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.
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.
OBJECTIVES: To make practical recommendations for improving oral hygiene behavior (OHB) potential predictors based on the Theory of Planned Behavior (TPB) were assessed. Measurements of oral health knowledge (OHK) and the expected social effect for having healthy teeth were included.METHODS: 216 recruits in the Dutch Army ground forces completed a questionnaire about oral hygiene behavior, attitudes, social norms, perceived behavioral control (PBC), intention to perform optimal OHB, OHK, and expected social outcomes.RESULTS: The multivariate regression analysis revealed that attitude and PBC explained 37.2% of the variance in intention to perform optimal oral hygiene behavior, which is a substantial proportion. Furthermore, actual oral hygiene behavior was only predicted by attitude, explaining 7.1% of the variance.CONCLUSION: The present findings suggest that recruits' oral hygiene behavior may be improved by promoting a more positive attitude and especially by enhancing perceived behavior control.
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Our world is changing rapidly as a result of societal and technological developments that create new opportunities and challenges. Extended Realities (XR) could provide solutions for the problems the world is facing. In this project we apply these novel solutions in food and hospitality. It aims to tackle fundamental questions on how to stimulate a healthy and vital society that is based on a sustainable and innovative economy. This project aims to answer the question: How can Extended Reality (XR) technologies be integrated in the design of immersive food experiences to stimulate sustainable consumption behavior? A multidisciplinary approach, that has demonstrated its strength in the creative industry, will be applied in the hospitality and food sector. The project investigates implications and design considerations for immersion through XR technology that can stimulate sustainable consumption behavior. Based on XR prototypes, physiological data will be collected using biometric measuring devices in combination with self-reports. The effect of stimuli on sustainable consumption behavior during the immersive experience will be tested to introduce XR implementations that can motivate long-term behavioral change in food consumption. The results of the project contribute towards developing innovations in the hospitality sector that can tackle global societal challenges by exploiting the impact of new technology and understanding of consumer behavior to promote a healthy lifestyle and economy. Next to academic publications and conference contributions, the project will develop a handbook for hospitality professionals. It will outline steps and design criteria for the implementation of XR technologies to create immersive experiences that can stimulate sustainable consumption behavior. The knowledge generated in the project will contribute to the development of the curriculum at the Academy for Hotel and Facility at Breda University of Applied Sciences by introducing a technology-driven experience design approach for the course Sustainable Strategic Business Design.
Lack of physical activity in urban contexts is an increasing health risk in The Netherlands and Brazil. Exercise applications (apps) are seen as potential ways of increasing physical activity. However, physical activity apps in app stores commonly lack a scientific base. Consequently, it remains unknown what specific content messages should contain and how messages can be personalized to the individual. Moreover, it is unknown how their effects depend on the physical urban environment in which people live and on personal characteristics and attitudes. The current project aims to get insight in how mobile personalized technology can motivate urban residents to become physically active. More specifically, we aim to gain insight into the effectiveness of elements within an exercise app (motivational feedback, goal setting, individualized messages, gaming elements (gamification) for making people more physically active, and how the effectiveness depends on characteristics of the individual and the urban setting. This results in a flexible exercise app for inactive citizens based on theories in data mining, machine learning, exercise psychology, behavioral change and gamification. The sensors on the mobile phone, together with sensors (beacons) in public spaces, combined with sociodemographic and land use information will generate a massive amount of data. The project involves analysis in two ways. First, a unique feature of our project is that we apply machine learning/data mining techniques to optimize the app specification for each individual in a dynamic and iterative research design (Sequential Multiple Assignment Randomised Trial (SMART)), by testing the effectiveness of specific messages given personal and urban characteristics. Second, the implementation of the app in Sao Paolo and Amsterdam will provide us with (big) data on use of functionalities, physical activity, motivation etc. allowing us to investigate in detail the effects of personalized technology on lifestyle in different geographical and cultural contexts.
Lack of physical activity in urban contexts is an increasing health risk in The Netherlands and Brazil. Exercise applications (apps) are seen as potential ways of increasing physical activity. However, physical activity apps in app stores commonly lack a scientific base. Consequently, it remains unknown what specific content messages should contain and how messages can be personalized to the individual. Moreover, it is unknown how their effects depend on the physical urban environment in which people live and on personal characteristics and attitudes. The current project aims to get insight in how mobile personalized technology can motivate urban residents to become physically active. More specifically, we aim to gain insight into the effectiveness of elements within an exercise app (motivational feedback, goal setting, individualized messages, gaming elements (gamification) for making people more physically active, and how the effectiveness depends on characteristics of the individual and the urban setting. This results in a flexible exercise app for inactive citizens based on theories in data mining, machine learning, exercise psychology, behavioral change and gamification. The sensors on the mobile phone, together with sensors (beacons) in public spaces, combined with sociodemographic and land use information will generate a massive amount of data. The project involves analysis in two ways. First, a unique feature of our project is that we apply machine learning/data mining techniques to optimize the app specification for each individual in a dynamic and iterative research design (Sequential Multiple Assignment Randomised Trial (SMART)), by testing the effectiveness of specific messages given personal and urban characteristics. Second, the implementation of the app in Sao Paolo and Amsterdam will provide us with (big) data on use of functionalities, physical activity, motivation etc. allowing us to investigate in detail the effects of personalized technology on lifestyle in different geographical and cultural contexts.
