Abstract
Objectives:
Artificial intelligence (AI) holds the promise to revolutionize the field of medicine and enhance the well-being of countless patients. Its capabilities span various areas, including disease prevention, accurate diagnosis, and the development of innovative treatments. Moreover, AI has the potential to streamline health-care delivery and lower expenses. The community should be aware of the potential applications of AI in health care, so that they can advocate for its development and adoption. Hence, the objective of this study is to assess the community’s perspectives regarding the utilization of AI in health care.
Methods:
A cross-sectional, questionnaire-based study was conducted in Saudi Arabia during the period of June to October 2023. The questionnaire was distributed to people on various social media platforms using a convenience sampling method. The collected data were analyzed using Statistical Package for the Social Sciences.
Results:
The study included 771 individuals, with 42.5% having a positive outlook on the use of AI in health care, 31.8% having a neutral view, and 7.5% having a negative view. The only factor associated with a positive opinion was regional differences (P = 0.006). Moreover, participants who used medical apps or programs (P = 0.026), wearables (P = 0.027), felt more confident in using technology (P < 0.001), enjoyed using technology (P < 0.001), found it easier to familiarize themselves with new devices or programs (P < 0.001), and had more knowledge about AI (P < 0.001) had more positive opinions regarding the use of AI in health care.
Conclusions:
The study found that most Saudis, especially those who were familiar with the use of technology, support the use of AI in health care, with a positive or neutral view. Yet, targeted campaigns in certain regions are needed to educate the entire community about AI’s potential benefits.
Keywords: Artificial intelligence, health care, medical technology, public opinion, Saudi Arabia
Résumé
Objectifs:
L’intelligence artificielle (IA) promet de révolutionner le domaine de la médecine et d’améliorer le bien-être d’innombrables patients. Ses capacités couvrent divers domaines, notamment la prévention des maladies, le diagnostic précis et le développement de traitements novateurs. En outre, l’IA a le potentiel de rationaliser la prestation de soins de santé et de réduire les dépenses. La communauté devrait être consciente des applications potentielles de l’IA dans les soins de santé, afin qu’elle puisse promouvoir son développement et son adoption. Par conséquent, l’objectif de cette étude est d’évaluer les perspectives de la communauté concernant l’utilisation de l’IA dans les soins de santé.
Méthodes:
Une étude transversale, fondée sur des questionnaires, a été menée en Arabie Saoudite entre juin et octobre 2023. Le questionnaire a été distribué à des personnes sur diverses plateformes de médias sociaux en utilisant une méthode d’échantillonnage de commodité. Les données recueillies ont été analysées à l’aide du package statistique pour les sciences sociales.
Résultats:
771 personnes ont participé à l’étude, dont 42,5 % avaient un point de vue positif sur l’utilisation de l’IA dans les soins de santé, 31,8 % étaient neutres et 7,5 % étaient négatifs. Le seul facteur associé à une opinion positive était les différences régionales (P = 0,006). En outre, les participants qui utilisaient des applications ou des programmes médicaux (P = 0,026), des appareils portatifs (P = 0,027), se sentaient plus confiants dans l’utilisation de la technologie (P < 0,001), particulièrement en utilisant la technique (P < 0,001), ont trouvé qu’il était plus facile de se familiariser avec les nouveaux dispositifs ou programmes (P < 0,001), et avaient plus de connaissances sur l’IA (P > 0,001).
Conclusions:
L’étude a révélé que la plupart des Saoudiens, en particulier ceux qui étaient familiers avec l’utilisation de la technologie, soutiennent l’emploi de l’IA dans les soins de santé, avec un point de vue positif ou neutre. Néanmoins, des campagnes ciblées dans certaines régions sont nécessaires pour éduquer l’ensemble de la communauté sur les avantages potentiels de l’IA.
