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The use of self-monitoring solutions amongst cyclists: An online survey and empirical study
Abstract
Abstract Self-monitoring has been shown to be one of the most efficient behaviour change techniques to promote physical activity. However, there has been no research on the exact nature and impact of using various self-monitoring solutions (e.g. cycle computer, cadence monitor, smartphone’ physical activity apps) amongst cyclists. Initially, an online survey was conducted with 227 adults who did or did not use self-monitoring solutions with their cycling. We found that the most important features for cyclists who use self-monitoring are: time it takes to travel, cycling speed, and distance covered. In contrast, cyclists who do not use self-monitoring perceived features related to location (e.g. directions with maps) as the most important ones. In a subsequent study we included self-monitoring solutions as a part of mixed-design, small-scale, longitudinal intervention aimed at changing transportation patterns. We found that self-monitoring is mainly suitable for performance oriented cyclists rather then recreational cyclists. We discuss the implications of those results for designing interventions to promote cycling.
... Additionally, expert users of FTSs tend to be more goaloriented than novice users (Stragier et al., 2015;Piwek et al., 2015). Cyclists that track QS metrics, usually using mobile apps such as Strava or Endomondo, tend to focus on tracking performance indicators, such as speed, distance, and time, while non-tracking cyclists tend to focus on aspects of cycling such as planning their route and knowing their current location and destination and care less about objective measures of performance. ...
... Additionally, cyclists that track also tend to set performance-oriented goals, such as increasing their speed or distance traveled. However, many casual cyclists are unlikely to find such performance metrics useful (Piwek et al., 2015). ...
... In addition to not finding QS data useful, novice users also tend to not set goals for themselves and expect immediate results from tracking QS metrics, but neglect the fact that habit formation is best done by setting smaller goals in a shorter period of time (Ledger & McCaffrey, 2014;Piwek et al., 2015;Rapp & Cena, 2016). As a result of the lack of perceived usefulness and goal setting habits, novice users tend to abandon their FTSs before they can actually form new healthy habits, such as exercising more or eating healthy (Ledger & McCaffrey, 2014;Rapp & Cena, 2016). ...
Self-quantifying fitness tracking services and wearable devices have become more ubiquitous but still suffer from high abandonment rates. Wearable devices can monitor the physiological changes of the body and alert patients and physicians of immediate needed actions and facilitate in the research process of disease prevention and treatment, especially in areas that have less access to healthcare. This proceeding discusses how to bridge the gap between novice and expert users by implementing gamification techniques and social communities within fitness tracking services to increase the enjoyment, perceived ease of use, perceived usefulness, and long-term engagement of fitness tracking services. Additionally, retention of wearable technology can be improved by applying human factors principles to make products more user-centered and friendly.
... For instance, in respective studies already has been shown that full-time employed people generally tend to use the internet more intensively (Bimber 2000;Conroy and Williams 2014), are more receptive for web-based distance learning (Christensen et al. 2001) and have a higher propensity to use social networking sites (Conroy and Williams 2014). More concrete in the context of mobile applications recent research shows that full-time employed people have a higher propensity to gamble mobile (Gainsbury et al. 2012), to use apps in sporting activities (Piwek et al. 2015) and to use more different types of mobile apps in general (Lai 2014). The identified effects can be justified by spillover effects from the technological environments at the workplaces (Ahuja and Thatcher 2005). ...
... Following recent research we control for effects of education (Chan-Olmsted et al. 2012, Gainsbury et al. 2012, Grosskopf et al. 2014, Lai et al. 2014, Vatanparast and Qadim 2009) as well as the home environment (Conroy and Williams 2014, Gainsbury et al 2012, Piwek et al. 2015 of the interviewees. Therefore we apply categorical variables for education as well as the population of the home residence. ...
Mobile applications which are installed and executed on smartphones (so called " mobile apps ") are currently an intensively debated topic in tourism. Mobile apps provide various potentials for applications in the industry as they enable tourism organizations to provide better services to their customers. Also, they allow tourists special travel experiences which significantly add value to their travel activities. Using a survey of 1'562 tourists in Switzerland we analyse influences of five different person-related factors on tourist's propensity for frequent use of mobile apps on their vacation. Our results show that the general propensity to use internet on holidays corresponds with the propensity to use mobile apps on vacation. In contrast, age and a foreign origin of tourists are negatively related to the propensity to use mobile apps on vacation.
... Advanced sports watches have a lot of multi-sport abilities. For instance, cyclists use smart watches for self-monitoring, and they are mostly used by "competitive cyclists" rather than commuters, in order to improve their cycling performance (Piwek, Joinson, & Morvan, 2015). Another example from the context of swimming relates to watches which can track and understand stroke type and give feedback about the efficiency of the strokes accordingly (i.e. ...
In recent years, design for behaviour change by means of design and technology has been the focus of a large body of research. Advancements in personal informatics systems and applications of these in research have testified to the potential of design for behaviour change strategies in the context of sports and exercise. However, these efforts have been mainly focused at people who are new to sports and not so much at people who are already active. With the success of design for behaviour change studies, this group of more active users (i.e., active exercisers) with an interest in personal informatics has grown. The needs of this group of users are different from those who are unable or unwilling to change their activity behaviour. While the latter might lack knowledge and motivation to change behaviour, active exercisers are already motivated and are willing to stay physically active. Thus, this paper draws out the need and importance of a shift in the focus of designing for physical activity tracking, and discusses the significance of designing for lifelong sports experience. active exercisers; behaviour change; design for sports experience
... Aside from this group of users taking place in the first step, other users who have priorities such as riding the bicycle as a lifestyle for recreation, riding it every other day, riding it when they are not busy, or riding it at specific times are emphasized to be in the recreational lifestyle group of riders. The professional group which is the third group seeing the bicycle as a means of transport meeting the demand professionally in the most extreme conditions follows this group (Piwek, Joinson and Morvan, 2015). In terms of the characteristics of the bicycle rider, bicycle use might be vary depending on social variables such as social norm, and social identity. ...
... Wearable sensors face challenges in their effective integration into clinical care, despite the known health benefits of physical activity and their potential in healthcare [64]. The technology is still new, with devices in early development stages, requiring further exploration of their capabilities, limitations, and practical applications [65]. ...
Purpose of Review
This study aims to evaluate the sensitivity and specificity of wearable devices for AF detection in older adults, as well as examine the incidence of AF across various studies, contextual factors impacting AF detection, and safety and adverse events associated with wearable use.
Recent Findings
A systematic search of three databases identified 30 studies on wearables for AF detection in older adults, encompassing 111,798 participants. Both PPG-based and single-lead electrocardiography-based wearables show scalable potential for screening and managing AF.
Summary
The results of this systematic review demonstrate that wearable devices, such as smartwatches, can effectively identify arrhythmias like AF in older adults, with scalable potential in PPG-based and single-lead electrocardiography-based wearables. As wearable technologies continue to gain prominence in healthcare, it is crucial to understand their challenges and incorporate them as preventative and monitoring tools for AF detection in elderly populations to improve patient care and prevention techniques.
... Understanding and improving cycling performance was also a topic of past studies. Through an online survey with 227 participants Piwek et al. [59] found that self-monitoring was mainly suitable for performance-oriented rather then recreational cyclists. This suggests that performance metrics are relevant for supporting amateurism in cycling. ...
Physical activity is entering the virtual realm. Zwift is an at-home cycling system that is enjoying increasing popularity, yet the specifics of the experience of a virtual cyclist have not been studied to date. Building virtual sports systems can make physical activity accessible to more diverse user groups. To understand how and why users engage in virtual cycling, we conducted n=22 interviews with Zwift users. Through charting the motivations behind using Zwift, we determined that it allowed users to engage in a range of cycling activities traditionally reserved for professional cyclists. Our work reports on key motivations and identifies five key strategies which Zwift uses to create an engaging virtual sports experience. Further, we discuss how Zwift creates a world of virtual professionalism. Our findings offer a structured understanding of the experience of Zwift which can be used to inspire the design of future virtual amateur sports systems.
... However, research on the use of technology to promote active travel is relatively scarce. Among those, the use of accelerometers to monitor activity is a common method, especially with the developments in the smartphone technology (Coombes & Jones, 2016;Piwek, Joinson, & Morvan, 2015). Regular accelerometers and smartphone apps can be used to monitor one's own travel behaviour and serve as a travel diary. ...
