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临床试验/NCT05777291
NCT05777291Unknown不适用

IntelligentCare: the Impact of a Wearable-based Intervention in an Ambulatory Hospital Setting to Improve Health in Multimorbidity Through Physical Activity and Sleep

GLSMED Learning Health S.A.2 个研究点 分布在 1 个国家目标入组 80 人开始时间: 2023年4月1日最近更新:
适应症
干预措施

试验速览

阶段
不适用
发起方
入组人数
80
试验地点
2
主要终点
Physical activity

研究概览

简要总结

The benefits of physical activity and adequate sleep are well documented, and their importance strengthens with the increasing prevalence of chronic diseases and multimorbidity. Interventions to promote physical activity and sleep that use commercial activity trackers may be useful non-pharmacological approaches to managing individual health; however, limited evidence exists on their use to improve physical activity in elderly patients with multimorbidity. This study aims to measure the effects of behavioral change techniques (BCTs) delivered by a wearable device on physical activity (PA) and quality of sleep (QS) in elderly patients with multimorbidity. The investigators designed an open-label randomized controlled trial with participants recruited through primary care and a specialist outpatient clinic. Participants must be more than 65 years old, have multimorbidity, and have access to smartphones. All eligible participants will receive PA promotion content and will be randomly assigned to wear a smartwatch. The primary outcome will be the participants' PA measurement at six months using the IPAQ-SF. Secondary outcomes will include changes in the participants' frailty status, biometric measurements, quality of life, and biopsychosocial assessments. A sample size of 40 participants per arm was calculated to detect group differences, with 50 participants recruited and randomized into each arm. This study aims to contribute to a better understanding of PA patterns and the impact of smartwatch-based PA interventions in patients with multimorbidity. The trial's findings are expected to improve our understanding of how physical activity patterns, patient-reported outcomes (PROMs), and healthcare resource utilization are linked in patients with multiple medical conditions. The study will use a registry for locally developed PROMs and data from the participants' medical records to determine how wearable data and medical information data can be used to predict PROMs and unplanned hospital admissions.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Treatment
盲法
Single (Outcomes Assessor)

盲法说明

The masking procedure will involve blinding the outcome assessors to the treatment allocation of the patients. This means that the outcome assessors will be kept unaware of whether the patients are wearing the device or not.

入排标准

年龄范围
65 Years 至 —(Older Adult)
性别
All
接受健康志愿者

入选标准

  • Multimorbidity defined as the presence of two or more of the following chronic conditions: hypertension, depression or anxiety, chronic musculoskeletal conditions causing pain or limitation, arthritis and/or rheumatoid arthritis, osteoporosis, asthma, COPD, ischemic heart disease, peripheral artery disease, heart failure, cerebrovascular diseases, chronic stomach or colon conditions, chronic hepatitis, diabetes mellitus, thyroid disorders, any active cancer in the previous five years, chronic kidney disease, chronic urinary conditions, hyperlipidemia, and obesity
  • Must have access to their smartphones

排除标准

  • patients who are sufficiently physically active (IPAQ-SF > 150 min aerobic physical activity per week)
  • existing absolute contraindication for PA according to the American College of Sports Medicine (acute myocardial infarction within two days, ongoing unstable angina, uncontrolled cardiac arrhythmia with hemodynamic compromise, active endocarditis, symptomatic severe aortic stenosis, decompensated heart failure, acute pulmonary embolism, pulmonary infarction, deep venous thrombosis, acute myocarditis or pericarditis, acute aortic dissection, physical disability that precludes safe and adequate testing)
  • poor comprehension of Portuguese language
  • disabling neurological disorder (defined as mRankin score ≥4), severe psychiatric illness, learning disability, dementia and cognitive impairment, registered blind
  • housebound or resident in a nursing home or non-ambulant
  • advanced cancer
  • scheduled for surgery within five months after the first consultation
  • orthopedic or rheumatologic diseases with severe impairment
  • chronic pain syndromes with inherently reduced mobility

研究组 & 干预措施

Experimental arm

Experimental

Patients will be given physical activity recommendations ABD will be using the study devices: activity watch (Fitbit Sense) and a sleep monitoring mattress (Withings, Sleep Analyzer)

干预措施: Activity watch monitoring (Device)

Experimental arm

Experimental

Patients will be given physical activity recommendations ABD will be using the study devices: activity watch (Fitbit Sense) and a sleep monitoring mattress (Withings, Sleep Analyzer)

干预措施: Sleep mattress monitoring (Device)

Experimental arm

Experimental

Patients will be given physical activity recommendations ABD will be using the study devices: activity watch (Fitbit Sense) and a sleep monitoring mattress (Withings, Sleep Analyzer)

干预措施: Physical activity counseling (Behavioral)

Control arm

Active Comparator

Patients will be given physical activity recommendations only

干预措施: Physical activity counseling (Behavioral)

结局指标

主要结局

Physical activity

时间窗: 6 months after study entry

Physical activity measured trough International Physical Activity Questionnaire Short Form. The responses to these questions are used to calculate an individual's total physical activity level, expressed in metabolic equivalent of task (MET) minutes per week. The IPAQ-Sf assigns a MET value to each activity reported by the individual and multiplies this value by the reported duration of the activity to calculate the total MET-minutes per week for each domain. The total MET-minutes per week for all domains are then summed to give the total physical activity level for the individual. The results of the IPAQ-Sf can be used to classify individuals into different categories of physical activity levels, such as low, moderate, or high.

次要结局

  • Fall risk(6 months after study entry)
  • Abdominal circunference(6 months after study entry)
  • Physical performance(6 months after study entry)
  • Weight(6 months after study entry)
  • Calf circunference(6 months after study entry)
  • Health-related quality of life(6 months after study entry)
  • Biopsychosocial complexity and health care needs(6 months after study entry)
  • Unplanned hospital admissions(6 months after study entry)

研究者

发起方
GLSMED Learning Health S.A.
申办方类型
Other
责任方
Sponsor

研究点 (2)

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