Mots-clés: Intelligence artificielle, soins de santé, technologie médicale, opinion publique, Arabie saoudite
INTRODUCTION
Artificial intelligence (AI) refers to computers’ capacity to do activities that humans normally equate with intellect. It has the potential to transform medicine and benefit millions of patients.[1] AI-powered systems may be divided into four categories: systems that think like humans, systems that behave like humans, systems that think rationally, and systems that act rationally.[2]
AI applications in medicine use enormous amounts of clinical data and computational power to inform evidence-based decision-making.[1] AI’s potential uses in medicine include illness prevention, diagnosis, and therapy. Specialties that rely on medical imaging data interpretation, such as dermatology and pathology (identifying cancerous skin lesions), radiology (interpreting chest radiographs and detecting cancer in mammograms, analyzing computer tomography scans, and identifying brain tumors on magnetic resonance images), and polyp detection from colonoscopy, have a particular scientific and economic focus.[3,4] This list, however, is not exhaustive and simply highlights significant areas of AI use.
Despite the potential benefits of AI, algorithms may have flaws such as inapplicability outside of the training area, bias, and brittleness (a proclivity to be easily misled). Even if a very successful algorithm overcomes these obstacles, there remain significant human hurdles to adoption.[4] To date, the full promise of AI in health care has not been realized, with just a few instances of clinical and financial improvements resulting from real-world usage of AI algorithms in clinical practice. The fast growth of AI’s applications in health care made it necessary to create guidelines for its utilization. These regulatory frameworks minimize the possible harm associated with the use of AI in health care.[5]
In a study conducted on German patients, only one from each four participants demonstrated good knowledge of the use of AI in health care.[6] Moreover, a systematic review of 38 studies assessing health-care student’s (for example, those who study medicine, ophthalmology, dermatology, dentistry, radiology, or medical physics) knowledge concluded that students in half of these studies possess poor knowledge.[7] In Saudi Arabia, a study in Riyadh suggests good knowledge and awareness among pharmacy students regarding the use of AI in health care.[8] Another study suggests a decent level of knowledge among the Saudi radiology staff.[9] Nonetheless, in another study, inadequate knowledge was found among the Saudi health-care staff regarding AI.[10] Unfortunately, no efforts were put into assessing the public perception of the use of AI in health care in Saudi Arabia. Hence, this study aims to evaluate the community view on the use of AI in health care.
METHODS
Study design
A cross-sectional study was undertaken during the period of June to October 2023, involving the five major regions of Saudi Arabia. This study utilizes a prevalidated questionnaire to assess the perspectives of the community toward the utilization of AI in the health-care system.[6]
Study population and sample size
The required sample size for this study was calculated to be 385 participants, based on the methodology proposed by Richard Geiger, with a confidence interval of 95% and a margin of error of 5%. The sample size of this study included individuals who met the specified inclusion and exclusion criteria. The inclusion criteria were all current residents of Saudi Arabia who were 18 years old or older, males or females, of all nationalities. There were no specific criteria for exclusion.
The questionnaire
The Google Forms questionnaire used in this study was derived from the research of Fritsch et al.[6] In addition, it was translated into Arabic, which is the native language of Saudi Arabia. The questionnaire was distributed in a randomized manner through various social media platforms, including Twitter, WhatsApp, Telegram, Facebook, and Instagram. The questionnaire comprised a total of 45 questions, which have been categorized into three distinct domains. The first domain involved was personal and demographic inquiry, which included residency, region, nationality, marital status, and income. This information was collected to obtain a more comprehensive understanding of the participants. The second domain, encompassing the utilization of computers and smartphones, included different aspects, application functionality, and usability challenges. The last domain focuses on the perception of different aspects of AI in health care. To assure the accuracy of the original content, a secondary translator was employed to translate the Arabic translation back into English.[11,12]
Statistical analysis
Both descriptive and inferential statistical analyses of the data were carried out. Descriptive statistics were used to summarize and describe the characteristics of the study participants and their responses. Frequencies and percentages were calculated for categorical variables, such as the participants’ responses to opinion questions. For continuous variables, medians and interquartile ranges (IQRs) were calculated and tabulated.
Regarding the 26 questions related to the opinions of AI in health care, each participant was assigned a score based on strongly agree = 5, agree = 4, neutral = 3, disagree = 2, and strongly disagree = 1. For the 10 questions that were negatively stated, the scoring was reversed. Thus, the total possible scores ranged from 26 to 130, and higher scores represented a more positive opinion regarding the use of AI in health care.