Active travel has many benefits for both individuals and societies. While the number of interventions aiming to promote active travel increases, it is usually not easy to deliver those interventions, identify ‘active components’ of them, and/or replicate them. The current paper reports two studies testing interventions that used SMS messages to deliver behaviour change techniques (BCTs) based on the Control Theory (i.e., goal-setting (behaviour), action planning, self-monitoring of behaviour). Study 1 sought to increase the use of a bike share scheme. Participants were randomly assigned to one of three experimental groups that received messages for three BCTs (n = 26), one BCT (n = 29), or no BCTs (n = 40) and were followed up one month later. The effect of intervention on bike use was significant when two intervention groups were combined and compared to the control group. Study 2 tested an intervention to decrease car use. Participants were randomly allocated to one of two experimental groups that receive three BCTs (n = 29) versus no BCTs (n = 32). The effect of the intervention on car use was marginally significant. The results of the two studies suggest that interventions delivering BCTs via SMS message may be used to promote active travel, although both studies were underpowered. Given the relative ease and low cost of delivering psychosocial interventions via SMS messages, the potential public health impact at a population level is, nonetheless, likely to be important.
... Die Anzahl der Smartphone-Nutzer in Deutschland betrug im Februar des Jahres 2018 57 Millionen Menschen, das entspricht 81% der Deutschen über 14 Jahren 1 . Neben einer hohen technologischen Ausrüstung der Bevölkerung, die eine Aufzeichnung gefahrener Wege grundsätzlich erlaubt, ist auch der Trend zum Self-Monitoring ein Wachstumstreiber für die Erfassung von Verkehrsdatensätzen auf GPS-Basis (Piwek, Joinson und Morvan, 2015). Hierfür sorgen im Radverkehrsbereich seit Jahren Tracking-, Navigations-und Sport-Apps wie Strava, Komoot oder Endomondo, mit denen die Nutzer ihre Radfahrten aufzeichnen sowie navigieren können und Kilometerzahlen, Geschwindigkeiten, Höhenmeter und verbrannte Kalorien zurückgespielt bekommen. ...
Analysis data is necessary for bicycle planning, but is hardly available in many municipal-ities. GPS data of cyclists can close this data gap. Existing data sets and research ap-proaches have so far failed to provide evidence of representativeness for the population of cyclists in the respective study area. Moreover, this is often discussed as a weak point of previous work.
In order to examine the question of the representativeness of GPS data sets for the Ger-man region, the present study analyses the cycling behaviour of cyclists in the Dresden area. The basis of the analysis is a GPS data set of 200 test persons collected within the framework of the research project "RadVerS", which contains 5,300 individual routes in the study area of the city of Dresden and allows insights into their cycling behaviour. The collected data was processed with different methods, e.g. trips with other traffic modes were removed and trips were divided into individual routes. The route data was then en-riched with data from the traffic network of the study area and statistically analysed. The influence of individual behavioural parameters was evaluated both descriptively and by means of a generalised linear model.
... In addition to the developments in interface design, increasingly popular tracking and monitoring apps also create new possibilities, especially for cyclists. It has been found that self-monitoring is most relevant for performance-oriented competitive or lifestyle cyclists, and the interesting features are often simple measures such as speed, time, and distance [17]. Moreover, tracking apps and networked bicycles can create big data as part of the smart cities [18]. ...
... Studies have found that several factors influence bicycle uptake in high-income countries, including attitudes [4,5], weather [6][7][8][9][10], social norms and identities [11][12][13]; individual socio-demographic characteristics [14][15][16], comfort and safety [17], environmental awareness [18], air quality [19], integration with public transport [20,21], gender [22], and purpose of cycling [23,24]. A recent study by Iwińska et al. [25] in Warsaw found that a car-oriented culture and fear of injury were the greatest impediments to cycling uptake. ...
Research on the adoption of the bicycle as a means of transport has been booming in high-income countries. However, little is known about bicycle adoption in lower-income countries where air pollution is high and cycling infrastructure is poor. Understanding the drivers of cycling adoption in developing economies can increase the efficiency of transport policies while reducing local air pollution, improving health, and cutting greenhouse gas emissions. The objective of this study is to identify the factors affecting cycling uptake in a low-income country using the city of Bishkek in Kyrgyzstan as a case study. The analysis is based on the Theory of Planned Behavior, a questionnaire-based survey of 900 respondents, factor analysis, and a logit model. In contrast to studies carried out in developed countries, this study finds that students are less likely to adopt cycling than other population groups. Other findings suggest that support for public transport, a desire for regular exercise and perceptions of the environmental benefits of cycling increase the probability of the use of cycling as a mode of transport in a low-income country. The paper also identifies positive and negative perceptions of cycling among cyclists and non-cyclists.
... The data produced by cycling mobile applications are being used to perform mobility analyses in cities. Analyzing the most commonly used routes as well as the origins and destinations will allow policymakers to map out mobility strategies and make decisions based on real data [78,79]. However, self-monitoring bike riding activities are related to a specific context or intent, such as sports and health monitoring [80], which lack some accuracy in data acquisition. Using data from different monitoring systems on cycling, like those that are used in Big Data systems, can be analyzed with multiple purposes. ...
According to the United Nations, cities will represent two-thirds of the world’s population in 2050, which presents some challenges, especially to the transportation sector. To improve the population’s quality of life and the sustainability of cities, mobility must be sustainable, and cycling will play an important role in achieving this. Literature shows that we can promote cycling with better infrastructures, through multimodality, and through behavioral changes. Promoting the use of bicycles through behavior can involve a number of aspects, but in this work, we explore what a digital platform should have in order to promote and increase bicycle usage, as well as to improve cycling conditions in a city. To evaluate what is needed, we conducted an analysis on different types of digital platforms that are available on the market in order to assess the main characteristics and outputs that they provide to cyclists, as well as the type of information that can and should be added to promote the use of bicycles in cities. Moreover, we also carried out a survey in a Portuguese mid-sized “starter cycling city”, which showed, among other data, the relevance and type of information that a digital platform dedicated to cyclists should have in such types of cities.
... However, big data sources may fill gaps in the needed information, as well. For instance, transportation agencies collect bicycling and pedestrian volume data sparingly, if at all, creating a challenge for understanding relative safety risks (Piwek et al. 2015). Big data also supports new approaches for managing freight modes, including maritime shipping (Peng et al. 2018). ...
Emerging big data resources and practices provide opportunities to improve transportation safety planning and outcomes. However, researchers and practitioners recognise that big data from mobile phones, social media, and on-board vehicle systems include biases in representation and accuracy, related to transportation safety statistics. This study examines both the sources of bias and approaches to mitigate them through a review of published studies and interviews with experts. Coding of qualitative data enabled topical comparisons and reliability metrics. Results identify four categories of bias and mitigation approaches that concern transportation researchers and practitioners: sampling, measurement, demographics, and aggregation. This structure for understanding and working with bias in big data supports research with practical approaches for rapidly evolving transportation data sources.
... However, big data sources may fill gaps in the needed information, as well. For instance, transportation agencies collect bicycling and pedestrian volume data sparingly, if at all, creating a challenge for understanding relative safety risks (Piwek et al. 2015). Big data also supports new approaches for managing freight modes, including maritime shipping (Peng et al. 2018). ...
Emerging big data resources and practices provide opportunities to improve transportation safety planning and outcomes. However, researchers and practitioners recognise that big data from mobile phones, social media, and on-board vehicle systems include biases in representation and accuracy, related to transportation safety statistics. This study examines both the sources of bias and approaches to mitigate them through a review of published studies and interviews with experts. Coding of qualitative data enabled topical comparisons and reliability metrics. Results identify four categories of bias and mitigation approaches that concern transportation researchers and practitioners: sampling, measurement, demographics, and aggregation. This structure for understanding and working with bias in big data supports research with practical approaches for rapidly evolving transportation data sources.
... With regard to that topic, devices such as smartwatches and fitness wrists are considered now the most common wearables [10,11]. In fact, the characteristics of these devices, especially in terms of size and weight, ease of use and direct contact with the athlete, make them very suitable for sports practice [12,13]. ...
