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BackgroundThe prescription of physical activity (PA) in clinical care has been advocated worldwide. This “exercise is medicine” (E=M) concept can be used to prevent, manage, and cure various lifestyle-related chronic diseases. Due to several challenges, E=M is not yet routinely implemented in clinical care. ObjectiveThis paper describes the rationale and design of the Physicians Implement Exercise = Medicine (PIE=M) study, which aims to facilitate the implementation of E=M in hospital care. MethodsPIE=M consists of 3 interrelated work packages. First, levels and determinants of PA in different patient and healthy populations will be investigated using existing cohort data. The current implementation status, facilitators, and barriers of E=M will also be investigated using a mixed-methods approach among clinicians of participating departments from 2 diverse university medical centers (both located in a city, but one serving an urban population and one serving a more rural population). Implementation strategies will be connected to these barriers and facilitators using a systematic implementation mapping approach. Second, a generic E=M tool will be developed that will provide tailored PA prescription and referral. Requirements for this tool will be investigated among clinicians and department managers. The tool will be developed using an iterative design process in which all stakeholders reflect on the design of the E=M tool. Third, we will pilot-implement the set of implementation strategies, including the E=M tool, to test its feasibility in routine care of clinicians in these 2 university medical centers. An extensive learning process evaluation will be performed among clinicians, department managers, lifestyle coaches, and patients using a mixed-methods design based on the RE-AIM framework. ResultsThis project was approved and funded by the Dutch grant provider ZonMW in April 2018. The project started in September 2018 and continues until December 2020 (depending on the course of the COVID-19 crisis). All data from the first work package have been collected and analyzed and are expected to be published in 2021. Results of the second work package are described. The manuscript is expected to be published in 2021. The third work package is currently being conducted in clinical practice in 4 departments of 2 university medical hospitals among clinicians, lifestyle coaches, hospital managers, and patients. Results are expected to be published in 2021. ConclusionsThe PIE=M project addresses the potential of providing patients with PA advice to prevent and manage chronic disease, improve recovery, and enable healthy ageing by developing E=M implementation strategies, including an E=M tool, in routine clinical care. The PIE=M project will result in a blueprint of implementation strategies, including an E=M screening and referral tool, which aims to improve E=M referral by clinicians to improve patients’ health, while minimizing the burden on clinicians.

BackgroundIncreasing physical activity is a viable strategy for improving both the health and quality of life of older adults. ObjectiveThe aim of this study was to assess if an Internet-based intervention aimed to increase physical activity was effective in improving quality of life of inactive older adults. In addition, we analyzed the effect of the intervention on quality of life among those participants who successfully reached their individually targeted increase in daily physical activity as indicated by the intervention program, as well as the dose-response effect of increasing physical activity on quality of life. MethodsThe intervention was tested in a randomized controlled trial and was comprised of an Internet program—DirectLife (Philips)—aimed at increasing physical activity using monitoring and feedback by accelerometry and feedback by digital coaching (n=119). The control group received no intervention (n=116). Participants were inactive 60-70-year-olds and were recruited from the general population. Quality of life and physical activity were measured at baseline and after 3 months using the Research ANd Development 36-item health survey (RAND-36) and wrist-worn triaxial accelerometer, respectively. ResultsAfter 3 months, a significant improvement in quality of life was seen in the intervention group compared to the control group for RAND-36 subscales on emotional and mental health (2.52 vs -0.72, respectively; P=.03) and health change (8.99 vs 2.03, respectively; P=.01). A total of 50 of the 119 participants (42.0%) in the intervention group successfully reached their physical activity target and showed a significant improvement in quality of life compared to the control group for subscales on emotional and mental health (4.31 vs -0.72, respectively; P=.009) and health change (11.06 vs 2.03, respectively; P=.004). The dose-response analysis showed that there was a significant association between increase in minutes spent in moderate-to-vigorous physical activity (MVPA) and increase in quality of life. ConclusionsOur study shows that an Internet-based physical activity program was effective in improving quality of life in 60-70-year-olds after 3 months, particularly in participants that reached their individually targeted increase in daily physical activity. Trial RegistrationNederlands Trial Register: NTR 3045; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3045 (Archived by WebCite at http://www.webcitation.org/6fobg2sjJ)

