Background: Patient empowerment reflects the ability of patients to positively influence their health and health behavior such as physical activity. While interactive Web-based interventions are increasingly used in various chronic disease settings to enhance empowerment and physical activity, such interventions are still uncommon for cancer survivors.
Objective: The objective of this study was to systematically review the literature regarding interactive Web-based interventions. We focused on interventions aimed at increasing patient empowerment and physical activity for various chronic conditions, and explored their possible relevance for cancer survivors.
Methods: Searches were performed in PubMed, Embase, and Scopus to identify peer-reviewed papers reporting on randomized controlled trials that studied the effects of Web-based interventions. These interventions were developed for adults with diabetes, cardiovascular disease, chronic obstructive pulmonary disease, heart failure, or cancer. Intervention characteristics, effects on patient empowerment and physical activity, information on barriers to and facilitators of intervention use, users’ experiences, and methodological quality were assessed. Results were summarized in a qualitative way. We used the recommendations of the Institute of Medicine (IOM) regarding cancer survivorship care to explore the relevance of the interventions for cancer survivors.
Results: We included 19 papers reporting on trials with 18 unique studies. Significant, positive effects on patient empowerment were reported by 4 studies and 2 studies reported positive effects on physical activity. The remaining studies yielded mixed results or no significant group differences in these outcomes (ie, no change or improvement for all groups). Although the content, duration, and frequency of interventions varied considerably across studies, commonly used elements included education, self-monitoring, feedback/tailored information, self-management training, personal exercise program, and communication (eg, chat, email) with either health care providers or patients. Limited information was found on barriers, facilitators, and users’ experiences. Methodological quality varied, with 13 studies being of moderate quality. The reported Web-based intervention elements appeared to be highly relevant to address the specific needs of cancer survivors as indicated by the IOM.
Conclusions: We identified 7 common elements of interactive, Web-based interventions in chronic disease settings that could possibly be translated into eHealth recommendations for cancer survivors. While further work is needed to determine optimal intervention characteristics, the work performed in other chronic disease settings provides a basis for the design of an interactive eHealth approach to improve patient empowerment and physical activity in cancer survivors. This may subsequently improve their health status and quality of life and reduce their need for supportive care.
Due to improvements in cancer screening and treatment, the number of people living with cancer or that have been successfully treated for cancer is increasing rapidly . Those people are often referred to as cancer survivors, and in the Netherlands this population is expected to increase from 419,000 in 2009 to 660,000 in 2020 [ ]. Cancer survivors are increasingly approached as individuals with a chronic disease, with either on-going or intermittent impact on their health status and quality of life. Therefore, many of them need supportive and rehabilitative services to alleviate side effects of treatment and to cope with psychosocial problems such as fear of disease recurrence or with physical health problems such as a painful arm after breast cancer surgery. Furthermore, these services can be used for health promotion [ , ]. To minimize the time and costs involved with the need for such supportive care services in response to the raising number of cancer survivors, it may be useful to enhance patient empowerment.
Patient empowerment can contribute to control over patients’ health and health behavior. It is frequently described as having knowledge about one’s health, and being able and motivated to influence one’s health . It refers to well-informed patients taking responsibility for their own health, to as great an extent as possible, and the expected benefits of improved quality of life [ ]. It is expected that increasing patient empowerment will result in a reduced need for support from the health care system, thus lowering health care costs [ , ].
Another factor that positively contributes to quality of life is physical activity. A number of studies have demonstrated many beneficial effects of physical activity on physical and psychosocial well-being, both during and after cancer treatment [- ]. This suggests that empowering cancer survivors and enabling them to become or stay physically active is very likely to be beneficial for both the patients and the society.
A promising medium for facilitating patient empowerment and physical activity is the Internet. Easily accessible, up-to-date, and tailored information can be provided, often in an interactive way. For example, patients could be asked to provide information or pose questions via a questionnaire to trigger either standardized or tailored feedback from the health care system (given automatically or by a health care provider). The Internet is increasingly used for the delivery of these interactive interventions, both for healthy individuals  and those with chronic conditions [ ]. For cancer survivors, other eHealth initiatives do exist, such as online support groups, online patient education programs [ , ], informative tools for decision support, and various mobile apps that could be used independent of provider activities. However, there are very few interactive websites that aim to empower cancer survivors, especially in the area of physical activity. Previously, researchers have reviewed Web-based interventions that aimed to increase either patient empowerment or physical activity level, with promising results [ , ]. These reviews included studies that were focused primarily on healthy individuals (in some cases sedentary or overweight, [ ]) or at increasing patient empowerment, but not physical activity levels, of individuals with chronic diseases [ ]. In view of the increasing number of cancer survivors and the potential role that interactive Web-based interventions could play in stimulating empowerment and physical activity, it is important to learn from empirical evidence about the efficacy of such interventions in chronic diseases. Considering the comparable chronic nature of these diseases and cancer survivorship, it is plausible that interventions that contribute to managing chronic diseases other than cancer contain elements that are appropriate for cancer survivors as well.
This systematic review has 5 aims: (1) to describe the characteristics (content, length, frequency, duration) of interactive, Web-based interventions in diabetes, chronic obstructive pulmonary disease (COPD), (congestive) heart failure, cardiovascular disease, and cancer, (2) to summarize the effects of these interventions on patient empowerment and physical activity. (3) to identify barriers for and facilitators of the use of Web-based interventions and to describe users’ experiences with such websites, (4) to assess the methodological quality of the studies reviewed, and (5) to evaluate the possible relevance of these interventions for cancer survivors.
We searched the literature in PubMed, Embase, and Scopus. The main search strategy combined four concepts: patient empowerment, physical activity, information technology (IT), and type of chronic disease. For each concept, several search terms were used (see). Because we also wanted to identify IT that focussed on either physical activity or patient empowerment, we also searched PubMed for the combination of patient empowerment, IT, and type of chronic disease, and separately for the combination of physical activity, IT, and type of chronic disease. As these searches resulted in many duplicates, this dual search strategy was not repeated in Embase or Scopus. To retrieve other relevant publications, we examined the reference lists of the selected publications and reviews that were excluded based on eligibility criteria.
We used the following inclusion criteria: (1) peer reviewed studies in English describing a randomized controlled trial (RCT), published between 1990 and November 20, 2012, (2) participants were adults and suffered from at least one of the following chronic diseases—cancer, diabetes, heart failure, cardiovascular disease, or COPD, (3) the intervention was Web-based and interactive, (4) the intervention group was compared to a similar patient group (receiving another intervention or usual care), and (5) the study included at least one outcome measure assessing patient empowerment and/or physical activity. For patient empowerment, relevant, related outcomes included self-efficacy, self-management, self-care behavior, and self-control. For physical activity, relevant outcomes could be based on self-report (eg, by questionnaire or interview), performance tests, or observation (eg, accelerometer data).