The use of smart watches and fitness wrists has been increasing in recent years. On the one hand, their cost has become cheaper and their performance has improved. On the other hand, the increase in the number of people who practice sports such as running and cycling is another factor to consider. The increase in the number of popular athletes has meant that these devices are no longer considered intended for a minority or an elite, but are even used in people’s daily movements or in simpler activities such as walking. Some of these devices simply count the number of steps taken, while more advanced devices include energy consumption, distance travelled, speed, GPS tracking position, altimetry or heart rate. Moreover, there are social networks that allow athletes to share information gathered by their own activities, especially track and altimetry. This opens up a wider range of possibilities in sports training. However, the gathering of this rich information makes many more applications possible. For example, city planners can analyze the movements of people to detect possible shortcomings in public transport systems, deficiencies in urban pathways, and so on. This research work shows a taxonomy of different applications that use the data gathered by physical activity monitors and shared in social networks. The opportunities and drawbacks regarding the use of such applications in intelligent environments are also discussed.
... Application data from GPS devices provides insights into spatio-temporal patterns of usage, but there is a lack of corresponding socio-demographic data. To fill this gap, Piwek et al. conducted an online survey to investigate the extent to which cyclists' travel behaviour was affected by cycling applications [33]. Zhao and Li sought to identify the reasons why people chose cycling as a transfer mode. ...
Cycling is known to be environmentally friendly and beneficial to public health and sustainable urban development. Cycling has recently increased in Chinese cities as a result of the emergence of station-less bike-sharing systems. This study examines the emergence, rapid growth and consolidation of station-less bike-sharing systems and the role of suppliers, users and government regulators. It shows that these systems developed unevenly, growing most in large cities in eastern and southeastern China, and explores the relationship between this spatial distribution and the nature of the service and the socioeconomic characteristics of cities. To investigate patterns of, and reasons for, the use of these systems, this research also reports the results of a survey of users and non-users, identifying their gender, age, income characteristics and attitudes to station-less systems.
... Finally, this study assesses built environment regarding physical activity potential. However, recent developments in smartphone and smartwatch technology are enabling researchers to analyze the actual movements of people [63,64]. Therefore, in future research, tracking the movement patterns of residents via wearable smart devices would enable the examination of the relationships between actual physical activities and active living potential measures developed in this study. ...
Many municipalities in the US are deploying urban planning approaches to resolve problems caused by urban sprawl, particularly the lack of support for physical activity. Although a variety of perspectives on the relationship between physical activity and built environment exist, many studies have suggested objective and reliable measures of urban form that encourage more opportunities for physical activity. Thus, based on the research context, this study builds a Geographic Information System (GIS) model using geospatial dimensions, yields a visualized map ranked by composite scores, and reveals the spatial distribution of quantified cells. Through the Jacksonville case study, it is shown that the GIS-based visualization method provides an expanded set of tools that can help urban planners and public health professionals understand the relationships between urban form and potential for active living. Consequently, these map-based visualized results provide valuable information to health and public policy professionals to coordinate and resolve mutual challenges.
... In some cases, the studies in the United Kingdom used written questionnaires simultaneously to two independent groups: targeted experts in transport field and random members of the public in order to compare discrepancies between two groups [38]. Some studies used short invitations to targeted experts for on-line survey on social networking forums and general interest groups on Facebook and Twitter [39]. ...
Level crossing (LC) accidents are a significant safety challenge worldwide and for that reason they have been subject of numerous research activities. Joint conclusion is that human behaviour is the main cause of accidents. This study examines how and to which extent certain influential parameters cause accident mechanisms on level crossings. To gain the necessary data we used an on-line survey questionnaire that was sent internationally to key experts in the field of road and railway safety. A total of 185 experts were asked to rank how much certain parameters influence level crossings accident mechanisms and what are the best countermeasures for diminishing accidents at level crossings. To our knowledge, this is the first time that an international survey among key experts was used to gain necessary data about influential parameters regarding level crossings safety. The results of this study could be used by road and railway traffic engineers and policy makers for further enhancement of LC’s safety.
... A Foucauldian analysis of utility cycling apps in the UK (Schwanen, 2015) is an example of more theoretical approach. An analysis of self-monitoring of cyclists (Piwek et al., 2015) draws on the quantified self context of activity, sports and health monitoring apps. Griffin and Jiao (2015) discuss app use in relation to health aspects of cycling, and Mone (2015) considers cycling apps in the context of Smart Cities. ...
This article develops the concept of ?smart velomobility? that is concerned with networked practices, systems and technologies of cycling. The concept draws on velomobility, Smart Mobility/Intelligent Transport Systems (ITS), Smart Cities and the Internet of Things (IoT). The article presents results from an empirical study, where 80 riders of a networked fleet of e-bikes discuss their experience of smart velomobility. The results show how digital and physical mobilities merge, the way riders of the networked fleet interact with the data, how they share the data and how they feel tracked (privacy). The conclusion sketches out future research of ?smart velomobilities? and also points out the policy and innovation potential of cycling as active, sustainable and networked mode of transport in the context of Smart Cities and the Internet of Things.
... One type of tool also very explored by the researchers was the use of semi-structured interviews and personal accounts of participants. Some of the reports were carried out as an administration of training [33] while others followed the form of interviews or diaries with the subjective opinions of participants [31,34]. The training administration allowed the collection and analysis of quantitative data regarding the practice while interviews and diaries allowed the collection and analysis of qualitative data from the participant's physical performance. ...
This research aimed to identify and analyse which tools have the greatest potential for measuring the user experience throughout the practice of recreational surfing. The method adopted to gather information was a systematic review of literature on the user experience in surfing. After analysing the selected articles, the tools with the greatest potential for measurement were highlighted. The results have shown that there are several ways to measure the user experience in different sports and in surfing. This led to the construction of a table with the potential tools for measuring the user experience on recreational surfing, highlighting their main features, their positive and negative aspects and the justification of their possible use. In the results, the following tools stood out above all the others: GPS, accelerometer and gyroscope to measure physiological variables; and the affective diary and semi-structured interviews to measure the psychological variables of the user experience.
The evolution of mobile devices has allowed the development of features, such as mobile applications (apps), which have contributed to making tourism services and destinations more accessible, significantly changing consumer habits. Currently, apps made available by mobile devices occupy a prominent place in the daily lives of individuals. Thus, the objective of this paper is, on the one hand, to understand the use and satisfaction of mobile applications in the context of tourist trips carried out by the Portuguese and, on the other hand, to know the offer of tourism-related apps available on the Google Play Store and App Store. For that, a quantitative methodology was applied, through the development and application of a survey through social media, between December 21, 2020 and January 8, 2021, and the quantification and description of travel and tourism Apps available in online stores in January 2021. In general, it can be observed that the respondents are knowledgeable and users of travel-related apps, especially in accommodation, navigation, and lodging field. The study offers a valuable contribution to the knowledge of consumer behavior in tourism and the app market.KeywordsTourismMobile applicationsAppsTechnology
Background
There are currently more than 200 million smartphones in Brazil. The potential of mobile technologies for favorable changes in health behavior such as physical activity has been previously described in the literature. Results of surveys in developed countries indicate that applications (APPs) are developed for people who are better educated, younger, and with higher incomes compared to non-users. However, the profile of users in developing countries like Brazil is not well-known. Understanding the profile of APP users might ease the development turned to physically inactive people and those at higher cardiovascular risk. Furthermore, the physiological and functional factors associated with the use of such APP are unknown.
Objectives
To characterize the profile of APP users to monitor the physical activity level (PAL) and assess the demographic, socioeconomic, clinical, physiological, and functional characteristics associated with the use of smartphone APPs to monitor physical activity in Brazilian adults.
