Development of a computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: OncoActive

A new data science trajectory for analysing multiple studies: a case study in physical activity research

The analysis of complex mechanisms within population data, and within sub-populations, can be empowered by combining datasets, for example to gain more understanding of change processes of health-related behaviours. Because of the complexity of this kind of research, it is valuable to provide more specific guidelines for such analyses than given in standard data science methodologies. Thereto, we propose a generic procedure for applied data science research in which the data from multiple studies are included. Furthermore, we describe its steps and associated considerations in detail to guide other researchers. Moreover, we illustrate the application of the described steps in our proposed procedure (presented in the graphical abstract) by means of a case study, i.e., a physical activity (PA) intervention study, in which we provided new insights into PA change processes by analyzing an integrated dataset using Bayesian networks. The strengths of our proposed methodology are subsequently illustrated, by comparing this data science trajectories protocol to the classic CRISP-DM procedure. Finally, some possibilities to extend the methodology are discussed.-A detailed process description for multidisciplinary data science research on multiple studies.-Examples from a case study illustrate methodological key points.

A systematic review on eHealth technology personalization approaches

Despite the widespread use of personalization of eHealth technologies, there is a lack of comprehensive understanding regarding its application. This systematic review aims to bridge this gap by identifying and clustering different personalization approaches based on the type of variables used for user segmentation and the adaptations to the eHealth technology and examining the role of computational methods in the literature. From the 412 included reports, we identified 13 clusters of personalization approaches, such as behavior + channeling and environment + recommendations. Within these clusters, 10 computational methods were utilized to match segments with technology adaptations, such as classification-based methods and reinforcement learning. Several gaps were identified in the literature, such as the limited exploration of technology-related variables, the limited focus on user interaction reminders, and a frequent reliance on a single type of variable for personalization. Future research should explore leveraging technology-specific features to attain individualistic segmentation approaches.

Long-term efficacy of a computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: A randomized controlled trial

BACKGROUND

Physical activity (PA) can improve the physical and psychological health of prostate and colorectal cancer survivors, but PA behavior change maintenance is necessary for long-term health benefits. OncoActive is a print- and web-based intervention in which prostate and colorectal cancer patients and survivors receive automatically generated, personalized feedback aimed at integrating PA into daily life to increase and maintain PA. We evaluated the long-term outcomes of OncoActive by examining the 12-month follow-up differences between OncoActive and a control group, and we explored whether PA was maintained during a 6-month non-intervention follow-up period.

METHODS

Prostate or colorectal cancer patients were randomly assigned to an OncoActive (n = 249) or a usual care waitlist control group (n = 229). OncoActive participants received PA advice and a pedometer. PA outcomes (i.e., ActiGraph and self-report moderate-to-vigorous intensity PA (MVPA) min/week and days with ≥30 min PA) and health-related outcomes (i.e., fatigue, depression, physical functioning) were assessed at baseline, 6 months, and 12 months. Differences between groups and changes over time were assessed with multilevel linear regressions for the primary outcome (ActiGraph MVPA min/week) and all additional outcomes.

RESULTS

At 12 months, OncoActive participants did not perform better than control group participants at ActiGraph MVPA min/week, self-report MVPA min/week, or ActiGraph days with PA. Only self-report days with PA were significantly higher in OncoActive compared to the control group. For health-related outcomes only long-term fatigue was significantly lower in OncoActive. When exploratively examining PA within OncoActive, the previously found PA effects at the end of the intervention (6 months follow-up) were maintained at 12 months. Furthermore, all PA outcomes improved significantly from baseline to 12 months. The control group showed small but non-significant improvements from 6 months to 12 months (and from baseline to 12 months), resulting in a decline of differences between groups.

CONCLUSION

The majority of previously reported significant between-group differences at 6 months follow-up were no longer present at long-term follow-up, possibly because of natural improvement in the control group. At long-term follow-up, fatigue was significantly lower in OncoActive compared to control group participants. Computer-tailored PA advice may give participants an early start toward recovery and potentially contributes to improving long-term health.

Effects of time-restricted feeding and walking exercise on the physical health of female college students with hidden obesity: a randomized trial

Purpose

Time-restricted feeding (TRF) is an emerging dietary pattern with many potential effects. This study focused on the effects of TRF and walking on the physical health of female college students with hidden obesity.

Methods

A total of 77 female college students with hidden obesity, aged 18-22 years, were randomly assigned to a control group (CON, N = 19), time-restricted feeding group (TRF, N = 19), exercise group (EXE, N = 20), and TRF combined with exercise group (TRF + EXE, N = 19). The interventions lasted for 8 weeks. Tests assessing body shape, body composition, bone mineral density, blood lipid levels, and blood pressure were performed before and after the intervention.

Results

(1) Intragroup comparison before and after the intervention revealed that the TRF, EXE, and TRF + EXE groups had significantly reduced body weight (p < 0.01), body mass index (BMI) (p < 0.05), and lean tissue mass (LTM) (p < 0.01) but increased total cholesterol (TC) levels (p < 0.05) after the intervention. Body fat percentage (BF%) increased considerably in the EXE and TRF + EXE groups (p < 0.01). (2) Post-intervention comparisons of body weight, BMI, LTM, adipose tissue mass (ATM), total bone mineral density (TBMD), blood lipid levels, and blood pressure between the intervention groups (TRF, EXE, and TRF + EXE) and the CON group showed no significant differences (p > 0.05). (3) A comparison of the changes between the groups before and after the intervention showed significant decreases in body weight in the TRF and TRF + EXE groups (p < 0.05) and in both BMI and LTM in the TRF, EXE, and TRF + EXE groups (p < 0.05) compared to those in the CON group. The BF% change in the EXE and TRF + EXE groups were significantly greater than that in the TRF group (p < 0.01).

Conclusion

TRF effectively decreased body weight and BMI in female college students with hidden obesity. However, increased blood lipid levels and decreased LTM levels were also observed. The effects of TRF combined with exercise were not superior to those of TRF or walking alone in terms of body weight, body mass index, body composition, TBMD, or blood lipid levels. Therefore, TRF cannot be considered the best option for fat reduction in female college students with hidden obesity.

