AI-based assessment of therapeutic communication skills showed high reliability (ICC > 0.97) in a cited quasi-experimental nursing study¶
Claim · All claims
Evidence · 1 study · reviewr3·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Erkayiran's quasi-experimental study demonstrated AI could evaluate therapeutic communication skills with high reliability (ICC > 0.97). → Xiang Yue 2026
Evidence¶
Xiang Yue 2026¶
Xiang Yue, Shi Haoning, Ren Keke, Yang Xilin, Li Lin, Zhao Qinghua, Huang Huanhuan. (2026). An artificial intelligence application framework for nursing education: a scoping review based on the KAS model. BMC Medical Education. https://doi.org/10.1186/s12909-026-09209-4
q2 · i? · review · r3
The review reports, citing Erkayiran, a quasi-experimental study with standardized patient-based education in which AI evaluation of therapeutic communication skills showed "high reliability (ICC > 0.97)". ICC is a reliability coefficient, not a standardized effect size.
"Erkayiran [39] provided critical empirical evidence within nursing education. Their quasi-experimental study demonstrated that AI could evaluate therapeutic communication skills with high reliability (ICC > 0.97)."
Discussion¶
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review |
generated |
by process:wiki-ingest on 2026-10-31 |
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