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The incidence of cancer continues to increase, and cancer patients still suffer from a range of burdens, leading to decreased quality of life. AI has been increasingly studied in the field of cancer care, demonstrating its enormous potential. However, most AI applications in cancer care are still in the developmental stage, and the strength of evidence from randomized controlled trials is not yet sufficient.
To evaluate the effects of AI-enhanced interventions in randomized controlled trials conducted in clinical settings and the impact of AI-enhanced interventions on the health outcomes of adult cancer patients.
Meta-analysis of randomized controlled trials.
Nine databases (MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, CINAHL, PsycINFO, Web of Science, CNKI, VIP, and Sinomed) were systematically searched, and metadata analysis was performed using R software and R Studio. The quality of the included studies was evaluated using the Cochrane Risk of Bias tool (RoB2) and the GRADE approach. The process was independently completed by two authors. The intervention effect was estimated by calculating the standardized mean difference (SMD) and 95% confidence interval (CI) using a random-effects model.
A total of ten articles were included. Meta-analysis results showed that AI-enhanced interventions can significantly improve the quality of life (SMD 0.89, 95% CI 0.06–1.73), symptom burden (SMD −0.81, 95% CI −1.44 to −0.18), anxiety (SMD −0.20, 95% CI −0.32 to −0.07), and self-efficacy (SMD 0.55, 95% CI 0.06 to 1.03) of cancer patients. The type of AI application and the duration of the intervention had an impact on the quality of life of cancer patients: the effect of algorithm recommendations (SMD 1.49, 95% CI 0.04–2.93) was better than that of risk alerts (SMD 0.33, 95% CI 0.03–0.63), and the effect of short-term interventions (< 3 months) (SMD 1.49, 95% CI 0.04–2.93) was better than that of long-term interventions (≥ 3 months) (SMD 0.19, 95% CI −0.04 to 0.43). Sensitivity analysis showed that the results of this study were stable and reliable.
AI-enhanced interventions are effective tools for improving patient outcomes. When integrating AI into clinical practice for cancer patients, priority should be given to the type of technology involved, ensuring its acceptability by enhancing perceived usefulness. AI technology should be adopted to relieve clinical nurses from documentation and low-complexity tasks, thereby addressing concerns about the loss of “humanistic care.” We recommend the formal integration of AI literacy frameworks, such as N.U.R.S.E.S., into nursing education and practice.
Trial Registration: PROSPERO (registration number: CRD420251040938).
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