The first author applied the eligibility criteria to the titles and abstracts. When the abstract was considered relevant or in case of ambiguity, two authors reviewed the full publication independently. In cases of disagreement, consensus was sought through discussion. When disagreement persisted, the judgement of a third reviewer was decisive.
The following information was extracted from each publication: study characteristics (source and year of publication, country of origin, aim, and sample size), patient characteristics (type of disease, age, gender, comorbidities, computer experience, and Internet use), intervention characteristics (content, duration, frequency, compliance, and dropout rate), outcome measures (instruments used, and effects on patient empowerment and physical activity), information about barriers to and facilitators of intervention use, and users’ reported experiences with the intervention. The first author independently extracted the data, and the second author checked the data extraction for 20% of the studies to determine inter-rater reliability. This was established by calculating the percentage of agreement. Consensus was reached by discussion. Due to the diversity of outcome measures, sample size, and intervention characteristics, it was not possible to conduct a formal meta-analysis.
The methodological quality of the studies was evaluated, but did not serve as an eligibility criterion. We used a list that was an adapted version of the Cochrane Collaboration Back Review Group , which was used previously in a systematic review of Internet-based physical activity interventions by van den Berg and co-workers. These authors modified the Cochrane list to better suit the type of studies they examined. For example, the Cochrane list contained the item “description of and acceptable dropout rate”, which was changed into “description of dropout rate plus comparison of dropouts with completers”. In addition, they deleted some items because they were not relevant for Web-based interventions [ ]. For our review, one additional change was made. “Long-term follow-up measurement” was defined as an outcome assessment more than 3 months after the post-intervention measurement. The final list of criteria included 13 items relating to the selection of patients, the intervention, outcome measurements, and statistics. The complete list can be found in , in which the outcomes of the methodological quality assessment are shown.
For each study, all criteria were scored with yes, no, or unclear, resulting in a maximum quality score of 13. In line with other researchers , we considered studies obtaining at least two-thirds of the total score (ie, ≥9 points) to be of high quality. Studies scoring 5 to 8 points were rated as moderate quality, and studies scoring lower than 5 points were rated as low quality. Quality assessment was performed by the first author, while the second author assessed the quality of a random sample of 4 studies. The inter-rater reliability was calculated as percentage of agreement on 52 aspects (4x13 criteria). Disagreements between researchers were discussed to reach consensus.
Evaluation of Potential Relevance for Cancer Survivors
To evaluate the relevance of the selected interventions for cancer survivors, we used the 5 factors included as characteristics of cancer survivorship identified by the Institute of Medicine (IOM): surveillance, management of late effects, rehabilitation, psychosocial support, and health promotion . We evaluated whether the interventions reviewed could be mapped onto these 5 features of cancer survivorship care.
Selection of Publications
The initial search yielded 3438 hits. Based on titles and abstracts, 62 publications were selected. The full text of these 62 publications were reviewed, resulting in a selection of 19 publications that met all eligibility criteria [- ]. A review of the reference lists of these publications, as well as the reference lists of the excluded reviews did not result in any additional studies. See for a flow chart of the selection process. For the cancer setting, we found 46 papers that met several of our inclusion criteria, but not all. Reasons for exclusion were diverse, varying from not being an RCT (eg, design papers or non-randomized pilot studies) to inappropriate outcome measures or not being Web-based and/or interactive (eg, a CD-ROM).
Reviewers’ ratings were in agreement for 89.5% (68/76) of the data extraction elements from the sample. This can be considered as a high level of agreement according to the guidelines of Landis and Koch , and justified the decision to have only one of the authors carry out the data extraction for the remaining studies.
All papers were published in year 2000 or later, with most being published after 2005. The 19 publications described 18 unique studies; two papers by Glasgow et al described the same study at different assessment time-points (4 and 12 months, [, ]). Twelve studies were conducted in the United States. The remaining studies took place in Canada (n=2), Korea (n=1), Norway (n=2), and Australia (together with the United States, n=1). Sample sizes at baseline varied between 15 and 1665. In the majority of RCTs, one group was exposed to a Web-based intervention and was compared to control group with usual care (n=7), an information only condition (n=2), an observational control group (n=1), a face-to-face intervention (n=1), both a print material intervention and usual care (n=1), or both a face-to-face intervention and an information only condition (n=1). In two RCTs, two intervention groups were compared with either control group with usual care or enhanced usual care. In one RCT, two groups receiving a Web-based intervention were compared with an information only condition. Finally, in two RCTs, two intervention groups were compared. Those groups received the same basic intervention, but with a different focus (high vs low self-efficacy and lifestyle goals versus structured goals).
Studies included patients with diabetes (n=11), heart failure (n=3), COPD (n=1), cardiovascular disease (n=1), cancer (n=1), and mixed patient groups (heart disease, lung disease, type 2 diabetes; n=1). The overall mean age of the participants was 60 years (SD 8.5 years, range 40-76 years). For the 18 studies that reported on gender, the median percentage of women was 53.1% (range 6.0%-73.3%). Individuals with comorbid conditions were excluded in 7 studies, and 6 studies provided information about comorbidity (eg, mean number of comorbid conditions). Only 6 studies collected information on participants’ prior experience with computers and/or Internet use. Both computer experience and Internet use were assessed with a variety of self-reported questionnaire items, ranging from times per week to years of experience, making it difficult to compare across studies.
Intervention characteristics for both intervention and control groups are described in. The degree of detail provided about the interventions varied greatly across studies. There was large variation in the duration, frequency, and content of the interventions. Duration varied between 1 month and 1 year (mean 23 weeks, SD 19 weeks). The intended frequency or intensity of the interventions was not clearly described in the majority of the papers. In some papers, a schedule for intervention use was proposed [ , , ], whereas in other papers only information about actual use was reported (eg, number of logins, percentage of individuals that used the different intervention elements).
Although the content of the interventions differed, 7 key elements used in the majority of the interventions were identified, including interventions that had significant effects and those that did not. These elements were used in different combinations and were adapted to the specific patient population. The first element was education, which included information about various aspects of the chronic health condition such as medication, nutrition, exercise, coping, and symptom management, provided via electronic newsletters, pamphlets, slides, or a digital library with articles. The second element, self-monitoring, involved uploading or registration of data such as blood glucose levels, blood pressure, medication use, food intake, and exercise behavior. In the study of Nguyen and colleagues for example, individuals had to submit real-time information about dyspnea, cough, and sputum via their computer or smart phone . This was often followed by the third element, feedback/tailored information. Based on the uploaded data, patients received individual feedback, which included individually tailored exercise advice, or a graphical overview of blood glucose levels for example. Other forms of tailored information included access to the medical record, medication reminders, and tips for overcoming personal exercise barriers. Fourth, interventions could include self-management training, involving lessons about the management of symptoms, psychosocial aspects, and fatigue. An important aspect of self-management training was goal setting. The fifth element, found only in interventions involving physical activity, was a personalized exercise program that was adapted on the basis of self-reported and/or objective physical activity data obtained before and during the intervention. The exercise programs took the individual's needs, preferences, and possibilities into account. In the study of McKay and co-workers for example, patients went through a 5-step process to select their personal motivators, goals, preferred activities and schedule, and to identify their personal barriers [ ]. Elements 6 and 7 both involved communication, either with health care providers or with fellow patients, respectively, using communication routes like email, live chat, videoconferences, and discussion boards (forums). Communication with health care providers was often used for questions, encouragement, and emotional support, whereas communication with fellow patients was included to share experiences, exchange information, and provide support. Additionally, elements that were used in only some studies were an educational quiz and periodic reminders for website use.