In addition, the Mann–Whitney U-test or Kruskal–Wallis test was conducted to compare the positive opinion scores among different groups, including gender, age, and usage of the Internet or computer. These nonparametric tests were chosen owing to the nonnormal distribution of the scores assessed by the Kolmogorov–Smirnov test (P < 0.05). The median opinion scores and IQRs were calculated for each group, and the P values from the Mann–Whitney U-test and Kruskal–Wallis test determined whether there were statistically significant differences in opinions among the groups.
The significance level for all statistical tests was set at P < 0.05, indicating a 95% confidence interval. All statistical calculations were performed using IBM Statistical Package for the Social Sciences version 27.0. (IBM Corp., Armonk, NY).
RESULTS
Sample characteristics
The study included 771 individuals, of which 64.2% were female and 35.8% were male. Regarding residency, 85.3% of the participants were from urban areas, while 14.7% were from rural areas. The age of the majority of the participants ranged from 20 to 29, with a median age of 23. In terms of region, the largest representation was from the Western Region (26.5%), followed by the Central Region (23.9%) and the Southern Region (24.1%). The majority of participants were Saudi nationals (92.1%). In terms of marital status, 69.5% were single, 27.1% were married, and 1.7% were either divorced or widowed. The largest occupational group was students, accounting for 62.6% of the participants, followed by employees (24.3%). A bachelor’s degree (57.3%) and secondary school (30.5%) were the two highest levels of educational attainment. Regarding household income, the majority (35.1%) reported earning more than 15,000 riyals, while 8.0% earned <2000 riyals. A significant proportion (81.6%) of the participants were not health-care professionals or health-care workers [Table 1].
Table 1.
Sociodemographic characteristics of the participants
| n (%) | |
|---|---|
| Gender | |
| Female | 495 (64.2) |
| Male | 276 (35.8) |
| Residency | |
| Rural | 113 (14.7) |
| Urban | 658 (85.3) |
| Age, median (IQR) | 23 (20–29) |
| Region | |
| Central region | 184 (23.9) |
| Eastern region | 145 (18.8) |
| Northern region | 52 (6.7) |
| Southern region | 186 (24.1) |
| Western region | 204 (26.5) |
| Nationality | |
| Non-Saudi | 61 (7.9) |
| Saudi | 710 (92.1) |
| Marital status | |
| Single | 536 (69.5) |
| Married | 209 (27.1) |
| Divorced | 13 (1.7) |
| Widowed | 13 (1.7) |
| Occupation | |
| Employee | 187 (24.3) |
| Housewife | 44 (5.7) |
| Retired | 11 (1.4) |
| Student | 483 (62.6) |
| Student and employee | 2 (0.3) |
| Unemployed | 44 (5.7) |
| Education level | |
| Bachelor | 442 (57.3) |
| Diploma | 49 (6.4) |
| Higher education or postgraduate | 33 (4.3) |
| Illiterate | 2 (0.3) |
| Intermediate school | 7 (0.9) |
| Primary school | 3 (0.4) |
| Secondary school | 235 (30.5) |
| Household income (riyals) | |
| 2000–5000 | 122 (15.8) |
| From 10,000 to 15,000 | 162 (21.0) |
| From 5000 to 10,000 | 154 (20.0) |
| <2000 | 62 (8.0) |
| >15,000 | 271 (35.1) |
| Health-care professional or health-care worker | |
| No | 629 (81.6) |
| Yes | 142 (18.4) |
IQR=Interquartile range
Knowledge/usage of technology
Table 2 presents information on the general knowledge and usage of technology among the participants. The majority of participants reported using a computer or similar electronic device on a daily basis (86.0%), while a smaller percentage used them more than three times a week (7.8%). The majority of participants (92.0%) reported daily Internet usage. Approximately half of the participants used medical apps or computer programs (50.2%) and wearables (46.0%) for monitoring health-related aspects. When it comes to confidence in using electronic devices, almost half of the participants felt confident (49.3%) or very confident (21.8%). The majority enjoyed using or working with computers and devices (77.7%). Familiarization with new devices or programs was generally easy for participants (71.2%). Regarding awareness of AI, a significant proportion had heard or read about it, with varying levels of understanding, ranging from a basic awareness (46.0%) to the ability to explain it well (20.8%). Overall, the findings indicate a high level of technology usage and a positive attitude toward technology among the participants, with notable interest in health-related applications and a reasonable awareness of AI.
Table 2.