Adding Mobile Elements to Online Physical Activity Interventions for Adults Aged Over 50 Years: Prototype Development Study

BACKGROUND

Only a minority of adults aged over 50 years meet physical activity (PA) guidelines of the World Health Organization (WHO). eHealth interventions are proven effective tools to help this population increase its PA levels in the short term, among which the Active Plus and I Move interventions have been developed by our own research group. To achieve long-term effects, increase intervention use, and decrease dropout rates, 3 emergent but different mobile elements (an activity tracker, an ecological momentary intervention [EMI] program, and a chatbot) were added separately to Active Plus and I Move. In this study, the prototype development and pilot-testing of these interventions is described.

OBJECTIVE

This study aims to enhance 2 existing PA-stimulating computer-based interventions with 3 mobile elements (an activity tracker, an EMI program, or a chatbot) and test the prototypes on usability and appreciation within a target population of adults aged over 50 years.

METHODS

A systematic design protocol consisting of development, evaluation, and adaptation procedures was followed with involvement of the target population. Literature searches separated per mobile element and interviews with the target population (N=11) led to 6 prototypes: Active Plus or I Move including (1) an activity tracker, (2) EMI, or (3) a chatbot. These prototypes were tested on usability and appreciation during pilot tests (N=47) and subsequently fine-tuned based on the results.

RESULTS

The literature searches and interviews provided important recommendations on the preferences of the target population, which enabled us to develop prototypes. The subsequent pilot tests showed that the mobile elements scored moderate to good on usability, with average System Usability Scale (SUS) scores of 52.2-82.2, and moderate to good on enjoyment and satisfaction, with average scores ranging from 5.1 to 8.1 on a scale of 1-10. The activity tracker received the best scores, followed by EMI, followed by the chatbot. Based on the findings, the activity tracker interventions were fine-tuned and technical difficulties regarding EMI and the chatbot were solved, which is expected to further improve usability and appreciation.

CONCLUSIONS

During this study, 6 prototypes of online PA interventions with added mobile elements were developed and tested for usability and appreciation. Although all prototypes scored moderate to high on usability, enjoyment, and satisfaction, it can be concluded that the integration of an activity tracker with a computer-based PA intervention is the most promising option among the 3 mobile elements tested during this study. The prototype development steps of the systematic design protocol followed can be considered useful and successful for the purposes of this study. The interventions can now be evaluated on a larger scale through a randomized controlled trial.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/31677.

Determinants of physical activity behaviour change in (online) interventions, and gender-specific differences: a Bayesian network model

BACKGROUND

Physical activity (PA) is known to be beneficial for health, but adherence to international PA guidelines is low across different subpopulations. Interventions have been designed to stimulate PA of different target groups by influencing relevant psycho-social determinants, essentially based on a combination of the Integrated Model for Change, the Theory of Planned Behaviour, its successor the Reasoned Action Approach and the self-determination theory. The current study investigates the pathways through which interventions influence PA. Further, gender differences in pathways of change are studied.

METHODS

An integrated dataset of five different randomised controlled trial intervention studies is analysed by estimating a Bayesian network. The data include measurements, at baseline and at 3, 6 (short-term), and 12 (long-term) months after the baseline, of important socio-cognitive determinants of PA, demographic factors, and PA outcomes. A fragment is extracted from the Bayesian network consisting of paths between the intervention variable, determinants, and short- and long-term PA outcomes. For each relationship between variables, a stability indicator and its mutual information are computed. Such a model is estimated for the full dataset, and in addition such a model is estimated based only on male and female participants' data to investigate gender differences.

RESULTS

The general model (for the full dataset) shows complex paths, indicating that the intervention affects short-term PA via the direct determinants of intention and habit and that self-efficacy, attitude, intrinsic motivation, social influence concepts, planning and commitment have an indirect influence. The model also shows how effects are maintained in the long-term and that previous PA behaviour, intention and attitude pros are direct determinants of long-term PA. The gender-specific models show similarities as well as important differences between the structures of paths for the male- and female subpopulations. For both subpopulations, intention and habit play an important role for short-term effects and maintenance of effects in the long-term. Differences are found in the role of self-efficacy in paths of behaviour change and in the fact that attitude is relevant for males, whereas planning plays a crucial role for females. The average of these differences in subpopulation mechanisms appears to be presented in the general model.

CONCLUSIONS

While previous research provided limited insight into how interventions influence PA through relevant determinants, the Bayesian network analyses show the relevance of determinants mentioned by the theoretical framework. The model clarifies the role that different determinants play, especially in interaction with each other. The Bayesian network provides new knowledge about the complex working mechanism of interventions to change PA by giving an insightful overview of influencing paths. Furthermore, by presenting subpopulation-specific networks, the difference between the influence structure of males and females is illustrated. These new insights can be used to improve interventions in order to enhance their effects. To accomplish this, we have developed a new methodology based on a Bayesian network analysis which may be applicable in various other studies.

Promoting Physical Activity among Workers: A Review of Literature and Future Directions on Developing Theory-Based Interventions

Insufficient physical activity (PA) has been identified as a leading risk factor for premature and all-cause death, as well as non-communicable diseases. Employees, especially those with low occupational PA, are more vulnerable to physical inactivity, and studies in this population are scarce. However, employees may receive benefits for both health and work productivity from PA. Therefore, well-designed behavior change studies to promote PA in employees are urgently needed, especially during the COVID-19 pandemic. Literature was searched before 30 July 2022, and updated evidence was summarized. This review elaborates on the evidence related to insufficient PA and further provides an overview of theory-based interventions for promoting PA. Evidence indicates that intervention mapping (IM) was a useful tool to develop, implement, and evaluate behavior change interventions. Based on the IM framework, reviewing the theory- and evidence-based change methods and delivery modes, and further identifying the research gaps and limitations of existing interventions could provide promising suggestions and directions for development of well-founded interventions promoting PA among employees. The updated knowledge base for developing future interventions may boost efficacy and provide firm conclusions for researchers in this area.

The Barriers and Facilitators of eHealth-Based Lifestyle Intervention Programs for People With a Low Socioeconomic Status: Scoping Review

BACKGROUND

Promoting health behaviors and preventing chronic diseases through a healthy lifestyle among those with a low socioeconomic status (SES) remain major challenges. eHealth interventions are a promising approach to change unhealthy behaviors in this target group.

