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Self-management can increase self-efficacy and quality of life and improve disease outcomes. Effective self-management may also help reduce the pressure on health care systems. However, patients need support in dealing with their disease and in developing skills to manage the consequences and changes associated with their condition. Web-based self-management support programs have helped patients with cardiovascular disease (CVD) and rheumatoid arthritis (RA), but program use has been low.
This study aimed to identify the patient, disease, and program characteristics that determine whether patients use web-based self-management support programs or not.
A realistic evaluation methodology was used to provide a comprehensive overview of context (patient and disease characteristics), mechanism (program characteristics), and outcome (program use). Secondary data of adult patients with CVD (n=101) and those with RA (n=77) were included in the study. The relationship between context (sex, age, education, employment status, living situation, self-management [measured using Patient Activation Measure-13], quality of life [measured using RAND 36-item health survey], interaction efficacy [measured using the 5-item perceived efficacy in patient-physician interactions], diagnosis, physical comorbidity, and time since diagnosis) and outcome (program use) was analyzed using logistic regression analyses. The relationship between mechanism (program design, implementation strategies, and behavior change techniques [BCTs]) and outcome was analyzed through a qualitative interview study.
This study included 68 nonusers and 111 users of web-based self-management support programs, of which 56.4% (101/179) were diagnosed with CVD and 43.6% (78/179) with RA. Younger age and a lower level of education were associated with program use. An interaction effect was found between program use and diagnosis and 4 quality of life subscales (social functioning, physical role limitations, vitality, and bodily pain). Patients with CVD with higher self-management and quality of life scores were less likely to use the program, whereas patients with RA with higher self-management and quality of life scores were more likely to use the program. Interviews with 10 nonusers, 10 low users, and 18 high users were analyzed to provide insight into the relationship between mechanisms and outcome. Program use was encouraged by an easy-to-use, clear, and transparent design and by recommendations from professionals and email reminders. A total of 5 BCTs were identified as potential mechanisms to promote program use: tailored information, self-reporting behavior, delayed feedback, providing information on peer behavior, and modeling.
This realistic evaluation showed that certain patient, disease, and program characteristics (age, education, diagnosis, program design, type of reminder, and BCTs) are associated with the use of web-based self-management support programs. These results represent the first step in improving the tailoring of web-based self-management support programs. Future research on the interaction between patient and program characteristics should be conducted to improve the tailoring of participants to program components.
Chronic diseases are a major burden for patients, and the growing number of people with (several) chronic conditions puts a strain on our health care systems. The pressure on health care services may be decreased and the quality of life of people with chronic conditions may be improved if these individuals can self-manage their condition and adapt to their situation [
Self-management support interventions have already been developed for a broad range of long-term medical conditions and have shown improvements in self-management and other health outcomes [
We recently developed 2 comprehensive, multicomponent, and theory-based web-based self-management interventions using the intervention mapping framework [
There are many reasons why participants use or do not use a web-based self-management program. Patient characteristics, such as older age, lower education levels, and lower income, have been associated with lower eHealth use [
In this study, we identified the patient, disease, and program characteristics that determine whether patients with CVD and patients with RA use the Vascular View and Coping with RA web-based self-management support programs. The findings can be used to tailor web-based self-management support programs to individual patients and thereby increase their use.
The realist evaluation methodology was used to gain a comprehensive understanding of why patients use or do not use web-based self-management support interventions [
Realistic evaluation: context, potential mechanisms, and outcome. PAM: Patient Activation Measure; PEPPI-5: 5-item version perceived efficacy in patient-physician interactions; RAND-36: RAND 36-item health survey.
This study included data of 2 patient groups with a chronic disease. Patients in the CVD group had experienced a myocardial infarction, cerebrovascular disease, or peripheral artery disease or a combination of these within 2 months to 1 year of the study starting. Patients in the RA group were diagnosed with RA, a chronic autoimmune disease that predominantly affects the joints, before the start of the study. The baseline data were collected at the start of each study. Inclusion criteria were as follows: (1) aged ≥18 years; (2) ability to read and understand Dutch; (3) access to a computer, internet, and email account; and (4) not receiving psychiatric or psychological treatment.