The overall percentage of dropouts varied between 0.0% and 52.3% (median 17.5%). For the intervention groups (including the control groups that also received a Web-based program) the median dropout rate was 19.7% and for the control groups this was 14.0%. Compliance with the intended intervention varied between 36.6% and 96.0% for the 9 studies that reported on it. The remaining studies did not report compliance, but described aspects of website use, such as number of logins, percentage of people using a certain feature, minutes per session, or percentage of tasks completed. Intervention use varied greatly between studies and participants. All studies that monitored website use found a decline during the intervention period. There was no obvious relationship between dropout rates, compliance, and website use on the one hand, and patient and intervention characteristics on the other hand.
presents patient empowerment and physical activity outcomes and dropout rates. A range of outcome measures was used (eg, different self-efficacy scales, diverse measures of different forms of physical activity).
A total of 13 studies included one or more patient empowerment measures. In 4 studies, patient empowerment increased significantly (P<.05) in the intervention group compared to usual care or observation [, , , ], while in 3 studies this increase was reported for both groups [ , , ] (ie, both the Web-based intervention group and the comparison group improved irrespective of receiving a Web-based, a face-to-face intervention or usual care). In the study of Nguyen et al for example, both the individuals receiving the Web-based intervention and those having personal contact improved on a measure of self-efficacy [ ]. Two studies yielded mixed results, with 1 of 2 outcome measures showing a significant increase [ , ]. For example, Wangberg et al measured both self-efficacy and self-care behavior, but observed improvement only in the latter. The remaining 4 studies did not observe a significant change in patient empowerment [ , , , ] for either the intervention group or the usual care group.
Of the14 studies that assessed physical activity, 2 reported significant improvement (P<.05) for the intervention group compared to usual care [, ] (eg, an increase in the number of individuals who exercised regularly or in physical activity behavior). Increases in physical activity were found for both groups in 6 studies [ - , , , ]. For instance, McKay et al compared their Web-based group with an information only approach. Both groups improved their moderate/vigorous exercise behavior as well as their walking performance. Three studies [ , , ] found mixed results, with one of their outcome measures being non-significant and the others showing a significant increase. For example, Lorig et al found no change in aerobic exercise behavior but did observe an increase in stretch/strength exercise [ ]. Finally, 3 studies did not find any effects on physical activity [ , , ].
|Study||Patient group (sample size)||Study design||Intervention||Follow-up period|
|Artinian et al (2007)||Congestive heart failure|
|Pilot RCT with an intervention group and a comparison group receiving usual care||Home care monitoring system:|
- pamphlet with education about self-care behavior
- medication reminders
- questions & response
- registration of pill taking
|Bond et al (2010)||Diabetes|
|RCT with an intervention group and a comparison group receiving usual care||Focus on self-management and psychosocial well-being:|
- usual care
- instructions (about issues regarding disease management)
- interaction with study nurse
- uploading data & receiving feedback
- online educational discussion group
- peer support via email and instant
|Glasgow et al (2003)||Type 2 diabetes|
|RCT with 3 intervention groups and an Internet information only comparison group (library with articles, automated dietary goal setting, online assessments)||Aspects of information only and:|
(1) Tailored self-management training:
- online professional suggesting tailored strategies
- question and answer with dietician
- blood glucose upload and dietary databases plus graphical feedback
|(2) Peer support:|
- exchange of information, coping strategies, and emotional support on a forum
- live chat
- 5 electronic newsletters
|(3) both 1 and 2|
|Glasgow et al (2010, 2011)||Type 2 diabetes|
|RCT with 2 intervention groups and an enhanced usual care comparison group (health risk appraisal feedback, recommendations of preventive care behavior)||Self-management program with:|
(1) Minimal support:
- goal selection
- progress recording
- community resources
- quiz questions
- motivational tips
- periodic prompting
|4 months and 12 months, respectively|
|(2) Moderate support:|
- aspects of minimal support
- follow-up calls
- invitation for a group visit with
|Kim & Kang (2006)||Type 2 diabetes|
|RCT with an intervention group, a print-material comparison group (booklets with tailored exercise strategies), and a comparison group receiving usual care||Physical activity (PA) intervention:|
- general information
- assessment tools for physical and
psychological readiness for exercise
- stage-based individual information about goal setting and exercise planning
- question and answer board
- interactive and animated features
- exercise test (in the lab), followed by an
individualized physical activity prescription
|Liebreich et al (2009)||Type 2 diabetes|
|RCT with an intervention group and a comparison group receiving usual care||Website and counselling:|
- link to clinical practice guidelines for physical activity
- interactive features (physical activity
logbook, forum, email counselling)
- weekly topic (eg, goal setting, time
|Lorig et al (2006)||Heart & lung disease, type 2 diabetes|
|RCT with an intervention group and a comparison group receiving usual care||Self-management program and usual care:|
- individual exercise program
- management of symptoms, fatigue,
- motivational email reminders
- overview of medications
- interaction with moderator
- action planning
|Lorig et al (2010)||Type 2 diabetes|
|RCT with 2 intervention groups (only difference was email support; analyzed together) and a comparison group receiving usual care||Self-management program:|
- 6 weekly sessions with different topics
- bulletin board
- exercise logs and monitoring tools
- communication with facilitators
|McKay et al (2001)||Type 2 diabetes|
|RCT with an intervention group and an information only comparison group (library articles, glucose tracking plus feedback)||PA intervention:|
- feedback on baseline activity levels
- personalized PA program and PA database
- personal coach counselling and support
- communication with other intervention participants
|Nguyen et al (2008)||COPD|
|RCT with an intervention group and a face-to-face intervention comparison group (same intervention components)||Self-management program:|
- education and skills training
- tailored exercise planning
- self-monitoring of symptoms and exercise
- personalized feedback
|Nguyen et al (2012)||COPD|
|RCT with an intervention group, a face-to-face intervention group and a general health education comparison group (home visit, monthly face-to-face education sessions, phone calls with health information)||Self-management program (same components for online and face-to-face group):|
