OBJECTIVE: The aim of this study was to develop an index for oral hygiene behavior (OHB) and to examine potential predictors of this actual behavior based on the theory of planned behavior (TPB). Measures of oral health knowledge (OHK) and the expected effect of having healthy teeth on social relationships were included too.MATERIAL AND METHODS: Using an Internet questionnaire, 487 participants were asked about actual OHB, attitudes (ATT), social norms (SN), perceived behavioral control (PBC), OHK, and expected social outcomes (ESO). Based on a Delphi method involving oral health professionals, a new index for OHB was developed, including tooth brushing, interdental cleaning, and tongue cleaning.RESULTS: Regression analysis revealed that the TPB variables (ATT, SN, and PBC) and OHK explained 32.3% of the variance in self-reported OHB.CONCLUSION: The present findings indicate that socio-psychological consequences play a role in oral health care.
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De verdediging hiervan was op 26 september. Background: The insertion of fixed orthodontic appliances increases the risk of dental caries, particularly in adolescents. Caries can be prevented through good oral health behavior. To support adolescents with fixed orthodontic appliances and for promoting oral health behavior, we developed a theory- and evidence-based mHealth program, the WhiteTeeth app. Objective: The objective of our paper was to describe the systematic development and content of the WhiteTeeth app. Methods: For systematic development of the program, we used the intervention mapping (IM) approach. In this paper, we present the results of applying the first 5 steps of IM to the design of an mHealth program: (1) identifying target behaviors and determinants through problem analysis, including a literature search, a survey study, and semistructured interviews, to explore adolescent oral health behavior during orthodontic therapy; (2) defining program outcomes and objectives; (3) selecting theoretical methods and translating them into practical strategies for the program design; (4) producing the program, including a pilot test with 28 adolescents testing the acceptability and usability of the WhiteTeeth app; and (5) planning implementation and adoption. Auteurs: Scheerman, J.F.M., van Empelen, P., van Loveren, C., & van Meijel, B. (2018)
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In BMC Oral Health verscheen het volgende artikel van Inholland-docente en promovenda Janneke Scheerman (en collega’s). Background: Adolescents with fixed orthodontic appliances are at high risk of developing dental caries. To date, new smartphone technologies have seldom been used to support them in the preventive behavior that can help prevent dental caries. After an intervention-mapping process, we developed a smartphone application (the WhiteTeeth app) for preventing dental caries through improved oral-health behavior and oral hygiene. The app, which is intended to be used at home, will help adolescents with fixed orthodontic appliances perform their oral self-care behavior. The app is based on the Health Action Process Approach (HAPA) theory, and incorporates several behavior-change techniques that target the psychosocial factors of oral-health behavior. This article describes the protocol of a randomized controlled trial (RCT) to evaluate the effects of the WhiteTeeth app on oral-health behavior and oral-hygiene outcomes (presence of dental plaque and gingival bleeding) compared with those of care as usual, in patients aged 12–16 with fixed orthodontic appliances.
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Background Movement behaviors (i.e., physical activity levels, sedentary behavior) in people with stroke are not self-contained but cluster in patterns. Recent research identified three commonly distinct movement behavior patterns in people with stroke. However, it remains unknown if movement behavior patterns remain stable and if individuals change in movement behavior pattern over time. Objectives 1) To investigate the stability of the composition of movement behavior patterns over time, and 2) determine if individuals change their movement behavior resulting in allocation to another movement behavior pattern within the first two years after discharge to home in people with a first-ever stroke. Methods Accelerometer data of 200 people with stroke of the RISE-cohort study were analyzed. Ten movement behavior variables were compressed using Principal Componence Analysis and K-means clustering was used to identify movement behavior patterns at three weeks, six months, one year, and two years after home discharge. The stability of the components within movement behavior patterns was investigated. Frequencies of individuals’ movement behavior pattern and changes in movement behavior pattern allocation were objectified. Results The composition of the movement behavior patterns at discharge did not change over time. At baseline, there were 22% sedentary exercisers (active/sedentary), 45% sedentary movers (inactive/sedentary) and 33% sedentary prolongers (inactive/highly sedentary). Thirty-five percent of the stroke survivors allocated to another movement behavior pattern within the first two years, of whom 63% deteriorated to a movement behavior pattern with higher health risks. After two years there were, 19% sedentary exercisers, 42% sedentary movers, and 39% sedentary prolongers. Conclusions The composition of movement behavior patterns remains stable over time. However, individuals change their movement behavior. Significantly more people allocated to a movement behavior pattern with higher health risks. The increase of people allocated to sedentary movers and sedentary prolongers is of great concern. It underlines the importance of improving or maintaining healthy movement behavior to prevent future health risks after stroke.
