TY  - JOUR
AU  - Ni, Ruping
AU  - Liu, Maobai
AU  - Huang, Shunmin
AU  - Yang, Jing
PY  - 2022
DA  - 2022/8/16
TI  - Effects of eHealth Interventions on Quality of Life and Psychological Outcomes in Cardiac Surgery Patients: Systematic Review and Meta-analysis
JO  - J Med Internet Res
SP  - e40090
VL  - 24
IS  - 8
KW  - eHealth
KW  - eHealth intervention
KW  - cardiac surgery
KW  - depression
KW  - anxiety
KW  - quality of life
KW  - meta-analysis
KW  - heart disease
KW  - surgery
KW  - heart surgery
KW  - post-operative
KW  - postoperative
KW  - mental health
KW  - home care
KW  - digital health intervention
KW  - digital health
KW  - outcomes
KW  - psychological
KW  - physiological
KW  - physiology
KW  - psychology
KW  - compliance
AB  - Background: Patients undergoing heart surgery may experience a range of physiological changes, and the postoperative recovery time is long. Patients and their families often have concerns about quality of life (QoL) after discharge. eHealth interventions may improve patient participation, ensure positive and effective health management, improve the quality of at-home care and the patient's quality of life, and reduce rates of depression. Objective: The purpose of this study was to evaluate the effects of eHealth interventions on the physiology, psychology, and compliance of adult patients after cardiac surgery to provide a theoretical basis for clinical practice. Methods: We conducted systematic searches of the following 4 electronic databases: PubMed, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials. Mean (SD) values were used to calculate the pooled effect sizes for all consecutive data, including QoL, anxiety, and depression. Where the same results were obtained using different instruments, we chose the standardized mean difference with a 95% CI to represent the combined effect size; otherwise, the mean difference (MD) with a 95% CI was used. Odds ratios were used to calculate the combined effect size for all dichotomous data. The Cohen Q test for chi-square distribution and an inconsistency index (I2) were used to test for heterogeneity among the studies. We chose a fixed-effects model to estimate the effect size if there was no significant heterogeneity in the data (I2≤50%); otherwise, a random-effects model was used. The quality of the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). Results: The search identified 3632 papers, of which 19 met the inclusion criteria. In terms of physical outcomes, the score of the control group was lower than that of the intervention group (MD 0.15, 95% CI 0.03-0.27, I2=0%, P=.02). There was no significant difference in the mental outcomes between the intervention and control groups (MD 0.10, 95% CI –0.03 to 0.24, I2=46.4%, P=.14). The control group’s score was lower than that of the intervention group for the depression outcomes (MD –0.53, 95% CI –0.89 to –0.17, I2=57.1%, P=.004). Compliance outcomes improved in most intervention groups. The results of the sensitivity analysis were robust. Nearly half of the included studies (9/19, 47%) had a moderate to high risk of bias. The quality of the evidence was medium to low. Conclusions: eHealth improved the physical component of quality of life and depression after cardiac surgery; however, there was no statistical difference in the mental component of quality of life. The effectiveness of eHealth on patient compliance has been debated. Further high-quality studies on digital health are required. Trial Registration: PROSPERO CRD42022327305; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=327305 
SN  - 1438-8871
UR  - https://www.jmir.org/2022/8/e40090
UR  - https://doi.org/10.2196/40090
UR  - http://www.ncbi.nlm.nih.gov/pubmed/35972792
DO  - 10.2196/40090
ID  - info:doi/10.2196/40090
ER  -