OBJECTIVE

This review aims to identify key components, barriers, and facilitators in the development, reach, use, evaluation, and implementation of eHealth lifestyle interventions for people with a low SES. This review provides an overview for researchers and eHealth developers, and can assist in the development of eHealth interventions for people with a low SES.

METHODS

We performed a scoping review based on Arksey and O'Malley's framework. A systematic search was conducted on PubMed, MEDLINE (Ovid), Embase, Web of Science, and the Cochrane Library, using terms related to a combination of the following key constructs: eHealth, lifestyle, low SES, development, reach, use, evaluation, and implementation. There were no restrictions on the date of publication for articles retrieved upon searching the databases.

RESULTS

The search identified 1323 studies, of which 42 met our inclusion criteria. An update of the search led to the inclusion of 17 additional studies. eHealth lifestyle interventions for people with a low SES were often delivered via internet-based methods (eg, websites, email, Facebook, and smartphone apps) and offline methods, such as texting. A minority of the interventions combined eHealth lifestyle interventions with face-to-face or telephone coaching, or wearables (blended care). We identified the use of different behavioral components (eg, social support) and technological components (eg, multimedia) in eHealth lifestyle interventions. Facilitators in the development included iterative design, working with different disciplines, and resonating intervention content with users. Facilitators for intervention reach were use of a personal approach and social network, reminders, and self-monitoring. Nevertheless, barriers, such as technological challenges for developers and limited financial resources, may hinder intervention development. Furthermore, passive recruitment was a barrier to intervention reach. Technical difficulties and the use of self-monitoring devices were common barriers for users of eHealth interventions. Only limited data on barriers and facilitators for intervention implementation and evaluation were available.

CONCLUSIONS

While we found large variations among studies regarding key intervention components, and barriers and facilitators, certain factors may be beneficial in building and using eHealth interventions and reaching people with a low SES. Barriers and facilitators offer promising elements that eHealth developers can use as a toolbox to connect eHealth with low SES individuals. Our findings suggest that one-size-fits-all eHealth interventions may be less suitable for people with a low SES. Future research should investigate how to customize eHealth lifestyle interventions to meet the needs of different low SES groups, and should identify the components that enhance their reach, use, and effectiveness.

Adding Mobile Elements to Online Physical Activity Interventions Targeted at Adults Aged 50 Years and Older: Protocol for a Systematic Design

BACKGROUND

Physical activity (PA) can increase mental and physical health in adults aged 50 years and older. However, it has been shown that PA guidelines are often not met within this population. Therefore, our research group developed 2 computer-tailored intervention programs in the last decade to stimulate PA: Active Plus and I Move. Although these programs were proven effective, positive effects diminished over time and attrition rates were relatively high. To respond to this, we will integrate 3 interactive mobile elements into the existing programs: activity tracker, ecological momentary intervention program, and virtual coach app.

OBJECTIVE

The goal of the research is to define systematic and evidence-based steps for extending our online computer-based PA intervention programs with 3 interactive mobile elements.

METHODS

Components often included in other (eHealth) design models were identified as key components and served as a base for the definition of systematic steps: exploration of context, involvement of the target population, prototype and intervention testing, and implementation. Based on these key components, 10 systematic steps were defined. The initial step is a literature search, with the results serving as a base for development of the low-fidelity prototypes in step 2. The pilot phase comprises the 3rd to 6th steps and includes semistructured interviews, pilot tests, and adaptations of the prototypes with intensive involvement of the target population of adults aged 50 years and older, where particular attention will be paid to lower educated persons. The 7th step is an effect evaluation in the form of a randomized controlled trial. During the 8th step, the most effective intervention programs will be selected and reinforced. These reinforced intervention programs will be used during the design of an implementation plan in the 9th step and the subsequent field study in the 10th step.

RESULTS

The project will be executed from December 2019 to December 2023. During this period, the systematic approach presented will be practically executed according to the methodological procedures described.

CONCLUSIONS

Based on the 4 identified key components, we were able to design an evidence-based systematic design approach for separately adding 3 mobile elements to our existing online PA intervention programs. The 10 steps are presented as a useful approach to guide future eHealth design studies.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/31677.

eHealth Interventions for Dutch Cancer Care: Systematic Review Using the Triple Aim Lens

BACKGROUND

Globally, the burden of cancer on population health is growing. Recent trends such as increasing survival rates have resulted in a need to adapt cancer care to ensure a good care experience and manageable expenditures. eHealth is a promising way to increase the quality of cancer care and support patients and survivors.

OBJECTIVE

The aim of this systematic review was 2-fold. First, we aimed to provide an overview of eHealth interventions and their characteristics for Dutch patients with and survivors of cancer. Second, we aimed to provide an overview of the empirical evidence regarding the impact of eHealth interventions in cancer care on population health, quality of care, and per capita costs (the Triple Aim domains).

METHODS

The electronic databases Web of Science, PubMed, Cochrane, and Ovid PsycINFO were searched using 3 key search themes: eHealth interventions, cancer care, and the Netherlands. The identified interventions were classified according to predetermined criteria describing the intervention characteristics (eg, type, function, and target population). Their impact was subsequently examined using the Triple Aim framework.

RESULTS

A total of 38 interventions were identified. Most of these were web portals or web applications functioning to inform and self-manage, and target psychosocial factors or problems. Few interventions have been tailored to age, disease severity, or gender. The results of this study indicate that eHealth interventions could positively affect sleep quality, fatigue, and physical activity of patients with and survivors of cancer. Inconclusive results were found regarding daily functioning and quality of life, psychological complaints, and psychological adjustment to the disease.

CONCLUSIONS

eHealth can improve outcomes in the Triple Aim domains, particularly in the population health and quality of care domains. Cancer-related pain and common symptoms of active treatment were not targeted in the included interventions and should receive more attention. Further research is needed to fully understand the impact of eHealth interventions in cancer care on participation, accessibility, and costs. The latter can be examined in economic evaluations by comparing eHealth interventions with care as usual.

eHealth-Based Interventions for Older Patients with Prostate Cancer: A Quick Review of the Literature

Background

The prevalence of prostate cancer (PC) is higher in older adults. Due to early diagnosis and treatment, there is an increase in the survival rate of these patients. The survival of patients with PC imposes the need for specific and effective care strategies.

Objective

To identify and analyze eHealth intervention programs for older adults with PC.