- dyspnea and exercise consultation at home (once)
- individualized exercise plan
- self-monitoring and reinforcement
- skills training
- peer interactions
|Richardson et al (2007)||Type 2 diabetes|
|Pilot RCT with 2 intervention groups (with a focus on either lifestyle goals or structured goals)||Pedometer-based walking program with a focus on:|
(1) Lifestyle goals (targeting accumulated steps)
- access to a personally-tailored Stepping Up to Health Web page
- tailored motivational messages
- tips about managing diabetes
- automatically calculated goals (based on pedometer results)
- feedback about performance toward goals
|(2) Structured goals (only targeting steps taken during bouts of at least 10 minutes with at least 60 steps per minute):|
- intervention see (1)
|Ross et al (2004)||Congestive heart failure|
|RCT with an intervention group and a comparison group receiving usual care||Secure Web-interface to 3 features, and reminders for system use:|
- medical record
- educational guide
- messaging system
|Ruland et al (2012)||Breast and prostate cancer|
|RCT with an intervention group and an information only comparison group||Self-management program:|
- self-monitoring plus tailored self-management support
- communication with other patients and expert nurses
- diary for personal notes
|Tomita et al (2009)||Heart failure|
|RCT with an intervention group and a comparison group receiving usual care||Self-management program in addition to usual care:|
- informational support
- recording vital signs and exercise
- appraisal support (feedback)
- emotional support
|Trief et al (2007)||Diabetes|
|RCT with an intervention group and a comparison group receiving usual care||Telemedicine case management:|
- access to educational materials
- upload data on blood glucose and blood pressure readings
- videoconference with a nurse case manager and dietician (to educate patients, facilitate goal setting/self-management, and discuss concerns)
|Wangberg (2008)||Type 2 diabetes|
|RCT with 2 intervention groups (with a focus on either high or low self-efficacy)||Self-care intervention tailored to either high or low self-efficacy:|
- behavior exercises (including monitoring and graphic feedback)
- quizzes with feedback
- videos of peers
- videos of lectures from health personnel
|Zutz et al (2007)||Cardiovascular disease|
|Pilot RCT with an intervention group and an observational control comparison group (no contact with either the research staff or the hospital)||Cardiac rehabilitation program:|
- chat sessions with health care professionals
- education sessions (slides)
- monitoring of blood and exercise
- group chat sessions
|Study||Patient empowerment outcome measurec||Patient empowerment outcomesa,c||Physical activity outcome measurec||Physical activity outcomesa,c||Dropout rate (overall)|
|Artinian et al (2007)||Revised Heart Failure Self-Care Behavior Scale||Self-care + (P=.02)e||6 Minutes Walking Test (6MWT)||Exercise performance - (P=.42)||0.0%|
|Bond et al (2010)||Diabetes Empowerment Scale||Self-efficacy + (P<.05)b,e||X||X||0.0%|
|Glasgow et al (2003)||X||X||Physical Activity Scale for the Elderly||Physical activity - (P=.41)||18.0%|
|Glasgow et al (2010)|
Glasgow et al (2011)
|Diabetes Self-Efficacy scale||Self-efficacy|
|Community Health Activities Model Program for Seniors Questionnaire||Caloric expenditure in physical activity|
4 months: + (P=.04)d
|4 months |
|12 months + (P<.10)b, f||12 months: + (P<.05)b,d||12 months |
|Kim & Kang (2006)||X||X||Self-report instrument adapted from the 7-day physical activity questionnaire (frequency, duration, intensity)||Metabolic equivalents (MET) x hours/week + (P<.001)d||0.0%|
|Liebreich et al (2009)||Likert scale (1-5); 12 items||Self-efficacy - (P=.31)||Godin Leisure-Time Exercise Questionnaire (GLTEQ)||MET minutes + (P=.04)d||10.3%|
|Likert scale (1-5); 4 items||Behaviour capacity + (P=.001)d||GLTEQ||Unweighted minutes + (P=.01)d|
|Incorporated in GLTEQ (times/week, average time per session)||Resistance training - (P=.06)|
|Lorig et al (2006)||Likert scale (1-10)||Self-efficacy - (P=.06)||Scale (0-4) measuring minutes of exercise per week||Stretch/strength exercise + (P=.02)d||18.8%|
|Aerobic exercise - (P=.70)|
|Lorig et al (2010)||Patient Activation Measure||Patient activation + (P=.01)d||A physical activities scale (minutes/week)||Aerobic exercise - (P>.05)b||15.8%|
|Diabetes Self-Efficacy scale||Self-efficacy + (P=.02)d|
|McKay et al (2001)||X||X||Behavioural Risk Factor Surveillance System||Moderate/vigorous exercise + (P<.001)e||12.7%|
|Walking + (P<.001)e|
|Nguyen et al (2008)||Single question on a 0- to 10- point response scale||Self-efficacy + (P=.02)e||Self-report (frequency & duration)||Endurance exercise + (P=.001)f||24.0%|
|Strength exercise + (P<.001)f|
|List of 5 descriptions||Stages of change + (P=.05)f|
|6MWT||Exercise performance + (P=.05)d|
|Nguyen et al (2012)||Single question on a 0- to 10- point response scale||Self-efficacy|
|Incremental treadmill test||Exercise performance|
|Lifting a wooden dowel||Arm endurance|
|Self-report (frequency & duration)||Endurance duration|
|Richardson et al (2007)||X||X||Pedometer (Omron HJ-720IT)||Total steps + (P=.003)d||14.0%|
|Bout steps + (P<.001)d|
|Ross et al (2004)||Kansas City Cardiomyopathy Questionnaire (self-efficacy domain)||Self-efficacy - (P=0.08)||X||X||24.0%|
|Ruland et al (2012)||Cancer Behavior Inventory version 2.0||Self-efficacy|
|Tomita et al (2009)||X||X||Self-reported frequency of exercise; participants exercising 2-3 times/week or more were seen as exercisers||Number of exercisers + ( P=.001)d||19.8%|
|Trief et al (2007)||Diabetes Self-Efficacy scale||Self-efficacy + (P<.001)d||X||X||52.3%|
|Wangberg (2008)||Perceived Competence Scales||Self-efficacy - (P=.17)||X||X||45.9%|
|Summary of Diabetes Self-Care Activities measure||Self-care behavior + (P=.026)d|
|Zutz et al (2007)||Likert scoring||Self-efficacy (exercise- specific) + (P<.05)b,d||Minnesota Leisure Time|
Physical Activity Questionnaire
|Physical activity + (P<.05)b,d||6.7%|
|Symptom-limited treadmill exercise stress test||Exercise capacity + (P<.05)b,d|
a+ is a positive effect; - is no effect
bThe researchers did not provide specific P values.
dPositive effect for the Web-based intervention group(s) only
ePositive effect for all groups (including usual care)
fPositive effect for the Web-based intervention group(s) and other intervention groups
Barriers for and Facilitators of Intervention Use and Reported Users’ Experiences
Five studies reported on perceived barriers, whereas no studies reported on perceived facilitators of the use of interactive, Web-based interventions. Perceived barriers were typically of a technical nature, including problems with Internet connection, slow loading of website, security concerns, discomfort with using the computer or Internet, and problems with related hardware (eg, PDA, monitor). Ten studies described some users’ experiences, for example, satisfaction scores and a judgment of intervention content. In general, patient satisfaction was high. The personalized nature of the interventions was often cited by participants as being important. In one study , nurses and physicians reported that their workload did not increase as a result of the intervention.