General knowledge and usage of technology by the participants
| n (%) | |
|---|---|
| Frequency of use of computer or similar electronic device (tablet, smartphone, etc.) | |
| Never | 12 (1.6) |
| Several times per month | 18 (2.3) |
| <3 times a week | 18 (2.3) |
| >3 times a week | 60 (7.8) |
| Daily | 663 (86.0) |
| Frequency of use of Internet | |
| Never | 4 (0.5) |
| Several times per month | 17 (2.2) |
| <3 times a week | 18 (2.3) |
| >3 times a week | 23 (3.0) |
| Daily | 709 (92.0) |
| Use of apps or computer programs from the medical field, e.g., as a calorie counter, medication reminder, blood sugar documentation, pain diary, etc. | |
| No | 384 (49.8) |
| Yes | 387 (50.2) |
| Use of so-called “wearables” (e.g., Apple Watch, Garmin Vivo, Fitbit, etc.) to monitor movement, calorie consumption or sleep quality | |
| No | 416 (54.0) |
| Yes | 355 (46.0) |
| Level of confidence (skill) in using computers and other electronic devices (smartphone, tablet, etc.) | |
| Very unconfident | 39 (5.1) |
| Unconfident | 39 (5.1) |
| Neither/nor | 145 (18.8) |
| Confident | 380 (49.3) |
| Very confident | 168 (21.8) |
| Preference of using or working with computers and other devices (smartphone, tablet, etc.) | |
| Neutral | 134 (17.4) |
| Dislike | 27 (3.5) |
| Dislike very much | 11 (1.4) |
| Like | 347 (45.0) |
| Like very much | 252 (32.7) |
| Difficulty familiarizing oneself with a new device, a new program, or a new function of a device | |
| Very difficult | 7 (0.9) |
| Difficult | 64 (8.3) |
| Neither/nor | 151 (19.6) |
| Easy | 398 (51.6) |
| Very easy | 151 (19.6) |
| Encounter of the term “AI” (e.g., read or heard) | |
| No | 52 (6.7) |
| Yes, but I don't know exactly what it is | 167 (21.7) |
| Yes, and I know somehow what it is | 355 (46.0) |
| Yes, and I could explain well, what it is about | 160 (20.8) |
| Yes, and I would consider myself an expert in that field | 37 (4.8) |
AI=Artificial intelligence
Opinions regarding the usage of artificial intelligence in health care
Table 3 presents the opinions of participants regarding the use of AI in health care. Overall, the majority of participants agreed or strongly agreed that the use of AI brought benefits for patients (63.8%) and that it can reduce treatment errors in the future (44.8%). However, participants were divided on whether doctors would play a less important role in patient therapy (32.8% agreed and 42.8% disagreed) and whether doctors are becoming too dependent on computer systems (56.3% agreed and 17.4% disagreed). Concerning trust, a higher percentage expressed trust in the assessment of doctors over AI (68.5%) compared to trusting AI more (21.3%). Participants generally believed that AI should be tested by an independent body before being used on patients (75.4%). There were mixed opinions about the impact of AI on the doctor–patient relationship (45.3% agreed it impairs the relationship and 45.9% disagreed). Participants were also divided on whether AI would reduce doctors’ workload (53.1% agreed and 16.9% disagreed). Overall, the findings suggested a varied range of opinions regarding the use of AI in health care, with participants acknowledging potential benefits when expressing concerns about the role of doctors, treatment decision-making, and the impact on the doctor–patient relationship.
Table 3.