Background: Although the prescription of physical activity in clinical care has been advocated worldwide, in the Netherlands, "Exercise is Medicine" (E = M) is not yet routinely implemented in clinical care. Methods: A set of implementation strategies was pilot implemented to test its feasibility for use in routine care by clinicians in 2 departments of a university medical center. An extensive learning process evaluation was performed, using structured mixed methods methodology, in accordance with the Reach, Effect, Adoption, Implementation, and Maintenance framework. Results: From 5 implementation strategies employed (education, E = M tool embedded in the electronic medical records, lifestyle coach situated within the department, overviews of referral options, and project support), the presence of adequate project support was a strong facilitator of the implementation of E = M. Also, the presence of the lifestyle coach within the department seemed essential for referral rate. Although clinicians appreciated the E = M tool, barriers hampered its use in practice. Conclusions: Specific implementation strategies, tailored to the setting, are effective in facilitating the implementation of E = M with specific regard to education for clinicians on E = M, deployment of a lifestyle coach within a department, and project coordination. Care providers do see a future for lifestyle coaches who are structurally embedded in the hospital, to whom they can easily refer. [ABSTRACT FROM AUTHOR]

BackgroundLow physical activity is a major risk factor for several age-related diseases. Recently, we showed in a randomized controlled trial that a 12-week Web-based intervention (Philips DirectLife) to increase physical activity was effective in increasing physical activity levels and metabolic health in an inactive population aged 60-70 years. ObjectiveThe goal of this paper was to assess how many participants successfully reached the physical activity level as targeted by the intervention and what the effects of the intervention on body composition and metabolic health in these successful individuals were to provide insight in the maximum attainable effect of the intervention. MethodsAmong the 235 participants in a randomized controlled trial of the Actief en Gezond Oud (AGO) study, we assessed the effects of the intervention on metabolic parameters in those who had successfully reached their personalized physical activity target compared with the entire intervention group. Furthermore, we studied the dose-response effect of increase in physical activity on metabolic outcome within the intervention group. ResultsOf the intervention group, 50 of 119 (42.0%) participants successfully reached the physical activity target (corresponding to a 10% increased daily physical activity on average). This group showed markedly higher effects of the intervention compared to the entire intervention group, with greater decreases in body weight (2.74 vs 1.49 kg), waist circumference (3.74 vs 2.33 cm), insulin resistance (HOMA index: 0.23 vs 0.20), and in cholesterol/HDL ratio (0.39 vs 0.20) and Framingham risk score (0.90% vs 0.54%). We found that men compared to women were more likely to be successful. The dose-response analysis showed that there was a significant association between increase in minutes spent in moderate-to-vigorous activity and body weight loss, BMI reduction, waist circumference reduction, HDL cholesterol increasing, and cholesterol/HDL ratio lowering. ConclusionsOf the intervention group, 42.0% (50/119) reached their daily physical activity end goal, which was associated with a markedly better effect on body composition and metabolic health compared to the effect in the entire intervention group. In this population, men are more likely to be successful in increasing physical activity. Findings demonstrate that improving the effect of such physical activity interventions requires finding new ways to increase the proportion of the population reaching the targeted goal. Trial RegistrationDutch Trial Registry: NTR 3045; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3045 (Archived by WebCite at http://www.webcitation.org/6KPw52dCc).