The concordance between reviewers in rating the methodological quality for the sample of papers evaluated was high (90.3% (47/52), ). For this reason, the first researcher independently performed the quality assessment for the remainder of the studies. The two papers of Glasgow that described the same study were judged together for methodological quality. shows that 3 of 18 studies [ , , , ] obtained a score of 9 or higher, indicating good methodological quality. Two studies were of low quality [ , ] and the remaining studies were of moderate quality, with most studies scoring a 5 or 6. All studies specified eligibility criteria and employed a comparable timing of outcome assessment for the different groups. The majority of the studies reported dropout rates, including a comparison between completers and non-completers, and gave point estimates together with measures of variability. Only a minority of studies (maximum n=7) provided information about the method of randomization, described their intervention explicitly, performed a power calculation and used an intention-to-treat approach to the data analysis. Most studies were unclear about concealing treatment allocation and blinding of the outcome assessor. In one study, groups were not similar at baseline, and for one study this was not clear. Only 2 studies described a long-term follow-up measurement. Because 12 out of 18 studies were of moderate quality, it was not possible to determine whether differences in outcomes were related to methodological quality.
|Artinian et al (2007)||√||X||?||√||X||√||?||√c||X||√||X||X||√||6|
|Bond et al (2010)||√||X||?||√||X||X||√||√c||X||√||√||X||√||7|
|Glasgow et al (2003)||√||X||?||√||X||X||?||√||X||√||√||X||√||5|
|Glasgow et al (2010, 2011)||√||√||?||√||√||√||?||√||X||√||√||√||√||10|
|Kim & Kang (2006)||√||X||?||√||X||X||?||√c||X||√||X||X||√||5|
|Liebreich et al (2009)||√||X||?||X||X||√||?||X||X||√||X||X||√||4|
|Lorig et al (2006)||√||X||?||√||√||X||?||√||√||√||X||√||√||8|
|Lorig et al (2010)||√||√||?||√||X||X||?||√||√||√||X||√||√||8|
|McKay et al (2001)||√||√||?||√||X||X||?||√||X||√||X||X||√||6|
|Nguyen et al (2008)||√||√||√||√||√||√||√||√||X||√||X||√||√||11|
|Nguyen et al (2012)||√||X||X||√||√||√||√||√||X||√||√||√||√||10|
|Richardson et al (2007)||√||X||?||?||√||√||?||X||X||√||X||X||√||5|
|Ross et al (2004)||√||√||?||√||X||X||?||X||X||√||X||X||X||4|
|Ruland et al (2012)||√||√||?||√||X||√||?||X||X||√||√||√||√||8|
|Tomita et al (2009)||√||X||?||√||√||√||?||X||X||√||√||√||X||7|
|Trief et al (2007)||√||X||?||√||X||X||√||√||X||√||X||√||X||6|
|Zutz et al (2007)||√||X||?||√||√||√||?||X||X||√||X||X||√||6|
a1=specification of eligibility criteria; 2=method of randomization explained; 3=treatment allocation concealed; 4=groups similar at baseline; 5=explicit description of interventions; 6=description of compliance; 7=outcome assessor blinded; 8=description of dropout and comparison with completers; 9=long-term follow-up (> 3 months after post-intervention assessment); 10=timing of outcome assessment comparable; 11=sample size described with power calculation; 12=intention-to-treat analysis; 13=point estimates and measures of variability
b√=reported item; X=unreported item; ?=unclear item
cDropout rate was 0%
dMaximum score was 13
Evaluation of Potential Relevance for Cancer Survivors
Our judgement of the relevance of the intervention elements for the cancer survivorship setting was based on their Web-based application (as opposed to their usefulness, in general).(the more cancer-related recommendations) and (the more health-related recommendations) show how these intervention elements could be mapped onto the recommendations for survivorship care as described by the IOM [ ]. Five intervention elements contributed to all recommendations, and two elements (personal exercise program and communication with fellow patients) would only be inappropriate for long-term follow-up/surveillance. The specific content of each element when adapted to the oncology setting depended on the recommendation for which it was used. For example, information provision will differ for surveillance versus healthy lifestyle recommendations. Similarly, a personal exercise plan for rehabilitation after surgery differs from an exercise plan that aims to enhance general physical activity levels.
