Expected values for pedometer-determined physical activity in older populations

The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as ≥ 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50–94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000–9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.

BioCondition assessment tool : a mobile application to aid vegetation assessment

Environmental degradation has become increasingly aggressive in recent years due to rapid urban development and other land use pressures. This chapter looks at BioCondition, a newly developed vegetation assessment framework by Queensland Department of Resource Management (DERM) and how mobile technology can assist beginners in conducting the survey. Even though BioCondition is designed to be simple, it is still fairly inaccessible to beginners due to its complex, time consuming, and repetitive nature. A Windows Phone mobile application, BioCondition Assessment Tool, was developed to provide on-site guidance to beginners and document the assessment process for future revision and comparison. The application was tested in an experiment at Samford Conservation Park with 12 students studying ecology in Queensland University of Technology.

Response to "a step in the right direction : commentary on expected values for pedometer-determined physical activity in youth"

The figure Beets took exception to displays sex‐ and age‐specific median values of aggregated published expected values for pedometer determined physical activity.

Expected values for pedometer-determined physical activity in youth

This review assembles pedometry literature focused on youth, with particular attention to expected values for habitual, school day, physical education class, recess, lunch break, out-of-school, weekend, and vacation activity. From 31 studies published since 1999, we constructed a youth habitual activity step-curve that indicates: (a) from ages 6 to 18 years, boys typically take more steps per day than girls; (b) for both sexes the youngest age groups appear to take fewer steps per day than those immediately older; and (c) from a young age, boys decline more in steps per day to become move consistent with girls at older ages. Additional studies revealed that boys take approximately 42-49% of daily steps during the school day; girls take 41-47%. Steps taken during physical education class contribute to total steps per day by 8.7-23.7% in boys and 11.4-17.2% in girls. Recess represents 8-11% and lunch break represents 15-16% of total steps per day. After-school activity contributes approximately 47-56% of total steps per day for boys and 47-59% for girls. Weekdays range from approximately 12,000 to 16,000 steps per day in boys and 10,000 to 14,000 steps per day in girls. The corresponding values for weekend days are 12,000-13,000 steps per day in boys and 10,000-12,000 steps per day in girls.

The next generation health intervention tool - Can smart phone applications help young people track and moderate alcohol use and potential harms?

Whilst alcohol is a common feature of many social gatherings, there are numerous immediate and long-term health and social harms associated with its abuse. Alcohol consumption is the world’s third largest risk factor for disease and disability with almost 4% of all deaths worldwide attributed to alcohol. Not surprisingly, alcohol use and binge drinking by young people is of particular concern with Australian data reporting that 39% of young people (18-19yrs) admitted drinking at least weekly and 32% drank to levels that put them at risk of alcohol-related harm. The growing market penetration and connectivity of smartphones may be an opportunities for innovation in promoting health-related self-management of substance use. However, little is known about how best to harness and optimise this technology for health-related intervention and behaviour change. This paper explores the utility and interface of smartphone technology as a health intervention tool to monitor and moderate alcohol use. A review of the psychological health applications of this technology will be presented along with the findings of a series of focus groups, surveys and behavioural field trials of several drink-monitoring applications. Qualitative and quantitative data will be presented on the perceptions, preferences and utility of the design, usability and functionality of smartphone apps to monitoring and moderate alcohol use. How these findings have shaped the development and evolution of the OnTrack app will be specifically discussed, along with future directions and applications of this technology in health intervention, prevention and promotion.

The Smartphone App Economy and App Ecosystems

This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

Development of Mobile Web App "ESP" for DeepBlue to interrogate how an audience is thinking

DeepBlue is much more than just an orchestra. Their innovative approach to audience engagement led it to develop ESP, their Electronic Show Programme web app which allows for real-time (synchronous) and delayed (asynchronous) audience interaction, customer feedback and research. The show itself is driven invisibly by a music technology operating system (currently QUT's Yodel) that allows them to adapt to a wide range of performance venues and varied types of presentation. DeepBlue's community engagement program has enabled over 5,500 young musicians and community choristers to participate in professional productions, it is also a cornerstone of DeepBlue's successful business model. You can view the ESP mobile web app at m.deepblue.net.au if you view this and only the landing page is active, there is not a show taking place or imminent. ESP prototype has already been used for 18 months. Imagine knowing what your audience really thinks – in real time so you can track their feelings and thoughts through the show. This tool has been developed and used by the performing group DeepBlue since late 2012 in Australia and Asia (even translated into Vietnamese). It has mostly superseded DeepBlue's SMS realtime communication during a show. It enables an event presenter or performance group to take the pulse of an audience through a series of targeted questions that can be anonymous or attributed. This will help build better, long-lasting, and more meaningful relationships with groups and individuals in the community. This can take place on a tablet, mobile phone or future platforms. There are three organisations trialling it so far.

