Table 3.

Summary of included studies.

Authors	Physiological/medical measures	Psychological measures	General measures	Outcomes
Varas et al., 2018	EST (exercise capacity) Step count (physical activity) Baecke physical activity questionnaire	SGRQ (quality of life)	Demographic characteristics	This study demonstrates that community-based Pulmonary Rehabilitation training in COPD patients improves exercise capacity, physical activity level, and quality of life over the medium and long term. The benefits obtained in exercise capacity and quality of life indicate that this type of programme both produced a short-term training effect and maintained these benefits over time, suggesting that patients autonomously adopted the regular practice of physical exercise.
J. Lee et al., 2019	Body composition measurement FIQ (disease activity) PtGA VAS (general health-status)	BDI (depression) EQ-5D-5L (quality of life)	Demographic characteristics	The PAAS WD was effectively used in FMS patients. No differences were found about depression symptoms and quality of life, but these results could be due to the inclusion of a limited number of patients and the short study period which may not have captured the impact of the WD on QoL and depression. However, the WD accurately reflected pain status between clinic visits, and the use of this system may help to alleviate pain.
Moor et al., 2019	Step count (physical activity) Home spirometry (pulmonary function) KSQ (health status in patients with sarcoidosis) VAS (general health-status) FAS (fatigue in patients with sarcoidosis)	EQ-5D-5L (quality of life) HADS (anxiety and depression)	Demographic characteristics Phone interview about opinion on the home monitoring programme and the usability of the device	Patient satisfaction and adherence to daily spirometry and activity tracking were high. All patients wished to continue the use of the home monitoring programme after the study. However, symptoms measures by HADS, FAS, VAS and QoL (KSQ, EQ-5D-5L) were not significantly different at baseline compared to month one, probably due to the inclusion of a limited number of patients and to the short period study.
Wulfovich et al., 2019	Step count and calories (physical activity)	EMA (self-efficacy)	Demographic characteristics	The results indicate that health apps and WD have the potential to enable better self-management and improve patients' wellbeing but must be further refined to address different human aspects of their use. Specifically, the apps/wearables should be easier to use, more personalized and context-aware for the patient's overall routine and lifestyle choices, and healthcare needs.
Andersen et al., 2020	Step count, sleep and health rate data (physical activity)	Interview on feeling (Anxiety)	Demographic characteristics Interview on knowledge acquired Interview on Evaluation on themselves and their overall health	Wearable activity trackers actualized patients' experiences across 3 dimensions with a spectrum of contrasting experiences: (a) knowing, which spanned gaining insight and evoking doubts; (b) feeling, which spanned being reassured and becoming anxious; and (c) evaluating, which spanned promoting improvements. The affective dimension of self-tracking when living with a chronic heart disease emerged as loaded with ambivalence: Fitbit data may provide numerical reassurance, which can relieve acute anxiety related to unclear bodily sensations but at the same time heightened attention to these data can also introduce new uncertainties and anxiety. Activity data from WD may be a resource for self-care; however, the data may simultaneously constrain and create uncertainty, fear, and anxiety.
Bentley et al., 2020	Medical Research Council Breathlessness Scale (COPD severity) Step count (physical activity) CHAMPS (physical activity) ISWT (exercise capacity) CAT (symptoms)	SGRQ (quality of life) PHQ-9 (anxiety and depression)	Demographic characteristics EQ-5D-3L (cost-effectiveness) SUS (WD usability)	Overall, the SMART-COPD intervention was well liked and perceived as easy to use into participants' daily lives by those who completed the study. However, there was a high dropout rate which implies high rates of people who were eligible for the intervention but who did not easily adopt the technology. The data suggest that people with COPD who had worse baseline health were more likely to withdraw from the study, which may indicate that this patient group is harder to reach with mHealth interventions. Moreover, participants who withdrew had worse baseline scores on quality of life and depression compared with those who completed.
Lee et al., 2020	Body composition measurement (height, weight, body mass index) Systolic/diastolic pressure Blood sugar level Cholesterol level	Walker's health-promoting lifestyle profile WHOQOL-BREF (Quality of Life) Self-Efficacy Scale	Demographic characteristics	The e-Motivate4Change programme based on the use of health apps and WD, selected based on user's need, was associated to increased physical activity, decreased BMI, lower cholesterol, and increased self-efficacy among experimental group, thus effectively promoting a health-related lifestyle.
Li et al., 2020	Body composition measurement Laboratory data (hemogram, serum biochemistry, electrolyte profile, renal function) Step count, distance, consumed calories, and heart rate (physical activity)	Self-efficacy questionnaire Self-management questionnaire KDQOL-SF (quality of life)	Demographic characteristics	A self-management intervention that combines WD, a health management platform, and social media could strengthen self-efficacy and self-management, and lead to improvements in quality of life for people with CKD stages 1–4. The effects of this nonpharmacologic intervention were also reflected in a slower decline in eGFR. These results outline a new self-management model to promote healthy lifestyle behaviours in patients with CKD.
Lukkahatai et al., 2021	Body composition measurement Blood pressure Symptom experience Step count (physical activity) Sleep hours	SDSCA (Self-management) DSES (Self-efficacy) SF-12 (Quality of life)	Demographic characteristics Questionnaire to measure the experience, acceptability, and satisfaction in using WD	The results demonstrate the feasibility of the use of the WD among people living with chronic conditions. Participants found that the step count screen provided immediate physical performance feedback that was helpful with their exercise. The behavioural changes, however, could not be examined due to the short duration of the usage. The study did not find significant differences but only slightly higher self-management behaviours and self-efficacy among patients who wore WD than those in the control group but this could be due to the short duration (2 days) of the WD use. Future studies that require longer device usage in larger sample sizes are needed.
Xie et al., 2021	Body composition measurement chronic diagnosis	Section of the HINTS survey (Self-efficacy, depression)	Demographic characteristics Questionnaire on WD use	This study examined the association between WD use and self-efficacy for managing health among adults aged 18 and older. Those who used WD in the past month were more likely to have higher self-efficacy (completely confident in managing health) than those who did not use WD. Use of WD can motivate individuals to obtain high self-efficacy to commit to manage their own health. Thus, high self-efficacy is desired for health behaviour change in health-promoting interventions.