The included patient and disease characteristics are expected to be associated with self-management and might, therefore, be related to program use. The following patient characteristics were studied to determine whether they were associated with program use: sex (male or female), age (years), education (low: no education, primary education, or lower secondary education; intermediate: secondary vocational education; and high: higher education or university), work participation (yes or no), living situation (alone or together), self-management, quality of life, and communication efficacy. Self-management was measured using the Patient Activation Measure (PAM-13), which includes statements about an individual’s knowledge, confidence, and skills for self-management of their behavior in response to their chronic illness and about their level of activation. The PAM-13 scores 13 items on a 5-point scale, with a higher score indicating a higher level of patient activation [
A total of 2 comprehensive, multicomponent, web-based self-management programs were studied for this realistic evaluation: Vascular View and Coping with RA.
Vascular View was developed for patients with CVD [
Coping with RA was developed for patients with RA [
Overview of applied determinants and behavior change techniques per program.
Determinant | Behavior change techniques | Vascular View | Coping with RAa |
Knowledge | Provide general information about health behavior | ✓b | ✓ |
Knowledge | Increase memory and/or understanding of transferred information | ✓ | ✓ |
Awareness | Risk communication | ✓ | ✓ |
Awareness | Self-monitoring of behavior | ✓ | ✓ |
Awareness | Self-report of behavior | N/Ac | ✓ |
Awareness | Delayed feedback of behavior | ✓ | N/A |
Social influence | Provide information about peer behavior | ✓ | ✓ |
Social influence | Mobilize social norm | ✓ | N/A |
Attitude | Re-evaluation of outcomes and self-evaluation | ✓ | N/A |
Attitude | Persuasive communication | ✓ | ✓ |
Attitude | Reward behavioral progress | N/A | ✓ |
Self-efficacy | Modeling | ✓ | ✓ |
Self-efficacy | Practice and guided practice | ✓ | ✓ |
Self-efficacy | Plan coping response | N/A | ✓ |
Self-efficacy | Graded tasks and goal setting | ✓ | N/A |
Self-efficacy | Reattribution training and external attribution of failure | ✓ | N/A |
Intention of behavior | General intention formation | ✓ | N/A |
Intention of behavior | Develop medication schedule | N/A | ✓ |
Intention of behavior | Specific goal setting | ✓ | N/A |
Intention of behavior | Review of general and/or specific goals | ✓ | N/A |
Intention of behavior | Use of social support | N/A | ✓ |
Action control | Use of cues | N/A | ✓ |
Action control | Self-persuasion | N/A | ✓ |
Maintenance | Goals for maintenance | ✓ | N/A |
aRA: rheumatoid arthritis.
b✓: The behavior change technique was included in the program.
cN/A: not applicable.
Program use was a dichotomous outcome and was divided into nonusers (0 or 1 visit) and users (≥2 visits). The cut-off point between users and nonusers was arbitrarily set at 2 visits because this was seen as a reflection of whether a patient would have had the opportunity to benefit from the program.
All quantitative data were analyzed using SPSS Statistics (version 25; IBM Corp). Descriptive analyses were used to describe the patient and disease characteristics of nonusers and users. Differences between the characteristics were tested using 2-tailed
Logistic regression analyses were used to determine which characteristics were associated with program use. Program use (nonuser or user) was the dependent factor. Patient and disease characteristics (sex, age, education, employment status, living situation, self-management, quality of life, interaction efficacy, diagnosis, physical comorbidity, and time since diagnosis) were tested as possible factors. The strength of the relations was interpreted using odds ratios with 95% CIs. Factors with a
Sensitivity analysis was performed to compare the characteristics of users and nonusers in the CVD and RA groups. Logistic regression analyses were performed for all characteristics (sex, age, education, employment status, living situation, self-management, quality of life, interaction efficacy, diagnosis, physical comorbidity, and time since diagnosis) and for diagnosis, characteristic, and diagnosis×characteristic. These analyses determined whether there was an interaction between the diagnosis and characteristic. The strengths of the relationships were interpreted using odds ratios with 95% CI.