Methods
We assessed 176 asymptomatic men and 178 women (43 ± 12 years; 27 ± 5 kg/m²). We initially asked participants about their current use of a smartphone APP containing PAL monitoring functionality, such as exercise session logs and/or step counts. In a cross-sectional design, we investigated schooling, socioeconomic status (Critério Brasil), and classic self-reported cardiovascular risk factors. We evaluated several physiological and functional variables such as maximum O2 consumption on a treadmill (VO2 max), blood pressure, body composition (bioelectrical impedance), handgrip strength, and isokinetic muscle strength of the dominant lower limb. Participants used a triaxial accelerometer for 7 days to quantify daily physical activity. We also assessed health-related quality of life (WHOQOL BREF), perceived stress (PSS14 Scale), and the built environment (NEWS Scale). We compared continuous variables using the Student's t-test and categorical variables using the χ² test, between APP users and non-users. After univariate analysis, we included the main variables associated with the use of APP in a multiple logistic regression model.
Results
One hundred and two participants (28.3%), unrelated to gender, reported using a smartphone APP for physical activity at the time of assessment. Except for perceived stress and the built environment that were not associated with the use of APP, users of APP were younger and had higher education, lower cardiovascular risk, better socioeconomic status, a better quality of life, better cardiorespiratory function, better body composition, greater physical fitness and more moderate to vigorous physical activity in daily life. The results of the multiple logistic regression showed that age, hypertension, VO2 max, socioeconomic status (Critério Brasil), and quality of life (WHOQOL BREF total score) were the variables most significantly associated with the use of the APP.
Conclusions
Our results indicate that smartphone APPs to monitor physical activity are developed for younger adults with better socioeconomic status, lower cardiovascular risk, higher quality of life, and greater cardiorespiratory fitness. Greater efforts are needed to develop a science-based APP for people who most need this technology, enabling greater potential to prevent undesirable health outcomes in asymptomatic adults.
This paper seeks to contribute to ongoing debates around the politics of hybrid mobilities, smart cities, surveillance capitalism and mobility fixing. Based on a set of qualitative interviews with key stakeholders and secondary sources, the paper uses the emergence of dockless public bike sharing in Shanghai between 2016 and 2018 as its case study. In order to explain the emergence of dockless PBSS and illustrate our contention that this system seeks to create surplus value from the work of mobility (in this case cycle commuting), we examine the processes of valorisation that have occurred in order to both position PBSS as a worthy activity (and therefore remunerate participants affectively) and produce use values for the data generated by users. In doing so we also highlight the ways in which these processes of valorisation seek to ensure that the mobility work of users is not aligned with the products of that labour in order to avoid calls for this mobility work to be remunerated as wage labour (which would reduce any surplus value extraction). Ultimately we argue that these processes of valorisation are not only invasive, but exclusionary in that they prioritise select aspects of social practice that address matters of (governmental) concern, rather than a more rounded interpretation. We argue that there is an urgent need to recognise mobility practices beyond registers that simply prepare the ground for their marketisation.
Cycling has the potential to address a number of personal and societal challenges, not least with respect to health and the need for more sustainable modes of transport. However, the best way(s) to promote cycling is still unclear. In an effort to answer this question, we identified 39 interventions designed to promote cycling, with a total sample of 46,102 participants. Random effects meta-analysis estimated a small but statistically significant effect of interventions on cycling behaviour (g+ = 0.14, 95% CI [0.05, 0.23]). To identify the most effective intervention strategies, we coded the behaviour change techniques used within each of the interventions. Interventions that prompted people to self-monitor their behaviour or added objects to the environment (e.g., provided shared bikes) were more effective than those that did not use these strategies. Interventions that restructured the physical environment (e.g., built new cycle paths) were less effective than the studies that did not do this. We also identified a number of factors that moderated the effect of the interventions on outcomes; specifically, interventions that targeted a specific group, used objective measures of cycling such as accelerometers, and that were tested using independent groups designs typically yielded stronger effects. The findings should help to guide interventions to promote cycling in the future.
Objetivo do estudo: Identificar o perfil do ciclista e cicloturista em Santa Catarina, em seus aspectos socioeconômicos, interesses e motivações no ciclismo e usos de aplicativos de monitoramento.Metodologia/abordagem: Quantitativa com enfoque qualitativo, descritiva com delineamento de levantamento e revisão da bibliografia. Foram utilizados 285 questionários, aplicados virtualmente para ciclistas e cicloturistas de Santa Catarina, através de amostragem não probabilística intencional e quantificados através de planilhas e gráficos no Excel para análise dos dados através do referencial teórico pesquisado.Originalidade/Relevância: A pesquisa apresenta, de forma inédita, o perfil dos ciclistas e cicloturistas em Santa Catarina, envolvendo dados socioeconômicos, interesses e motivações e os usos da tecnologia no acompanhamento e compartilhamento dos pedais com aplicativo (Strava), possibilitando novas análise sobre o cicloturismo dentro do turismo.Principais resultados: As principais motivações para a prática do ciclismo são exercício físico, conhecer paisagens naturais e patrimônio cultural e realizar novas amizades. O aplicativo é utilizado para automonitoramento de tempo, distância e velocidade durante o percurso e compartilhamento com rede social.Contribuições teóricas/metodológicas: O planejamento de roteiros de cicloturismo ou o incentivo do uso da bicicleta como atrativo turístico requer atenção as necessidades e expectativas desse público, que se difere do turista usual, requerendo bens e serviços específicos, tanto para si como para seu equipamento, seja durante os trajetos como nos momentos de descanso.Contribuições sociais/para a gestão: As pesquisas dentro dessa temática podem auxiliar em no planejamento das políticas públicas de turismo para atender as expectativas e necessidades dos cicloturistas e ciclistas em geral. Os usos da bicicleta como esporte e/ou lazer ganharam espaço nas últimas décadas, com o compartilhamento das experiências nas redes sociais, com a visibilidade para os destinos e atrativos avaliadas pelos praticantes, gerando redes de interesse e mobilização sobre este tema.
Using guidance from the reach, efficacy, adoption, implementation, and maintenance evaluation framework, we aimed to qualitatively evaluate the participant experiences of a workplace high-intensity interval training (HIIT) intervention. Twelve previously insufficiently active individuals (four males and eight females) were interviewed once as part of three focus groups. Perceptions of program satisfaction, barriers to and facilitators of adherence, and persistence to exercise were explored. HIIT initiates interest because of its novelty, provides a sense of accomplishment, and overcomes the barriers of perceived lack of time. The feeling of relatedness between the participants can attenuate negative unpleasant responses during the HIIT sessions. HIIT, in this workplace setting, is an acceptable intervention for physically inactive adults. However, participants were reluctant to maintain the same mode of exercise, believing that HIIT sessions were for the very fit.
Research dealing with various aspects of* the theory of planned behavior (Ajzen, 1985,
1987) is reviewed, and some unresolved issues are discussed. In broad terms, the theory is
found to be well supported by empirical evidence. Intentions to perform behaviors of different
kinds can be predicted with high accuracy from attitudes toward the behavior, subjective
norms, and perceived behavioral control; and these intentions, together with perceptions of
behavioral control, account for considerable variance in actual behavior. Attitudes, subjective
norms, and perceived behavioral control are shown to be related to appropriate sets of salient
behavioral, normative, and control beliefs about the behavior, but the exact nature of these
relations is still uncertain. Expectancy value formulations are found to be only partly
successful in dealing with these relations. Optimal rescaling of expectancy and value
measures is offered as a means of dealing with measurement limitations. Finally, inclusion of
past behavior in the prediction equation is shown to provide a means of testing the theory*s
sufficiency, another issue that remains unresolved. The limited available evidence concerning
this question shows that the theory is predicting behavior quite well in comparison to the
ceiling imposed by behavioral reliability.
The number of devices on the Internet exceeded the number of people on the Internet in 2008, and is estimated to reach 50 billion in 2020. A wide-ranging Internet of Things (IOT) ecosystem is emerging to support the process of connecting real-world objects like buildings, roads, household appliances, and human bodies to the Internet via sensors and microprocessor chips that record and transmit data such as sound waves, temperature, movement, and other variables. The explosion in Internet-connected sensors means that new classes of technical capability and application are being created. More granular 24/7 quantified monitoring is leading to a deeper understanding of the internal and external worlds encountered by humans. New data literacy behaviors such as correlation assessment, anomaly detection, and high-frequency data processing are developing as humans adapt to the different kinds of data flows enabled by the IOT. The IOT ecosystem has four critical functional steps: data creation, information generation, meaning-making, and action-taking. This paper provides a comprehensive review of the current and rapidly emerging ecosystem of the Internet of Things (IOT).