BDI: Beck Depression Inventory; CAT: Chronic Obstructive Pulmonary Disease Assessment Test; CHAMPS: Community Healthy Activities Model Programme for Seniors; DSES: Diabetes Self-efficacy Scale; EST: endurance shuttle test; EQ-5D-3L: EuroQoL 5 Dimensions 3 Level; EQ-5D-5L: EuroQoL-5 Dimension 5 Level; Ex-SRES: Exercise Self-Regulatory Efficacy Scale; FAS: Fatigue Assessment Scale; FIQ: Fibromyalgia Impact Questionnaire; HADS: Hospital Anxiety and Depression Scale; HINTS: Health Information National Trends Survey; ISWT: Incremental Shuttle Walk Test; KDQOL-SF: Kidney Disease Quality of Life Survey; KSQ: King's Sarcoidosis Questionnaire; PAAS: Pain Assessment and Analysis System; PHQ-9, Patient Health Questionnaire-9 (Anxiety and depression); PtGA: Patient global assessment; SDSCA: summary of diabetes self-care activities (self-management behaviours); SGRQ: St George's Respiratory Questionnaire; SF-12: General Health Short Form 12; SUS: System Usability Scale; VAS: Visual Analogue Scale; WHOQOL-BREF: World Health Organization Quality of Life-BREF; WD: wearable device; eGFR: estimated glomerular filtration rate; FMS: fibromyalgia syndrome; CKD: chronic kidney disease; EMA: Ecological Momentary Assessment.