Methods

A quick review of evidence from the current literature was employed to address the objective of the study. The recommendations of the Cochrane Rapid Reviews Methods Group were used. The PubMed, Embase, Capes Journals, and Lilacs-BVS databases were searched, covering studies published from January 2010 to July 2021. The articles selected were classified considering the modalities and type of eHealth strategies.

Results

A total of 10 articles were included in this review. Two types of modalities were identified and classified: the intervention that used the web-based platform (WBP) was the most used in the studies (n = 7), followed by the interactive smartphone application (ISA) (n = 3) and mixed (WBP + ISA) (n = 1). As for the classification, mixed interventions were the most used (n = 4), followed by self-monitoring (n = 3), educational (n = 2), and behavioral counseling (n = 1). The clustering of articles generated three groups for the presentation of results and discussion, being eHealth interventions: integrated care, detection of symptoms, and quality of life in older patients with PC, psychological eHealth interventions in older adults with PC, and physical activity eHealth interventions in older adults with PC.

Conclusion

eHealth interventions for patients with PC are relatively new but promising in the support of current care options.

The Use of Theory to Develop Physical Activity Interventions in Urological Cancer Survivors: A Narrative Review

OBJECTIVES

To summarize the current available evidence on the use of behavior change theories to explain and change physical activity behavior in urological cancer survivors.

DATA SOURCES

Five electronic databases including Medline, Web of Science, Embase, Cochrane, and Psych INFO and reference lists of key studies were searched between database inception and November 2020. Peer-reviewed articles on the use of behavior change theories to understand or change physical activity in urological cancer survivors were included.

CONCLUSION

The theory of planned behavior and the social cognitive theory were the most used theories to explain and change physical activity behavior in urological cancers, respectively. However, the use of behavior change theories in physical activity interventions for urological cancers is still low across all urological tumor groups. Planning frameworks such as the intervention mapping approach should be used to enhance the systematic use of behavior change theories during every phase of intervention development. In addition, more research is needed to identity which behavior change techniques are most effective to change physical activity behavior in urological cancer survivors.

IMPLICATIONS FOR NURSING PRACTICE

Nurses play a key role in the urological cancer patients' clinical pathway and should be able to motivate patients to engage in sufficient physical activity levels. Therefore, it is important that nurses understand the underlying reasons why patients (do not) engage in physical activity and which behavior change techniques are most effective in changing a patients' behavior.

Feasibility and Acceptability of a Remotely Delivered, Web-Based Behavioral Intervention for Men With Prostate Cancer: Four-Arm Randomized Controlled Pilot Trial

Background

Diet and exercise may be associated with quality of life and survival in men with prostate cancer.

Objective

This study aimed to determine the feasibility and acceptability of a remotely delivered web-based behavioral intervention among men with prostate cancer.

Methods

We conducted a multi-site 4-arm pilot randomized controlled trial of a 3-month intervention (TrueNTH Community of Wellness). Eligibility included self-reported prostate cancer diagnosis, having a personal device that connected to the internet, age ≥18 years, and ability to read English and receive text messages and emails. Men receiving chemotherapy or radiation, or those who reported contraindications to exercise, could participate with physician clearance. Participants were randomized (1:1:1:1) to additive intervention levels: website; website and personalized diet and exercise prescription; website, personalized prescription, Fitbit, and text messages; and website, personalized prescription, Fitbit, text messages, and 2 30-minute phone calls—one with an exercise trainer and one with a registered dietician. Primary outcomes were feasibility (accrual and attrition) and acceptability (survey data and website use). We described self-reported diet and exercise behavior at the time of enrollment, 3 months, and 6 months as secondary outcomes.

Results

In total, 202 men consented and were randomized between August 2017 and September 2018 (level 1: 49, level 2: 51, level 3: 50, level 4: 52). A total of 160 men completed the onboarding process and were exposed to their randomly assigned intervention (38, 38, 42, and 42 in levels 1, 2, 3, and 4, respectively). The follow-up rate was 82.7% (167/202) at 3 months and 77.2% (156/202) at 6 months. Participants had a median age of 70 years and were primarily White and college educated. Website visit frequency over the 3-month intervention period increased across levels (median: 2, 9, 11, and 16 visits for levels 1, 2, 3, and 4, respectively). Most were satisfied or very satisfied with the intervention (20/39, 51%; 27/42, 64%; 23/44, 52%; and 27/42, 64% for levels 1, 2, 3, and 4, respectively). The percentage of men who reported being very satisfied was highest among level 4 participants (10/42, 24% vs 4/39, 10%; 5/42, 12%; and 5/44, 11% for levels 1, 2, and 3, respectively). Dissatisfaction was highest in level 1 (5/39, 13% vs 1/42, 2%; 3/44, 7%; and 2/42, 5% for levels 2, 3, and 4, respectively). We observed small improvements in diet and physical activity at 3 months among men in level 4 versus those in level 1.

Conclusions

A web-based, remotely delivered, tailored behavioral intervention for men with prostate cancer is feasible. Future studies are warranted to increase the effect of the intervention on patient behavior while maintaining sustainability and scalability as well as to design and implement interventions for more diverse populations.

Trial Registration

ClinicalTrials.gov NCT03406013; http://clinicaltrials.gov/ct2/show/NCT03406013

Web-Based Lifestyle Interventions for Prostate Cancer Survivors: Qualitative Study

Background

Exercise and a healthy diet can improve the quality of life and prognosis of prostate cancer survivors, but there have been limited studies on the feasibility of web-based lifestyle interventions in this population.

Objective

This study aims to develop a data-driven grounded theory of web-based engagement by prostate cancer survivors based on their experience in the Community of Wellness, a 12-week randomized clinical trial designed to support healthy diet and exercise habits.

Methods

TrueNTH’s Community of Wellness was a four-arm pilot study of men with prostate cancer (N=202) who received progressive levels of behavioral support (level 1: website; level 2: website with individualized diet and exercise recommendations; level 3: website with individualized diet and exercise recommendations, Fitbit, and text messages; and level 4: website with individualized diet and exercise recommendations, Fitbit and text messages, and separate phone calls with an exercise trainer and a registered dietitian). The primary aim of the study is to determine the feasibility and estimate the effects on behaviors (results reported in a separate paper). Following the 12-week intervention, we invited participants to participate in 4 focus groups, one for each intervention level. In this report, we used grounded theory analyses including open, axial, and selective coding to generate codes and themes from the focus group transcripts. Categories were refined across levels using embodied categorization and constant comparative methods.

