Betsie G. I. van Gaal

Early identification of the palliative phase in patients with chronic obstructive pulmonary disease (COPD) and heart failure (HF) remains challenging. Time

Background: 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. Objective: This study aimed to identify the patient, disease, and program characteristics that determine whether patients use web-based self-management support programs or not. Methods: 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. Results: 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. Conclusions: 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.

BACKGROUND 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. OBJECTIVE This study aimed to identify the patient, disease, and program characteristics that determine whether patients use web-based self-management support programs or not. METHODS 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. RESULTS 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. CONCLUSIONS 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.

Background: We conducted a trial to test the electronic Illness Management and Recovery (e-IMR) intervention to provide conclusions on the potential efficacy of eHealth for people with severe mental illness (SMI). In the e-IMR intervention, we used the standard IMR program content and methodology and combined face-to-face sessions with internet-based strategies on the constructed e-IMR internet platform. During the trial, the e-IMR platform was sparsely used. Objective: This study aimed to evaluate the added value of the e-IMR intervention and the barriers and facilitators that can explain the low use of the e-IMR platform. Methods: This process evaluation was designed alongside a multicenter, cluster randomized controlled trial. In this study, we included all available participants and trainers from the intervention arm of the trial. Baseline characteristics were used to compare users with nonusers. Qualitative data were gathered at the end of the semistructured interviews. Using theoretical thematic analyses, the data were analyzed deductively using a pre-existing coding frame. Results: Out of 41 eligible participants and 14 trainers, 27 participants and 11 trainers were interviewed. Of the 27 participants, 10 were identified as users. eHealth components that had added value were the persuasive nature of the goal-tracking sheets, monitoring, and the peer testimonials, which had the potential to enhance group discussions and disclosure by participants. The low use of the e-IMR platform was influenced by the inflexibility of the platform, the lack of information technology (IT) resources, the group context, participants’ low computer skills and disabilities, and the hesitant eHealth attitude of the trainers. Conclusions: The extent of eHealth readiness and correlations with vulnerabilities in persons with SMI need further investigation. This study shows that flexible options were needed for the use of e-IMR components and that options should be provided only in response to a participant’s need. Use of the e-IMR intervention in the future is preconditioned by checking the available IT resources (such as tablets for participants) providing computer or internet guidance to participants outside the group sessions, evaluating the eHealth attitude and skills of trainers, and tailoring eHealth training to increase the skills of future e-IMR trainers. Trial Registration: Netherlands Trial Register NTR4772; https://www.trialregister.nl/trial/4621 International Registered Report Identifier (IRRID): RR2-10.1186/s12913-016-1267-z

Background: Web-based self-management programs have the potential to support patients with cardiovascular disease (CVD) in their self-management (eg, by focusing on behavior change and improving physical activity). The intervention mapping framework was used to develop a web-based program called Vascular View. The Vascular View program contained 6 modules (coping with CVD, setting boundaries, lifestyle, healthy nutrition, being physically active, interaction with health professionals) aiming to increase self-management behavior by tailoring to the perceived problems and (support) needs of patients after CVD. Objective: The aim was to test the effectiveness of Vascular View before embarking on a full-scale randomized clinical trial (RCT) by evaluating the potential effectiveness and effect sizes of the Vascular View program and identifying outcome measures most likely to capture the potential benefits. Methods: An explorative RCT was performed. Both control and intervention groups received care as usual and, in addition, the intervention group received 12 months of access to a web-based self-management program. Assessment occurred at baseline, 6 months, and 12 months. Outcome measures included general patient-reported outcome measurements: Illness Perception Questionnaire (IPQ), Rand-36, Patient Activation Measure, and patient self-efficacy. Module-specific patient-reported outcome measurements were Beliefs about Medicines Questionnaire, International Physical Activity Questionnaire, Dutch Healthy Diet Index, Fagerström Test for Nicotine Dependence (FTND), Alcohol Use Disorders Identification Test, and Perceived Efficacy in Patient-Physician Interaction. Linear mixed models for repeated measures using intention-to-treat and per-protocol analysis were applied to study differences between the patients in the intervention and control groups. Floor and ceiling effects were explored to give insight into the outcome measures most likely to capture the potential benefits. Results: A total of 105 patients in the control group and 103 patients in the intervention group participated in the study. A positive direction of change between baseline and 12 months was shown for most outcome measurements in favor of the intervention group, of which 2 out of 10 outcomes showed a significant effect: attribution of cause of the disease to risk factors and immunity factors (IPQ) and dependency of nicotine (FTND). Floor and ceiling effects were seen in the IPQ, Rand-36, and the self-efficacy questionnaire. Conclusions: No conclusion for the efficacy of the Vascular View program or selection of outcome measurements can be taken yet. A process evaluation will be conducted to gain thorough insight into the working elements of the program, patient needs in eHealth, and the use of the program by patients. This can determine for whom web-based self-management programs will work and help to adapt the program. Trial Registration: Dutch Trial Register NTR5412; https://www.trialregister.nl/trial/5303 International Registered Report Identifier (IRRID): RR2-10.2196/resprot.6352