As a sequence of efficacy studies of Vascular View and Coping with RA, interviews were conducted to provide insight into (1) why patients used or did not use the web-based program and (2) the experiences with the web-based program among users. The results of the qualitative study on the Coping with RA program have been described elsewhere [
A random selection of Vascular View and Coping with RA users and nonusers were invited for an interview after data on the explorative randomized controlled trials were collected. Purposive sampling was used to select patients regarding the degree to which they used the program. The participants were divided into 3 groups: nonusers, low users, and high users. After providing written consent, each patient was interviewed once via telephone. Semistructured interviews, lasting no longer than 30 minutes, were audio-recorded and anonymized. Interviews were transcribed verbatim and transferred to Excel (Microsoft). A total of 3 themes were determined beforehand: Program design, implementation strategies, and BCTs. The first researcher (ME) thematically analyzed the interviews to identify the potential program characteristics that influence use. First, the verbatim text was read and the relevant parts were marked. Next, the researcher determined barriers and facilitating factors for program use, which were divided into the 3 themes.
We investigated the relations between context, mechanism, and outcome to determine which factors are associated with the use of a web-based self-management support program.
Overview of patient and disease characteristics (context) and program characteristics (potential mechanisms) that influence program use (outcome). Underlined variables are factors associated with program use; italicized variables are factors associated with program use in the interaction effect with diagnosis; and the font size reflects the degree of prediction; *
To analyze the relation between patient and disease characteristics (context) and program use (outcome), 68 patients were defined as nonusers and 111 were defined as users. More users were diagnosed with CVD (63/111, 56.8%) than with RA (48/111, 43.2%). Patient and disease characteristics of the nonuser and user groups are presented in
Characteristics of the users and nonusers in the total group, cardiovascular disease (CVD) group, and rheumatoid arthritis (RA) group.
Characteristics | Total group | CVD group | RA group | |
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Male | 59 (59.6) | 42 (58.3) | 17 (63.0) |
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Female | 52 (65) | 21 (72.4) | 31 (60.8) |
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Low | 21 (77.8) | 14 (82.4) | 7 (70.0) |
|
Intermediate | 40 (51.9) | 16 (47.1) | 24 (55.8) |
|
High | 50 (66.7) | 33 (66.0) | 17 (68) |
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Yes | 51 (66.2) | 24 (60.0) | 27 (73.0) |
|
No | 60 (58.8) | 39 (63.9) | 21 (51.2) |
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|
Alone | 19 (61.3) | 10 (62.5) | 9 (60.0) |
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Together | 92 (62.2) | 53 (62.4) | 39 (61.9) |
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Yes | 50 (61.0) | 24 (60.0) | 26 (61.9) |
|
No | 61 (62.9) | 39 (63.9) | 22 (61.1) |
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|
Nonusers | 64.5 (10.0)a | 65.1 (9.7)b | 63.8 (10.5)c |
|
Users | 60.5 (10.4)d | 61.5 (9.4)e | 59.2 (11.6)f |
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Nonusers | 8.7 (10.6)g | 5.0 (7.9)h | 13.4 (11.9)c |
|
Users | 8.1 (10.6)d | 3.8 (7.7)e | 13.8 (11.2)f |
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Nonusers | 40.2 (4.8)j | 40.7 (4.4)b | 39.5 (5.4)k |
|
Users | 40.4 (5.5)l | 40.4 (5.5)e | 40.3 (5.6)m |
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Nonusers | 21.4 (3.3)j | 21.3 (2.8)b | 21.5 (3.8)k |
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Users | 20.5 (3.3)d | 20.0 (3.6)e | 21.1 (2.9)f |
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Nonusers | 64.0 (27.8)a | 71.3 (25.3)b | 54.3 (28.3)c |
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Users | 68.8 (25.1)d | 70.9 (26.0)p | 66.1 (23.9)f |
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Nonusers | 71.9 (24.1)a | 77.6 (22.2)b | 64.6 (24.8)k |
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Users | 74.9 (22.4)d | 74.4 (26.0)p | 75.5 (16.7)f |
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Nonusers | 51.1 (43.9)a | 62.5 (41.0)b | 36.7 (43.9)k |
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Users | 56.8 (41.1)d | 56.7 (41.2)e | 56.8 (41.5)f |
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Nonusers | 75.1 (40.3)a | 75.4 (40.0)b | 74.7 (41.5)c |
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Users | 80.8 (34.1)d | 78.8 (35.1)e | 83.3 (33.0)f |
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Nonusers | 75.5 (17.0)a | 78.1 (17.4)b | 72.1 (16.1)k |
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Users | 76.4 (13.9)d | 75.7 (15.4)e | 77.4 (11.7)f |
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Nonusers | 58.4 (21.2)a | 62.5 (19.2)b | 53.1 (22.9)k |
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Users | 57.5 (18.9)d | 56.1 (20.4)e | 59.3 (16.9)f |
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Nonusers | 70.0 (26.9)a | 80.2 (23.5)b | 56.9 (25.5)k |
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Users | 72.6 (21.8)d | 75.4 (23.5)e | 68.9 (19.0)f |
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Nonusers | 51.3 (19.1)a | 55.4 (18.1)b | 46.0 (19.4)c |
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Users | 53.5 (19.0)d | 53.3 (19.9)e | 53.8 (17.8)f |
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Nonusers | 47.8 (22.3)a | 51.3 (23.2)b | 43.3 (20.7)k |
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Users | 51.6 (24.8)d | 52.4 (25.3)e | 50.5 (24.5)f |
an=67.