Results

In total, 20 men with prostate cancer participated in the focus groups: 5, 4, 5, and 6 men in levels 1, 2, 3, and 4, respectively. Participants converged on 5 common factors influencing engagement with the intervention: environment (home environment, competing priorities, and other lifestyle programs), motivation (accountability and discordance experienced within the health care system), preparedness (technology literacy, health literacy, trust, and readiness to change), program design (communication, materials, and customization), and program support (education, ally, and community). Each of these factors influenced the survivors’ long-term impressions and habits. We proposed a grounded theory associating these constructs to describe the components contributing to the intuitiveness of a web-based lifestyle intervention.

Conclusions

These analyses suggest that web-based lifestyle interventions are more intuitive when we optimize participants’ technology and health literacy; tailor interface design, content, and feedback; and leverage key motivators (ie, health care providers, family members, web-based coach) and environmental factors (ie, familiarity with other lifestyle programs). Together, these grounded theory–based efforts may improve engagement with web-based interventions designed to support prostate cancer survivorship.

Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach

Emerging evidence indicates IBD is a risk factor for the increasing incidence of colorectal cancer (CRC) development. We used a system biology approach to identify common molecular signatures and pathways that interact between IBD and CRC and the indispensable pathological mechanisms. First, we identified 177 common differentially expressed genes (DEGs) between IBD and CRC. Gene set enrichment, protein-protein, DEGs-transcription factors, DEGs-microRNAs, protein-drug interaction, gene-disease association, Gene Ontology, pathway enrichment analyses were conducted to these common genes. The inclusion of common DEGs with bimolecular networks disclosed hub proteins (LYN, PLCB1, NPSR1, WNT5A, CDC25B, CD44, RIPK2, ASAP1), transcription factors (SCD, SLC7A5, IKZF3, SLC16A1, SLC7A11) and miRNAs (mir-335-5p, mir-26b-5p, mir-124-3p, mir-16-5p, mir-192-5p, mir-548c-3p, mir-29b-3p, mir-155-5p, mir-21-5p, mir-15a-5p). Analysis of the interaction between protein and drug discovered ASAP1 interacts with cysteine sulfonic acid and double oxidized cysteine drug compounds. Gene-disease association analysis retrieved ASAP1 also associated with pulmonary and bladder neoplasm diseases.

Physical activity interventions for disease-related physical and mental health during and following treatment in people with non-advanced colorectal cancer

BACKGROUND

Colorectal cancer is the third most commonly diagnosed cancer worldwide. A diagnosis of colorectal cancer and subsequent treatment can adversely affect an individuals physical and mental health. Benefits of physical activity interventions in alleviating treatment side effects have been demonstrated in other cancer populations. Given that regular physical activity can decrease the risk of colorectal cancer, and cardiovascular fitness is a strong predictor of all-cause and cancer mortality risk, physical activity interventions may have a role to play in the colorectal cancer control continuum. Evidence of the efficacy of physical activity interventions in this population remains unclear.

OBJECTIVES

To assess the effectiveness and safety of physical activity interventions on the disease-related physical and mental health of individuals diagnosed with non-advanced colorectal cancer, staged as T1-4 N0-2 M0, treated surgically or with neoadjuvant or adjuvant therapy (i.e. chemotherapy, radiotherapy or chemoradiotherapy), or both.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2019, Issue 6), along with OVID MEDLINE, six other databases and four trial registries with no language or date restrictions. We screened reference lists of relevant publications and handsearched meeting abstracts and conference proceedings of relevant organisations for additional relevant studies. All searches were completed between 6 June and 14 June 2019.

SELECTION CRITERIA

We included randomised control trials (RCTs) and cluster-RCTs comparing physical activity interventions, to usual care or no physical activity intervention in adults with non-advanced colorectal cancer.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected studies, performed the data extraction, assessed the risk of bias and rated the quality of the studies using GRADE criteria. We pooled data for meta-analyses by length of follow-up, reported as mean differences (MDs) or standardised mean differences (SMDs) using random-effects wherever possible, or the fixed-effect model, where appropriate. If a meta-analysis was not possible, we synthesised studies narratively.

MAIN RESULTS

We identified 16 RCTs, involving 992 participants; 524 were allocated to a physical activity intervention group and 468 to a usual care control group. The mean age of participants ranged between 51 and 69 years. Ten studies included participants who had finished active treatment, two studies included participants who were receiving active treatment, two studies included both those receiving and finished active treatment. It was unclear whether participants were receiving or finished treatment in two studies. Type, setting and duration of physical activity intervention varied between trials. Three studies opted for supervised interventions, five for home-based self-directed interventions and seven studies opted for a combination of supervised and self-directed programmes. One study did not report the intervention setting. The most common intervention duration was 12 weeks (7 studies). Type of physical activity included walking, cycling, resistance exercise, yoga and core stabilisation exercise. Most of the uncertainty in judging study bias came from a lack of clarity around allocation concealment and blinding of outcome assessors. Blinding of participants and personnel was not possible. The quality of the evidence ranged from very low to moderate overall. We did not pool physical function results at immediate-term follow-up due to considerable variation in results and inconsistency of direction of effect. We are uncertain whether physical activity interventions improve physical function compared with usual care. We found no evidence of effect of physical activity interventions compared to usual care on disease-related mental health (anxiety: SMD -0.11, 95% confidence interval (CI) -0.40 to 0.18; 4 studies, 198 participants; I2 = 0%; and depression: SMD -0.21, 95% CI -0.50 to 0.08; 4 studies, 198 participants; I2 = 0%; moderate-quality evidence) at short- or medium-term follow-up. Seven studies reported on adverse events. We did not pool adverse events due to inconsistency in reporting and measurement. We found no evidence of serious adverse events in the intervention or usual care groups. Minor adverse events, such as neck, back and muscle pain were most commonly reported. No studies reported on overall survival or recurrence-free survival and no studies assessed outcomes at long-term follow-up We found evidence of positive effects of physical activity interventions on the aerobic fitness component of physical fitness (SMD 0.82, 95% CI 0.34 to 1.29; 7 studies, 295; I2 = 68%; low-quality evidence), cancer-related fatigue (MD 2.16, 95% CI 0.18 to 4.15; 6 studies, 230 participants; I2 = 18%; low-quality evidence) and health-related quality of life (SMD 0.36, 95% CI 0.10 to 0.62; 6 studies, 230 participants; I2 = 0%; moderate-quality evidence) at immediate-term follow-up. These positive effects were also observed at short-term follow-up but not medium-term follow-up. Only three studies reported medium-term follow-up for cancer-related fatigue and health-related quality of life.

