primary care in meeting these needs.

RECENT FINDINGS

Patients have increased contact with primary care after a cancer diagnosis but the role of the primary care team in the formal delivery of cancer aftercare is not clearly defined and varies depending on setting and context. Research suggests that both patients and health professionals are receptive to greater involvement of primary care, with informational and personal continuity of care, and good co-ordination of care being particularly valued by patients. Recent evidence indicates that shared care between oncologists and primary care physicians can be as effective as and more cost effective than secondary care-led follow-up, and that primary-care nurses could play a role in optimizing survivorship care.

SUMMARY

The four pillars of primary care - contact, comprehensiveness, continuity and coordination - are recurring themes in the cancer survivorship literature and emphasize that the traditional core values of general practice lend themselves to innovative interventions to improve the efficiency and efficacy of survivorship care.

Technology-Supported Self-Guided Nutrition and Physical Activity Interventions for Adults With Cancer: Systematic Review

Background

Nutrition and physical activity interventions are important components of cancer care. With an increasing demand for services, there is a need to consider flexible, easily accessible, and tailored models of care while maintaining optimal outcomes.

Objective

This systematic review describes and appraises the efficacy of technology-supported self-guided nutrition and physical activity interventions for people with cancer.

Methods

A systematic search of multiple databases from 1973 to July 2018 was conducted for randomized and nonrandomized trials investigating technology-supported self-guided nutrition and physical activity interventions. Risk of bias was assessed using the Cochrane Risk of Bias tool. Outcomes included behavioural, health-related, clinical, health service, or financial measures.

Results

Sixteen randomized controlled trials representing 2684 participants were included. Most studies were web-based interventions (n=9) and had a 12-week follow-up duration (n=8). Seven studies assessed dietary behaviour, of which two reported a significant benefit on diet quality or fruit and vegetable intake. Fifteen studies measured physical activity behaviour, of which eight studies reported a significant improvement in muscle strength and moderate-to-vigorous physical activity. Four of the nine studies assessing the health-related quality of life (HRQoL) reported a significant improvement in global HRQoL or a domain subscale. A significant improvement in fatigue was found in four of six studies. Interpretation of findings was influenced by inadequate reporting of intervention description and compliance.

Conclusions

This review identified short-term benefits of technology-supported self-guided interventions on the physical activity level and fatigue and some benefit on dietary behaviour and HRQoL in people with cancer. However, current literature demonstrates a lack of evidence for long-term benefit.

Trial Registration

PROSPERO CRD42017080346; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=80346

SurvivorCHESS to increase physical activity in colon cancer survivors: can we get them moving?

PURPOSE

This randomized controlled trial evaluated the impact of SurvivorCHESS, an eHealth intervention, on physical activity in colon cancer survivors and to explore the impact of SurvivorCHESS on quality of life and distress.

METHODS

This was a two-arm single-blinded multi-site randomized controlled trial comparing a control group to an intervention group receiving a smartphone with the SurvivorCHESS program.

RESULTS

Participants using SurvivorCHESS (n = 144) increased their moderate to vigorous physical activities from 19.4 min at baseline to 50 min compared to the control group (n = 140) increasing from 15.5 to 40.3 min at 6 months (p = .083) but was not sustained 3 months after the study ended. No significant differences were found between groups over time for quality of life or distress items. Reports of physical symptoms were greater than other categories for distress items. Patients who had a higher body mass index and number of comorbid conditions were less likely to increase their physical activity. Self-determination theory including autonomous motivation and relatedness was not associated with the outcomes.

CONCLUSIONS

Physical activity did increase over time in both groups and was not significantly different with the use of the eHealth intervention, SurvivorCHESS, compared to the control group. The amount of SurvivorCHESS use was not associated with physical activity.

IMPLICATIONS FOR CANCER SURVIVORS

Increasing physical activity in colon cancer survivors has the potential to improve quality of life and reduce recurrences. Using smartphone-tracking devices may be useful in helping to change this health behavior.