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The current physical activity (PA) recommendations advise adults toperform moderate-intensity aerobic PA for a minimum of 30 minutes five days a week or vigorous-intensity aerobic activity for a minimum of 20 minutes three days a week. Despite many evidence supporting PA for the prevention and management of several health problems such as metabolic disorders, cardiovascular disease and certain forms of cancer, 41% of the Belgian population does not take part in these recommended levels of exercise. Even though they are well aware of the health benefits, sometimes they are unable to take action or change their behavior and to adopt a healthier lifestyle. </>
The PA recommendations can be difficult to achieve, especially because physically inactive people are often unaware of their own inactivity. Unlike dichotomous behaviors such as smoking, PAis complex and multi-dimensional which makes it difficult to assess. Itis identified by frequency, duration, intensity and type, takes place in a variety of different domains and can consist of both incidental as habitual activities over a 24-hour period. Evidence to date suggests that48 to 61% of adults of the currently insufficiently active population overestimate their own level of PA. Despite being at greatest risk of health problems, those who fail to recognize their inactivity are unlikely to perceive a need to change and may be less susceptible to health promotion strategies. Therefore inventing simple, easy to implement methods which help to provide awareness of the own PA level and motivation to increase PA should be investigated. </>
Many intervention studies have been performed in the past, trying to increase the PA levels of inactive adults. While most of these studies report moderate success by achievingshort-term improvements, recent reviews show that effect sizes are generally small and longer-term gains are difficult to achieve. However, it is indicated that measurement of the activity behavior and feedback on the activity behavior and/or behavioral outcome may help to increase bothawareness of health behavior and intentions to change that behavior. </>
Interest in monitoring individual PA levels is rising as the benefits of PA are being increasingly emphasized. Researchers are looking for innovative measurement technologies that are accurate, reliable, practical and affordable. Pedometers have been used in numerous research interventions aimed at increasing levels of PA. They provide immediate feedback on levels of PA and in this way acts both as a motivator and a monitorof activity. For motivational purposes, a step counter may suffice, andthese are more feasible from a cost standpoint. However, if PA energy expenditure (EE) is desired outcome variable, more sophisticated accelerometer-based devices have some advantages. </></>
The SenseWear Armband (SWA) (BodyMedia, Inc. Pittsburgh, PA) is a PA monitor that is worn onthe upper arm and receives information from different sensors includinga near-body ambient temperature sensor, a skin temperature sensor, a galvanic skin sensor, a heat flux sensor and an accelerometer to estimate EE. The innovation of integrating physiological measurements with accelerometry may enhance EE prediction, particularly in low-intensity activities and during activities with limited body movements (e.g., resistance exercises). The SWA has been validated as an accurate measure of both minute-by-minute as well as average EE for low-to-moderate intensity activities. Because new recommendation of PA states the involvement of higherintensity exercise bouts, it is important to accurately assess the validity of the SWA during vigorous and very vigorous intensities</></>. Recently a new algorithm was developed aiming to further improve estimationof EE during free-living activities. To our knowledge, previous validation studies do not include different speeds ranging from moderate to very vigorous intensity in one single exercise trial. Furthermore, no studyhas ever validated the new SWA algorithm. In addition, the validity of the SWA in different ambient temperature conditions relative to a reference method has never been tested. Measuring the EE of people exercising in various temperatures at different intensities can be interesting to objectively and unobtrusively determine the exercise load. These gaps in the literature were the starting point of the methodological chapter</> of the doctoral study. </>
</>
The first paper of our methodological chapter examined the ability of the new SWA algorithm to accurately assess EE at different speeds ranging from moderate to very vigorous intensity through comparison with the golden standard of indirect calorimetry (IC)(paper 1).</> The results indicated that SWA underestimated EE ranging from 0.93 ± 1.21 kcal/min (p<0.001) when jogging at 6 km/h to10.27 ± 3.04 kcal/min (p<0.001) when running at 16.2 km/h. Despite thisunderestimation, EE measured by the SWA and IC were significantly and substantially correlated for each running speed. A ceiling effect was found at 9.6 METs with a corresponding running speed of 9 km/h. Exceeding this threshold level resulted in an underestimation of EE. We advised to adapt the SenseWear algorithm to enhance the accuracy to estimate EE during high intensity running exercises. </>
</>
The second paper determined the validity of the SWA during intermittent training (paper 2).</> The results of this study supported the use of the SWA for moderate intensity exercises and confirmed the underestimation of EE at higher intensities. The recently developed SWA algorithm showed a better accuracy over the old SWA algorithm. Overall, the differences in EE estimates with IC were significant smaller for the newer algorithm (difference=-0.88 ± 0.09 kcal/min; p<0.001) than for the old algorithm (difference=-1.88 ± 0.09 kcal/min; p<0.001). However, measuring EE at higher intensities remained challenging. Our data implied that athletes should be cautious when using the SWA during their intermittent training because of theunderestimation of EE at high intensity exercise.</>