We study fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resolution and the available outside information. This formula shows that the uniqueness of mobility traces decays approximately as the 1/10 power of their resolution. Hence, even coarse datasets provide little anonymity. These findings represent fundamental constraints to an individual's privacy and have important implications for the design of frameworks and institutions dedicated to protect the privacy of individuals.
We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait "Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.
Objective:
Evidence on the effectiveness of walking and cycling interventions is mixed. This may be partly attributable to differences in intervention content, such as the cognitive and behavioral techniques (BCTs) used. Adopting a taxonomy of BCTs, this systematic review addressed two questions: (a) What are the behavior change techniques used in walking and cycling interventions targeted at adults? (b) What characterizes interventions that appear to be associated with changes in walking and cycling in adults?
Method:
Previous systematic reviews and updated database searches were used to identify controlled studies of individual-level walking and cycling interventions involving adults. Characteristics of intervention design, context, and methods were extracted in addition to outcomes. Intervention content was independently coded according to a 26-item taxonomy of BCTs.
Results:
Studies of 46 interventions met the inclusion criteria. Twenty-one reported a statistically significant effect on walking and cycling outcomes. Analysis revealed substantial heterogeneity in the vocabulary used to describe intervention content and the number of BCTs coded. "Prompt self-monitoring of behavior" and "prompt intention formation" were the most frequently coded BCTs.
Conclusion:
Future walking and cycling intervention studies should ensure that all aspects of the intervention are reported in detail. The findings lend support to the inclusion of self-monitoring and intention formation techniques in future walking and cycling intervention design, although further exploration of these and other BCTs is required. Further investigation of the interaction between BCTs and study design characteristics would also be desirable.
Relying on the theory of planned behavior (Ajzen, 1991), a longitudinal study investigated the effects of an intervention-introduction of a prepaid bus ticket-on increased bus use among college students. In this context, the logic of the proposition that past behavior is the best predictor of later behavior was also examined. The intervention was found to influence attitudes toward bus use, subjective norms, and perceptions of behavioral control and, consistent with the theory, to affect intentions and behavior in the desired direction. Furthermore, the theory afforded accurate prediction of intention and behavior both before and after the intervention. In contrast, a measure of past behavior improved prediction of travel mode prior to the intervention, but lost its predictive utility for behavior following the intervention. In a test of the proposition that the effect of past on later behavior is due to habit formation, an independent measure of habit failed to mediate the effects of past on later behavior. It is concluded that choice of travel mode is largely a reasoned decision; that this decision can be affected by interventions that produce change in attitudes, subjective norms, and perceptions of behavioral control; and that past travel choice contributes to the prediction of later behavior only if circumstances remain relatively stable.
Since the beginning of the century, feedback interventions (FIs) produced negative--but largely ignored--effects on performance. A meta-analysis (607 effect sizes; 23,663 observations) suggests that FIs improved performance on average (
d = .41) but that over one-third of the FIs decreased performance. This finding cannot be explained by sampling error, feedback sign, or existing theories. The authors proposed a preliminary FI theory (FIT) and tested it with moderator analyses. The central assumption of FIT is that FIs change the locus of attention among 3 general and hierarchically organized levels of control: task learning, task motivation, and meta-tasks (including self-related) processes. The results suggest that FI effectiveness decreases as attention moves up the hierarchy closer to the self and away from the task. These findings are further moderated by task characteristics that are still poorly understood. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Scales were developed to assess 10 specific facet traits within the broad Big Five personality domains from the item pool of the Big Five Inventory (BFI). In two independent samples, the BFI facet scales dem-onstrated substantial (a) reliability, (b) convergence with self-reports on the Revised NEO Personality Inventory and peer-reports on the BFI, and (c) discriminant validity. These brief scales offer new oppor-tunities for researchers who wish to assess specific personality characteristics within an overarching Big Five framework. for serving as judges for the correlate-matching task.
An experiment examined the effects of an intervention (combination of information and a free public transport ticket) in a changed decision context (moving to a new residence) on travel mode choice by car users. If past frequency of car use has resulted in an automatic response to goal-related cues, one should expect resistant to change of travel mode. However, the results failed to show this. Neither past behavior or a direct habit measure predicted future travel behavior. Instead, the intervention influenced attitude, subjective norm, and perceived behavioral control, and consistent with Ajzen's theory of planned behavior, these were the main causes of the change of travel mode.
Information systems (IS) implementation is costly and has a relatively low success rate. Since the seventies, IS research has contributed to a better understanding of this process and its outcomes. The early efforts concentrated on the identification of factors that facilitated IS use. This produced a long list of items that proved to be of little practical value. It became obvious that, for practical reasons, the factors had to be grouped into a model in a way that would facilitate analysis of IS use.In 1985, Fred Davis suggested the technology acceptance model (TAM). It examines the mediating role of perceived ease of use and perceived usefulness in their relation between systems characteristics (external variables) and the probability of system use (an indicator of system success). More recently, Davis proposed a new version of his model: TAM2. It includes subjective norms, and was tested with longitudinal research designs. Overall the two explain about 40% of system’s use. Analysis of empirical research using TAM shows that results are not totally consistent or clear. This suggests that significant factors are not included in the models.We conclude that TAM is a useful model, but has to be integrated into a broader one which would include variables related to both human and social change processes, and to the adoption of the innovation model.
Chronic heart failure (CHF) is a chronic debilitating condition with economic consequences, mostly because of frequent hospitalisations. Physical activity and adequate self-management capacity are important risk reduction strategies in the management of CHF. The Home-Heart-Walk is a self-monitoring intervention. This model of intervention has adapted the 6-minute walk test as a home-based activity that is self-administered and can be used for monitoring physical functional capacity in people with CHF. The aim of the Home-Heart-Walk program is to promote adherence to physical activity recommendations and improving self-management in people with CHF.
A randomised controlled trial is being conducted in English speaking people with CHF in four hospitals in Sydney, Australia. Individuals diagnosed with CHF, in New York Heart Association Functional Class II or III, with a previous admission to hospital for CHF are eligible to participate. Based on a previous CHF study and a loss to follow-up of 10%, 166 participants are required to be able to detect a 12-point difference in the study primary endpoint (SF-36 physical function domain).All enrolled participant receive an information session with a cardiovascular nurse. This information session covers key self-management components of CHF: daily weight; diet (salt reduction); medication adherence; and physical activity. Participants are randomised to either intervention or control group through the study randomisation centre after baseline questionnaires and assessment are completed. For people in the intervention group, the research nurse also explains the weekly Home-Heart-Walk protocol. All participants receive monthly phone calls from a research coordinator for six months, and outcome measures are conducted at one, three and six months. The primary outcome of the trial is the physical functioning domain of quality of life, measured by the physical functioning subscale of the Medical Outcome Study Short Form -36. Secondary outcomes include physical functional capacity measured by the standard six minute walk test, self-management capacity, health related quality of life measured by Medical Outcome Study Short Form -36 and Minnesota Living With Heart Failure Questionnaire, self-efficacy and self-care behaviour.
A self-monitoring intervention that can improve individual's exercise self-efficacy, self-management capacity could have potential significance in improving the management of people with chronic heart failure in community settings.
Australian New Zealand Clinical Trial Registry 12609000437268.
This study is the preliminary evaluation of acceptability and feasibility of physical activity self-monitoring survey by pedometer. The authors recruited 375 people from a possible 1,200 who completed a randomized, population-based telephone survey administered in 2001 to individuals living in Sumter Co3unty, South Carolina. Mailed kits included pedometer, instructions, a recording calendar, and a postage-paid return envelope. Participants wore the pedometer during waking hours and recorded day-end steps taken for seven days. Up to three telephone prompts were made to get participants to return data. Despite the limitations of initial recruitment, this study provides preliminary information on the acceptability and feasibility of a pedometer-assessed physical activity self-monitoring survey.
Recent systematic reviews have suggested that pedometers may be effective motivational tools to promote walking. However, studies tend to be of a relatively short duration, with small clinical based samples. Further research is required to demonstrate their effectiveness in adequately powered, community based studies.
Using a randomized controlled trial design, this study assessed the impact of a 12-week graduated pedometer-based walking intervention on daily step-counts, self-reported physical activity and health outcomes in a Scottish community sample not meeting current physical activity recommendations.
