Perceptions of uncertainty in medical care among non-medical citizens and nurses in Japan: A cross- sectional internet-based survey

doi:10.21203/rs.3.rs-3401803/v1

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Perceptions of uncertainty in medical care among non-medical citizens and nurses in Japan: A cross- sectional internet-based survey

https://doi.org/10.21203/rs.3.rs-3401803/v1

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Background

Patient safety impacts not only patients and their relatives but also patients’ health outcomes and lives. While medical care providers make efforts to prevent medical accidents, medical care is inherently characterized by uncertainty in its processes and outcomes. This study aimed to compare tolerance of uncertainty in medical care between non-medical citizens and nurses.

Methods

We conducted a cross-sectional internet-based survey. Participants included 2,100 individuals (600 nurses and 1,500 non-medical citizens) from different parts of Japan, aged 20 years and above. Of these, we excluded 70 participants who were classified as non-medical citizens but were registered nurses. Finally, we analyzed data from 2,030 participants (600 nurses and 1,430 non-medical citizens). Three registered nurses and nursing researchers developed an original questionnaire on tolerance of uncertainty in medical care. Data regarding participants’ characteristics (age, sex, education level, marital status, having children, population size of the residential area, medical care usage, and occupation) were obtained. We conducted a one-way analysis of variance to compare data from non-medical citizens and nurses and used a multiple regression model to investigate the factors related to the scores of tolerance of uncertainty in medical care.

Results

A high percentage of participants were aged 40−50 years (n = 745, 36.7%); the sample mostly consisted of female participants (n = 1,210, 59.6%) and had a higher percentage of medical care users (n = 1,309, 64.5%). Non-medical citizens were found to be less tolerant of uncertainty than nurses, and uncertainty scores were associated with medical care usage, occupation, and population size of the residential area.

Conclusions

Our results indicated differences in the perceptions of uncertainty in medical care between non-medical citizens and medical care providers. To reduce conflicts related to medical issues, medical care providers need to improve citizen education regarding perceptions of uncertainty in medical care.

uncertainty

tolerance

medical care

nurse

citizen

Medical accident victims often experience feelings of frustration and anger after such accidents [1]. Meanwhile, medical staff experience fear concerning malpractice, which is associated with burnout; thus, they are secondary victims of medical accidents [2, 3]. Conflicts related to medical accidents between patients and medical staff cause frustration to both parties.

Medical personnel provide medical care and support to patients to the best of their abilities and try to prevent casualties and medical accidents. However, medical personnel are also subject to human factors, such as memory illusions and slips, and they may make errors in their practice [4]. Human factors therefore play a role in the occurrence of medical accidents. Thus, medical practitioners should consider developing a systemic approach to accident prevention instead of relying solely on a human approach dependent on individual effort and ability [5–7].

Medical care is impacted by uncertainty caused by various factors. Han et al. reviewed articles from diverse fields, such as decision science, psychology, communication, engineering, and health services, and clarified that scientific uncertainty encompasses uncertainties about diagnosis, prognosis, causal explanations, and treatment recommendations [8, 9]. Practical uncertainty applies to the structures and processes of care, the competence of one’s physicians, and the rules and procedures of institutions [8, 9]. Mackintosh et al. reported that conceptual uncertainty in health care is related to moral and normative dimensions, such as patients’ experiences of diseases or their culture and social practices [10]. In particular, five factors leading to uncertainty have been identified: patients’ biological variability, patient and physician bias, error in test interpretation, differing values and opinion of patients and physicians, and uncertainty surrounding decision-making [11]. One of the reasons physicians and patients disagree on treatment issues is their divergent views on treatment goals. As goals change over the course of treatment, the physician must communicate these changes to the patient [12, 13]. Based on the medical staff’s responses and communication, patients often feel that the staff lack empathy and do not provide sufficient information, leading to complaints; concerns related to medicines, examinations, and treatment are among some concrete examples [14].

The Joint Commission, an organization dedicated to global health equity, launched the Speak Up™ program, encouraging patients to play an active role in preventing health care errors by becoming involved and informed in health care processes related to medication, treatment, and examinations [15]. Indeed, the World Health Organization emphasizes that engaging patients and families in health care is equally important worldwide [16]. However, it has not been confirmed whether a gap exists in the perceptions and awareness regarding medical care between medical professionals and the public that could lead to complaints and medical litigations. Therefore, this study aimed to compare the tolerance of uncertainty in medical care between non-medical citizens and nurses through an online cross-sectional survey.

Participants

We developed a cross-sectional internet survey for citizens and nurses, aged 20 years and above. Members of the survey company who met this study’s eligibility criteria were provided the document explaining this survey’s purpose—that is, to compare tolerance of uncertainty in medical care between non-medical citizens and nurses. Those who read the document and expressed interest were included in the study.

