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1.
Digit Health ; 10: 20552076241255658, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38854921

RESUMEN

Objective: Theoretical frameworks are essential for understanding behaviour change, yet their current use is inadequate to capture the complexity of human behaviour such as physical activity. Real-time and big data analytics can assist in the development of more testable and dynamic models of current theories. To transform current behavioural theories into more dynamic models, it is recommended that researchers adopt principles such as control systems engineering. In this article, we aim to describe a control system model of capability-opportunity-motivation and behaviour (COM-B) framework for reducing sedentary behaviour (SB) and increasing physical activity (PA) in adults. Methods: The COM-B model is explained in terms of control systems. Examples of effective behaviour change techniques (BCTs) (e.g. goal setting, problem-solving and social support) for reducing SB and increasing PA were mapped to the COM-B model for illustration. Result: A fluid analogy of the COM-B system is presented. Conclusions: The proposed integrated model will enable empirical testing of individual behaviour change components (i.e. BCTs) and contribute to the optimisation of digital behaviour change interventions.

2.
Food Sci Nutr ; 12(1): 3-12, 2024 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-38268891

RESUMEN

Cardamom has the potential to offer anti-inflammatory and antihypertensive advantages, but the findings from clinical trials have been inconsistent. To address this knowledge gap, the present systematic review and meta-analysis were conducted to evaluate the anti-inflammatory and antihypertensive effects of cardamom in adults. We systematically searched databases including PubMed, Scopus, and ISI Web of Sciences, for papers published up to October 2022 to identify clinical studies. Eight eligible studies were included in the meta-analysis. A fixed model was used to estimate weighted mean difference (WMD), standardized mean difference (SMD), and 95% confidence interval (95% CI). The results showed that cardamom significantly reduced the levels of inflammatory factors, including hs-CRP (SMD: -0.60 mg/dL; 95% CI: -0.78 to 0.42), IL-6 (WMD: -1.25 mg/dL; 95% CI: -1.48 to -1.03), TNF-α (WMD: -2.10 kg; 95% CI: -2.36 to -1.84, p < .001), and measures of systolic (WMD: -0.54 mmHg, 95% CI: -0.88, -0.19, p = .002) and diastolic (WMD: -0.90 mmHg; 95% CI: -1.07 to -0.73) blood pressure. The current meta-analysis showed that cardamom can help reduce inflammation and improve blood pressure. However, due to the limited number of studies, caution must be exercised when interpreting the current results.

3.
JMIR Form Res ; 8: e47157, 2024 Jan 24.
Artículo en Inglés | MEDLINE | ID: mdl-38265864

RESUMEN

BACKGROUND: This study assesses the accuracy of a Bluetooth-enabled prototype activity tracker called the Sedentary behaviOR Detector (SORD) device in identifying sedentary, standing, and walking behaviors in a group of adult participants. OBJECTIVE: The primary objective of this study was to determine the criterion and convergent validity of SORD against direct observation and activPAL. METHODS: A total of 15 healthy adults wore SORD and activPAL devices on their thighs while engaging in activities (lying, reclining, sitting, standing, and walking). Direct observation was facilitated with cameras. Algorithms were developed using the Python programming language. The Bland-Altman method was used to assess the level of agreement. RESULTS: Overall, 1 model generated a low level of bias and high precision for SORD. In this model, accuracy, sensitivity, and specificity were all above 0.95 for detecting sitting, reclining, standing, and walking. Bland-Altman results showed that mean biases between SORD and direct observation were 0.3% for sitting and reclining (limits of agreement [LoA]=-0.3% to 0.9%), 1.19% for standing (LoA=-1.5% to 3.42%), and -4.71% for walking (LoA=-9.26% to -0.16%). The mean biases between SORD and activPAL were -3.45% for sitting and reclining (LoA=-11.59% to 4.68%), 7.45% for standing (LoA=-5.04% to 19.95%), and -5.40% for walking (LoA=-11.44% to 0.64%). CONCLUSIONS: Results suggest that SORD is a valid device for detecting sitting, standing, and walking, which was demonstrated by excellent accuracy compared to direct observation. SORD offers promise for future inclusion in theory-based, real-time, and adaptive interventions to encourage physical activity and reduce sedentary behavior.

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