AUTHORS' CONCLUSIONS

The findings of this review should be interpreted with caution due to the low number of studies included and the quality of the evidence. We are uncertain whether physical activity interventions improve physical function. Physical activity interventions may have no effect on disease-related mental health. Physical activity interventions may be beneficial for aerobic fitness, cancer-related fatigue and health-related quality of life up to six months follow-up. Where reported, adverse events were generally minor. Adequately powered RCTs of high methodological quality with longer-term follow-up are required to assess the effect of physical activity interventions on the disease-related physical and mental health and on survival of people with non-advanced colorectal cancer. Adverse events should be adequately reported.

Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis

BACKGROUND

Mobile health (mHealth), refers to healthcare practices supported by mobile devices, such as mobile phones and tablets. Within primary care, health workers often use mobile devices to register clients, track their health, and make decisions about care, as well as to communicate with clients and other health workers. An understanding of how health workers relate to, and experience mHealth, can help in its implementation.

OBJECTIVES

To synthesise qualitative research evidence on health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services, and to develop hypotheses about why some technologies are more effective than others.

SEARCH METHODS

We searched MEDLINE, Embase, CINAHL, Science Citation Index and Social Sciences Citation Index in January 2018. We searched Global Health in December 2015. We screened the reference lists of included studies and key references and searched seven sources for grey literature (16 February to 5 March 2018). We re-ran the search strategies in February 2020. We screened these records and any studies that we identified as potentially relevant are awaiting classification.

SELECTION CRITERIA

We included studies that used qualitative data collection and analysis methods. We included studies of mHealth programmes that were part of primary healthcare services. These services could be implemented in public or private primary healthcare facilities, community and workplace, or the homes of clients. We included all categories of health workers, as well as those persons who supported the delivery and management of the mHealth programmes. We excluded participants identified as technical staff who developed and maintained the mHealth technology, without otherwise being involved in the programme delivery. We included studies conducted in any country.

DATA COLLECTION AND ANALYSIS

We assessed abstracts, titles and full-text papers according to the inclusion criteria. We found 53 studies that met the inclusion criteria and sampled 43 of these for our analysis. For the 43 sampled studies, we extracted information, such as country, health worker category, and the mHealth technology. We used a thematic analysis process. We used GRADE-CERQual to assess our confidence in the findings.

MAIN RESULTS

Most of the 43 included sample studies were from low- or middle-income countries. In many of the studies, the mobile devices had decision support software loaded onto them, which showed the steps the health workers had to follow when they provided health care. Other uses included in-person and/or text message communication, and recording clients' health information. Almost half of the studies looked at health workers' use of mobile devices for mother, child, and newborn health. We have moderate or high confidence in the following findings. mHealth changed how health workers worked with each other: health workers appreciated being more connected to colleagues, and thought that this improved co-ordination and quality of care. However, some described problems when senior colleagues did not respond or responded in anger. Some preferred face-to-face connection with colleagues. Some believed that mHealth improved their reporting, while others compared it to "big brother watching". mHealth changed how health workers delivered care: health workers appreciated how mHealth let them take on new tasks, work flexibly, and reach clients in difficult-to-reach areas. They appreciated mHealth when it improved feedback, speed and workflow, but not when it was slow or time consuming. Some health workers found decision support software useful; others thought it threatened their clinical skills. Most health workers saw mHealth as better than paper, but some preferred paper. Some health workers saw mHealth as creating more work. mHealth led to new forms of engagement and relationships with clients and communities: health workers felt that communicating with clients by mobile phone improved care and their relationships with clients, but felt that some clients needed face-to-face contact. Health workers were aware of the importance of protecting confidential client information when using mobile devices. Some health workers did not mind being contacted by clients outside working hours, while others wanted boundaries. Health workers described how some community members trusted health workers that used mHealth while others were sceptical. Health workers pointed to problems when clients needed to own their own phones. Health workers' use and perceptions of mHealth could be influenced by factors tied to costs, the health worker, the technology, the health system and society, poor network access, and poor access to electricity: some health workers did not mind covering extra costs. Others complained that phone credit was not delivered on time. Health workers who were accustomed to using mobile phones were sometimes more positive towards mHealth. Others with less experience, were sometimes embarrassed about making mistakes in front of clients or worried about job security. Health workers wanted training, technical support, user-friendly devices, and systems that were integrated into existing electronic health systems. The main challenges health workers experienced were poor network connections, access to electricity, and the cost of recharging phones. Other problems included damaged phones. Factors outside the health system also influenced how health workers experienced mHealth, including language, gender, and poverty issues. Health workers felt that their commitment to clients helped them cope with these challenges.

AUTHORS' CONCLUSIONS

Our findings propose a nuanced view about mHealth programmes. The complexities of healthcare delivery and human interactions defy simplistic conclusions on how health workers will perceive and experience their use of mHealth. Perceptions reflect the interplay between the technology, contexts, and human attributes. Detailed descriptions of the programme, implementation processes and contexts, alongside effectiveness studies, will help to unravel this interplay to formulate hypotheses regarding the effectiveness of mHealth.

A critical literature review of dyadic web-based interventions to support cancer patients and their caregivers, and directions for future research

OBJECTIVE

With the rapid development of the Internet, e-health interventions are becoming popular and are showing positive impacts. Cancer affects not only patients but also their caregivers, leading to a recognition that cancer patient-caregiver dyads cope with cancer as a unit rather than as individuals. The objectives of this paper are to explore web-based interventions for cancer patient-caregiver dyads coping with cancer from the aspects of intervention content, delivery format, outcome measurements, and outcomes and to provide recommendations on developing patient-caregiver dyadic web-based interventions for future research.

METHODS

Literature focused on cancer patient-caregiver dyadic web-based interventions, published in English or Chinese from the launch of five databases (CINAHL, PsycINFO, EMBase, Medline, Science Citation Index Expanded) to April 2019, was systematically searched. Manual searching through the references of full-text articles was also conducted.