|Recommendations for survivorship care|
|Elements of Web-based intervention||Long-term follow-up/surveillance||Management of (late) effects|
|Education||Information about reasons for surveillance||Information about possible late effects of cancer treatment|
|Recommendations for self-screening|
|Self-monitoring||Reporting results of self-screening||Upload of relevant vital signs (eg, pain scores, blood values)|
|Feedback/Tailored information||A personal follow-up schedule with frequency and type of screening||Advice for managing (late) effects as identified by self-monitoring data|
|Feedback on reported self-screening|
|Self-management training||Training aimed at performing regular self-screening||Training to learn to cope with late effects of cancer treatment|
|Personal exercise program||X||Individual exercise advice to prevent or reduce (late) effects, taking into account a survivor\'s specific needs and preferences|
|Communication with health care provider||Possibility to ask questions about follow-up and self-screening||Possibility to ask questions about symptoms and how to deal with them|
|Communication with fellow patients||X||Share experiences and tips about managing (late) effects|
aX=application not relevant
|Recommendations for survivorship care|
|Elements of Web-based intervention||Rehabilitation||Psychosocial support||Health promotion|
|Education||Information about the importance of and possibilities for rehabilitation||Information about possible psychosocial problems and possibilities to solve them||Information about the importance of and ways to obtain a healthy lifestyle (eg, physical activity, nutrition, smoking cessation)|
|Self-monitoring||Upload of relevant vital signs (eg, blood pressure, lung function) or exercise behavior (either self-reported or objective)||Questionnaire(s) measuring psychosocial aspects||Upload of relevant data such as food intake and exercise behavior|
|Feedback/Tailored information||Rehabilitation advice based on self-monitoring data||Advice for dealing with psychosocial problems as identified with questionnaires; following the stepped care principle||Health advice based on uploaded data; following the stepped care principle|
|Self-management training||Training to learn to sustain doing rehabilitation exercises||Training aimed at coping with psychosocial problems like anger, fear or frustration||Training aimed at obtaining and sustaining a healthy lifestyle|
|Personal exercise program||Individual exercise advice aimed at rehabilitation, taking into account a survivor\'s specific needs and preferences||Individual exercise advice, taking into account a survivor\'s specific needs and preferences||Individual exercise advice, taking into account a survivor\'s specific needs and preferences|
|Communication with health care provider||Possibility to ask questions about rehabilitation||Possibility to ask questions about psychosocial problems; receiving support||Possibility to ask questions about exercise advice|
|Communication with fellow patients||Share experiences and tips about rehabilitation||Share experiences and tips about dealing with psychosocial problems||Share experiences and tips about health behavior|
|Provide support||Provide support|
In this paper we have systematically reviewed the empirical literature on Web-based interventions for people with diabetes, COPD, heart failure, cardiovascular disease, and cancer, and have evaluated their potential relevance for cancer survivors. Nineteen publications covering 18 unique studies were included in this review. The RCTs varied greatly in content, duration, and frequency. Significant, positive effects on patient empowerment were found in 4 studies and 2 studies reported positive effects on physical activity. The remaining studies reported mixed results or no significant differences between intervention and comparison groups (ie, either both groups or neither group improved) on these outcomes. The information we could obtain about barriers and facilitators for intervention use and users’ experiences was limited. Nevertheless, we identified 7 elements that were common for the majority of interventions: education, self-monitoring, feedback/tailored information, self-management training, personal exercise program, and communication (with either health care providers or fellow patients). We were able to map these elements onto eHealth features for the recommendations for survivorship care of the IOM.
The 7 common intervention elements were used in different combinations and were adapted to the specific patient population. It is therefore not possible to make a judgment about the individual contribution of these elements to intervention outcomes. Future studies should be more structured, in order to determine the role of individual intervention elements and should also take the duration and frequency of interventions into account. In most studies no intervention schedule was prescribed. Rather, the intensity, frequency, and duration of website use were determined by the participants themselves. In contrast, structured rehabilitation programs usually have schedules to which patients are expected to adhere (eg, performing moderate intensity physical activity (running or cycling) for 30 minutes, 3 times a week, during a 12-week period). It is debatable whether Web-based interventions should or should not have a structured program, but it is conceivable that a certain combination of duration and frequency is optimal for achieving improved patient empowerment and physical activity. A recent review of Web-based interventions for type 2 diabetes  indicated that interventions of longer duration (more than 12 weeks) resulted in better outcomes, and it is likely that the same is valid for cancer survivors. However, future studies need to confirm this.
The relative importance and value of intervention elements, duration, and frequency on outcomes is not yet clear. Other factors may also have played a role in the large variation in patient empowerment and physical activity outcomes observed in the studies reviewed. These include the different measurement tools that were used within and between studies, different sample sizes and different periods between the start of the intervention and the post-intervention measurement. To facilitate future meta-analyses, new investigations should preferably use uniform outcome measures and time intervals for the outcome assessment. The need for a uniform measure of patient empowerment was also pointed out in a paper that discussed the role of assessing patient empowerment in health care evaluation .
Another issue to be considered is that, in the majority of studies where no significant differences between groups were observed, significant, positive effects were found for all groups. In many of these studies, the comparison group(s) received an intervention as well. This may have limited the possibility of detecting an effect in favour of the Web-based interventions. More generally, it is becoming increasingly difficult to establish appropriate control groups, because the usual care situation is evolving rapidly. Although previous studies have shown that effects on knowledge and behavior change were higher for individuals using a Web-based intervention than for individuals using a non-Web-based intervention , more work is needed to determine whether this also applies to cancer survivors.
It would have been useful if the RCTs reviewed had provided more information on barriers and facilitators for intervention use. Insight into these factors is very important, because Web-based interventions are often characterised by high dropout rates . Dropout can refer to patients being lost to follow-up or to patients not using the intervention. Bennett and Glasgow indicated that an important reason for dropout is loss of interest [ ]. Furthermore, 2 literature reviews showed that peer support, counsellor support, email and phone contact, frequent website updates, record keeping, and individualized feedback were related to sustained intervention use (and conversely, to less dropout, [ , ]). Most of these components were present in the studies included in the current review. The mean percentage of dropouts in the Web-based intervention groups of the studies reviewed was 19.7%, which is comparable to the dropout rate found in another review (21.0%, [ ]). More research on program adherence is needed. Or, in other words, it should be determined “what works and why” [ ].
The assessment of the methodological quality of the studies reviewed suggests a number of areas in which there is room for improvement. Future RCTs in the field of Web-based interventions could be improved by clearly describing the method of randomization, concealment of treatment allocation, and an adequate description of sample size calculation. Additionally, researchers should preferably describe explicitly their intervention(s), including specific information about intervention elements, length, frequency, and duration. Studies should carry out the statistical analysis on an intention-to-treat basis (as opposed to only analyzing the participants who completed the intervention). This is important because participants who complete an intervention may differ from those who do not, as a result of which intervention effects may be over- or underestimated. Because it is often the goal to not only enhance patient empowerment and facilitate a physically active lifestyle in the short-term, but to sustain these outcomes over a longer period of time, it is important that RCTs include not only immediate post-intervention outcome assessment, but also longer-term follow-up assessments.
Web-based interventions are being developed at a rapid pace. This is also true for Web-based interventions for cancer survivors. In this review we identified only 1 paper in the cancer field that met our eligibility criteria. Recently, however, positive results of a Web-based intervention to reduce depression in cancer survivors , and of a Web-based, tailored education program to reduce cancer-related fatigue and anxiety [ ] have been reported. Several additional RCT’s of Web-based interventions for cancer patients and survivors are currently on-going [ ]. It is likely that in several years there will be sufficient, mature studies to facilitate a formal meta-analysis to more precisely determine the effects of Web-based interventions for both chronic diseases and cancer, rather than the more qualitative review presented here.
Although we identified 7 elements of eHealth interventions that may be relevant for cancer survivors, based on the available evidence, we could not determine which of these elements are the most important and effective. It was also unclear which combinations of intervention elements would be optimal. However, the benefit of the educational element for cancer survivors was supported by a review, which showed that cancer survivors who received sufficient information reported a better quality of life . An emerging approach in cancer survivorship that may encompass or incorporate many of the intervention elements described in the eHealth literature is the use of a survivorship care plan. Such a plan includes a summary of the individual patient’s diagnosis and treatment, as well as recommendations for appropriate follow-up care [ ]. Currently, survivorship care plans are typically provided on paper, and consequently are quite static documents. There is no reason why they cannot be adapted for eHealth use, including interactive elements.