Eligibility criteria

The study participants were nurses and non-medical citizens from different parts of Japan, aged 20 years and above. Additionally, access to a computer or another device with an internet connection was mandatory. Moreover, they had to be registered monitors of the internet survey company.

Study setting

We conducted an internet-based cross-sectional survey using the platform of an internet survey company that maintains a database of over 3 million people. The recruitment and survey period lasted two weeks in March 2023.

Ethical considerations

This study was approved by the ethics committee at the Gifu University of Health Sciences (approval number: 2022_19). We outsourced the internet survey administration to an online research company, which contacted the survey monitors and collected the study data. The purpose of the survey was shown at the beginning of the questionnaire, and only those who agreed with this study were allowed to proceed to the questions. The data were anonymized by the company and subsequently sent to the researchers.

Measures

The survey tool included questions about participants characteristics, such as age, sex, education level, marital status, having children, medical care use as inpatient or outpatient at a medical institution, population size of residential area, occupation, and their perceptions of uncertainty in health care.

Participants were aged 20 years and above and split into three categories based on their age: 20−39 years, 40−59 years, and 60 years and above. Education levels were classified as university/graduate school, vocational school/junior college, and junior high school/high school; junior colleges included two- or three-year courses. Marital status was categorized as married, which included divorced and death of spouse, or unmarried. Child status was categorized as without children and having children, which included those children living with the participant and those not. The population size of residential area was categorized as follows: capital, including 23 wards of Tokyo or ordinance-designated cities with a population of 500,000 people or more; city, with a population of 200,000 people or more; middle city, with a population of 100,000 people or more; town, with a population of less than 100,000 people; and small town, with a population of less than 10,000 people. Regarding hospitalization or medical institution visit status, binary variables were used; the participant answered “Yes” if they were currently an inpatient or outpatient at a medical institution (designated “medical care user”) and “No” if they were not. Occupations were classified into two: nurses or non-medical citizen. In addition, occupations details included six categories: nurses, office workers (company workers and civil servant workers), self-employed (farmers, fishermen, and owners), housewives and students, unemployed, and others.

Questions about perceptions of uncertainty in health care were as follows: “Do you think that the saying ‘humans make mistakes’ applies to medical professionals as well?” (Q1); “Do you think that doctors may not be able to make a diagnosis in one visit?” (Q2); “Do you think that there are individual differences in how the effects of treatments and drugs appear?” (Q3); “Do you think that some people will have severe side effects even if they take the same medicine, while others will not?” (Q4); “Do you think that sudden deterioration (sudden worsening of the condition) or death that medical professionals cannot predict will occur?” (Q5); and “What do you think is the probability of neuropathy (numbness, sensation, movement abnormalities, etc.) from blood collection?” (Q6). The responses to Q1 through Q5 were rated on a 7-point Likert scale (absolutely agree: 1; absolutely disagree: 7); Q3 and Q5 were reverse-scored. Higher scores indicated lower tolerance of uncertainty in health care, and vice versa.

Item Q6 specifically indicated the probability of neuropathy due to blood sampling through 7 options: 1 in 100 chances of developing neuropathy; 1 in 1,000; 1 in 100,000; 1 in 1,000,000; 1 in 10,000,000; 1 in 100,000,000; and no chance of developing neuropathy.

This original questionnaire was created by three nurse researchers based on previous research on uncertainty in health care. A pre-study was conducted with five people (including registered nurses and non-medical citizens) to test the questionnaire. Based on their feedback, we revised the survey sheet so that it could be more easily understood by the respondents. The questionnaire consisted of a total of 25 questions. The participants answered all questions within 5 to 10 minutes.

Sample size

The participants were randomly sampled from among the monitors of the internet survey company stratified according to age, sex groups (in similar proportions), and residential area. Regarding residential area, the number of participants to be selected from the monitors was determined according to the population composition ratio of the prefecture. The internet survey company sent a questionnaire to all participants and collected the questionnaire until the target number of responses was reached. To allow a 6.5% margin error with a 95% confidence level and assume the population composition published by the Statistics Bureau of the Ministry of Internal Affairs and Communications [17], 228 participants were required for each category constructed by age and sex. The target number of participants was set at 1430, allowing for invalid responses. For the nurses, the sex ratio of Japanese nurses was biased—with the percentage of female and male nurses being 91.9% and 8.1%, respectively [18]. Therefore, nurses were randomly sampled stratified according to age. Similarly, 228 participants were calculated for 40–59 years and fewer participants with a wider margin were set for the remaining age categories owing to lack of nurses based on a survey of employed nurses by age group in 2020 [18]. The target number of nurses was set at 600, considering that it was unlikely that medical professionals would give invalid answers.