To investigate if the underestimation in EE at high intensity was a result of inaccuracy of the sensors, we decided to manipulate the ambient temperature (19°C, 26°C and 33°C) and examine the validity of SWA in those different temperatures (paper 3)</>. Our results revealed that the old SenseWear algorithm was inaccurate in estimating EE in the hot temperature condition (mean bias=-1.55 ± 1.59 kcal/min; p<0.001). A possible explanation for this underestimation of EE is an error in the reading of the heat-related sensors. With respect to the evaluation of the new algorithm, our study showed a significant improvement for the new algorithm in assessing EE while exercising in a hot environment and at high intensity. </>
</>
Overall, from the results of our validation papers, it can be concluded that the new SenseWear algorithm is valid at moderate intensity, but that it inaccurately estimates EE at intensities above 9.6 METs or at a running speed above 9 km/h. The newly developed algorithm demonstrates improved accuracy for high intensity exercises and a hot environment;however it should further be adapted to accurately assess EE. </>
</>
The second chapter of this dissertation illustrates a randomized controlled trial study which was conducted in a sample of insufficiently active working adults. The intervention study</> evaluated the short-term and one-year effectiveness of different degrees of measurement feedback to enhance PA and investigated the added value of need-supportivecoaching. Follow-up measurements were obtained immediately after the 4-week intervention period and 3 months, 6 months and 1 year after baseline measurement. The first paper on this intervention study (paper 4</>) explained the design of the randomized controlled trial, discussed the characteristics of the participants, looked at the recruitment and randomization process and gave a detailed description of the intervention arms.Furthermore, the self-determination theory was described, which is the psychological theory underlying the need-supportive coaching. </>
</>
The second and third paper on the intervention study presentedthe short-term and one-year effectiveness of these different degrees offeedback on the activity behavior and investigated the added value of need-supportive coaching. The short-term paper (paper 5</>) aimed at evaluating the efficacy of providing real-time feedback on the walking behavior (Pedometer Group) compared with a no-feedback condition (Minimal Intervention Group). Moreover, this study aimed at investigating whether feedback on both the activity behavior (e.g. steps and minutes of moderateto vigorous PA) and behavioral outcome (e.g. total calories burned; Display Group) would increase the PA level more in comparison with a standard 10,000 step program (Pedometer Group). Our final aim was to test whether a weekly meeting with a Personal Coach (Coaching Group) would createa need-supportive environment and thereby influencing the PA behavior. Our results showed more steps/day for the Pedometer Group compared with the Minimal Intervention Group, but only the 1st week of the intervention. No differences were reported between the Pedometer Group and the Display Group after completion of the intervention. When comparing the Coaching Group with the Display Group, the Coaching Group had higher PA values throughout and after the intervention compared with the Display Group.It appeared that adding need-supportive coaching was necessary to successfully increase the activity behavior throughout and immediately after a 4-week intervention period.</>
</>
In the third paper on the intervention study (paper 6</>), we evaluated the one-year effectiveness of different degrees of measurement feedback and whether the promising short-term results of need-supportive coaching could be maintained over a 1-year period. No significant differences were reported between theMinimal Intervention Group and the Pedometer Group with the exception of post6m, where the Minimal Intervention Group showed a lower total EE. One year after randomization, participants of the Display Group spent significantly fewer time at PA, had a lower active EE and a lower PA levelcompared with the Pedometer Group. When comparing the Coaching Group with the Display Group, our results showed that the Coaching Group took more steps, spent more minutes at PA and had a higher PA level. These findings suggest that feedback interventions should be accompanied by a Personal Coach in order to increase the long-term likelihood of success</>
</>
The current study demonstrates the potential importance of need-supportive coaching for both short and long-term PA behavioral change. Attention should be paid to providing individuals with feedback onthe progress they made in changing their PA behavior. This should be supported in a need-supportive climate. Mechanisms that can provide feedback in real-time are promising on the short-term but should be supported by need-supportive coaching to expand their effects. An important role is thus predetermined for the Personal Coach</> which can help increasingthe prevalence of people who are physically active. Particular contributions of the coaches include investigating the determinants of active and insufficiently active lifestyles, developing appropriate theoretical frameworks for interventions, training other professionals in behavioral change strategies, advising on the positive health-related outcomes fromactivity and supporting individuals in becoming more autonomously motivated in changing their lifestyle. </></>
Project
Effectiveness of feedback and need-supportive coaching on physical activity among working adults: Validation of a multisensory activity device and evaluation of an intervention
