Samenvatting Inleiding De helft van de volwassen Nederlanders heeft matig tot ernstig overgewicht. De gecombineerde leefstijlinterventie begeleidt mensen met overgewicht naar een gezonde leefstijl. Naast fysieke contactmomenten kunnen digitale coachingsmiddelen ingezet worden om cliënten op afstand te begeleiden. In de praktijk blijkt dat digitale toepassingen nog niet ten volle worden benut. Om het gebruik te stimuleren is inzicht nodig in de ervaringen en ondersteuningsbehoeften van leefstijlcoaches ten aanzien van de inzet van digitale technologie. Methode Met één vragenlijst en twee focusgroepgesprekken zijn data verzameld over het gebruik, de wensen en ondersteuningsbehoeften rond het inzetten van digitale coachingsmiddelen bij leefstijlcoaches. De vragenlijsten zijn descriptief geanalyseerd en de focusgroepgesprekken zijn thematisch geanalyseerd. Resultaten Uit de vragenlijstresultaten ( N = 79) en de focusgroepgesprekken ( N = 10) bleek dat leefstijlcoaches vooral ervaring hebben opgedaan met videobellen, applicaties en online informatie. Ze gaven aan dat digitale coaching de zelfredzaamheid van hun cliënten ondersteunt. Online groepsbegeleiding wordt als minder effectief ervaren dan fysieke groepssessies, omdat er weinig interactie tussen cliënten plaatsvindt. Ook ervaren leefstijlcoaches praktische barrières bij het gebruik. Ze hebben behoefte aan uitwisseling van ervaringen met collega’s, scholing en instructies over de manier waarop digitale coachingsmiddelen ingezet kunnen worden. Conclusie Leefstijlcoaches achten digitale coachingsmiddelen van toegevoegde waarde bij de individuele begeleiding van hun cliënten. Het wegnemen van praktische barrières en het faciliteren van uitwisseling en scholing kunnen een ruimere inzet van digitale coachingsmiddelen stimuleren.

Primary healthcare professionals face an increasing number of geriatrics patients, and patient care often involves different disciplines. eHealth offers opportunities to support interprofessional collaboration (IPC). This exploratory study aimed to gain insight in 1) IPC in community-based rehabilitation, 2) facilitators and barriers for technology-based IPC and 3) technological IPC solutions envisioned by the primary healthcare professionals An focus group with six primary healthcare professionals and a design thinking session with four participants were conducted. Data analysis was based upon an IPC model. Results indicate that facilitators and barriers for IPC can be clustered in three categories: human, organization and technology, and provide some requirements to develop suitable IPC technological solutions Primary healthcare professionals recognise the urgency of working collaboratively. Current barriers are understanding each other's professional vocabulary, engaging the older adults, and using technology within the patient's environment. Further research is needed to integrate IPC components in a technological solution.

Introduction:In the Netherlands, half of the adult population is overweight. Combined Lifestyle Interventions guide overweight clients towards a healthy lifestyle. In addition to the face-to face sessions with clients, lifestyle professionals can use digital coaching tools to guide their clients remotely. In practice it appears that the digital applications are not fully used. To stimulate the use of digital technology, insight is needed into the experiences and support needs of lifestyle professionals. Method:Data about the use, wishes and support needs regarding the use of digital coaching tools among lifestyle professionals were collected by a questionnaire and two focus groups. The results of the questionnaires were analyzed descriptively and the focus groups were analyzed thematically. Results:Seventy-nine lifestyle professionals completed the questionnaire. Ten lifestyle professionals participated in a focus group. Both methods showed that professionals have gained experience with video communication, apps and online information. Lifestyle professionals mention that these digital coaching tools support the self-reliance of clients. Online group sessions are perceived as less effective than face-to-face group sessions, because of the lack of interaction between clients. Lifestyle professionals also experience practical barriers in using digital coaching tools. To stimulate the use of digital coaching tools, they need an exchange of experience with colleagues, training and instruction on how to use these tools. Conclusion:Lifestyle professionals consider digital coaching tools to be an added value to individual coaching. They see opportunities for wider use in the future when practical barriers are overcome, and exchange of experience and training are facilitated.