BackgroundDepressive disorders are highly prevalent in the working population and are associated with excessive costs. The evidence for effective worker-directed interventions for employees with depressive symptoms is limited. Treating employees with depressive symptoms via the Internet before they report sick from work could be beneficial and cost saving. ObjectiveIn this study, we tested the effectiveness over the period of 1 year of a Web-based guided self-help intervention, called Happy@Work, for employees with depressive symptoms who were not on sick leave. MethodsA two-arm randomized controlled trial comparing a worker-directed, Web-based, guided self-help intervention to care as usual (CAU) was carried out. We recruited employees from 6 companies via the company’s Intranet and by putting up posters. The inclusion criteria were elevated depressive symptoms as measured by a score ≥16 on the Center for Epidemiologic Studies Depression scale (CES-D) and not being on sick leave. The intervention contained 6 lessons and consisted of problem-solving treatment and cognitive therapy. Participants were asked to submit weekly assignments via the website after completion of a lesson and they received feedback from a coach via the website. Self-report questionnaires on depressive symptoms (CES-D; primary outcome), burnout (Maslach Burnout Inventory, MBI), work performance (Health and Work Performance Questionnaire, HPQ), duration of absenteeism, and anxiety (Hospital Anxiety and Depression Scale, HADS; secondary outcomes), were completed at baseline, posttreatment, and at 6-, and 12-month follow-up. Several subgroup and per-protocol analyses were performed. ResultsA total of 231 employees were randomized to either the intervention group (n=116) or to CAU (n=115). Completion of assessments varied between 54%-74%. Improvement in depressive symptoms between baseline and posttreatment was shown in all participants and these effects sustained over time. However, there were no differences between the 2 groups (adjusted regression coefficient=0.46, 95% CI –2.11 to 3.03, P=.72; Cohen’s d=0.05). Differences between groups were also not significant for the secondary outcomes. No subgroups were identified to show differences between the groups, nor did we find a between-group effect in the per-protocol analyses. ConclusionsThis study showed that a worker-directed, Web-based, guided self-help intervention was not more effective than CAU in reducing depressive symptoms among employees with depressive symptoms who were not on sick leave over the period of 1 year. An intervention for this specific target group might not be necessary because the recovery in the CAU group was comparable to the intervention group and sustained over a 12-month period. Trial RegistrationNederlands Trial Register (NTR): NTR2993; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2993 (Archived by WebCite at http://www.webcitation.org/6PL9pFC0n).

BackgroundDepressive disorders are highly prevalent in the working population and are associated with excessive costs. The evidence for effective worker-directed interventions for employees with depressive symptoms is limited. Treating employees with depressive symptoms before sick leave via the Internet could be beneficial and cost saving. ObjectiveIn this study, we developed and tested the effectiveness of a Web-based guided self-help course for employees with depressive symptoms. We report on the posttreatment effectiveness of the intervention. MethodsThis study is a two-arm randomized controlled trial comparing a Web-based guided self-help course to care as usual (CAU). We recruited employees from 6 different companies via the companies’ intranet and posters. The main inclusion criterion was elevated depressive symptoms as measured by a score of ≥16 on the Center for Epidemiological Studies Depression scale (CES-D). The intervention (Happy@Work) was based on problem-solving treatment and cognitive therapy and consisted of 6 weekly lessons. Participants were asked to submit their weekly assignment via the website after completion. They subsequently received feedback from a coach via the website. Self-report questionnaires on depressive symptoms (CES-D; primary outcome), anxiety measured by the Hospital Anxiety and Depression Scale (HADS), burnout measured by the Maslach Burnout Inventory (MBI), and work performance measured by the Health and Work Performance Questionnaire (HPQ; secondary outcomes) were completed at baseline and at posttreatment. ResultsA total of 231 employees were randomized to either the intervention group (n=116) or CAU (n=115).The posttreatment assessment was completed by 171 (74.0%) participants. Both the intervention and the CAU group showed significant improvements in the primary outcome of depressive symptoms, but no differences between the conditions was found (d=0.16, 95% CI –0.10 to 0.41, P=.29). Significant but small effects in favor of the intervention group were found for anxiety symptoms (d=0.16, 95% CI –0.09 to 0.42, P=.04) and exhaustion (d=0.17, 95% CI –0.09 to 0.43, P=.02). ConclusionsThis study showed that a Web-based guided self-help course for employees with depressive symptoms was not more effective in reducing depressive symptoms among employees than CAU. Large improvements in depressive symptoms in the CAU group were unforeseen and potential explanations are discussed.