Analysis

Data were analyzed using t-tests and chi-square tests to compare the scores on the awareness of uncertainty in medical care questionnaire between non-medical citizens and nurses. We estimated regression coefficients using a multiple regression model. In the model, the medical uncertainty scores of items Q1−Q6 served as the dependent continuous variables, while age, sex, education level, marital status, child status, population size of residential area, medical care user, and occupations were all independent categorical variables. All statistical analyses were performed using SAS software version 9.4 (SAS Institute, Cary, NC) and Stata version 11.0 (Light Stone Inc., TX, USA).

Participants’ flowchart

The data were collected from a total of 2,100 participants, including non-medical citizens (n = 1,500) and nurses who currently work in medical institutions (n = 600). We excluded 70 participants who were classified as non-medical citizens but were medically licensed. Finally, we analyzed data from 2,030 participants (non-medical citizens: 1,430; nurses: 600). The flowchart of the participants is presented in Fig. 1.

Study characteristics

Table 1 shows the characteristics of the participants from both groups. A high percentage of all participants were aged 40–59 years (n = 745, 36.7%), female (n = 1210, 59.6%), and had completed university/graduate school (n = 825, 40.6%).

Table 1

Participant characteristics: non-medical citizens and nurses
	All	Non-medical citizens	Nurses	P value
		n = 1,430	n = 600
Age (years)
20–39	670 (33.0)	470 (32.9)	200 (33.3)	<0.001
40–59	745 (36.7)	474 (33.1)	271 (45.2)
60 and above	615 (30.3)	486 (34.0)	129 (21.5)
Sex
Male	820 (40.4)	725 (50.7)	95 (15.8)	<0.001
Female	1210 (59.6)	705 (49.3)	505 (84.2)
Education level
University/graduate school	825 (40.6)	664 (46.4)	161 (26.8)	<0.001
Vocational school/junior college	726 (35.8)	295 (20.6)	431 (71.8)
Junior high school/high school	479 (23.6)	471 (33.0)	8 (1.4)
Marital status
Unmarried	698 (34.4)	535 (37.4)	163 (27.2)	<0.001
Married	1332 (65.6)	895 (62.6)	437 (72.8)
Child status
Without children	970 (47.8)	732 (51.2)	238 (39.7)	<0.001
Having children	1060 (52.2)	698 (48.8)	362 (60.3)
Population size in the living area
Capital	706 (34.8)	509 (35.6)	197 (32.8)	0.114
City	472 (23.3)	323 (22.6)	149 (24.8)
Middle city	332 (16.4)	245 (17.1)	87 (14.5)
Town	410 (20.2)	272 (19.0)	138 (23.0)
Small town	110 (5.4)	81 (5.7)	29 (4.8)
Medical care user
Yes	721 (35.5)	501 (35.0)	220 (36.7)	0.483
No	1309 (64.5)	929 (65.0)	380 (63.3)
Occupation details
Nurses	600 (29.6)	-	600 (100.0)	-
Office workers	599 (29.5)	599(41.9)	-
Self-employed	72(3.5)	72(5.0)	-
Housewives and Students	247(12.2)	247(17.3)	-
Unemployed	254 (12.5)	254(17.8)	-
Others	258 (12.7)	258(18.0)	-
Numbers shown (%). Results based on chi-square test

A high percentage of nurses were aged 40−59 years (n = 271, 45.2%), which was higher than the percentage of non-medical citizens aged 40−59 years (n = 474, 33.1%). Regarding sex, nurses were mostly female (n = 505, 84.2%,), compared with the percentage of women among non-medical citizens (n = 705, 49.3%). Vocational school/junior college was the most highly reported education level by nurses (n = 431, 71.8%), whereas university/graduate school was the highest level reported by non-medical citizens. Regarding marital status, most nurses were married (unmarried: 27.2%, married: 72.8%), and a similar trend was observed among non-medical citizens (unmarried: 37.4%, married: 62.6%). The percentage of those with children was higher among nurses (having children: 60.3%) and lower among non-citizens (having children: 37.4%). The population sizes of residential area did not differ between non-medical citizens and nurses; the capital category had the highest percentage, reported by approximately 34.8% (n = 706) of the participants. The most common response for medical user was “No” (n = 1,309, 64.5%).

Scores on the perceptions of uncertainty in medical care and comparisons between non-medical citizens and nurses are presented in Fig. 2. All the means of non-medical citizens were higher than those of nurses (p < 0.01 for Q1-Q6).