In conclusion, our review suggests that Web-based, interactive interventions have a beneficial effect on patient empowerment and/or physical activity in people with various chronic conditions. Program elements that were frequently observed included education, self-monitoring, feedback/tailored information, self-management training, personal exercise program, and communication (with either health care providers or fellow patients). Although the results of these studies did not necessarily differ from those of traditional interventions, it is likely that the elements increased patient centeredness and efficiency of the interventions. Empowered individuals who are physically active are likely to have a better health status and quality of life, therefore the use of interactive Internet interventions in this field would appear promising. Further research is needed to establish optimal intervention characteristics and specific effects in cancer survivor populations. Future studies should also identify perceived barriers for and facilitators of the use of Web-based interventions. The studies that have been conducted in other chronic diseases are likely to constitute a basis for the development of an interactive, Web-based intervention to effectively empower the rapidly growing number cancer survivors.
This research was supported by Alpe d'HuZes, a foundation which is part of the Dutch Cancer Society (KWF Kankerbestrijding). This study was part of the A-CaRe Program . The authors acknowledge the A-CaRe2Move Research Group.
Conflicts of Interest
Multimedia Appendix 1
Search strategy in PubMed.PDF File (Adobe PDF File), 28KB
- Verdecchia A, Francisci S, Brenner H, Gatta G, Micheli A, Mangone L, EUROCARE-4 Working Group. Recent cancer survival in Europe: a 2000-02 period analysis of EUROCARE-4 data. Lancet Oncol 2007 Sep;8(9):784-796. [CrossRef] [Medline]
- Signaleringscommissie Kanker van KWF Kankerbestrijding. Kanker in Nederland. Trends en prognoses. Oisterwijk: VDB Almedeon bv; 2011.
- Alfano CM, Ganz PA, Rowland JH, Hahn EE. Cancer survivorship and cancer rehabilitation: revitalizing the link. J Clin Oncol 2012 Mar 20;30(9):904-906. [CrossRef] [Medline]
- Hewitt M, Greenfield S, Stovall E. From cancer patient to cancer survivor lost in transition. Washington, DC: National Academies Press; 2006.
- Aujoulat I, d'Hoore W, Deccache A. Patient empowerment in theory and practice: polysemy or cacophony? Patient Educ Couns 2007 Apr;66(1):13-20. [CrossRef] [Medline]
- Anderson RM, Funnell MM. Patient empowerment: myths and misconceptions. Patient Educ Couns 2010 Jun;79(3):277-282 [FREE Full text] [CrossRef] [Medline]
- Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA 2002 Nov 20;288(19):2469-2475. [Medline]
- Neuhauser D. The coming third health care revolution: personal empowerment. Qual Manag Health Care 2003 Jul;12(3):171-84; discussion 185. [Medline]
- Fong DY, Ho JW, Hui BP, Lee AM, Macfarlane DJ, Leung SS, et al. Physical activity for cancer survivors: meta-analysis of randomised controlled trials. BMJ 2012;344:e70 [FREE Full text] [Medline]
- Speck RM, Courneya KS, Mâsse LC, Duval S, Schmitz KH. An update of controlled physical activity trials in cancer survivors: a systematic review and meta-analysis. J Cancer Surviv 2010 Jun;4(2):87-100. [CrossRef] [Medline]
- Spence RR, Heesch KC, Brown WJ. Exercise and cancer rehabilitation: a systematic review. Cancer Treat Rev 2010 Apr;36(2):185-194. [CrossRef] [Medline]
- Hamel LM, Robbins LB, Wilbur J. Computer- and web-based interventions to increase preadolescent and adolescent physical activity: a systematic review. J Adv Nurs 2011 Feb;67(2):251-268. [CrossRef] [Medline]
- Samoocha D, Bruinvels DJ, Elbers NA, Anema JR, van der Beek AJ. Effectiveness of web-based interventions on patient empowerment: a systematic review and meta-analysis. J Med Internet Res 2010;12(2):e23 [FREE Full text] [CrossRef] [Medline]
- Klemm P, Bunnell D, Cullen M, Soneji R, Gibbons P, Holecek A. Online cancer support groups: a review of the research literature. Comput Inform Nurs 2003 May;21(3):136-142. [Medline]
- Ryhänen AM, Siekkinen M, Rankinen S, Korvenranta H, Leino-Kilpi H. The effects of Internet or interactive computer-based patient education in the field of breast cancer: a systematic literature review. Patient Educ Couns 2010 Apr;79(1):5-13. [CrossRef] [Medline]
- van den Berg MH, Schoones JW, Vliet Vlieland TP. Internet-based physical activity interventions: a systematic review of the literature. J Med Internet Res 2007;9(3):e26 [FREE Full text] [CrossRef] [Medline]
- van Tulder MW, Assendelft WJ, Koes BW, Bouter LM. Method guidelines for systematic reviews in the Cochrane Collaboration Back Review Group for Spinal Disorders. Spine (Phila Pa 1976) 1997 Oct 15;22(20):2323-2330. [Medline]
- Artinian NT, Harden JK, Kronenberg MW, Vander Wal JS, Daher E, Stephens Q, et al. Pilot study of a Web-based compliance monitoring device for patients with congestive heart failure. Heart Lung 2003 Jul;32(4):226-233. [Medline]
- Bond GE, Burr RL, Wolf FM, Feldt K. The effects of a web-based intervention on psychosocial well-being among adults aged 60 and older with diabetes: a randomized trial. Diabetes Educ 2010 May;36(3):446-456. [CrossRef] [Medline]
- Glasgow RE, Boles SM, McKay HG, Feil EG, Barrera M. The D-Net diabetes self-management program: long-term implementation, outcomes, and generalization results. Prev Med 2003 Apr;36(4):410-419. [Medline]
- Glasgow RE, Kurz D, King D, Dickman JM, Faber AJ, Halterman E, et al. Outcomes of minimal and moderate support versions of an internet-based diabetes self-management support program. J Gen Intern Med 2010 Dec;25(12):1315-1322 [FREE Full text] [CrossRef] [Medline]
- Glasgow RE, Kurz D, King D, Dickman JM, Faber AJ, Halterman E, et al. Twelve-month outcomes of an Internet-based diabetes self-management support program. Patient Educ Couns 2012 Apr;87(1):81-92. [CrossRef] [Medline]
- Kim CJ, Kang DH. Utility of a Web-based intervention for individuals with type 2 diabetes: the impact on physical activity levels and glycemic control. Comput Inform Nurs 2006 Nov;24(6):337-345. [Medline]