BackgroundLack of physical activity leads to detrimental changes in body composition and metabolism, functional decline, and increased risk of disease in old age. The potential of Web-assisted interventions for increasing physical activity and improving metabolism in older individuals holds great promise but to our knowledge it has not been studied. ObjectiveThe goal of our study was to assess whether a Web-based intervention increases physical activity and improves metabolic health in inactive older adults. MethodsWe conducted a 3-month randomized, waitlist-controlled trial in a volunteer sample of 235 inactive adults aged 60-70 years without diabetes. The intervention group received the Internet program Philips DirectLife, which was directed at increasing physical activity using monitoring and feedback by accelerometer and digital coaching. The primary outcome was relative increase in physical activity measured objectively using ankle- and wrist-worn accelerometers. Secondary outcomes of metabolic health included anthropometric measures and parameters of glucose metabolism. ResultsIn total, 226 participants (97%) completed the study. At the ankle, activity counts increased by 46% (standard error [SE] 7%) in the intervention group, compared to 12% (SE 3%) in the control group (Pdifference

BackgroundFull recovery after gynecological surgery takes much longer than expected regardless of surgical technique or the level of invasiveness. After discharge, detailed convalescence recommendations are not provided to patients typically, and postoperative care is fragmented, poorly coordinated, and given only on demand. For patients, this contributes to irrational beliefs and avoidance of resumption of activities and can result in a prolonged sick leave. ObjectiveTo develop an eHealth intervention that empowers gynecological patients during the perioperative period to obtain timely return to work (RTW) and prevent work disability. MethodsThe intervention mapping (IM) protocol was used to develop the eHealth intervention. A literature search about behavioral and environmental conditions of prolonged sick leave and delayed RTW in patients was performed. Patients’ needs, attitudes, and beliefs regarding postoperative recovery and resumption of work were identified through focus group discussions. Additionally, a literature search was performed to obtain determinants, methods, and strategies for the development of a suitable interactive eHealth intervention to empower patients to return to normal activities after gynecological surgery, including work. Finally, the eHealth intervention was evaluated by focus group participants, medical doctors, and eHealth specialists through questionnaires. ResultsTwenty-one patients participated in the focus group discussions. Sufficient, uniform, and tailored information regarding surgical procedures, complications, and resumption of activities and work were considered most essential. Knowing who to contact in case of mental or physical complaints, and counseling and tools for work reintegration were also considered important. Finally, opportunities to exchange experiences with other patients were a major issue. Considering the determinants of the Attitude–Social influence–self-Efficacy (ASE) model, various strategies based on a combination of theory and evidence were used, resulting in an eHealth intervention with different interactive functionalities including tailored convalescence recommendations and a video to communicate the most common pitfalls during the perioperative period to patients and employers. Fifteen patients in the focus groups, 11 physicians, and 3 eHealth specialists suggested points for improvement to optimize the usability of the eHealth intervention and judged it an approachable, appropriate, and attractive eHealth intervention to empower gynecological patients. ConclusionsThe IM protocol was a useful method to develop an eHealth intervention based on both theory and evidence. All patients and stakeholders judged the eHealth intervention to be a promising tool to empower gynecological patients during the perioperative period and to help them to return to normal activities and work.