Combined lifestyle interventions (CLI) are focused on guiding clients with weight-related health risks into a healthy lifestyle. CLIs are most often delivered through face-to-face sessions with limited use of eHealth technologies. To integrate eHealth into existing CLIs, it is important to identify how behavior change techniques are being used by health professionals in the online and offline treatment of overweight clients. Therefore, we conducted online semi-structured interviews with providers of online and offline lifestyle interventions. Data were analyzed using an inductive thematic approach. Thirty-eight professionals with (n = 23) and without (n = 15) eHealth experience were interviewed. Professionals indicate that goal setting and action planning, providing feedback and monitoring, facilitating social support, and shaping knowledge are of high value to improve physical activity and eating behaviors. These findings suggest that it may be beneficial to use monitoring devices combined with video consultations to provide just-in-time feedback based on the client's actual performance. In addition, it can be useful to incorporate specific social support functions allowing CLI clients to interact with each other. Lastly, our results indicate that online modules can be used to enhance knowledge about health consequences of unhealthy behavior in clients with weight-related health risks.

Persuasive design in the context of home rehabilitation of the elderly has been applied. Developing various prototypes based on persuasive features and behavioral changes helps to tune to more personalized solutions and serves as a valuable tool for implementing blended care in the practice.

Background The last decade has seen a substantial increase in the use of mobile health apps and research into the effects of those apps on health and health behaviors. In parallel, research has aimed at identifying population subgroups that are more likely to use those health apps. Current evidence is limited by two issues. First, research has focused on broad health apps, and little is known about app usage for a specific health behavior. Second, research has focused on comparing current users and current nonusers, without considering subgroups of nonusers. Objective We aimed to provide profile distributions of current users, previous users, and informed nonusers, and to identify predictor variables relevant for profile classification. Methods Data were available from 1683 people who participated in a Dutch walking event in Amsterdam that was held in September 2017. They provided information on demographics, self-reported walking behavior, and walking app usage, as well as items from User Acceptance of Information Technology, in an online survey. Data were analyzed using discriminant function analysis and multinomial logistic regression analysis. Results Most participants were current walking app users (899/1683, 53.4%), while fewer participants were informed nonusers (663/1683, 39.4%) and very few were previous walking app users (121/1683, 7.2%). Current walking app users were more likely to report walking at least 5 days per week and for at least 30 minutes per bout (odds ratio [OR] 1.44, 95% CI 1.11-1.85; P=.005) and more likely to be overweight (OR 1.72, 95% CI 1.24-2.37; P=.001) or obese (OR 1.49, 95% CI 1.08-2.08; P=.005) as compared with informed nonusers. Further, current walking app users perceived their walking apps to be less boring, easy to use and retrieve information, and more helpful to achieve their goals. Effect sizes ranged from 0.10 (95% CI 0.08-0.30) to 1.58 (95% CI 1.47-1.70). Conclusions The distributions for walking app usage appeared different from the distributions for more general health app usage. Further, the inclusion of two specific subgroups of nonusers (previous users and informed nonusers) provides important information for health practitioners and app developers to stimulate continued walking app usage, including making information in those apps easy to understand and making it easy to obtain information from the apps, as well as preventing apps from becoming boring and difficult to use for goal attainment.

In dit abstract wordt de ontwikkeling van een online onderwijsmodule beschreven gericht op eHealth voor leefstijlverbetering

Deze workshop werd door Katja Braam en Joan Dallinga verzorgd op het Symposium Participatie in Gezondheidsinnovatie. In deze workshop werden deelnemers meegenomen in het ontwikkelproces van de online module die we met en voor Sportkunde studenten ontwikkelen. Hierin leren studenten een leefstijl interventie te ontwikkelen waarin eHealth wordt gebruikt. Hoe hebben we dit gedaan, wat waren de uitdagingen en hoe ver zijn we nu? De concept module werd getoond zien en deelnemers gingen aan de slafg om de module aan te scherpen. Ook zijn ervaringen in andere opleidingen met de ontwikkeling van eHealth onderwijs opgehaald.

