Background: Several studies have examined how the implementation of behavior change techniques (BCTs) varies between different activity trackers. However, activity trackers frequently allow tracking of activity, sleep, and sedentary behaviors; yet, it is unknown how the implementation of BCTs differs between these behaviors.
Objective: The aim of this study was to assess the number and type of BCTs that are implemented by wearable activity trackers (self-monitoring systems) in relation to activity, sleep, and sedentary behaviors and to determine whether the number and type of BCTs differ between behaviors.
Methods: Three self-monitoring systems (Fitbit [Charge HR], Garmin [Vivosmart], and Jawbone [UP3]) were each used for a 1-week period in August 2015. Each self-monitoring system was used by two of the authors (MJD and BM) concurrently. The Coventry, Aberdeen, and London-Refined (CALO-RE) taxonomy was used to assess the implementation of 40 BCTs in relation to activity, sleep, and sedentary behaviors. Discrepancies in ratings were resolved by discussion, and interrater agreement in the number of BCTs implemented was assessed using kappa statistics.
Results: Interrater agreement ranged from 0.64 to 1.00. From a possible range of 40 BCTs, the number of BCTs present for activity ranged from 19 (Garmin) to 33 (Jawbone), from 4 (Garmin) to 29 (Jawbone) for sleep, and 0 (Fitbit) to 10 (Garmin) for sedentary behavior. The average number of BCTs implemented was greatest for activity (n=26) and smaller for sleep (n=14) and sedentary behavior (n=6).
Conclusions: The number and type of BCTs implemented varied between each of the systems and between activity, sleep, and sedentary behaviors. This provides an indication of the potential of these systems to change these behaviors, but the long-term effectiveness of these systems to change activity, sleep, and sedentary behaviors remains unknown.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575434 | PMC |
| http://dx.doi.org/10.2196/ijmr.6685 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Role of Probiotics in Depression: Connecting Dots of Gut-Brain-Axis Through Hypothalamic-Pituitary Adrenal Axis and Tryptophan/Kynurenic Pathway involving Indoleamine-2,3-dioxygenase.
Mol Neurobiol
January 2025
Cellular and Molecular Neurobiology and Drug Targeting Laboratory, Department of Zoology, Indira Gandhi National Tribal University, Amarkantak-484 887, MP, India.
Depression is one of the most disabling mental disorders worldwide and characterized by symptoms including worthlessness, anhedonia, sleep, and appetite disturbances. Recently, studies have suggested that tryptophan (Trp) metabolism plays a key role in depressed mood through serotonin and kynurenine pathway involving enzyme tryptophan 5-monooxygenase (TPH) and indoleamine-2,3-dioxygenase (IDO) respectively. Moreover, during neuroinflammation, IDO is activated by proinflammatory cytokines and affects neurogenesis, cognition, disturbed hypothalamic-pituitary-adrenal (HPA) axis, and gut homeostasis by altering the gut bacteria and its metabolites like Trp derivatives.
View Article and Find Full Text PDFEffects of 24-h sleep deprivation on whole-body heat exchange in young men during exercise in the heat.
Eur J Appl Physiol
January 2025
Human and Environmental Physiology Research Unit, School of Human Kinetics, University of Ottawa, 125 University, Montpetit Hall, Room 367, Ottawa, ON, Canada.
Sleep deprivation has been associated with impaired thermoregulatory function. However, whether these impairments translate to changes in whole-body heat exchange during exercise-heat stress remains unknown. Therefore, following either a night of normal sleep or 24 h of sleep deprivation, 10 young men (mean (SD): 23 (3) years) completed three 30-min bouts of semi-recumbent cycling at increasing fixed rates of metabolic heat production (150, 200, 250 W/m), each separated by a 15-min rest in dry heat (40 °C, ~ 13% relative humidity).
View Article and Find Full Text PDFPreliminary evidence of immune infiltration and neutrophil degranulation in peripheral blood of non-obese OSA patients related to cognitive decline.
Sci Rep
January 2025
Department of Pulmonary and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
Obstructive sleep apnea (OSA) patients have varying degrees of cognitive impairment, but the specific pathogenic mechanism is still unclear. Meanwhile, poor compliance with continuous positive airway pressure (CPAP) in OSA prompts better solutions. This study aimed to identify differentially expressed genes between the non-obese OSA patients and healthy controls, and to explore potential biomarkers associated with cognitive impairment.
View Article and Find Full Text PDFThe link between sleep bruxism and oxidative stress based on a polysomnographic study.
Sci Rep
January 2025
Clinical Department of Diabetology, Hypertension and Internal Diseases, Institute of Internal Diseases, Wroclaw Medical University, 213 Borowska St, Wroclaw, 50-556, Poland.
Oxidative stress is proven to increase cardiovascular risk and to diminish healthy life expectancy. Sleep bruxism (SB) is a prevalent masticatory muscle activity during sleep characterized by heterogeneous etiology and inadequately recognized pathophysiology. Recent theories have proposed a potential association between SB and oxidative stress.
View Article and Find Full Text PDF"Multimodal Sleep Signal Tensor Decomposition and Hidden Markov Modeling for Temazepam-Induced Anomalies Across Age Groups".
J Neurosci Methods
January 2025
School of Electrical and Computer Engineering, Gallogly College of Engineering, University of Oklahoma, Norman, OK 73019, USA.
Background: Recent advances in multimodal signal analysis enable the identification of subtle drug-induced anomalies in sleep that traditional methods often miss.
New Method: We develop and introduce the Dynamic Representation of Multimodal Activity and Markov States (DREAMS) framework, which embeds explainable artificial intelligence (XAI) techniques to model hidden state transitions during sleep using tensorized EEG, EMG, and EOG signals from 22 subjects across three age groups (18-29, 30-49, and 50-66 years). By combining Tucker decomposition with probabilistic Hidden Markov Modeling, we quantified age-specific, temazepam-induced hidden states and significant differences in transition probabilities.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!