The Siconolfi step test: a valid and reliable assessment of cardiopulmonary fitness in older men with prostate cancer

Examining reactivity to the measurement of physical activity and sedentary behavior among women in midlife with elevated risk for cardiovascular disease

OBJECTIVES

To estimate the extent of reactivity to measurement of physical activity (PA) and sedentary behavior among women in midlife with elevated risk for cardiovascular disease (CVD).

DESIGN

Secondary analysis of a 10-day observational study of PA and sedentary behavior.

MAIN OUTCOME MEASURES

PA (steps, minutes of light PA, total minutes of moderate-to- vigorous PA [MVPA]) and percent time in sedentary behavior per day were assessed using ActiGraph GT3X tri-axial accelerometers in 75 women in midlife with elevated CVD risk (e.g. hypertension; MAge = 51.61, MBMI = 34.02 kg/m2). Two-level multilevel models were used to test for evidence of reactivity, with the addition of random effects to test for evidence of individual differences in observed trends.

RESULTS

All outcomes showed linear trends across days (ps < 0.001), though this masked what appeared to be meaningful dropoff after Day 1 or Day 2 (with little difference between subsequent days; srs ranging from 0.15 to 0.32). The random effect was significant only for percent time in sedentary behavior (χ2[1] = 10.40, p = 0.02).

CONCLUSIONS

Consistent small to medium effects were found for all PA and sedentary behavior outcomes, underscoring the importance of considering measurement reactivity in populations with elevated CVD risk.

Social dimensions impact individual sleep quantity and quality

While sleep positively impacts well-being, health, and productivity, the effects of societal factors on sleep remain underexplored. Here we analyze the sleep of 30,082 individuals across 11 countries using 52 million activity records from wearable devices. Our data are consistent with past studies of gender and age-associated sleep characteristics. However, our analysis of wearable device data uncovers differences in recorded vs. self-reported bedtime and sleep duration. The dataset allowed us to study how country-specific metrics such as GDP and cultural indices relate to sleep in groups and individuals. Our analysis indicates that diverse sleep metrics can be represented by two dimensions: sleep quantity and quality. We find that 55% of the variation in sleep quality, and 63% in sleep quantity, are explained by societal factors. Within a societal boundary, individual sleep experience was modified by factors like exercise. Increased exercise or daily steps were associated with better sleep quality (for example, faster sleep onset and less time awake in bed), especially in countries like the U.S. and Finland. Understanding how social norms relate to sleep will help create strategies and policies that enhance the positive impacts of sleep on health, such as productivity and well-being.

Do executive functions predict physical activity behavior? A meta-analysis

BACKGROUND

Executive functions (EFs) are important determinants of health behaviors. In the present study, a meta-analysis was conducted to investigate the relationship between EFs and physical activity (PA) behavior.

METHODS

Systematic searches were carried out in PsycInfo, MEDLINE, and SPORTDiscus databases throughout April 2021. Prospective empirical studies conducted with general healthy populations across the lifespan, which reported the relationship between baseline EFs and later PA behavior were selected.

RESULTS

Eight studies were found eligible. Results of the multilevel meta-analysis revealed a small but significant total effect size for EFs on PA behavior of z = 0.12. High heterogeneity was observed among studies. When potential moderators were tested, residual heterogeneity remained significant and the effects of the moderators were not significant. The effect size dropped when accounted for publication bias.

CONCLUSIONS

Despite limitations, the study provided evidence for EFs' determinant role on PA behavior. More research is however encouraged to inform PA promotion programs that are well-prepared for individual differences in EFs.

A systematic review and meta-analysis of studies of reactivity to digital in-the-moment measurement of health behaviour

Self-report measures of health behaviour have several limitations including measurement reactivity, i.e., changes in people's behaviour, cognitions or emotions due to taking part in research. This systematic review investigates whether digital in-the-moment measures induce reactivity to a similar extent and why it occurs. Four databases were searched in December 2020. All observational or experimental studies investigating reactivity to digital in-the-moment measurement of a range of health behaviours were included if they were published in English in 2008 or later. Of the 11,723 records initially screened, 30 publications reporting on 31 studies were included in the qualitative synthesis/ 7 studies in the quantitative synthesis. Eighty-one percent of studies focused on reactivity to the measurement of physical activity indicators; small but meaningful pooled effects were found (Cohen's ds: 0.27-0.30). Only a small number of studies included other behaviours, yielding mixed results. Digital in-the-moment measurement of behaviour thus may be as prone to reactivity as self-reports in questionnaires. Measurement reactivity may be amplified by (1) ease of changing the behaviour (2) awareness of being measured and social desirability, and (3) resolving discrepancies between actual and desired behaviour through self-regulation.

Testing of a Self-administered 6-Minute Walk Test Using Technology: Usability, Reliability and Validity Study

BACKGROUND

The need to attend a medically supervised hospital- or clinic-based appointment is a well-recognized barrier to exercise participation. The development of reliable and accurate home-based functional tests has the potential to decrease the burden on the health care system while enabling support, information, and assessment.

OBJECTIVE

This study aims to explore the usability (ie, acceptability, satisfaction, accuracy, and practicality) of the EasyMeasure app to self-administer the 6-minute walk test (6MWT) in young, healthy adults and determine parallel form reliability and construct validity of conducting a self-administered 6MWT using technology.

METHODS

We used a usability study design. English-speaking, undergraduate university students who had access to an iPhone or iPad device running iOS 10 or later and self-reported ability to walk for 6 minutes were recruited for this study. Consenting participants were randomized to either a standard 6MWT group (ie, supervised without the use of the app) or a technology 6MWT group (ie, unsupervised with the app to mimic independent implementation of the test). All participants performed a maximal treadmill test. Participants in the 6MWT group completed the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire and a satisfaction questionnaire after completing the assessment. Parallel form reliability of the 6MWT using technology was analyzed by comparing participant self-administered scores and assessor scores using Pearson correlation coefficients across and between trials. Construct validity was assessed by comparing participant 6MWT scores (both standard and using technology) with maximum treadmill test variables (peak oxygen uptake and ventilatory threshold [VT]).

RESULTS

In total, 20 university students consented to participate in the study. All but 2 participants (8/10, 80%) in the technology 6MWT group had deviations that prevented them from accurately conducting the 6MWT using the app, and none of the participants were able to successfully score the 6MWT. However, a significantly strong correlation was found (r=.834; P=.003) when comparing participants' scores for the 6MWT using technology with the assessors' scores. No significant correlations were found between maximal treadmill test peak oxygen uptake scores and 6MWT prediction equations using standard 6MWT scores (equation 1: r=0.119; P=.78; equation 2: r=0.095; P=.82; equation 3: r=0.119; P=.78); however, standard 6MWT scores were significantly correlated with VT values (r=0.810; P=.02). The calculated submaximal treadmill scores and assessor 6MWT scores using technology also demonstrated a significant correlation (r=0.661; P=.04).

CONCLUSIONS

This study demonstrated significant usability concerns regarding the accuracy of a self-administered 6MWT using the EasyMeasure app. However, the strong and significant correlation between the 6MWT and VT values demonstrates the potential of the 6MWT to measure functional capacity for community-based exercise screening and patient monitoring.