Objectives To report (1) the injury incidence in recreational runners in preparation for a 8-km or 16-km running event and (2) which factors were associated with an increased injury risk. Methods Prospective cohort study in Amsterdam, the Netherlands. Participants (n=5327) received a baseline survey to determine event distance (8 km or 16 km), main sport, running experience, previous injuries, recent overuse injuries and personal characteristics. Three days after the race, they received a follow-up survey to determine duration of training period, running distance per week, training hours, injuries during preparation and use of technology. Univariate and multivariate regression models were applied to examine potential risk factors for injuries. Results 1304 (24.5%) participants completed both surveys. After excluding participants with current health problems, no signed informed consent, missing or incorrect data, we included 706 (13.3%) participants. In total, 142 participants (20.1%) reported an injury during preparation for the event. Univariate analyses (OR: 1.7, 95% CI 1.1 to 2.4) and multivariate analyses (OR: 1.7, 95% CI 1.1 to 2.5) showed that injury history was a significant risk factor for running injuries (Nagelkerke R-square=0.06). Conclusion An injury incidence for recreational runners in preparation for a running event was 20%. A previous injury was the only significant risk factor for running-related injuries.

BackgroundA large number of people participate in individual or unorganized sports on a recreational level. Furthermore, many participants drop out because of injury or lowered motivation. Potentially, physical activity–related apps could motivate people during sport participation and help them to follow and maintain a healthy active lifestyle. It remains unclear what the quality of running, cycling, and walking apps is and how it can be assessed. Quality of these apps was defined as having a positive influence on participation in recreational sports. This information will show which features need to be assessed when rating physical activity–related app quality. ObjectiveThe aim of this study was to identify expert perception on which features are important for the effectiveness of physical activity–related apps for participation in individual, recreational sports. MethodsData were gathered via an expert panel approach using the nominal group technique. Two expert panels were organized to identify and rank app features relevant for sport participation. Experts were researchers or professionals in the field of industrial design and information technology (technology expert panel) and in the field of behavior change, health, and human movement sciences who had affinity with physical activity–related apps (health science expert panel). Of the 24 experts who were approached, 11 (46%) agreed to participate. Each panel session consisted of three consultation rounds. The 10 most important features per expert were collected. We calculated the frequency of the top 10 features and the mean importance score per feature (0-100). The sessions were taped and transcribed verbatim; a thematic analysis was conducted on the qualitative data. ResultsIn the technology expert panel, applied feedback and feedforward (91.3) and fun (91.3) were found most important (scale 0-100). Together with flexibility and look and feel, these features were mentioned most often (all n=4 [number of experts]; importance scores=41.3 and 43.8, respectively). The experts in the health science expert panels a and b found instructional feedback (95.0), motivating or challenging (95.0), peer rating and use (92.0), motivating feedback (91.3), and monitoring or statistics (91.0) most important. Most often ranked features were monitoring or statistics, motivating feedback, works good technically, tailoring starting point, fun, usability anticipating or context awareness, and privacy (all n=3-4 [number of experts]; importance scores=16.7-95.0). The qualitative analysis resulted in four overarching themes: (1) combination behavior change, technical, and design features needed; (2) extended feedback and tailoring is advised; (3) theoretical or evidence base as standard; and (4) entry requirements related to app use. ConclusionsThe results show that a variety of features, including design, technical, and behavior change, are considered important for the effectiveness of physical activity–related apps by experts from different fields of expertise. These insights may assist in the development of an improved app rating scale.

During the persuasive technology symposium, Marije Deutekom - Baart de la Faille and colleagues organised a symposium session with 4 presentations: • Presentation 1: A home based exercise program: are older adults able to use mHealth technology? (Sumit Mehra). • Presentation 2: Promoting healthy diet and physical activity in children through the use of games: bridging the gap between industry and science (Monique Simons). • Presentation 3: Increased motivation for exercise through exercise apps such as BAMBEA (Joey van der Bie & Nicky Nibbeling) • Presentation 4: Which factors are important for effectiveness of sport- and health-related apps? Results of focus groups with experts (Joan Dallinga).

objectives To evaluate dynamic stability index (DSI) differences between males and females for different jump directions. To examine both preseason DSI differences between players with and without a history of ankle sprain, and between players with and without an ankle sprain during the subsequent season. Design Prospective cohort design.

