Knowledge, Attitude and Practice Toward Artificial Intelligence Among Healthcare Workers in Private Polyclinics in Jeddah, Saudi Arabia

Figures & data

Table 1 Socio-Demographic Characteristics of Healthcare Workers Working in Private Polyclinics in Jeddah (n = 361)

Characteristics	n = 361	%
Age (years), Mean (SD)	35.2 ± 9.9
≤ 30 years	155	42.9
31–45 years	152	42.1
> 45 years	54	15.0
Gender
Male	138	38.2
Female	223	61.8
Healthcare workers
Physician	90	25.1
Nurse	128	35.8
Administrative Staff	39	10.9
Others	101	28.2
Professional Qualification
Graduate	183	51.1
Postgraduate (any degree after graduation)	69	19.3
Diploma	74	20.7
Others	32	8.9
Years of experience	9.5±8.6
≤ 5 years	147	40.7
6–15 years	157	43.5
> 15 years	57	15.8

Table 2 Knowledge, Attitude, and Practices Toward Artificial Intelligence (AI) Among Healthcare Workers in Jeddah (n = 361)

KNOWLEDGE VARIABLES	n = 361		%
Do you agree that you have good familiarity with artificial intelligence?
Agree	170		47.1
Disagree	131		36.3
Do not know	57		15.8
I have an understanding of the basic computational principle of AI.
Agree	269		74.5
Disagree	38		10.5
Do not know	67		18.6
I am comfortable with the nomenclature of AI.
Agree	286		79.4
Disagree	19		5.2
Do not know	75		20.9
I have an understanding of the limitations of AI.
Agree	178		77.0
Disagree	27		15.6
Do not know	92		25.6
AI abilities are superior to human experience.
Agree	178		49.6
Disagree	106		29.5
Do not know	51		14.2
Do you agree that artificial intelligence has useful applications in the medical field?
Agree	252		70.0
Disagree	36		10.0
Do not know	25		6.9
Median knowledge score (IQR)	5 (3–6)
ATTITUDE VARIABLES
How useful do you think AI could be in your area of work?
Useful	300		83.1
Limited or no use	61		16.9
Do you agree that the diagnostic ability of AI is superior to the clinical experience of a human doctor?
Agree	170		47.1
Disagree	131		36.3
Do not know	60		16.6
AI can help reduce the number of medical errors.
Agree	269		74.5
Disagree	38		10.5
Do not know	54		15.0
AI can deliver clinically relevant, vast amounts of high-quality data in real time.
Agree	286		79.4
Disagree	19		5.2
Do not know	55		15.4
AI has no emotional exhaustion or physical limitation.
Agree	178		77.0
Disagree	27		15.6
Do not know	56		7.4
Do you agree that you would always use AI when making medical decisions in the future?
Agree	178		49.6
Disagree	106		29.5
Do not know	75		20.9
Do you think there may be serious privacy issues with the use of AI?
Agree	252		70.0
Disagree	36		10.0
Do not know	72		20.0
How worried are you that AI will replace you at your job?
Worried	210		58.3
Not worried at all	150		41.7
Median attitude score (IQR)	5 (4–7)
PRACTICE VARIABLES	Agree n (%)	Disagree n (%)	Do not know n (%)
AI cannot be used to provide opinions in unexpected situations.	260 (72.2)	37 (10.3)	63 (17.5)
AI is not flexible enough to be applied to every patient.	277 (76.9)	32 (8.9)	51 (14.2)
AI has low ability to sympathize and consider the emotional well-being of the patient.	290 (79.4)	24 (6.7)	50 (13.9)
Median practice score (IQR)	0 (0)

Figure 1 Participant’s concerns about application of AI in medicine (n=361).

Figure 2 Participant’s think use of Artificial Intelligence would be most useful in.

Table 3 Bivariate Association of Knowledge, Attitude, and Practice Scores of Artificial Intelligence (AI) with Other Variables Among Healthcare Workers in Jeddah (n = 361)

Value	Knowledge Score Mean ± SD		Attitude Score Mean ± SD		Practice Score Mean ± SD
		p-value		p-value		p-value
Age (Pearson correlation)	0.048	0.362	0.056	0.292	‒0.004	0.940
Gender
Male	4.3 ± 1.8	0.109	5.4 ± 1.6	0.176	0.25 ± 0.49	0.624
Female	4.1 ± 1.8		5.1 ± 1.9		0.26 ± 0.62
Healthcare workers
Physician	4.0	0.032*	5.3	0.471	0.18	0.031*
Nurse	4.4		5.2		0.27
Administrative staff	3.6		4.9		0.46
Others	4.3		5.2		0.22
Professional Qualification
Graduate	4.1	0.391	5.3	0.824	0.21	0.099
Postgraduate	4.1		5.3		0.19
Diploma	4.5		5.1		0.42
Others	4.2		5.2		0.31
Years of experience (Pearson correlation)	0.077	0.146	0.100	0.059	‒0.038	0.480

Note: *P<0.05.

Table 4 Linear Regression Showing the Relation Between Knowledge, Attitude, and Practice Scores of Artificial Intelligence (AI) with Other Socio-Demographic Variables Among Healthcare Workers in Jeddah (n = 361)

Parameter	Category	Knowledge Score		Attitude Score		Practice Score
		Beta	P value	Beta	P value	Beta	P value
Age		−0.18	0.370	−0.03	0.107	0.007	0.239
Gender	Male	0.555	0.010*	0.369	0.088	−0.026	0.705
	Female	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Job type	Physician	−0.364	0.203	0.027	0.925	−0.012	0.893
	Nurse	0.255	0.313	0.012	0.962	0.013	0.876
	Administrative	−0.560	0.201	−0.923	0.037*	0.276	0.050
	Others	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Education level	Postgraduate	0.45	0.910	0.151	0.702	−0.113	0.369
	Graduate	−0.016	0.961	0.369	0.274	−0.109	0.309
	Diploma	0.414	0.277	0.261	0.497	0.075	0.537
	Others	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Experience in years		0.027	0.233	0.049	0.03*	−0.007	0.312

Note: *P<0.05.