The current physical activity (PA) recommendations advise adults toperform moderate-intensity aerobic PA for a minimum of 30 minutes five days a week or vigorous-intensity aerobic activity for a minimum of 20 minutes three days a week. Despite many evidence supporting PA for the prevention and management of several health problems such as metabolic disorders, cardiovascular disease and certain forms of cancer, 41% of the Belgian population does not take part in these recommended levels of exercise. Even though they are well aware of the health benefits, sometimes they are unable to take action or change their behavior and to adopt a healthier lifestyle. </>
The PA recommendations can be difficult to achieve, especially because physically inactive people are often unaware of their own inactivity. Unlike dichotomous behaviors such as smoking, PAis complex and multi-dimensional which makes it difficult to assess. Itis identified by frequency, duration, intensity and type, takes place in a variety of different domains and can consist of both incidental as habitual activities over a 24-hour period. Evidence to date suggests that48 to 61% of adults of the currently insufficiently active population overestimate their own level of PA. Despite being at greatest risk of health problems, those who fail to recognize their inactivity are unlikely to perceive a need to change and may be less susceptible to health promotion strategies. Therefore inventing simple, easy to implement methods which help to provide awareness of the own PA level and motivation to increase PA should be investigated. </>
Many intervention studies have been performed in the past, trying to increase the PA levels of inactive adults. While most of these studies report moderate success by achievingshort-term improvements, recent reviews show that effect sizes are generally small and longer-term gains are difficult to achieve. However, it is indicated that measurement of the activity behavior and feedback on the activity behavior and/or behavioral outcome may help to increase bothawareness of health behavior and intentions to change that behavior. </>
Interest in monitoring individual PA levels is rising as the benefits of PA are being increasingly emphasized. Researchers are looking for innovative measurement technologies that are accurate, reliable, practical and affordable. Pedometers have been used in numerous research interventions aimed at increasing levels of PA. They provide immediate feedback on levels of PA and in this way acts both as a motivator and a monitorof activity. For motivational purposes, a step counter may suffice, andthese are more feasible from a cost standpoint. However, if PA energy expenditure (EE) is desired outcome variable, more sophisticated accelerometer-based devices have some advantages. </></>
The SenseWear Armband (SWA) (BodyMedia, Inc. Pittsburgh, PA) is a PA monitor that is worn onthe upper arm and receives information from different sensors includinga near-body ambient temperature sensor, a skin temperature sensor, a galvanic skin sensor, a heat flux sensor and an accelerometer to estimate EE. The innovation of integrating physiological measurements with accelerometry may enhance EE prediction, particularly in low-intensity activities and during activities with limited body movements (e.g., resistance exercises). The SWA has been validated as an accurate measure of both minute-by-minute as well as average EE for low-to-moderate intensity activities. Because new recommendation of PA states the involvement of higherintensity exercise bouts, it is important to accurately assess the validity of the SWA during vigorous and very vigorous intensities</></>. Recently a new algorithm was developed aiming to further improve estimationof EE during free-living activities. To our knowledge, previous validation studies do not include different speeds ranging from moderate to very vigorous intensity in one single exercise trial. Furthermore, no studyhas ever validated the new SWA algorithm. In addition, the validity of the SWA in different ambient temperature conditions relative to a reference method has never been tested. Measuring the EE of people exercising in various temperatures at different intensities can be interesting to objectively and unobtrusively determine the exercise load. These gaps in the literature were the starting point of the methodological chapter</> of the doctoral study. </>
</>
The first paper of our methodological chapter examined the ability of the new SWA algorithm to accurately assess EE at different speeds ranging from moderate to very vigorous intensity through comparison with the golden standard of indirect calorimetry (IC)(paper 1).</> The results indicated that SWA underestimated EE ranging from 0.93 ± 1.21 kcal/min (p<0.001) when jogging at 6 km/h to10.27 ± 3.04 kcal/min (p<0.001) when running at 16.2 km/h. Despite thisunderestimation, EE measured by the SWA and IC were significantly and substantially correlated for each running speed. A ceiling effect was found at 9.6 METs with a corresponding running speed of 9 km/h. Exceeding this threshold level resulted in an underestimation of EE. We advised to adapt the SenseWear algorithm to enhance the accuracy to estimate EE during high intensity running exercises. </>
</>
The second paper determined the validity of the SWA during intermittent training (paper 2).</> The results of this study supported the use of the SWA for moderate intensity exercises and confirmed the underestimation of EE at higher intensities. The recently developed SWA algorithm showed a better accuracy over the old SWA algorithm. Overall, the differences in EE estimates with IC were significant smaller for the newer algorithm (difference=-0.88 ± 0.09 kcal/min; p<0.001) than for the old algorithm (difference=-1.88 ± 0.09 kcal/min; p<0.001). However, measuring EE at higher intensities remained challenging. Our data implied that athletes should be cautious when using the SWA during their intermittent training because of theunderestimation of EE at high intensity exercise.</>