RESULTS

Of a total of 812 articles, 17 articles met the inclusion criteria. The content of these web-based dyadic interventions mainly included information support, communication and support, skills-building, and psycho-education. These web-based interventions reported a small to large positive impact on patients with cancer and their caregivers in terms of physical health (d = 0.17-0.75), psychological health (d = 0.04-0.80), overall quality of life (d = 0.20-0.68), and dyadic relationship (d = 0.30-0.95).

CONCLUSIONS

Web-based dyadic interventions can be designed for tailored content, which benefits both patients and their caregivers. Future research on cancer patient-caregiver web-based interventions should be conducted in diverse cultures.

Development of interventions for an intelligent and individualized mobile health care system to promote healthy diet and physical activity: using an intervention mapping framework

BACKGROUND

The mortality of coronary heart disease can be largely reduced by modifying unhealthy lifestyles. However, the long-term effectiveness of interventions for modifying unhealthy diet and physical inactivity of patients with coronary heart disease remain unsatisfactory worldwide. This study aims to systematically design a set of theory-based and evidence-based, individualized, and intelligent interventions for promoting the adoption and maintenance of a healthy diet and physical activity level in patients with coronary heart disease.

METHODS

The interventions will be delivered by a mobile health care system called Individualized, Intelligent and Integrated Cardiovascular Application for Risk Elimination. Three steps of the intervention mapping framework were used to systematically develop the interventions. Step 1: needs assessment, which was carried out by a literature review, in-depth interviews and focus group discussions. Step 2: development of objective matrix for diet and physical activity changes, based on the intersection of objectives and determinants from the Contemplation-Action-Maintenance behavior change model. Step 3: formulation of evidence-based methods and strategies, and practical applications, through a systematic review of existing literature, research team discussions, and consultation with multidisciplinary expert panels.

RESULTS

Three needs relevant to content of the intervention, one need relevant to presentation modes of the intervention, and four needs relevant to functional features of the application were identified. The objective matrix includes three performance objectives, and 24 proximal performance objectives. The evidence-based and theory-based interventions include 31 strategies, 61 evidence-based methods, and 393 practical applications.

CONCLUSIONS

This article describes the development of theory-based and evidence-based interventions of the mobile health care system for promoting the adoption and maintenance of a healthy diet and physical activity level in a structured format. The results will provide a theoretical and methodological basis to explore the application of intervention mapping in developing effective behavioral mobile health interventions for patients with coronary heart disease.

TRIAL REGISTRATION

Chinese Clinical Trial Registry: ChiCTR-INR-16010242. Registered 24 December 2016. http://www.chictr.org.cn/index.aspx.

Impact of physical activity and diet on colorectal cancer survivors' quality of life: a systematic review

Background

Post-treatment management is essential for improving the health and quality of life of colorectal cancer (CRC) survivors. The number of cancer survivors is continually increasing, which is causing a corresponding growth in the need for effective post-treatment management programs. Current research on the topic indicates that such programs should include aspects such as physical activity and a proper diet, which would form the basis of lifestyle change among CRC survivors. Therefore, this study aimed to identify the impact of physical activity and diet on the quality of life of CRC survivors.

Methods

We performed a systematic literature review regarding CRC survivors. We searched the Embase, PubMed, and EBSCOhost databases, considering papers published between January 2000 and May 2017 in any language, using a combination of the following subject headings: “colorectal cancer,” “colorectal carcinoma survivor,” “survivorship plan,” “survivorship care plan,” “survivorship program,” “lifestyle,” “activities,” “exercise,” “diet program,” and “nutrition.”

Results

A total of 14,036 articles were identified, with 35 satisfying the eligibility criteria for the systematic review. These articles were grouped by the study questions into physical activity and diet: 24 articles were included in the physical activity group and 11 in the diet group.

Conclusions

The research showed that an effective survivorship program can significantly help CRC survivors maintain good health and quality of life for long periods. However, there is a lack of consensus and conclusive evidence regarding how the guidelines for such a program should be designed, in terms of both its form and content.

Engaging stakeholders in the co-development of programs or interventions using Intervention Mapping: A scoping review

BACKGROUND

Health care innovations tailored to stakeholder context are more readily adopted. This study aimed to describe how Intervention Mapping (IM) was used to design health care innovations and how stakeholders were involved.

METHODS

A scoping review was conducted. MEDLINE, EMBASE, Cochrane Library, Scopus and Science Citation Index were searched from 2008 to November 2017. English language studies that used or cited Intervention Mapping were eligible. Screening and data extraction were done in triplicate. Summary statistics were used to describe study characteristics, IM steps employed, and stakeholder involvement.

RESULTS

A total of 852 studies were identified, 449 were unique, and 333 were excluded based on title and abstracts, 116 full-text articles were considered and 61 articles representing 60 studies from 13 countries for a variety of clinical issues were included. The number of studies published per year increased since 2008 and doubled in 2016 and 2017. The majority of studies employed multiple research methods (76.7%) and all 6 IM steps (73.3%). Resulting programs/interventions were single (55.4%) or multifaceted (46.4%), and 60.7% were pilot-tested. Programs or interventions were largely educational material or meetings, and were targeted to patients (70.2%), clinicians (14.0%) or both (15.8%). Studies provided few details about current or planned evaluation. Of the 4 (9.3%) studies that reported impact or outcomes, 3 achieved positive improvements in patient or professional behaviour or patient outcomes. Many studies (28.3%) did not involve stakeholders. Those that did (71.7%) often involved a combination of patients, clinicians, and community organizations. However, less than half (48.8%) described how they were engaged. Most often stakeholders were committee members and provide feedback on program or intervention content or format.

CONCLUSIONS

It is unclear if use of IM or stakeholder engagement in IM consistently results in effective programs or interventions. Those employing IM should report how stakeholders were involved in each IM step and how involvement influenced program or intervention design. They should also report the details or absence of planned evaluation. Future research should investigate how to optimize stakeholder engagement in IM, and whether use of IM itself or stakeholder engagement in IM are positively associated with effective programs or interventions.