Opinion of participants regarding use of artificial intelligence in health care
| Strongly disagree, n (%) | Disagree, n (%) | Neutral, n (%) | Agree, n (%) | Strongly agree, n (%) | |
|---|---|---|---|---|---|
| I think that the use of AI brings benefits for the patient | 41 (5.3) | 46 (6.0) | 192 (24.9) | 354 (45.9) | 138 (17.9) |
| Doctors will play a less important role in the therapy of patients in the future | 150 (19.5) | 179 (23.2) | 189 (24.5) | 199 (25.8) | 54 (7.0) |
| Through the use of AI, there will be less treatment errors in the future | 57 (7.4) | 99 (12.8) | 270 (35.0) | 261 (33.9) | 84 (10.9) |
| AI should not be used in medicine as a matter of principle | 56 (7.3) | 91 (11.8) | 225 (29.2) | 241 (31.3) | 158 (20.5) |
| Doctors are becoming too dependent on computer systems | 41 (5.3) | 95 (12.3) | 201 (26.1) | 313 (40.6) | 121 (15.7) |
| The testing of AI before it is used on patients should be carried out by an independent body (e.g., such as the government, ministry of health, or similar) | 42 (5.4) | 34 (4.4) | 113 (14.7) | 237 (30.7) | 345 (44.7) |
| I would trust the assessment of an AI more than the assessment of a doctor | 148 (19.2) | 217 (28.1) | 242 (31.4) | 125 (16.2) | 39 (5.1) |
| Doctors know too little about AI to use it on patients | 71 (9.2) | 131 (17.0) | 315 (40.9) | 191 (24.8) | 63 (8.2) |
| If a patient has been harmed, a doctor should be held responsible for not following the recommendations of AI | 119 (15.4) | 156 (20.2) | 263 (34.1) | 173 (22.4) | 60 (7.8) |
| The influence of AI on medical treatment scares me | 74 (9.6) | 126 (16.3) | 269 (34.9) | 220 (28.5) | 82 (10.6) |
| The use of AI prevents doctors from learning to make their own correct judgement of the patient | 82 (10.6) | 112 (14.5) | 285 (37.0) | 215 (27.9) | 77 (10.0) |
| If AI predicts a low chance of survival for the patient, doctors will not fight for that patient's life as much as before | 156 (20.2) | 135 (17.5) | 238 (30.9) | 183 (23.7) | 59 (7.7) |
| The use of AI is changing the demands of the medical profession | 62 (8.0) | 101 (13.1) | 248 (32.2) | 265 (34.4) | 95 (12.3) |
| I would like my personal, medical treatment to be supported by AI | 104 (13.5) | 142 (18.4) | 284 (36.8) | 187 (24.3) | 54 (7.0) |
| I would make my anonymous patient data available for noncommercial research (universities, hospitals, etc.) if this could improve future patient care | 92 (11.9) | 70 (9.1) | 197 (25.6) | 247 (32.0) | 165 (21.4) |
| AI-based decision support systems for doctors should only be used for patient care if their benefit has been scientifically proven | 52 (6.7) | 73 (9.5) | 261 (33.9) | 276 (35.8) | 109 (14.1) |
| I am more afraid of a technical malfunction of AI than of a wrong decision by a doctor | 60 (7.8) | 79 (10.2) | 244 (31.6) | 261 (33.9) | 127 (16.5) |
| I am not worried about the security of my data | 131 (17.0) | 131 (17.0) | 225 (29.2) | 214 (27.8) | 70 (9.1) |
| By using AI, doctors will again have more time for the patient | 71 (9.2) | 110 (14.3) | 284 (36.8) | 228 (29.6) | 78 (10.1) |
| A doctor should always have the final control over diagnosis and therapy | 47 (6.1) | 45 (5.8) | 161 (20.9) | 228 (29.6) | 290 (37.6) |
| I am worried that AI-based systems could be manipulated from the outside (terrorists, hackers,...) | 56 (7.3) | 92 (11.9) | 220 (28.5) | 236 (30.6) | 167 (21.7) |
| The use of AI impairs the doctor-patient relationship | 59 (7.7) | 107 (13.9) | 256 (33.2) | 218 (28.3) | 131 (17.0) |
| The use of AI is an effective instrument against the overload of doctors and the shortage of doctors | 49 (6.4) | 81 (10.5) | 255 (33.1) | 287 (37.2) | 99 (12.8) |
| I would like my doctor to override the recommendations of AI if he comes to a different conclusion based on his experience or knowledge | 40 (5.2) | 74 (9.6) | 235 (30.5) | 270 (35.0) | 152 (19.7) |
| The use of AI will reduce the workload of doctors | 56 (7.3) | 74 (9.6) | 223 (28.9) | 297 (38.5) | 121 (15.7) |
AI=Artificial intelligence
Overall, the majority of participants expressed a positive or neutral view toward AI in medicine. Specifically, 42.5% of participants had a positive outlook, considering it beneficial for health care. In addition, 31.8% expressed a neutral stance toward AI in medicine. Conversely, a smaller percentage of participants held negative opinions, with 7.5% having a negative view and 1.6% holding a very negative view. A notable proportion of participants (16.6%) expressed a very positive outlook on the use of AI in health care [Table 4].