To investigate if the underestimation in EE at high intensity was a result of inaccuracy of the sensors, we decided to manipulate the ambient temperature (19°C, 26°C and 33°C) and examine the validity of SWA in those different temperatures (paper 3)</>. Our results revealed that the old SenseWear algorithm was inaccurate in estimating EE in the hot temperature condition (mean bias=-1.55 ± 1.59 kcal/min; p<0.001). A possible explanation for this underestimation of EE is an error in the reading of the heat-related sensors. With respect to the evaluation of the new algorithm, our study showed a significant improvement for the new algorithm in assessing EE while exercising in a hot environment and at high intensity. </>
</>
Overall, from the results of our validation papers, it can be concluded that the new SenseWear algorithm is valid at moderate intensity, but that it inaccurately estimates EE at intensities above 9.6 METs or at a running speed above 9 km/h. The newly developed algorithm demonstrates improved accuracy for high intensity exercises and a hot environment;however it should further be adapted to accurately assess EE. </>
</>
The second chapter of this dissertation illustrates a randomized controlled trial study which was conducted in a sample of insufficiently active working adults. The intervention study</> evaluated the short-term and one-year effectiveness of different degrees of measurement feedback to enhance PA and investigated the added value of need-supportivecoaching. Follow-up measurements were obtained immediately after the 4-week intervention period and 3 months, 6 months and 1 year after baseline measurement. The first paper on this intervention study (paper 4</>) explained the design of the randomized controlled trial, discussed the characteristics of the participants, looked at the recruitment and randomization process and gave a detailed description of the intervention arms.Furthermore, the self-determination theory was described, which is the psychological theory underlying the need-supportive coaching. </>
</>
The second and third paper on the intervention study presentedthe short-term and one-year effectiveness of these different degrees offeedback on the activity behavior and investigated the added value of need-supportive coaching. The short-term paper (paper 5</>) aimed at evaluating the efficacy of providing real-time feedback on the walking behavior (Pedometer Group) compared with a no-feedback condition (Minimal Intervention Group). Moreover, this study aimed at investigating whether feedback on both the activity behavior (e.g. steps and minutes of moderateto vigorous PA) and behavioral outcome (e.g. total calories burned; Display Group) would increase the PA level more in comparison with a standard 10,000 step program (Pedometer Group). Our final aim was to test whether a weekly meeting with a Personal Coach (Coaching Group) would createa need-supportive environment and thereby influencing the PA behavior. Our results showed more steps/day for the Pedometer Group compared with the Minimal Intervention Group, but only the 1st week of the intervention. No differences were reported between the Pedometer Group and the Display Group after completion of the intervention. When comparing the Coaching Group with the Display Group, the Coaching Group had higher PA values throughout and after the intervention compared with the Display Group.It appeared that adding need-supportive coaching was necessary to successfully increase the activity behavior throughout and immediately after a 4-week intervention period.</>
</>
In the third paper on the intervention study (paper 6</>), we evaluated the one-year effectiveness of different degrees of measurement feedback and whether the promising short-term results of need-supportive coaching could be maintained over a 1-year period. No significant differences were reported between theMinimal Intervention Group and the Pedometer Group with the exception of post6m, where the Minimal Intervention Group showed a lower total EE. One year after randomization, participants of the Display Group spent significantly fewer time at PA, had a lower active EE and a lower PA levelcompared with the Pedometer Group. When comparing the Coaching Group with the Display Group, our results showed that the Coaching Group took more steps, spent more minutes at PA and had a higher PA level. These findings suggest that feedback interventions should be accompanied by a Personal Coach in order to increase the long-term likelihood of success</>
</>
The current study demonstrates the potential importance of need-supportive coaching for both short and long-term PA behavioral change. Attention should be paid to providing individuals with feedback onthe progress they made in changing their PA behavior. This should be supported in a need-supportive climate. Mechanisms that can provide feedback in real-time are promising on the short-term but should be supported by need-supportive coaching to expand their effects. An important role is thus predetermined for the Personal Coach</> which can help increasingthe prevalence of people who are physically active. Particular contributions of the coaches include investigating the determinants of active and insufficiently active lifestyles, developing appropriate theoretical frameworks for interventions, training other professionals in behavioral change strategies, advising on the positive health-related outcomes fromactivity and supporting individuals in becoming more autonomously motivated in changing their lifestyle. </></>
Date:17 Feb 2009 → 20 Mar 2015
Keywords:Real-time feedback, Physical activity
Disciplines:Education curriculum
Project type:PhD project