BACKGROUND We conducted a trial to test the electronic Illness Management and Recovery (e-IMR) intervention to provide conclusions on the potential efficacy of eHealth for people with severe mental illness (SMI). In the e-IMR intervention, we used the standard IMR program content and methodology and combined face-to-face sessions with internet-based strategies on the constructed e-IMR internet platform. During the trial, the e-IMR platform was sparsely used. OBJECTIVE This study aimed to evaluate the added value of the e-IMR intervention and the barriers and facilitators that can explain the low use of the e-IMR platform. METHODS This process evaluation was designed alongside a multicenter, cluster randomized controlled trial. In this study, we included all available participants and trainers from the intervention arm of the trial. Baseline characteristics were used to compare users with nonusers. Qualitative data were gathered at the end of the semistructured interviews. Using theoretical thematic analyses, the data were analyzed deductively using a pre-existing coding frame. RESULTS Out of 41 eligible participants and 14 trainers, 27 participants and 11 trainers were interviewed. Of the 27 participants, 10 were identified as users. eHealth components that had added value were the persuasive nature of the goal-tracking sheets, monitoring, and the peer testimonials, which had the potential to enhance group discussions and disclosure by participants. The low use of the e-IMR platform was influenced by the inflexibility of the platform, the lack of information technology (IT) resources, the group context, participants’ low computer skills and disabilities, and the hesitant eHealth attitude of the trainers. CONCLUSIONS The extent of eHealth readiness and correlations with vulnerabilities in persons with SMI need further investigation. This study shows that flexible options were needed for the use of e-IMR components and that options should be provided only in response to a participant’s need. Use of the e-IMR intervention in the future is preconditioned by checking the available IT resources (such as tablets for participants) providing computer or internet guidance to participants outside the group sessions, evaluating the eHealth attitude and skills of trainers, and tailoring eHealth training to increase the skills of future e-IMR trainers. CLINICALTRIAL Netherlands Trial Register NTR4772; https://www.trialregister.nl/trial/4621 INTERNATIONAL REGISTERED REPORT RR2-10.1186/s12913-016-1267-z

BACKGROUND Web-based self-management programs have the potential to support patients with cardiovascular disease (CVD) in their self-management (eg, by focusing on behavior change and improving physical activity). The intervention mapping framework was used to develop a web-based program called Vascular View. The Vascular View program contained 6 modules (coping with CVD, setting boundaries, lifestyle, healthy nutrition, being physically active, interaction with health professionals) aiming to increase self-management behavior by tailoring to the perceived problems and (support) needs of patients after CVD. OBJECTIVE The aim was to test the effectiveness of Vascular View before embarking on a full-scale randomized clinical trial (RCT) by evaluating the potential effectiveness and effect sizes of the Vascular View program and identifying outcome measures most likely to capture the potential benefits. METHODS An explorative RCT was performed. Both control and intervention groups received care as usual and, in addition, the intervention group received 12 months of access to a web-based self-management program. Assessment occurred at baseline, 6 months, and 12 months. Outcome measures included general patient-reported outcome measurements: Illness Perception Questionnaire (IPQ), Rand-36, Patient Activation Measure, and patient self-efficacy. Module-specific patient-reported outcome measurements were Beliefs about Medicines Questionnaire, International Physical Activity Questionnaire, Dutch Healthy Diet Index, Fagerström Test for Nicotine Dependence (FTND), Alcohol Use Disorders Identification Test, and Perceived Efficacy in Patient-Physician Interaction. Linear mixed models for repeated measures using intention-to-treat and per-protocol analysis were applied to study differences between the patients in the intervention and control groups. Floor and ceiling effects were explored to give insight into the outcome measures most likely to capture the potential benefits. RESULTS A total of 105 patients in the control group and 103 patients in the intervention group participated in the study. A positive direction of change between baseline and 12 months was shown for most outcome measurements in favor of the intervention group, of which 2 out of 10 outcomes showed a significant effect: attribution of cause of the disease to risk factors and immunity factors (IPQ) and dependency of nicotine (FTND). Floor and ceiling effects were seen in the IPQ, Rand-36, and the self-efficacy questionnaire. CONCLUSIONS No conclusion for the efficacy of the Vascular View program or selection of outcome measurements can be taken yet. A process evaluation will be conducted to gain thorough insight into the working elements of the program, patient needs in eHealth, and the use of the program by patients. This can determine for whom web-based self-management programs will work and help to adapt the program. CLINICALTRIAL Dutch Trial Register NTR5412; https://www.trialregister.nl/trial/5303 INTERNATIONAL REGISTERED REPORT RR2-10.2196/resprot.6352