Table 4.
Overall view of participants regarding use of artificial intelligence in health care
| Taken all together: How positive or negative do they feel about the use of AI in medicine? | n (%) |
|---|---|
| Very negative | 12 (1.6) |
| Negative | 58 (7.5) |
| Neutral | 245 (31.8) |
| Positive | 328 (42.5) |
| Very positive | 128 (16.6) |
AI=Artificial intelligence
Factors affecting opinions of artificial intelligence use in health care
The overall median positive opinion score was 81.00, with an IQR of 77.00–86.00. The analysis found no significant associations between a positive opinion and gender (P = 0.439), residency (P = 0.316), nationality (P = 0.474), marital status (P = 0.776), occupation (P = 0.762), education level (P = 0.178), household income (P = 0.258), and being a health-care professional or health-care worker (P = 0.295). However, regional differences were observed, with participants from the Northern Region having the highest median positive opinion score of 84.00, followed by the Southern Region (82.50). Participants from the Central Region had a median score of 80.00, which was significantly lower compared to the other regions (P = 0.006). In summary, while most sociodemographic factors did not show a significant association with a positive opinion of AI in health care, regional differences indicated the influence of geographical location on participants’ perceptions [Table 5].
Table 5.
Association of positive opinion of use of artificial intelligence with sociodemographic factors
| Positive opinion score (total=130) |
||||
|---|---|---|---|---|
| Median | IQR | P K,U | ||
| Overall | 81.00 | 77.00–86.00 | - | |
| Gender | ||||
| Female | 81.00 | 77.00–85.00 | 0.439 | |
| Male | 82.00 | 76.50–86.00 | ||
| Residency | ||||
| Rural | 83.00 | 77.00–86.00 | 0.316 | |
| Urban | 81.00 | 77.00–85.00 | ||
| Region | ||||
| Central region | 80.00 | 75.00–85.00 | 0.006* | |
| Eastern region | 80.00 | 75.00–85.00 | ||
| Northern region | 84.00 | 80.50–87.00 | ||
| Southern region | 82.50 | 78.00–86.00 | ||
| Western region | 81.00 | 77.00–85.00 | ||
| Nationality | ||||
| Non-Saudi | 82.00 | 77.00–86.00 | 0.474 | |
| Saudi | 81.00 | 77.00–85.00 | ||
| Marital status | ||||
| Divorced | 84.00 | 78.00–84.00 | 0.776 | |
| Married | 81.00 | 77.00–85.00 | ||
| Single | 81.00 | 76.00–86.00 | ||
| Widowed | 78.00 | 77.00–80.00 | ||
| Occupation | ||||
| Employee | 82.00 | 77.00–86.00 | 0.762 | |
| Housewife | 81.00 | 78.00–84.00 | ||
| Retired | 78.00 | 72.00–87.00 | ||
| Student | 81.00 | 77.00–86.00 | ||
| Student and employee | 83.50 | 83.00–84.00 | ||
| Unemployed | 80.50 | 76.00–84.00 | ||
| Education level | ||||
| Bachelor | 81.00 | 77.00–86.00 | 0.178 | |
| Diploma | 80.00 | 74.00–84.00 | ||
| Higher education or postgraduate | 82.00 | 77.00–87.00 | ||
| Illiterate | 76.50 | 75.00–78.00 | ||
| Intermediate school | 75.00 | 72.00–82.00 | ||
| Primary school | 78.00 | 66.00–84.00 | ||
| Secondary school | 81.00 | 77.00–86.00 | ||
| Household income (riyals) | ||||
| 2000–5000 | 80.00 | 75.00–85.00 | 0.258 | |
| From 10,000 to 15,000 | 80.50 | 77.00–85.00 | ||
| From 5000 to 10,000 | 81.00 | 76.00–85.00 | ||
| <2000 | 82.00 | 77.00–88.00 | ||
| >15,000 | 82.00 | 76.00–86.00 | ||
| Health-care professional, or health-care worker? | ||||
| No | 81.00 | 77.00–85.00 | 0.295 | |
| Yes | 82.50 | 77.00–86.00 | ||
KIndependent samples Kruskal–Wallis test, UIndependent samples Mann–Whitney U-test, *P<0.05, Significant. IQR=Interquartile range
The participants’ positive opinion scores were also assessed based on their frequency of using electronic devices, Internet usage, use of medical apps or programs, use of wearables, confidence in using technology, liking for using technology, ease of familiarizing themselves with new devices or programs, and their knowledge of AI. The analysis found that participants who used medical apps or programs (P = 0.026) and wearables (P = 0.027) had significantly higher positive opinion scores compared to those who did not use them. Furthermore, there was a significant association between confidence in using technology and positive opinion scores (P < 0.001), with participants who felt more confident or very confident having higher positive opinion scores. Similar findings were observed regarding participants’ liking