Background: To better understand physical activity behavior and its health benefits in people living with health conditions, we studied people with and without 20 different self-reported health conditions with regard to (1) their physical activity levels, (2) factors correlated with these physical activity levels, and (3) the association between physical activity and all-cause mortality. Methods: We used a subsample (n = 88,659) of the Lifelines cohort study from the Netherlands. For people living with and without 20 different self-reported health conditions, we studied the aforementioned factors in relation to physical activity. Physical activity was assessed with the Short Questionnaire to Assess Health-Enhancing Physical Activity Questionnaire, and mortality data were obtained from the Dutch death register. Results: People with a reported health condition were less likely to meet physical activity guidelines than people without a reported health condition (odds ratios ranging from 0.55 to 0.89). Higher body mass index and sitting time, and lower self-rated health, physical functioning, and education levels were associated with lower odds of meeting physical activity guidelines across most health conditions. Finally, we found a protective association between physical activity and all-cause mortality in both people living with and without different health conditions. Conclusion: People living with different health conditions are generally less physically active compared with people living without a health condition. Both people living with and without self-reported health conditions share a number of key factors associated with physical activity levels. We also observed the expected protective association between physical activity and all-cause mortality. [ABSTRACT FROM AUTHOR]

BackgroundA healthy diet, low in saturated fat and high in fiber, is a popular medical recommendation in preventing cardiovascular disease (CVD). One approach to motivating healthier eating is to raise individuals’ awareness of their CVD risk and then help them form specific plans to change. ObjectivesThe aim was to explore the combined impact of a Web-based CVD risk message and a fully automated planning tool on risk perceptions, intentions, and saturated fat intake changes over 4 weeks. MethodsOf the 1187 men and women recruited online, 781 were randomly allocated to one of four conditions: a CVD risk message, the same CVD risk message paired with planning, planning on its own, and a control group. All outcome measures were assessed by online self-reports. Generalized linear modeling was used to analyze the data. ResultsSelf-perceived consumption of low saturated fat foods (odds ratio 11.40, 95% CI 1.86–69.68) and intentions to change diet (odds ratio 21.20, 95% CI 2.6–172.4) increased more in participants allocated to the planning than the control group. No difference was observed between the four conditions with regard to percentage saturated fat intake changes. Contrary to our expectations, there was no difference in perceived and percentage saturated fat intake change between the CVD risk message plus planning group and the control group. Risk perceptions among those receiving the CVD risk message changed to be more in line with their age (change in slopeindividual = 0.075, P = .01; change in slopecomparative = 0.100, P = .001), whereas there was no change among those who did not receive the CVD risk message. ConclusionThere was no evidence that combining a CVD risk message with a planning tool reduces saturated fat intake more than either alone. Further research is required to identify ways in which matching motivational and volitional strategies can lead to greater behavior changes. Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 91154001; http://www.controlled-trials.com/ISRCTN91154001 (Archived by WebCite at http://www.webcitation.org/62sBoGeOO)

BackgroundInactive people are often not aware of the fact that they are insufficiently active. Providing insight into their actual physical activity (PA) levels may raise awareness and could, in combination with tailored PA advice, stimulate a physically active lifestyle. ObjectiveThis study evaluated the feasibility and effectiveness of a 3-month intervention in which Dutch office workers were provided with a personal activity monitor (PAM) coupled to simple and concise Web-based tailored PA advice (PAM COACH). MethodParticipants were randomly assigned to the 3-month PAM intervention (n = 51) or received a single written information brochure with brief general PA recommendations (n = 51). Study outcome measures were changes in PA (recall of minutes per week spent on PA, as measured by the Activity Questionnaire for Adolescents and Adults), determinants of PA, aerobic fitness, and body composition. Follow-up measurements were performed immediately after the 3-month intervention and at 8-months, 5 months after the end of the 3-month intervention period. ResultsA total of 102 workers, 23 to 39 years old, completed the baseline measurement at the worksite. 48 completed the 3-month follow up and 38 the 8-month follow-up in the intervention group, 50 completed the 3-month follow up and 42 the 8-month follow up in the control group. 35 out of 48 (73%) participants in the PAM intervention group reported wearing the PAM regularly, and the PAM COACH was used almost once a week; 24 out of 46 (52%) PAM users set a personal goal, and 33 (72%) entered their favorite activities on the website. Main reasons for not using these items were lack of interest or not being able to find the item on the website. The majority of PAM users (34 out of 46, 74%) read the advice, of whom 14 (39%) found it unappealing. After the 3-month intervention, no significant intervention effect was observed (adjusted difference in min/week) for sedentary behavior (β = 10, 95% CI = −435 to 455), light-intensity PA (β = −129, 95% CI = −337 to 79), moderate-intensity PA (β = −13, 95% CI = −89 to 63), vigorous-intensity PA (β= −6, 95% CI = −75 to 62), and moderate- to vigorous-intensity PA (β = −23, 95% CI = −121 to 76). No significant intervention effect was observed in the PA outcomes at the 8-month follow-up. For the determinants of PA, aerobic fitness, and body composition, no statistically significant intervention effect was observed in the total study population immediately after the 3-month intervention or the 8-month follow-up. ConclusionsThe intervention appeared to be easily applicable to real-life settings. The intervention was ineffective in improving PA behavior or its determinants in healthy office workers. More attention should have been given to the quality and appropriateness of the tailored advice. Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 93896459; http://www.controlled-trials.com/ISRCTN93896459/ (Archived by WebCite at http://www.webcitation.org/5iR3mf7ex)