Background Injuries to lower extremities are common in team sports such as soccer, basketball, volleyball, football and field hockey. Considering personal grief, disabling consequences and high costs caused by injuries to lower extremities, the importance for the prevention of these injuries is evident. From this point of view it is important to know which screening tools can identify athletes who are at risk of injury to their lower extremities. objective The aim of this article is to determine the predictive values of anthropometric and/or physical screening tests for injuries to the leg, anterior cruciate ligament (ACL), knee, hamstring, groin and ankle in team sports. Methods A systematic review was conducted in MEDLINE (1966 to September 2011), EMBASE (1989 to September 2011) and CINAHL (1982 to September 2011). Based on inclusion criteria defined a priori, titles, abstracts and full texts were analyzed to find relevant studies. Results The analysis showed that different screening tools can be predictive for injuries to the knee, ACL, hamstring, groin and ankle. For injuries in general there is some support in the literature to suggest that general joint laxity is a predictive measure for leg injuries. The anterior right/left reach distance >4 cm and the composite reach distance <4.0% of limb length in girls measured with the star excursion balance test (SEBT) may predict leg injuries. Furthermore, an increasing age, a lower hamstring/quadriceps (H : Q) ratio and a decreased range of motion (RoM) of hip abduction may predict the occurrence of leg injuries. Hyperextension of the knee, side-to-side differences in anterior-posterior knee laxity and differences in knee abduction moment between both legs are suggested to be predictive tests for sustaining an ACL injury and height was a predictive screening tool for knee ligament injuries. There is some evidence that when age increases, the probability of sustaining a hamstring injury increases. Debate exists in the analyzed literature regarding measurement of the flexibility of the hamstring as a predictive screening tool, as well as using the H : Q ratio. Hip-adduction-to-abduction strength is a predictive test for hip adductor muscle strain. Studies do not agree on whether RoM of the hamstring is a predictive screening tool for groin injury. Body mass index and the age of an athlete could contribute to an ankle sprain. There is support in the literature to suggest that greater strength of the plantar flexors may

Video feedback may be a powerful tool to change biomechanical landing patterns associated with anterior cruciate ligament (ACL) injury risk. This study investigated the effect of video feedback on drop vertical jump (DVJ) landing strategies in team sport athletes. 59 athletes were assigned to a video feedback (VI) or control (CTRL) group. A pretest, 2 training sessions and a posttest were conducted. In both training sessions, video feedback, consisting of a video of the athlete's contour superimposed onto an expert's contour performing the DVJ landing task, was provided to the VI group; the CTRL group did not receive feedback. Outcomes included: kinematics and kinetics at peak knee valgus/varus moment during pre- and posttest and percentage overlap of expert and athlete during the training sessions. At posttest, males in the VI group showed greater hip flexion angles (p=0.001) and range of motion (p<0.001), smaller vertical ground reaction force, and smaller ankle dorsiflexion moment (p<0.001) compared to pretest. At posttest, males in the VI group demonstrated smaller vertical ground reaction force (p=0.031) and ankle dorsiflexion moment (p=0.001) compared to males in the CTRL group. The VI group increased percentage overlap with the expert during training sessions and from start of the first to the end of the second training session (p<0.001). Overall, video feedback was effective to modify landing strategies favorably in males. While females imitated the expert model, their landing strategy did not change significantly. While Females may need additional (verbal) feedback to benefit from video feedback.

Dit rapport bevat een evaluatie van de maatschappelijke impact van deelname aan de Dam tot Damloop. Hierbij wordt aandacht besteed aan het gebruik van technologie, gezondheidseffecten, effecten op werkgerelateerde uitkomsten en profielen van hardlopers worden in kaart gebracht.