Sixty-three women and 16 men (49.2 years +/- 8.8) were randomly assigned to either an intervention (physical activity consultation and 12-week pedometer-based walking program) or control (no action) group. Measures for step-counts, 7-day physical activity recall, affect, quality of life (n = 79), body mass, BMI, % body fat, waist and hip circumference (n = 76), systolic/diastolic blood pressure, total cholesterol and HDL cholesterol (n = 66) were taken at baseline and week 12. Analyses were performed on an intention to treat basis using 2-way mixed factorial analyses of variance for parametric data and Mann Whitney and Wilcoxon tests for non-parametric data.
Significant increases were found in the intervention group for step-counts (p < .001), time spent in leisure walking (p = .02) and positive affect (p = .027). Significant decreases were found in this group for time spent in weekday (p = .003), weekend (p = .001) and total sitting (p = .001) with no corresponding changes in the control group. No significant changes in any other health outcomes were found in either group. In comparison with the control group at week 12, the intervention group reported a significantly greater number of minutes spent in leisure time (p = .008), occupational (p = .045) and total walking (p = .03), and significantly fewer minutes in time spent in weekend (p = .003) and total sitting (p = .022).
A pedometer-based walking program, incorporating a physical activity consultation, is effective in promoting walking and improving positive affect over 12 weeks in community based individuals. The discussion examines possible explanations for the lack of significant changes in health outcomes. Continued follow-up of this study will examine adherence to the intervention and possible resulting effects on health outcomes.
Reports that a comparison of the outcomes of major stop-smoking studies reveals an intriguing similarity of data across a variety of different procedures, populations, and theoretical orientations. The elements of motivated volunteering, structure, and self-monitoring are regarded as nonspecific factors common to all these stop-smoking studies. A stop-smoking clinic was designed which offered no "treatment" but encouraged motivated volunteers to employ self-control and required them to monitor their smoking and report progress at regular intervals. The outcome of the nontreatment clinic program was comparable to others reviewed and suggests that the nonspecific factors studied may account for the temporary behavior change found in most smoking treatments. (23 ref.)
To evaluate Watch, Discover, Think and Act (WDTA), a theory-based application of CD-ROM educational technology for pediatric asthma self-management education.
A prospective pretest posttest randomized intervention trial was used to assess the motivational appeal of the computer-assisted instructional program and evaluate the impact of the program in eliciting change in knowledge, self-efficacy, and attributions of children with asthma. Subjects were recruited from large urban asthma clinics, community clinics, and schools. Seventy-six children 9 to 13 years old were recruited for the evaluation.
Repeated-measures analysis of covariance showed that knowledge scores increased significantly for both groups, but no between-group differences were found (P: = 0.55); children using the program scored significantly higher (P: < 0.01) on questions about steps of self-regulation, prevention strategies, and treatment strategies. These children also demonstrated greater self-efficacy (P: < 0.05) and more efficacy building attribution classification of asthma self-management behaviors (P: < 0.05) than those children who did not use the program.
The WDTA is an intrinsically motivating educational program that has the ability to effect determinants of asthma self-management behavior in 9- to 13-year-old children with asthma. This, coupled with its reported effectiveness in enhancing patient outcomes in clinical settings, indicates that this program has application in pediatric asthma education.
To assess, in a 1-year randomized controlled trial, the efficacy of eDiets.com (a commercial Internet weight loss program) in improving weight, cardiovascular health, and quality of life.
Participants were 47 women with a mean age of 43.7 +/- 10.2 (SD) years and a mean BMI of 33.5 +/- 3.1 kg/m2. They were randomly assigned to either: 1) eDiets.com, a commercial Internet-based program available to the public; or 2) a weight loss manual (i.e., LEARN Program for Weight Control 2000). At baseline, participants in both groups met briefly with a psychologist who instructed them to follow the components of their program as closely as possible. Additional brief visits were provided at weeks 8, 16, 26, and 52 to review their progress. Change in weight was the main outcome measure.
At week 16, participants in eDiets.com lost 0.9 +/- 3.2% of initial weight compared with 3.6 +/- 4.0% for women assigned to the weight loss manual. At week 52, losses increased to 1.1 +/- 4.0% and 4.0 +/- 5.1%, respectively. Results of a last-observation-carried-forward analysis found that women in the manual group lost significantly (p < 0.05) more weight (at both times) than those treated by eDiets.com. (Results, however, of baseline-carried-forward and completers analyses did not reach statistical significance.) There were no significant differences between groups in changes in cardiovascular risk factors or quality of life.
This study provides consumers with important information about the probable benefits they can expect from participating in a popular Internet-based weight loss program.
To evaluate the efficacy of two internet interventions for community-dwelling individuals with symptoms of depression--a psychoeducation website offering information about depression and an interactive website offering cognitive behaviour therapy.
Randomised controlled trial.
Internet users in the community, in Canberra, Australia.
525 individuals with increased depressive symptoms recruited by survey and randomly allocated to a website offering information about depression (n = 166) or a cognitive behaviour therapy website (n = 182), or a control intervention using an attention placebo (n = 178).
Change in depression, dysfunctional thoughts; knowledge of medical, psychological, and lifestyle treatments; and knowledge of cognitive behaviour therapy.
Intention to treat analyses indicated that information about depression and interventions that used cognitive behaviour therapy and were delivered via the internet were more effective than a credible control intervention in reducing symptoms of depression in a community sample. For the intervention that delivered cognitive behaviour therapy the reduction in score on the depression scale of the Center for Epidemiologic Studies was 3.2 (95% confidence interval 0.9 to 5.4). For the "depression literacy" site (BluePages), the reduction was 3.0 (95% confidence interval 0.6 to 5.2). Cognitive behaviour therapy (MoodGYM) reduced dysfunctional thinking and increased knowledge of cognitive behaviour therapy. Depression literacy (BluePages) significantly improved participants' understanding of effective evidence based treatments for depression (P < 0.05).
Both cognitive behaviour therapy and psychoeducation delivered via the internet are effective in reducing symptoms of depression.
To determine if a patient-centered, computer-assisted diabetes care intervention increased perceived autonomy support, perceived competence (from self-determination theory), and if these constructs mediated the effect of the intervention on ADA/NCQA recommended diabetes care outcomes.
A randomized controlled trial of 866 adult type 2 diabetes patients in heterogeneous primary care settings in Colorado.
Perceived autonomy support, perceived competence, patient satisfaction, glycemic control (HbA1c), ratio of total to HDL cholesterol, diabetes distress, and depressive symptoms.
The computer-assisted intervention increased patient perception of autonomy support relative to a computer-based control condition ( p = .05). Change in perceived competence partially mediated the effects of increased autonomy support on the change in lipids, diabetes distress, and depressive symptoms. The construct of autonomy support was found to be separate from that of patient satisfaction.
A patient-centered, computer-assisted intervention was effective in improving diabetes self-management outcomes, in part, because it increased patients' perception that their autonomy was supported which changed perceived competence. These findings support the self-determination model for health behavior change and the chronic care model and support the further study of the use of these technologies to motivate patients to improve their health outcomes.
Equipped with cutting-edge sensing technology and high-end processors, smartphones can unobtrusively sense human behavior and deliver feedback and behavioral therapy. The authors discuss two applications for behavioral monitoring and change and present UBhave, the first holistic platform for large-scale digital behavior change intervention.
Can computers change what you think and do? Can they motivate you to stop smoking, persuade you to buy insurance, or convince you to join the Army? "Yes, they can," says Dr. B.J. Fogg, director of the Persuasive Technology Lab at Stanford University. Fogg has coined the phrase "Captology"(an acronym for computers as persuasive technologies) to capture the domain of research, design, and applications of persuasive computers.In this thought-provoking book, based on nine years of research in captology, Dr. Fogg reveals how Web sites, software applications, and mobile devices can be used to change peoples attitudes and behavior. Technology designers, marketers, researchers, consumers-anyone who wants to leverage or simply understand the persuasive power of interactive technology-will appreciate the compelling insights and illuminating examples found inside. Persuasive technology can be controversial-and it should be. Who will wield this power of digital influence? And to what end? Now is the time to survey the issues and explore the principles of persuasive technology, and B.J. Fogg has written this book to be your guide.