for using technology (P < 0.001) and the ease of familiarizing themselves with new devices or programs (P < 0.001). In addition, participants who had more knowledge about AI displayed higher positive opinion scores (P < 0.001). However, no significant associations were found between positive opinion scores and the frequency of using electronic devices or the Internet. In summary, participants who used medical apps or programs, wearables, felt more confident in using technology, enjoyed using technology, found it easier to familiarize themselves with new devices or programs, and had more knowledge about AI had more positive opinions regarding the use of AI in health care [Table 6].
Table 6.
Association of positive opinion of use of artificial intelligence with The familiarization of participants with techonology
| Positive opinion score (total=130) |
|||
|---|---|---|---|
| Median | IQR | P K,U | |
| Frequency of use of computer or similar electronic device (tablet, smartphone, etc.) | |||
| Never | 79.00 | 75.00–82.50 | 0.579 |
| <3 times a week | 80.00 | 77.00–85.00 | |
| >3 times a week | 83.00 | 78.00–85.00 | |
| Several times per month | 83.50 | 76.00–87.00 | |
| Daily | 81.00 | 77.00–86.00 | |
| Frequency of use of Internet | |||
| Never | 78.00 | 73.00–81.00 | 0.642 |
| <3 times a week | 83.00 | 80.00–86.00 | |
| >3 times a week | 82.00 | 76.00–87.00 | |
| Several times per month | 82.00 | 77.00–85.00 | |
| Daily | 81.00 | 77.00–86.00 | |
| Use of apps or computer programs from the medical field, e.g., as a calorie counter, medication reminder, blood sugar documentation, pain diary, etc. | |||
| No | 80.00 | 76.00–85.00 | 0.026* |
| Yes | 82.00 | 77.00–86.00 | |
| Use of so-called “wearables” (e.g., Apple Watch, Garmin Vivo, Fitbit, etc.) to monitor movement, calorie consumption or sleep quality | |||
| No | 80.00 | 76.00–85.00 | 0.027* |
| Yes | 82.00 | 77.00–86.00 | |
| Level of confidence (skill) in using computers and other electronic devices (smartphone, tablet, etc.) | |||
| Very unconfident | 77.00 | 72.00–82.00 | <0.001* |
| Unconfident | 79.00 | 76.00–83.00 | |
| Neither/nor | 78.00 | 74.00–84.00 | |
| Confident | 82.00 | 77.50–86.00 | |
| Very confident | 83.50 | 77.50–88.50 | |
| Preference of using or working with computers and other devices (smartphone, tablet, etc.) | |||
| Dislike very much | 78.00 | 70.00–81.00 | <0.001* |
| Dislike | 80.00 | 72.00–86.00 | |
| Neutral | 78.00 | 74.00–82.00 | |
| Like | 82.00 | 77.00–85.00 | |
| Like very much | 83.00 | 78.00–90.00 | |
| Difficulty familiarizing oneself with a new device, a new program, or a new function of a device | |||
| Very difficult | 77.00 | 72.00–85.00 | <0.001* |
| Difficult | 78.00 | 71.50–82.50 | |
| Neither/nor | 78.00 | 76.00–84.00 | |
| Easy | 83.00 | 77.00–86.00 | |
| Very easy | 83.00 | 77.00–89.00 | |
| Encounter of the term “AI” (e.g., read or heard) | |||
| No | 80.00 | 75.50–84.00 | <0.001* |
| Yes, but I don't know exactly what it is | 79.00 | 74.00–85.00 | |
| Yes, and I know somehow what it is | 81.00 | 77.00–86.00 | |
| Yes, and I could explain well, what it is about | 83.50 | 78.00–88.00 | |
| Yes, and I would consider myself an expert in that field | 84.00 | 78.00–90.00 | |
KIndependent samples Kruskal–Wallis test, UIndependent samples Mann–Whitney U-test, *P<0.05, Significant. AI=Artificial intelligence, IQR=Interquartile range
DISCUSSION
The current study sought to evaluate the participants’ knowledge and usage of technology as well as their perceptions and views regarding the implementation of AI in health care. Our research reveals widespread daily use of smart devices and the Internet across social and geographic borders. This reflects the rapid advancements and accessibility of these technologies.[13,14] The literature revealed that as of the beginning of Q4 2023, approximately 5.30 billion people worldwide were using the Internet.[15] The high rate of using technologies recently in the health-care field among the population may be noticeably augmented after the COVID-19 pandemic, which forced the whole world to use technologies for receiving health care among nonemergency patients due to lockdowns and the avoidance of catching infection through visiting health-care settings.[16,17,18]
