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. 2024 Sep 20;24(1):335.
doi: 10.1186/s12871-024-02724-1.

Knowledge, attitude and practice toward to artificial intelligent patient-controlled analgesia among anesthesiologists: a cross-sectional study in east China's Jiangsu Province

Jiaqin Cai #  1 , Shiyi Huang #  1 , Yueyi Jiang  2 , Yihu Zhou  2 , Lin Zhang  2 , Lianbing Gu  3   4 , Jing Tan  5   6
Affiliations

Knowledge, attitude and practice toward to artificial intelligent patient-controlled analgesia among anesthesiologists: a cross-sectional study in east China's Jiangsu Province

Jiaqin Cai et al. BMC Anesthesiol. .

Abstract

Background: Inadequate postoperative analgesia greatly affects the recovery of patients, can poses a substantial health and economic burden. Patient-controlled analgesia is the most commonly used method for postoperative pain relief. However, the situation of inadequate analgesia still exists. Artificial intelligent Patient-controlled analgesia (Ai-PCA) system can make it easier for medical staff to understand the pain level of patients in order to deal with it in time. So far, several studies have investigated anesthesiologists' knowledge and management of Ai-PCA.

Objective: This study aimed to assess the degree of anesthesiologists' knowledge, attitude and their practice (KAP) towards Ai-PCA in east China's Jiangsu Province.

Methods: This cross-sectional study was conducted among 396 anesthesiologists working in tertiary hospitals. The data were collected using a pretested, structured and self-administered KAP questionnaire. The data were analyzed using Independent t-test, analysis of variance, Pearson's correlation and multiple linear regression tests.

Results: Five hundred twelve questionnaires were collected, 396 anesthesiologists (190 Male, and 206 Female) were included in our study for statistical analysis. The score of knowledge, attitude, practice was 5.49 ((SD = 1.65; range:0-8), 37.45 (SD = 4.46; range:9-45), and 26.41 (SD = 9.61; range:9-45), respectively. Among the participants, 309 (78%) and 264 (66.7%) had good knowledge and positive attitudes toward Ai-PCA, respectively. However, only 81 (20.5%) of the participants exhibited good practice regarding Ai-PCA. Participation in Ai-PCA training showed a significant correlation with knowledge, attitude and practice scores. Besides, age, years of experience and professional titles of anesthesiologists were correlated with knowledge scores. The title of the anesthesiologist was associated with attitude scores. And the marital status of anesthesiologists was correlated with practice scores.

Conclusion: Our findings revealed the score of practice regarding Ai-PCA are very poor among anesthesiologists in east China's Jiangsu Province. The utilization of Ai-PCA was found to be impacted by whether the individual had received training. This calls for a comprehensive approach should be conducted for raising the level of knowledge, attitude, and practice of anesthesiologist on using Ai-PCA and more Ai-PCA training to be included in the daily learning.

Trial registration: Chinese Clinical Trial Registry ( www.chictr.org.cn ; 27/10/2023; ChiCTR2300077070).

Keywords: Ai-PCA; Anesthesiologists; Attitude; Knowledge; Practice.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Mean knowledge, attitude and practice scores of anesthesiologist. Knowledge score < 8 = poor knowledge, and ≥ 8 = good knowledge; Attitude score < 36 = poor attitude, and ≥ 36 = good attitude; Practice score < 36 = poor practice, and ≥ 36 = good practice
Fig. 2
Fig. 2
Response of anesthesiologist’ knowledge towards to Ai-PCA
Fig. 3
Fig. 3
Response of anesthesiologist’s attitude towards Ai-PCA
Fig. 4
Fig. 4
Response of anesthesiologist’ practice towards to Ai-PCA
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