Short-term efficacy of a computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: a randomized controlled trial

BACKGROUND

Physical activity (PA) is beneficial in improving negative physical and psychological effects of cancer and cancer treatment, but adherence to PA guidelines is low. Computer-tailored PA interventions can reach large populations with little resources. They match with patients' preference for home-based, unsupervised PA programs and are thus promising for the growing population of cancer survivors. The current study assessed the efficacy of a computer-tailored PA intervention in (four subgroups of) prostate and colorectal cancer survivors.

METHODS

Prostate and colorectal cancer patients and survivors were randomized to the OncoActive intervention group (N = 249), or a usual-care waiting-list control group (N = 229). OncoActive participants received a pedometer and computer-tailored PA advice, both Web-based via an interactive website and with printed materials. Minutes moderate-to-vigorous PA (MVPA) and days ≥30 min PA were assessed with an accelerometer (ActiGraph) at baseline and 6 months. Further, questionnaires were used to assess self-reported PA, fatigue, distress, and quality of life at baseline, 3 and 6 months. Differences between both groups were assessed using linear regression analyses (complete cases and intention-to-treat). In addition, efficacy in relation to age, gender, education, type of cancer, and time since treatment was examined.

RESULTS

Three months after baseline OncoActive participants significantly increased their self-reported PA (PA days: d = 0.46; MVPA: d = 0.23). Physical functioning (d = 0.23) and fatigue (d = - 0.21) also improved significantly after three months. Six months after baseline, self-reported PA (PA days: d = 0.51; MVPA: d = 0.37) and ActiGraph MVPA (d = 0.27) increased significantly, and ActiGraph days (d = 0.16) increased borderline significantly (p = .05; d = 0.16). Furthermore, OncoActive participants reported significantly improvements in physical functioning (d = 0.14), fatigue (d = - 0.23) and depression (d = - 0.32). Similar results were found for intention-to-treat analyses. Higher increases in PA were found for colorectal cancer participants at 3 months, and for medium and highly educated participants' PA at 6 months. Health outcomes at 6 months were more prominent in colorectal cancer participants and in women.

CONCLUSIONS

The OncoActive intervention was effective at increasing PA in prostate and colorectal cancer patients and survivors. Health-related effects were especially apparent in colorectal cancer participants. The intervention provides opportunities to accelerate cancer recovery. Long-term follow-up should examine further sustainability of these effects.

TRIAL REGISTRATION

The study was registered in the Dutch Trial Register ( NTR4296 ) on October 17 2018.

Effect of psychosocial interventions on the quality of life of patients with colorectal cancer: a systematic review and meta-analysis

Background

We conducted a systematic review and meta-analysis of randomized controlled trials examining the effect of psychosocial interventions on the quality of life of patients with colorectal cancer.

Methods

We searched the main health-related databases for relevant papers. Then, we examined the titles and abstracts of the retrieved papers, applying exclusion criteria to filter out irrelevant papers; a more in-depth filtering process was then conducted by reading the full texts. Eight studies remained at the end of this process. Next, we performed data extraction and assessed the methodological quality of the selected studies. This was followed by computation of effect sizes and the heterogeneity of the results, and then an assessment of the potential bias.

Results

The systematic review found that most of the interventions in these eight studies did not have a significant effect on quality of life. Meanwhile, the meta-analysis, the overall effect of psychosocial interventions at the post-intervention period was found to be statistically significant but small.

Conclusions

This meta-analysis provides evidence for the beneficial effect of face-to-face psychosocial interventions on the quality of life of colorectal cancer patients. It is, however, suggested that further studies be conducted on this topic to assess the roles of physical functioning and severity of symptoms before utilizing such face-to-face interventions.

Electronic supplementary material

The online version of this article (10.1186/s12955-018-0943-6) contains supplementary material, which is available to authorized users.

A Web-Based and Print-Based Computer-Tailored Physical Activity Intervention for Prostate and Colorectal Cancer Survivors: A Comparison of User Characteristics and Intervention Use

Background

Physical activity (PA) is beneficial in improving negative physical and psychological effects of cancer. The rapidly increasing number of cancer survivors, resulting from aging and improved cancer care, emphasizes the importance to develop and provide low cost, easy accessible PA programs. Such programs could be provided through the Internet, but that could result in the exclusion of cancer survivors not familiar with the Internet. Therefore, we developed a computer-tailored PA intervention for prostate and colorectal cancer survivors in which both Web-based and print materials are provided, and participants can choose their own preferred delivery mode.

Objective

The aim of this study was to assess participants’ characteristics related to delivery mode and use of intervention materials.

Methods

We studied characteristics of participants using Web-based and printed intervention materials in a randomized controlled trial (RCT). Prostate and colorectal cancer survivors recruited from hospitals were randomized to OncoActive (computer-tailored PA intervention) or a usual-care control group. OncoActive participants received both Web-based and printed materials. Participants were classified into initial print- or Web-based participants based on their preferred mode of completion of the first questionnaire, which was needed for the computer-tailored PA advice. Intervention material use during the remainder of the intervention was compared for initial print- or Web-based participants. Additionally, participants were classified into those using only print materials and those using Web-based materials. Differences in participant characteristics and intervention material use were studied through analysis of variance (ANOVAs), chi-square tests, and logistic regressions.

Results

The majority of the participants in the intervention group were classified as initial Web-based participants (170/249, 68.3%), and 84.9% (191/249) used Web-based intervention materials. Dropout was low (15/249, 6.0%) and differed between initial Web-based (4/170, 2.4%) and print-based (11/79, 14%) participants. Participants were less likely to start Web-based with higher age (odds ratio [OR]=0.93), longer time since last treatment (OR=0.87), and higher fatigue (OR=0.96), and more likely with higher education (OR=4.08) and having completed treatments (OR=5.58). Those who were older (OR=0.93) and post treatment for a longer time (OR=0.86) were less likely to use Web-based intervention materials. Initial print-based participants predominantly used print-based materials, whereas initial Web-based participants used both print- and Web-based materials.

Conclusions

To our knowledge, this is one of the first studies that assessed participant characteristics related to delivery mode in an intervention in which participants had a free choice of delivery modes. Use of print-based materials among the initial Web-based participants was substantial, indicating the importance of print-based materials. According to our findings, it may be important to offer Web- and print-based materials alongside each other. Providing Web-based materials only may exclude older, less educated, more fatigued, or currently treated participants; these groups are especially more vulnerable and could benefit most from PA interventions.