Purpose: A lifestyle front office (LFO) in the hospital is a not yet existing, novel concept that can refer patients under treatment in the hospital to community-based lifestyle interventions (CBLI). The aim of this study was to identify implementation barriers and facilitators regarding the implementation of an LFO in the hospital from the perspective of CBLI-professionals and to develop evidence-based implementation strategies to reduce these identified barriers. Methods: We conducted semi-structured interviews until data saturation, with 23 lifestyle professionals working in the community. A semi-structured topic guide was used, inquiring about (1) community-based lifestyle interventions; (2) their views about referral from the LFO; and (3) their preferences, needs and recommendations for collaboration with the LFO in the hospital. The online interviews lasted on average 46 minutes, were audio-recorded and transcribed verbatim. A thematic content analysis was conducted. Found barriers and facilitators regarding the LFO where mapped using the consolidated framework for implementation research (CFIR) whereafter evidence based strategies were developed using the CFIR-Expert Recommendations for Implementing Change Strategy Matching Tool V.1.0 (CFIR-ERIC). Results: Barriers and facilitators were divided into two main themes: 1) barriers and facilitators related to the referral from LFO to CBLI (i.e. financial, cultural, geographical, quality) and 2) barriers and facilitators related to the collaboration between LFO and CBLI (i.e. referral, communication platform and partnership). Thirty-seven implementation strategies concerning 15 barriers were developed and clustered into six overarching strategies: identify referral options, determine qualifications lifestyle professionals, develop support tools, build networks, facilitate learning collaboratives, and optimize workflow. Conclusions: In this study, barriers and facilitators for the development of the LFO were found and matching implementation strategies were developed. Practical improvements, like identifying specific referral options or develop support tools, can be implemented immediately. The implementation of other strategies, like connecting care pathways in basic services, primary, secondary and tertiary care, will take more time and effort to come to full potential. Future research should evaluate all implemented strategies. [ABSTRACT FROM AUTHOR]

This study investigates if and to what extent the Dutch Obesity Intervention in Teenagers (DOiT) program was implemented as intended and how this affected program effectiveness. We collected data at 20 prevocational education schools in the Netherlands. We assessed seven process indicators: recruitment, reach, dosage, fidelity, satisfaction, effectiveness and continuation. Data collection involved teacher questionnaires (n = 110), adolescent questionnaires and adiposity measures (n = 938). Using multi-level confirmatory factor analyses, we applied an innovative method to obtain explorative implementation index scores. The percentage of accomplished activities ranged from 9% (for "closure meeting") up to 93% (for "obtaining support within the school for adoption"). The percentage of lessons delivered decreased from 74 to 18% towards the end of the program. Fidelity to the teacher manual ranged from 85 to 26%. In general, teachers were satisfied with the DOiT lessons and teaching materials. Despite teachers' satisfaction with the DOiT lessons and teaching materials, degree of program implementation was lower than expected, especially towards the end of the program. Further, some evidence was found for an association between a higher implementation index score and program effectiveness, but more research is needed to test the validity of the implementation index.