Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Objectives Pedometers are an effective self-monitoring tool to increase users' physical activity. However, a range of advanced trackers that measure physical activity 24 hours per day have emerged (eg, Fitbit). The current study aims to determine people's current use, interest and preferences for advanced trackers. Design and participants A cross-sectional national telephone survey was conducted in Australia with 1349 respondents. Outcome measures Regression analyses were used to determine whether tracker interest and use, and use of advanced trackers over pedometers is a function of demographics. Preferences for tracker features and reasons for not wanting to wear a tracker are also presented. Results Over one-third of participants (35%) had used a tracker, and 16% are interested in using one. Multinomial regression (n=1257) revealed that the use of trackers was lower in males (OR=0.48, 95% CI 0.36 to 0.65), non-working participants (OR=0.43, 95% CI 0.30 to 0.61), participants with lower education (OR=0.52, 95% CI 0.38 to 0.72) and inactive participants (OR=0.52, 95% CI 0.39 to 0.70). Interest in using a tracker was higher in younger participants (OR=1.73, 95% CI 1.15 to 2.58). The most frequently used tracker was a pedometer (59%). Logistic regression (n=445) revealed that use of advanced trackers compared with pedometers was higher in males (OR=1.67, 95% CI 1.01 to 2.79) and younger participants (OR=2.96, 95% CI 1.71 to 5.13), and lower in inactive participants (OR=0.35, 95% CI 0.19 to 0.63). Over half of current or interested tracker users (53%) prefer to wear it on their wrist, 31% considered counting steps the most important function and 30% regarded accuracy as the most important characteristic. The main reasons for not wanting to use a tracker were, ‘I don't think it would help me’ (39%), and ‘I don't want to increase my activity’ (47%). Conclusions Activity trackers are a promising tool to engage people in self-monitoring a physical activity. Trackers used in physical activity interventions should align with the preferences of target groups, and should be able to be worn on the wrist, measure steps and be accurate.

This study aims to analyze psychometric properties and validity of the Compulsive Internet Use Scale (CIUS) and the Internet Addiction Test (IAT) and, second, to determine a threshold for the CIUS which matches the IAT cut-off for detecting problematic Internet use. A total of 292 subjects with problematic or pathological gambling (237 men, 55 women) aged 14-63 years and with private Internet use for at least 1 h per working or weekend day were recruited via different recruitment channels. Results include that both scales were internally consistent (Cronbach's α = 0.9) and had satisfactory convergent validity (r = 0.75; 95% CI 0.70-0.80). The correlation with duration of private Internet use per week was significantly higher for the CIUS (r = 0.54) compared to the IAT (r = 0.40). Among all participants, 25.3% were classified as problematic Internet users based on the IAT with a cut-off ≥40. The highest proportion of congruent classified cases results from a CIUS cut-off ≥18 (sensitivity 79.7%, specificity 79.4%). However, a higher cut-off (≥21) seems to be more appropriate for prevalence estimation of problematic Internet use.

This study aims to examine the relationship of lifestyle behaviors (physical activity, work and non-work sitting time, sleep quality, and sleep duration) with presenteeism while controlling for sociodemographics, work- and health-related variables. Data were collected from 710 workers (aged 20 to 76 years; 47.9% women) from randomly selected Australian adults who completed an online survey. Linear regression was used to examine the relationship between lifestyle behaviors and presenteeism. Poorer sleep quality (standardized regression coefficients [B] = 0.112; P < 0.05), suboptimal duration (B = 0.081; P < 0.05), and lower work sitting time (B = -0.086; P < 0.05) were significantly associated with higher presenteeism when controlling for all lifestyle behaviors. Engaging in three risky lifestyle behaviors was associated with higher presenteeism (B = 0.150; P < 0.01) compared with engaging in none or one. The results of this study highlight the importance of sleep behaviors for presenteeism and call for behavioral interventions that simultaneously address sleep in conjunction with other activity-related behaviors.