Comparing national device-based physical activity surveillance systems: a systematic review.

BACKGROUND: Physical activity surveillance systems are important for public health monitoring but rely mostly on self-report measurement of physical activity. Integration of device-based measurements in such systems can improve population estimates, however this is still relatively uncommon in existing surveillance systems. This systematic review aims to create an overview of the methodology used in existing device-based national PA surveillance systems. METHODS: Four literature databases (PubMed, Embase.com, SPORTDiscus and Web of Science) were searched, supplemented with backward tracking. Articles were included if they reported on population-based (inter)national surveillance systems measuring PA, sedentary time and/or adherence to PA guidelines. When available and in English, the methodological reports of the identified surveillance studies were also included for data extraction. RESULTS: This systematic literature search followed the PRISMA guidelines and yielded 34 articles and an additional 18 methodological reports, reporting on 28 studies, which in turn reported on one or multiple waves of 15 different national and 1 international surveillance system. The included studies showed substantial variation between (waves of) systems in number of participants, response rates, population representativeness and recruitment. In contrast, the methods were similar on data reduction definitions (e.g. minimal number of valid days, non-wear time and necessary wear time for a valid day). CONCLUSIONS: The results of this review indicate that few countries use device-based PA measurement in their surveillance system. The employed methodology is diverse, which hampers comparability between countries and calls for more standardized methods as well as standardized reporting on these methods. The results from this review can help inform the integration of device-based PA measurement in (inter)national surveillance systems.

Implementing Individually Tailored Prescription of Physical Activity in Routine Clinical Care: A Process Evaluation of the Physicians Implement Exercise = Medicine Project.

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.

Implementation barriers and facilitators for referral from the hospital to community-based lifestyle interventions from the perspective of lifestyle professionals: A qualitative study.

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.

Physical Activity Levels, Correlates, and All-Cause Mortality Risk in People Living With Different Health Conditions.

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.