bn=38.
cn=29.
dn=111.
en=63.
fn=48.
gn=66.
hn=37.
iPAM-13: Patient Activation Measure.
jn=68.
kn=30.
ln=110.
mn=47.
nPEPPI-5: 5-item perceived efficacy in patient-physician interactions.
oRAND-36: RAND 36-item health survey.
pn=63.
Univariate analyses showed that age, education, and communication efficacy with health care professionals (5-item perceived efficacy in patient-physician interactions) were associated with the use of web-based self-management interventions (
Results of the univariate logistic regressions for all possible factors for total group.
|
ORa (95% CI) | |
Sex | 0.79 (0.43-1.46) | .46 |
Age | 0.96 (0.93-0.99) | .02b |
Education (reference: low)—intermediate | 0.31 (0.11-0.85) | .02b |
Education (reference: low)—high | 0.57 (0.21-1.60) | .29 |
Employment status | 1.37 (0.74-2.54) | .31 |
Living situation | 1.04 (0.47-2.30) | .93 |
Diagnosis | 0.97 (0.53-1.77) | .97 |
Physical comorbidity | 0.92 (0.50-1.69) | .79 |
Time since diagnosis | 1.00 (0.97-1.02) | .72 |
Self-management (PAMc) | 1.01 (0.95-1.07) | .77 |
Communication efficacy (PEPPId) | 0.92 (0.83-1.01) | .08e |
Physical functioning (RAND-36f) | 1.01 (1.00-1.02) | .23 |
Social functioning (RAND-36) | 1.01 (0.99-1.02) | .40 |
Role physical (RAND-36) | 1.00 (1.00-1.01) | .38 |
Role emotional (RAND-36) | 1.00 (1.00-1.01) | .32 |
Mental health (RAND-36) | 1.00 (0.98-1.02) | .68 |
Vitality (RAND-36) | 1.00 (0.98-1.01) | .78 |
Bodily pain (RAND-36) | 1.01 (0.99-1.02) | .47 |
General health (RAND-36) | 1.01 (0.99-1.02) | .47 |
Health change (RAND-36) | 1.01 (0.99-1.02) | .30 |
aOR: odds ratio.
b
cPAM: Patient Activation Measure.
dPEPPI-5: 5-item perceived efficacy in patient-physician interactions.
e
fRAND-36: RAND 36-item health survey.
Final model of factors associated with the use of web-based self-management programsa.
|
B | SE | ORb (95% CI) | |
Constant | 3.58 | 1.16 | N/Ac | .002 |
Age | −0.04 | 0.017 | 0.96 (0.93-1.00) | .03 |
Education (intermediate vs low) | −1.06 | 0.52 | 0.35 (0.12-0.96) | .04 |
aNagelkerke R2=0.049.
bOR: odds ratio.
cN/A: not applicable.