Adolescent pedometer protocols : examining reactivity, tampering and participants' perceptions

The aim of this study was to investigate adolescents' potential reactivity and tampering while wearing pedometers by comparing different monitoring protocols to accelerometer output. The sample included adolescents (N=123, age range=14-15 years) from three secondary schools in New South Wales, Australia. Schools were randomised to one of the three pedometer monitoring protocols: (i) daily sealed (DS) pedometer group, (ii) unsealed (US) pedometer group or (iii) weekly sealed (WS) pedometer group. Participants wore pedometers (Yamax Digi-Walker CW700, Yamax Corporation, Kumamoto City, Japan) and accelerometers (Actigraph GT3X+, Pensacola, USA) simultaneously for seven days. Repeated measures analysis of variance was used to examine potential reactivity. Bivariate correlations between step counts and accelerometer output were calculated to explore potential tampering. The correlation between accelerometer output and pedometer steps/day was strongest among participants in the WS group (r=0.82, P <= 0.001), compared to the US (r=0.63, P <= 0.001) and DS (r=0.16, P=0.324) groups. The DS (P <= 0.001) and US (P=0.003), but not the WS (P=0.891), groups showed evidence of reactivity. The results suggest that reactivity and tampering does occur in adolescents and contrary to existing research, pedometer monitoring protocols may influence participant behaviour.

Comparison of 3 accelerometer data reduction approaches, step counts, and 2 self-report measures for estimating physical activity in free-living adults

Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

Towards strongly consistent online HMM parameter estimation using one-step Kerridge inaccuracy

In this paper, we propose a novel online hidden Markov model (HMM) parameter estimator based on the new information-theoretic concept of one-step Kerridge inaccuracy (OKI). Under several regulatory conditions, we establish a convergence result (and some limited strong consistency results) for our proposed online OKI-based parameter estimator. In simulation studies, we illustrate the global convergence behaviour of our proposed estimator and provide a counter-example illustrating the local convergence of other popular HMM parameter estimators.

A mobile app offering distractions and tips to cope with cigarette craving: A qualitative study

Background Despite considerable effort, most smokers relapse within a few months after quitting due to cigarette craving. The widespread adoption of mobile phones presents new opportunities to provide support during attempts to quit. Objective To design and pilot a mobile app "DistractMe" to enable quitters to access and share distractions and tips to cope with cigarette cravings. Methods A qualitative study with 14 smokers who used DistractMe on their mobiles during the first weeks of their quit attempt. Based on interviews, diaries, and log data, we examined how the app supported quitting strategies. Results Three distinct techniques of coping when using DistractMe were identified: diversion, avoidance, and displacement. We further identified three forms of engagement with tips for coping: preparation, fortification, and confrontation. Overall, strategies to prevent cravings and their effects (avoidance, displacement, preparation, and fortification) were more common than immediate coping strategies (diversion and confrontation). Tips for coping were more commonly used than distractions to cope with cravings, because they helped to fortify the quit attempt and provided opportunities to connect with other users of the application. However, distractions were important to attract new users and to facilitate content sharing. Conclusions Based on the qualitative results, we recommend that mobile phone-based interventions focus on tips shared by peers and frequent content updates. Apps also require testing with larger groups of users to assess whether they can be self-sustaining.

Mobile phone consumption and implications for SMS marketing

This paper reports on a Q-methodology study on the consumption of mobile phones and opinions on SMS-marketing, extracted from interpretive interviews and focus groups. The Metaphors Q-sort, developed within a framework of Holt's (1995) four metaphors of consumption, identifies three experiential value clusters in the consumption of mobile phones: the Mobile Pragmatists, the Mobile Connectors and the Mobile Revelers. The SMS-marketing Q-sort identifies two key clusters of subjective opinions on various aspects of SMS-based mobile-marketing. By integrating the findings from these two Q-sorts, we demonstrate that while all three value clusters express positive opinions towards ‘location specific’ and ‘customer initiated contact’ SMS-marketing, there are noticeable differences in how marketers should develop their strategies to maximize the consumers’ perceived experiential value derived from the consumption of their mobile phones. Keywords: mobile phones; experiential consumption: SMS-marketing; Q-methodology