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Background: The built environment is increasingly recognized as a determinant for health and health behaviors. Existing evidence regarding the relationship between environment and health (behaviors) is varying in significance and magnitude, and more high-quality longitudinal studies are needed. The aim of this study was to evaluate the effects of a major urban redesign project on physical activity (PA), sedentary behavior (SB), active transport (AT), health-related quality of life (HRQOL), social activities (SA) and meaningfulness, at 29–39 months after opening of the reconstructed area. Methods: PA and AT were measured using accelerometers and GPS loggers. HRQOL and sociodemographic characteristics were assessed using questionnaires. In total, 241 participants provided valid data at baseline and follow-up. We distinguished three groups, based on proximity to the intervention area: maximal exposure group, minimal exposure group and no exposure group. Results: Both the maximal and minimal exposure groups showed significantly different trends regarding transportbased PA levels compared to the no exposure group. In the exposure groups SB decreased, while it increased in the no exposure group. Also, transport-based light intensity PA remained stable in the exposure groups, while it significantly decreased in the no exposure group. No intervention effects were found for total daily PA levels. Scores on SA and meaningfulness increased in the maximal exposure group and decreased in the minimal and no exposure group, but changes were not statistically significant. Conclusion: The results of this study emphasize the potential of the built environment in changing SB and highlights the relevance of longer-term follow-up measurements to explore the full potential of urban redesign projects.
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The global epidemic of overweight and obesity results from individual factors and from meso- and macro environmental factors. Adolescents are especially vulnerable to unhealthy changes in life style. One major influence on health behavior in this age group is represented by friends in peer groups. Young people tend to select and mimic each other with respect to both eating behavior and physical exercise. Peer groups are a close and important source of influence on health behavior and social media strengthens this influence. New research and interventions should take account of the influence of the peer group and social media.
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Objective: Health beliefs of overweight adults who did and did not enter an exercise program were compared to identify possible factors that hamper people to increase physical exercise. Method: Participants (n = 116, 78 women and 38 men) were overweight adults without comorbidities. Self-report instruments examined the burden of suffering, beliefs related to physical exercise and obesity, somatic complaints, and obesity-related quality of life of new participants of exercise programs versus sedentary non-exercisers. Results: Mean BMI of exercisers was and of non-exercisers was 34.6 (7.0) and 32.8 (5.8) respectively. The exercisers were more often female, had fathers with less overweight, and considered overweight a more serious health problem. Fear of injury was higher and perceived health benefits were lower in the non-exercisers, who also more often attributed their overweight to physical causes and believed overweight to be irreversible. Body weight, age, education level, somatic complaints, and quality of life of the groups were comparable. Conclusion: With respect to health beliefs, overweight non-exercisers reported more fear of injury and perceived their overweight as more irreversible than exercisers. Considering these factors in intervention and public health promotion may help overweight sedentary people to start physical exercise.
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Founded in 2004, the Games for Health Project supports community, knowledge and business development efforts to use cutting-edge games and game technologies to improve health and health care. The Games for Health Conference brings together researchers, medical professionals and game developers to share information about the impact of games, playful interaction and game technologies on health, health care and policy. Over two days, more than 400 attendees participate in over 60 sessions provided by an international array of 80+ speakers, cutting across a wide range of activities in health and health care. Topics include exergaming, physical therapy, disease management, health behavior change, biofeedback, rehab, epidemiology, training, cognitive health, nutrition and health education.
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Abstract: 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.
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Movement behaviors, that is, both physical activity and sedentary behavior, are independently associated with health risks. Although both behaviors have been investigated separately in people after stroke, little is known about the combined movement behavior patterns, differences in these patterns between individuals, or the factors associated with these patterns. Therefore, the objectives of this study are (1) to identify movement behavior patterns in people with first-ever stroke discharged to the home setting and (2) to explore factors associated with the identified patterns.
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