Sensitivity analysis showed a significant interaction between diagnosis and the RAND-36 subscales social functioning, physical role limitations, vitality, and bodily pain (
Results of the interaction effects between diagnosis (cardiovascular disease and rheumatoid arthritis) and possible factors.
|
ORa (95% CI) | |
Sex | 2.06 (0.54-7.89) | .29 |
Age | 1.00 (0.94-1.07) | .95 |
Education (reference: low)—intermediate | 2.84 (0.37-22.06) | .32 |
Education (reference: low)—high | 2.19 (0.27-17.98) | .47 |
Employment status | 3.04 (0.87-10.66) | .08b |
Living situation | 1.09 (0.22-5.37) | .92 |
Physical comorbidity | 1.22 (0.36-4.18) | .75 |
Time since diagnosis | 1.02 (0.96-1.09) | .50 |
Self-management (PAMc) | 1.04 (0.93-1.17) | .52 |
Communication efficacy (PEPPId) | 1.09 (0.90-1.33) | .39 |
Physical functioning (RAND-36e) | 1.02 (0.99-1.04) | .14b |
Social functioning (RAND-36) | 1.03 (1.00-1.06) | .03f |
Role physical (RAND-36) | 1.02 (1.00-1.03) | .05f |
Role emotional (RAND-36) | 1.00 (0.99-1.02) | .64 |
Mental health (RAND-36) | 1.04 (1.00-1.08) | .08b |
Vitality (RAND-36) | 1.03 (1.00-1.07) | .04f |
Bodily pain (RAND-36) | 1.04 (1.01-1.06) | .02f |
General health (RAND-36) | 1.03 (1.00-1.07) | .09b |
Health change (RAND-36) | 1.01 (0.99-1.04) | .37 |
aOR: odds ratio.
b
cPAM: Patient Activation Measure.
dPEPPI: Perceived Efficacy in Patient-Physician Interactions.
eRAND-36: RAND 36-item health survey.
f
A random sample of study participants was interviewed to gain insight into why they did or did not use the web-based self-management program. In the CVD group, 6 nonusers, 6 low users, and 6 high users were interviewed. In the RA group, 4 nonusers, 4 low users, and 13 high users were interviewed. The results were divided into 3 themes: program design, implementation strategies, and BCTs.
Most interviewees were pleased with the program design. However, some experienced difficulties in using the program, and so they did not use it as often. A search function would make it easier to find relevant information. Several users and nonusers stated that they had overlooked parts of the program; for example, 1 participant only used the diaries because he did not know that training modules were available. Another major reason for not using the program were problems with logging in. These observations indicate that ease of use was an important factor for program use among our respondents.
Explanations given by the respondents as to why they did or did not use the program also revealed factors affecting program use. Several respondents stated that they did not participate for their own benefit but rather to facilitate scientific research. Others used the program following advice from their health care professional or because they were curious and wanted to better understand their disease. The biweekly reminders to fill out the diaries in the Coping with RA program helped many respondents to use the diaries.
Quotes from the interviews with users and nonusers.
|
Barriers | Facilitators |
Program design | “Well, I couldn’t log in. Somehow I really couldn’t, or it wasn’t clear to me. Through the internet I find it very difficult to do.” (Coping with RAa, participant 5) |
“Yes I liked the lay-out. The information was orderly, you could easily click on what you wanted to see. So the program was very well organized.” (Coping with RA, participant 21) |
Implementation strategies | Barriers for implementation were not described. |
“The hospital nurse advised me to use the program.” (Vascular View, participant 1) “If I received an email that said I still had something to do, I always did.” (Coping with RA, participant 8) |
Behavior change techniques | “The program only gives input but I missed feedback options, for example to keep track of my weight.” (Vascular View, participant 16) |
“I wanted information on how to deal with my recent diagnosis.” (Vascular View, participant 7) |
aRA: rheumatoid arthritis.
Comments related to program content were assigned to the relevant BCTs, and some of these BCTs were identified as potential mechanisms affecting program use. The first BCT (providing general information about health behavior) was often mentioned in the interviews. For example, respondents with a long disease history stated that the information was too general. Furthermore, some respondents saw on the overview page that none of the modules contained new or interesting information, and so they did not use the program further. Respondents reported that reliable information was a reason for using the program. The Vascular View program includes a physical activity and nutrition diary (for the self-monitoring of behavior BCT), which was rarely used. One respondent said they had missed a feedback function in the diaries and had already used other, more advanced, mobile apps instead. The pain and fatigue diaries in the Coping with RA program were used more often by respondents (for the self-report of behavior BCT). Patients appreciated the possibility of keeping track of their pain and fatigue and of receiving a graphical overview of their input (the delayed feedback of behavior BCT). Program users also liked the stories and videos of peers (which provided information about peer behavior BCT and modeling BCT). One respondent said that these made her feel recognized and supported and showed her that she was on the right track.