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Online self-management enhancing programmes has the potential to support patients with Rheumatoid Arthritis in their self-management, for example improve their health status and self-efficacy or decrease overuse of medication. We developed an online self-management enhancing program in collaboration with RA patients and professionals as co-designers, based on the Intervention Mapping Framework. While self-management programs are complex interventions, it is informative to perform an explorative Randomized Controlled Trial before embarking on a larger trial. Objective: This study aimed to evaluate the efficacy of an online self-management enhancing programme for patients with rheumatoid arthritis and to identify outcome measures most likely to capture potential benefits. Methods: A multicentre exploratory randomised controlled trial was performed with an intervention and a control group. Both groups received care as usual. In addition, the intervention group received 12 months of access to an online self-management programme. Assessment occurred at baseline, 6 and 12 months. Outcome measures included self-management behaviour (PAM-13, SMAS-S), self-efficacy (RASE, PEPPI-5), general health status (RAND-36), focus on fatigue (MPCI-F), perceived pain and fatigue (NRS scales). A linear mixed model for repeated measures, using the intention-to-treat principle, was applied to study differences between the patients in the intervention (n=78) and control (n=79) groups. A sensitivity analysis was performed in the intervention group to study the influence of patients with high (N=30) and low (N=40) use of the intervention. Results: The intervention group scored statistically significantly better on the subscale RAND-36 vitality. The group with high use scored statistically significantly better on the subscale RAND-36 perception, although the effect sizes were small. No other statistically significant or clinically relevant effects were found. Conclusions: Based on these results, it is not possible to conclude on the positive effects of the intervention or to select outcome measures to be regarded as the primary/main or secondary outcomes for a future trial. A process evaluation should be performed to provide more insight into the low compliance with and effectiveness of the intervention. Clinical Trial: The trial is registered in the Dutch Trial Register (ID: NTR4871). URL: http://www.trialregister.nl/trialreg/admin/rctsearch.asp?Term=4871

E-mental health holds promise for people with severe mental illness, but has a limited evidence base. This study explored the effect of e-health added to face-to-face delivery of the Illness Management and Recovery Programme (e-IMR). In this multi-centre exploratory cluster randomized controlled trial, seven clusters (n = 60; 41 in intervention group and 19 in control group) were randomly assigned to e-IMR + IMR or IMR only. Outcomes of illness management, self-management, recovery, symptoms, quality of life, and general health were measured at baseline (T0), halfway (T1), and at twelve months (T2). The data were analysed using mixed model for repeated measurements in four models: in 1) we included fixed main effects for time trend and group, in 2) we controlled for confounding effects, in 3) we controlled for interaction effects, and in 4) we performed sub-group analyses within the intervention group. Notwithstanding low activity on e-IMR, significant effects were present in model 1 analyses for self-management (p = .01) and recovery (p = .02) at T1, and for general health perception (p = .02) at T2, all in favour of the intervention group. In model 2, the confounding covariate gender explained the effects at T1 and T2, except for self-management. In model 3, the interacting covariate non-completer explained the effects for self-management (p = .03) at T1. In model 4, the sub-group analyses of e-IMR-users versus non-users showed no differences in effect. Because of confounding and interaction modifications, effectiveness of e-IMR cannot be concluded. Low use of e-health precludes definite conclusions on its potential efficacy. Low use of e-IMR calls for a thorough process evaluation of the intervention. The Dutch Trial Register ( NTR4772 )