- Liebreich T, Plotnikoff RC, Courneya KS, Boulé N. Diabetes NetPLAY: A physical activity website and linked email counselling randomized intervention for individuals with type 2 diabetes. Int J Behav Nutr Phys Act 2009;6:18 [FREE Full text] [CrossRef] [Medline]
- Lorig K, Ritter PL, Laurent DD, Plant K, Green M, Jernigan VB, et al. Online diabetes self-management program: a randomized study. Diabetes Care 2010 Jun;33(6):1275-1281 [FREE Full text] [CrossRef] [Medline]
- Lorig KR, Ritter PL, Laurent DD, Plant K. Internet-based chronic disease self-management: a randomized trial. Med Care 2006 Nov;44(11):964-971. [CrossRef] [Medline]
- McKay HG, King D, Eakin EG, Seeley JR, Glasgow RE. The diabetes network internet-based physical activity intervention: a randomized pilot study. Diabetes Care 2001 Aug;24(8):1328-1334. [Medline]
- Nguyen HQ, Donesky-Cuenco D, Wolpin S, Reinke LF, Benditt JO, Paul SM, et al. Randomized controlled trial of an internet-based versus face-to-face dyspnea self-management program for patients with chronic obstructive pulmonary disease: pilot study. J Med Internet Res 2008;10(2):e9 [FREE Full text] [CrossRef] [Medline]
- Nguyen HQ, Donesky D, Reinke LF, Wolpin S, Chyall L, Benditt JO, et al. Internet-based dyspnea self-management support for patients with chronic obstructive pulmonary disease. J Pain Symptom Manage 2012 Oct 13. [CrossRef] [Medline]
- Richardson CR, Mehari KS, McIntyre LG, Janney AW, Fortlage LA, Sen A, et al. A randomized trial comparing structured and lifestyle goals in an internet-mediated walking program for people with type 2 diabetes. Int J Behav Nutr Phys Act 2007;4:59 [FREE Full text] [CrossRef] [Medline]
- Ross SE, Moore LA, Earnest MA, Wittevrongel L, Lin CT. Providing a web-based online medical record with electronic communication capabilities to patients with congestive heart failure: randomized trial. J Med Internet Res 2004 May 14;6(2):e12 [FREE Full text] [CrossRef] [Medline]
- Ruland CM, Andersen T, Jeneson A, Moore S, Grimsbø GH, Børøsund E, et al. Effects of an internet support system to assist cancer patients in reducing symptom distress: a randomized controlled trial. Cancer Nurs 2013;36(1):6-17. [CrossRef] [Medline]
- Tomita MR, Tsai BM, Fisher NM, Kumar NA, Wilding G, Stanton K, et al. Effects of multidisciplinary Internet-based program on management of heart failure. J Multidiscip Healthc 2008 Dec 1;2009(2):13-21 [FREE Full text] [Medline]
- Trief PM, Teresi JA, Izquierdo R, Morin PC, Goland R, Field L, et al. Psychosocial outcomes of telemedicine case management for elderly patients with diabetes: the randomized IDEATel trial. Diabetes Care 2007 May;30(5):1266-1268. [CrossRef] [Medline]
- Wangberg SC. An Internet-based diabetes self-care intervention tailored to self-efficacy. Health Educ Res 2008 Feb;23(1):170-179 [FREE Full text] [CrossRef] [Medline]
- Zutz A, Ignaszewski A, Bates J, Lear SA. Utilization of the internet to deliver cardiac rehabilitation at a distance: a pilot study. Telemed J E Health 2007 Jun;13(3):323-330. [CrossRef] [Medline]
- Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977 Mar;33(1):159-174. [Medline]
- Ramadas A, Quek KF, Chan CK, Oldenburg B. Web-based interventions for the management of type 2 diabetes mellitus: a systematic review of recent evidence. Int J Med Inform 2011 Jun;80(6):389-405. [CrossRef] [Medline]
- McAllister M, Dunn G, Payne K, Davies L, Todd C. Patient empowerment: the need to consider it as a measurable patient-reported outcome for chronic conditions. BMC Health Serv Res 2012;12:157 [FREE Full text] [CrossRef] [Medline]
- Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The effectiveness of Web-based vs. non-Web-based interventions: a meta-analysis of behavioral change outcomes. J Med Internet Res 2004 Nov 10;6(4):e40 [FREE Full text] [CrossRef] [Medline]
- Eysenbach G. The law of attrition. J Med Internet Res 2005;7(1):e11 [FREE Full text] [CrossRef] [Medline]
- Bennett GG, Glasgow RE. The delivery of public health interventions via the Internet: actualizing their potential. Annu Rev Public Health 2009;30:273-292. [CrossRef] [Medline]
- Brouwer W, Kroeze W, Crutzen R, de Nooijer J, de Vries NK, Brug J, et al. Which intervention characteristics are related to more exposure to internet-delivered healthy lifestyle promotion interventions? A systematic review. J Med Internet Res 2011;13(1):e2 [FREE Full text] [CrossRef] [Medline]
- Schubart JR, Stuckey HL, Ganeshamoorthy A, Sciamanna CN. Chronic health conditions and internet behavioral interventions: a review of factors to enhance user engagement. Comput Inform Nurs 2011 Feb;29(2 Suppl):TC9-T20. [CrossRef] [Medline]
- Duffecy J, Sanford S, Wagner L, Begale M, Nawacki E, Mohr DC. Project onward: an innovative e-health intervention for cancer survivors. Psychooncology 2012 Mar 21. [CrossRef] [Medline]
- Yun YH, Lee KS, Kim YW, Park SY, Lee ES, Noh DY, et al. Web-based tailored education program for disease-free cancer survivors with cancer-related fatigue: a randomized controlled trial. J Clin Oncol 2012 Apr 20;30(12):1296-1303. [CrossRef] [Medline]
- ClinicalTrials.gov. URL: http://www.clinicaltrials.gov/ [accessed 2013-02-15] [WebCite Cache]
- Husson O, Mols F, van de Poll-Franse LV. The relation between information provision and health-related quality of life, anxiety and depression among cancer survivors: a systematic review. Ann Oncol 2011 Apr;22(4):761-772 [FREE Full text] [CrossRef] [Medline]
- A-CaRe. URL: http://www.a-care.org/home/ [accessed 2013-02-15] [WebCite Cache]
|6MWT: 6 Minutes Walking Test|
|COPD: chronic obstructive pulmonary disease|
|GLTEQ: Godin Leisure-Time Exercise Questionnaire|
|IOM: Institute of Medicine|
|IT: information technology|
|MET: metabolic equivalents|
|PA: physical activity|
|RCT: randomized controlled trial|
Edited by G Eysenbach; submitted 24.07.12; peer-reviewed by C Davis, YM Schoenberger, M Wise; comments to author 16.11.12; revised version received 21.12.12; accepted 18.01.13; published 20.02.13Copyright
©Wilma Kuijpers, Wim G Groen, Neil K Aaronson, Wim H van Harten. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.02.2013.
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