In this realistic evaluation of 2 web-based self-management interventions, we searched for patient, disease, and program characteristics that determine whether patients will use the programs. Regarding the relationship between context and outcome, patient and disease characteristics, younger age, and lower level of education were associated with program use. In addition, 4 quality of life subscales (social function, physical role limitations, vitality, and bodily pain) interacted significantly with the diagnosis group to affect program use. Regarding the relationship between Potential Mechanisms (program characteristics) and outcome, participants indicated that an easy-to-use, clear, and transparent design would motivate them to use the program. Email reminders and recommendations from health care professionals were found to be potential implementation mechanisms for promoting program use. The top five BCT techniques that encouraged interviewees to use the program were (1) tailored information, (2) self-report of behavior, (3) delayed feedback, (4) information about peer behavior, and (5) modeling.
Our findings show that patient and disease characteristics can be used to tailor web-based self-management interventions and, therefore, increase their use. Younger age increased program use in our study, which is in agreement with the results of previous studies. However, in contrast to our finding that a lower level of education increased program use, earlier studies showed that a higher level of education increased program use [
Disease burden can be both mental and physical and is another possible factor related to the use of web-based self-management support programs. Patients with RA have a lower physical quality of life and experience more pain than those with CVD. Individuals with episodic or deteriorating diseases such as RA have different self-management support needs than those with stable chronic diseases [
The study participants provided some recommendations for an effective web-based self-management support program. These recommendations included being easy to use, providing appropriate reminders, tailoring information to the user, allowing patients to self-report their behavior and receive delayed feedback, and providing information about peer behavior and modeling. These results are in line with those of a Delphi study that identified new information and the possibility of monitoring personal progress as important factors promoting the use of an eHealth self-management intervention [
Our results emphasize that one program will not be suitable for every patient. Self-management programs should be tailored to patients’ individual needs. It should also be noted that not all patients can use and benefit from web-based interventions. The validated Self-Management Screening (SeMaS) questionnaire can help identify potential barriers to self-management and can help health care professionals determine their patients’ support needs [
Given the complexity of web-based self-management interventions, realistic evaluations can reveal what makes an intervention work, which a simple cause-and-effect relationship between an intervention and its outcome may not be able to do. This is especially important for eHealth interventions because dropout and nonuse rates are high [
The findings of our realistic evaluation should be considered in the context of several limitations. The principal limitation was that we used retrospective data collected in 2 separate studies. However, both studies were conducted by the same research group and had the same study design. It was already decided in the development phase that the data would be merged for an overarching study; however, we could not include more questions about factors related to program use in the questionnaires. The interviews were conducted to retrieve patients’ experiences, not to identify program characteristics that influence program use. Vascular View and Coping with RA were developed based on BCTs, and most of these were unobtrusively included in the program. In addition, Vascular View and Coping with RA applied different implementation strategies that could have influenced program use, making the programs harder to compare. Therefore, the program characteristics identified in this study are
This realistic evaluation identified contexts and potential mechanisms, in the form of patient, disease, and program characteristics, that are associated with the use of web-based self-management support programs. Our results emphasized the importance of (1) tailoring interventions to patients’ needs (depending on age, education, and program characteristics) to increase program use and (2) considering whether all patients can use eHealth interventions (depending on disease burden and eHealth literacy) and providing alternative self-management support when needed. These results are a first step toward improving the tailoring and use of web-based self-management support programs. Future research into the interaction between patient and program characteristics and how this affects program use should be conducted to improve the tailoring of participants to program components.
Description of the web-based self-management support programs Vascular View and Coping with Rheumatoid Arthritis.
behavior change technique
cardiovascular disease
Patient Activation Measure
rheumatoid arthritis
RAND 36-item health survey
Self-Management Screening
This study was funded by ZonMw, the Netherlands Organization for Health Research and Development (grant 520001001). The authors would like to thank all the patients with cardiovascular disease (CVD) and rheumatoid arthritis (RA) who contributed to this study.
None declared.