Promoting bicycling is important for individual health, environmental sustainability and transport demand management. However, very few people use a bicycle on a regular basis. This paper explores what views bicyclists and non-bicyclists in England may hold about the typical bicyclist and how such views are related to bicycling behaviour and intentions. A survey was conducted among 244 bicyclists and non-bicyclists. On the basis of a range of statements on behaviour, motivation and characteristics of the typical bicyclist, four different stereotypes could be distinguished: responsible, lifestyle, commuter and hippy-go-lucky. These views differed between bicyclists and non-bicyclists. Moreover, independent of past bicycling behaviour, reported intentions to use a bicycle in the future were positively related to perceptions of the typical bicyclist as a commuter or hippy-go-lucky bicyclist. These findings have implications for encouraging bicycling, which may benefit from promoting bicycling as a common day-to-day activity rather than something that is only relevant for a few.
The praxis-oriented interdisciplinary field of feminist technology studies (FTS) has done most among the social sciences to build a vibrant and coherent school of gender and technology studies. Given their shared commitment to exploring emergent forms of power in the contemporary world, there is surprisingly little dialogue between FTS and mainstream cultural anthropology. This review begins by outlining FTS and its concepts and methods. I then turn to the anthropology of technology, which also offers useful conceptual frameworks and methods for exploring gender regimes. Then, to highlight the ideological and methodological contrasts between social and cultural analyses of technology and the implications for gender analysis, I discuss the treatment of technology in two leading theoretical fields in the cultural anthropology of modernity and globalization: the anthropology of technoscience, and material culture studies. I conclude by asking which forms of engagement might be envisaged between the fields.
On the basis of laboratory research on self-regulation, it was hypothesized that positive self-monitoring, more than negative self-monitoring or comparison and control procedures, would improve the bowling averages of unskilled league bowlers (N =60). Conversely, negative self-monitoring was expected to produce the best outcome for relatively skillful league bowlers (N =67). In partial support of these hypotheses, positive self-monitors significantly improved their bowling averages from the 90-game baseline to the 9- to 15-game postintervention assessment (Ximprovement = 11 pins) more than all other groups of low-skilled bowlers; higher skilled bowlers' groups did not change differentially. In conjunction with other findings in cognitive behavior therapy and sports psychology, the implications of these results for delineating the circumstances under which positive self-monitoring facilitates self-regulation are discussed.
In 1996 the UK government introduced the National Cycle Strategy which aimed to double the number of cycling trips by the end of 2002 and double them again by 2012. So far, however, these targets have not been met. The House of Commons ascribes this to ‘a fundamental lack of commitment to cycling on an individual, regional and national level’. This paper addresses the individual level by examining the views of commuters in different stages of change as distinguished by Prochaska’s model [Prochaska, J.O., DiClemente, C.C., 1984. The Transtheoretical Approach: Crossing Traditional Boundaries of Change. Dow Jones/Irwin, Homewood IL]. This model views behaviour change as a process rather than an event. Two studies were conducted amongst university staff and students: a survey study and an action study. The studies showed that as people progress from precontemplation to action their attitudes towards cycling become more positive and their perceptions of various personal and external barriers change. This suggests that different strategies are necessary to move people in different stages of change to action and maintenance. At the moment, it seems that regular cyclists form a very small minority of people who will cycle under most circumstances simply because they like cycling. The majority of people have never contemplated cycling. There is, however, also a group of people who would like to cycle and could be persuaded to cycle under the right circumstances.
The health benefits of regular exercise and the low participation rates combine to create a strong rationale for research into the determinants of this important health behavior. The purpose of the present study was to examine the relationship between personality and exercise behavior, motives, barriers and preferences. The five-factor model (FFM) of personality was selected to guide this investigation. Participants were 264 undergraduate students who completed a battery of self-administered questionnaires including the NEO Five-Factor Inventory (Costa & McCrae, 1992) and the Godin Leisure Time Exercise Questionnaire (Godin & Shephard, 1985). Consistent with hypotheses, the results of the study indicated that: 1.(a) extraversion and conscientiousness were positively related whereas neuroticism was negatively related to exercise behavior,2.(b) each “Big Five” dimension correlated with theoretically expected exercise motives,3.(c) neuroticism and conscientiousness were the personality dimensions most consistently related to exercise barriers4.(d) all “Big Five” personality dimensions were related to some aspect of preferences for exercise context and structure.
It was concluded that the FFM may be a useful framework for understanding not only how much exercise people perform, but also their exercise motives, barriers, and preferences.
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The aim of this study was to evaluate the use of the pedometer in epidemiologic research on physical activity. Within the framework of a health examination survey in 1988–1989, physical activity was assessed in a representative population sample of 493 men and women aged 25–74 years who were residents of Switzerland. They wore a pedometer for 1 week at work and during leisure time, and the results, converted into steps per day, were compared with answers to a questionnaire. The average number of steps per day decreased from 11,900 to 6,700 and from 9,300 to 7,300 for men and women, respectively, in the youngest to the oldest age groups. For men, categorized according to type of physical activity at work, there was a highly significant difference in the number of steps (p< 0.001), whereas in women the results were associated with leisure-time physical activity (p = 0.003). For both sexes, practicing sports more than once a week was associated with an important increase in steps per day. Analyzing the number of steps according to the day of the week and occupational category produced an unexpected result: Men with a physically active job engaged in more leisure-time physical activity on the weekend. The pedometer proved to be useful in assessing physical activity in a large, free-living population.
Increasing self-efficacy is an effective method to increase physical activity. Despite this, the evidence concerning the most effective techniques to increase self-efficacy in physical activity interventions has not been systematically reviewed. The aim of the present research is to systematically gather, and meta-analyse, intervention studies which aimed to increase self-efficacy for physical activity; to estimate the association between intervention techniques used, and change in self-efficacy achieved.
A systematic database search was conducted for papers reporting lifestyle or recreational physical activity interventions. Published intervention studies explicitly targeting self-efficacy in order to change physical activity behaviour in 'healthy' adults were eligible for inclusion.
The search strategy identified 27 unique physical activity intervention studies, with a total of 5,501 participants. A significant, yet small, relationship between the interventions and changes in self-efficacy was found (mean d=0.16, p<.001). Owing to significant heterogeneity, moderator analyses were conducted, examining the association of changes in self-efficacy with whether or not specific intervention techniques were used. Interventions that included feedback on past or others' performance produced the highest levels of self-efficacy found in this review. Vicarious experience was also associated with higher levels of self-efficacy. Persuasion, graded mastery, and barrier identification were associated with lower levels of self-efficacy.
This meta-analysis forms an evidence base for which psychological techniques are most effective in increasing self-efficacy for physical activity. The results are presented in terms of recommendations for those developing interventions and directions for future research.
The aim of this study was to evaluate the use of the pedometer in epidemiologic research on physical activity. Within the framework of a health examination survey in 1988-1989, physical activity was assessed in a representative population sample of 493 men and women aged 25-74 years who were residents of Switzerland. They wore a pedometer for 1 week at work and during leisure time, and the results, converted into steps per day, were compared with answers to a questionnaire. The average number of steps per day decreased from 11,900 to 6,700 and from 9,300 to 7,300 for men and women, respectively, in the youngest to the oldest age groups. For men, categorized according to type of physical activity at work, there was a highly significant difference in the number of steps (p < 0.001), whereas in women the results were associated with leisure-time physical activity (p = 0.003). For both sexes, practicing sports more than once a week was associated with an important increase in steps per day. Analyzing the number of steps according to the day of the week and occupational category produced an unexpected result: Men with a physically active job engaged in more leisure-time physical activity on the weekend. The pedometer proved to be useful in assessing physical activity in a large, free-living population.
Prevalence estimates of meeting the guidelines for physical activity based on various self-report measures were compared, and the effects of various scoring protocols on the estimates were evaluated.
A sample of 575 university students aged 24.5 +/- 1.9 yr (56% women, 54% Euro-American) completed the Seven-Day Physical Activity Recall interview (PAR), Youth Risk Behavior Survey (YRBS), and National Health Interview Survey 1991 (NHIS). To determine the prevalence of meeting the ACSM (1990) fitness and the CDC/ACSM (1995) health-related guidelines, various scoring protocols were employed that closely approximated the recommendations. Protocols varied by whether frequency and duration or duration only were considered. For the health-related guidelines, scoring protocols also varied depending on the intensity of activities considered.