Regarding the participants’ knowledge, less than half of the respondents merely knew somehow what AI meant (46.0%), and fewer did not know what AI exactly was (21.7%), which was in line with previous findings for Germans and other populations.[6,19,20] This can be explained by the fact that the concept of AI is still abstract and evolving, potentially making it hard for some respondents to grasp its full breadth and significance.
As for the opinions of participants regarding the use of AI in health care, the study showed that more than half of them showed positive attitudes and perceptions. Similarly, a systematic review assessed 23 studies and concluded that patients and the public generally had a positive view toward AI use, but they also expressed concerns and preferred human supervision.[21] Two other recent studies asked patients and the public what they thought about AI being used in health care in general. Both found that people were uncertain about AI, knowing that it could have both good and bad effects.[1,22] On the other hand, in the USA, it was found that 60% of adults in the United States would feel uneasy if their health-care provider used AI to diagnose illnesses and suggest treatments. Furthermore, only 39% of participants reported feeling comfortable with this idea.[23] Another study showed controversial perceptions where the participants had high hopes for improvements in hospital administration, health-care quality, patient experience, and positive changes in roles and relationships.[24]
Our results demonstrated that most sociodemographic factors did not exhibit a significant connection with a positive view of AI in health care. Interestingly, regional variations showed that participants’ perspectives were influenced by their location, potentially due to variations in educational opportunities and knowledge levels about AI across regions. Moreover, AI acceptance was even more strongly influenced by the technical affinity. Logically, individuals with technical affinity tend to have a better understanding of how AI works and its potential benefits. Thus, they are more acceptable and optimistic about its use and advancement. These influencing factors are consistent with several past investigations.[6,25,26,27] On the other hand, numerous studies emphasize the influence of sociodemographic variables within a developed society on access to new digital technologies.[25,26,28,29] One project found that older patients, women, and participants with lower education and technical affinity were more cautious on health-care-related AI usage.[6] This also was reported by another article as higher scores were reported among women and low-educated participants.[30] Comparative research must be conducted to understand how different cultural contexts and health systems influence nations’ views on AI in health care.
We recommend launching initiatives, especially in certain regions, to educate the public about AI in health care, its benefits, and limitations, and how it may impact their care. In addition, community involvement in developing and monitoring these frameworks is essential to foster trust and address concerns.
The current study has a few difficulties and limitations. These include using a self-reported online survey, an uneven distribution of participants from various Saudi provinces, and convenience sampling as a data collection method. Hence, the results may not be generalizable to Saudi Arabia’s entire population. Despite these limitations, this study in Saudi Arabia is the first to assess public opinion, perception, and understanding of the use of AI in health care. As such, it can serve as a benchmark for additional studies.
CONCLUSIONS
The study determined that the Saudi community views the use of AI in health care positively and holds favorable opinions toward it. Our findings indicate a strong inclination toward technology and an optimistic outlook on its potential, particularly in health-related applications. In addition, most participants expressed positive or neutral sentiments regarding AI in medicine. However, education and training are necessary to address any concerns associated with the adoption of new technologies and to ensure the successful integration of clinical AI.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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