Depending on the scoring protocol and instrument used, the proportion meeting the fitness guidelines ranged from 32 to 59%. The NHIS, YRBS, and PAR resulted in significantly different proportions of those meeting the health-related guideline, ranging from 4 to 70%.
The type of measure as well as the scoring protocol affected prevalence estimates of meeting the physical activity guidelines. This study indicates the difficulty of comparing prevalence rates across studies using different measures.
Valid assessment of physical activity is important to researchers and practitioners interested in surveillance, screening, programme evaluation and intervention. The validity of an assessment instrument is commonly considered its most important attribute. Convergent validity is the extent to which an instrument's output is associated with that of other instruments intended to measure the same exposure of interest. A systematic review of the literature produced 25 articles directly relevant to the question of convergent validity of pedometers against accelerometers, observation, and self-reported measures of physical activity. Reported correlations were pooled and a median r-value was computed. Pedometers correlate strongly (median r = 0.86) with different accelerometers (specifically uniaxial accelerometers) depending on the specific instruments used, monitoring frame and conditions implemented, and the manner in which the outputs are expressed. Pedometers also correlate strongly (median r = 0.82) with time in observed activity. Time in observed inactivity correlated negatively with pedometer outputs (median r = -0.44). The relationship with observed steps taken depended upon monitoring conditions and speed of walking. The highest agreement was apparent during ambulatory activity (running, walking) or during sitting (when both observation and pedometers would register few steps taken). There was consistent evidence of reduced accuracy during slow walking. Pedometers correlate moderately with different measures of energy expenditure (median r = 0.68). The relationship between pedometer outputs and energy expenditure is complicated by the use of many different direct and indirect measures of energy expenditure and population samples. Concordance with self-reported physical activity (median r = 0.33) varied depending upon the self-report instrument used, individuals assessed, and how pedometer outputs are expressed (e.g. steps, distance travelled, energy expenditure). Pedometer output has an inverse relationship with reported time spent sitting (r = -0.38). The accumulated evidence herein provides ample support that the simple and inexpensive pedometer is a valid option for assessing physical activity in research and practice.
The purposes of this study were to: (a) identify which determinants of physical activity among African American and Caucasian women predict adherence to a 24-week home-based walking program; and (b) explore differences between African American and Caucasian women. Participants were 153 working women who were sedentary at leisure. The program included an exercise prescription, instructions, and support. Background determinants included demographics, previous exercise experience, and social role influences. Intrapersonal determinants (self-efficacy, self-determinism) were measured at baseline and 24 weeks. Adherence was measured with heart rate monitors and logs. Adherence was significantly higher in Caucasians, those with less previous exercise experience, and those with higher self-efficacy. Findings suggest that adherence to a walking program is influenced by multiple factors including background and intrapersonal determinants of physical activity.
The purpose of this study was to determine the accuracy and reliability of the following electronic pedometers for measuring steps: Freestyle Pacer Pro (FR), Kenz Lifecorder (KZ), New Lifestyles NL-2000 (NL), Omron HJ-105 (OM), Oregon Scientific PE316CA (OR), Sportline 330 (SL330) and 345 (SL345), Walk4Life LS 2525 (WL), Yamax Skeletone EM-180 (SK), and the Yamax Digi-Walker SW-701 (DW).
Ten males (34.7 +/- 12.6 yr) (mean +/- SD) and 10 females (43.1 +/- 19.9 yr) ranging in BMI from 19.8 to 33.6 kg.m-2 walked 400-m around an outdoor track while wearing two pedometers of the same model (one on the right and left sides of the body) for each of 10 models. Four pedometers of each model were assessed in this fashion. The actual steps taken were tallied by a researcher.
The KZ, NL, and DW were the most accurate in counting steps, displaying values that were within +/-3% of the actual steps taken, 95% of the time. The SL330 and OM were the least accurate, displaying values that were within +/-37% of the actual steps, 95% of the time. The reliability within a single model (Cronbach's alpha) was >0.80 for all pedometers with the exception of the SL330. The intramodel reliability was exceptionally high (>0.99) in the KZ, OM, NL, and the DW.
Due to the variation that exists among models in regard to the internal mechanism and sensitivity, not all pedometers count steps accurately. Thus, it is important for researchers who use pedometers to assess physical activity to be aware of their accuracy and reliability.
Valid assessment of physical activity is necessary to fully understand this important health-related behaviour for research, surveillance, intervention and evaluation purposes. This article is the second in a companion set exploring the validity of pedometer-assessed physical activity. The previous article published in Sports Medicine dealt with convergent validity (i.e. the extent to which an instrument's output is associated with that of other instruments intended to measure the same exposure of interest). The present focus is on construct validity. Construct validity is the extent to which the measurement corresponds with other measures of theoretically-related parameters. Construct validity is typically evaluated by correlational analysis, that is, the magnitude of concordance between two measures (e.g. pedometer-determined steps/day and a theoretically-related parameter such as age, anthropometric measures and fitness). A systematic literature review produced 29 articles published since > or =1980 directly relevant to construct validity of pedometers in relation to age, anthropometric measures and fitness. Reported correlations were combined and a median r-value was computed. Overall, there was a weak inverse relationship (median r = -0.21) between age and pedometer-determined physical activity. A weak inverse relationship was also apparent with both body mass index and percentage overweight (median r = -0.27 and r = -0.22, respectively). Positive relationships regarding indicators of fitness ranged from weak to moderate depending on the fitness measure utilised: 6-minute walk test (median r = 0.69), timed treadmill test (median r = 0.41) and estimated maximum oxygen uptake (median r = 0.22). Studies are warranted to assess the relationship of pedometer-determined physical activity with other important health-related outcomes including blood pressure and physiological parameters such as blood glucose and lipid profiles. The aggregated evidence of convergent validity (presented in the previous companion article) and construct validity herein provides support for considering simple and inexpensive pedometers in both research and practice.
Pedometers have been identified as a potential motivational aid for increasing physical activity, but their efficacy has not been demonstrated in a community-based, nonclinical sample.
A randomized controlled trial was conducted from August to December 2005. Analysis was completed in June 2006.
Inactive adults aged 30-65 years (n=369) recruited from the community.
Comparison of a theoretically based self-help walking program (WP) and weekly diaries (sent by mail); the same walking program with a pedometer (WPP) (also by mail); and a no-treatment control group (C).
Change in self-reported leisure time in any sports/recreation in the last 3 months, and all-purpose walking (APW) for exercise, recreation, and travel, and other moderate, vigorous physical activity in the last week. Proportions meeting physical activity recommendations (equal to or greater than 150 minutes and equal to or greater than five sessions/week(-1)) were determined.
A 3-month follow-up interview was conducted with 314 (85%) participants. Intention-to-treat analyses indicated significance within-group increases of APW and leisure-time walking (LTW), but mean and median sessions and minutes changes were greatest in the WPP group. There were no significant between-group differences in regular LTW (walked equal to or greater than 5 sessions/week(-1) for at least 30 minutes/session), but the WPP group increased significantly participation in other sports/recreations and was more likely than the control group to meet physical activity recommendations by all leisure-time physical activity (adjusted odds ratio=2.40, 95% CI=1.17-4.93), by APW (adjusted odds ratio=1.75 95% CI=0.92-3.34) and all physical activity (adjusted odds ratio=1.59 95% CI=0.92-2.79) in the last week.
Pedometers enhanced the effects of the self-help walking program. This low-cost intervention should be tested for sustainability.
Qualtrics Research Suite
- Qualtrics
Qualtrics, 2013. Qualtrics Research Suite. <http://www.qualtrics.com>.
Gender and technology
- F Bray
- M Wyer
- M Barbercheck
- D Cookmeyer
- H Ozturk
Bray, F., 2013. Gender and technology. In: Wyer, M., Barbercheck, M., Cookmeyer, D., Ozturk, H., Wayne, M. (Eds.), Women, Science, and Technology: A
Reader in Feminist Science Studies. Routledge, pp. 370-381.