Tables 2 and 3 present the perception of uncertainty scores from the multiple regression model. These present comparisons between the various characteristics of non-medical citizens and nurses. The scores of all the questions were associated with ages 20–39 years and occupations. Ages 20–39 years and occupation among non-medical citizens were strongly positively associated with Q1-Q6 (Ages 20–39 years: Q1 coef.=0.174, p = 0.045; Q2 coef.=0.209, p = 0.002; Q3 coef.=0.201, p = 0.015, Q4 coef.=0.185, p = 0.008; Q5 coef.=0.272, p = 0.002; Q6 coef.=0.260, p = 0.004, non-medical citizens, Q1 coef.=1.227, p < 0.001; Q2 coef.=0.662, p < 0.001; Q3 coef.=0.314, p < 0.001; Q4 coef.=0.417, p < 0.001; Q5 coef.=0.650, p < 0.001; Q6 coef.=0.393, p < 0.001). Small towns (a population size of residential area) were positively associated with all questions (Q1 coef.=0.573, p < 0.001; Q2 coef.=0.775, p < 0.001; Q4 coef.=0.952, p < 0.001; Q5 coef.=0.520, p = 0.001; Q6 coef.=0.057, p = 0.001) except Q3. Meanwhile, being a medical care user was negatively associated with all questions (Q1 coef.=-0.187, p = 0.014; Q2 coef.=-0.241, p < 0.001; Q4 coef.=-0.291, p < 0.001; Q5 coef.=-0.195, p = 0.010; Q6 coef.=-0.313, p < 0.001) except Q3.

Table 2

Multiple regression analysis of the scores on perceptions of medical uncertainty (items Q1−Q3)
	Q1		Q2		Q3
	Coef.	P value	Coef.	P value	Coef.	P value
Age (ref.=40–59 years)
20–39	0.174	0.045	0.209	0.002	0.201	0.015
60 and above	0.104	0.252	-0.060	0.401	-0.116	0.179
Sex (ref.=Female)
Male	-0.332	< 0.001	-0.109	0.071	-0.069	0.346
Education level (ref.=University/graduate school)
Vocational school/junior college	0.043	0.631	-0.003	0.963	0.063	0.459
Junior high school/high school	0.337	< 0.001	0.135	0.064	0.008	0.932
Marital status (ref.=Married)
Unmarried	-0.060	0.585	0.034	0.698	0.093	0.392
Child status (ref.=Having children)
Without children	-0.157	0.131	-0.099	0.222	-0.256	0.010
Population size in the living area (ref.=Capital)
City	-0.028	0.765	0.021	0.774	0.093	0.298
Middle city	0.018	0.866	0.038	0.648	0.158	0.114
Town	0.137	0.163	0.055	0.473	0.051	0.586
Small town	0.573	< 0.001	0.775	< 0.001	0.215	0.162
Medical care user (ref.=No)
Yes	-0.187	0.014	-0.241	< 0.001	-0.130	0.073
Occupations (ref.=Nurses)
Non-medical citizens	1.227	< 0.001	0.662	< 0.001	0.314	< 0.001
Coef.: Regression Coefficient
Ref.: Reference
Q1: “Do you think that the saying, “human makes mistakes” applies to medical professionals as well?”
Q2: “Do you think that doctors may not be able to make a diagnosis in one visit ?”
Q3: “Do you think that there are individual differences in how the effects of treatments and drugs appear?”

Table 3

Multiple regression analysis of the scores on perceptions of medical uncertainty (items Q4−Q6)
	Q4		Q5		Q6
	Coef.	P value	Coef.	P value	Coef.	P value
Age (ref.=40–59 years)
20–39	0.185	0.008	0.272	0.002	0.260	0.004
60 and above	-0.083	0.252	-0.061	0.495	0.187	0.045
Sex (ref.=Female)
Male	0.036	0.568	0.036	0.637	0.142	0.076
Education level (ref.=University/graduate school)
Vocational school/junior college	-0.051	0.486	0.002	0.982	0.004	0.963
Junior high school/high school	0.079	0.172	-0.088	0.343	0.210	0.029
Marital status (ref.=Married)
Unmarried	0.078	0.387	0.042	0.701	-0.015	0.898
Having children (ref.=Having children)
Without children	-0.114	0.172	-0.304	0.003	0.058	0.590
Population size in the living area (ref.=Capital)
City	0.008	0.921	0.123	0.186	0.008	0.934
Middle city	0.033	0.699	0.182	0.081	-0.032	0.756
Town	0.048	0.548	0.057	0.559	-0.036	0.726
Small town	0.952	< 0.001	0.520	0.001	0.057	0.001
Medical care user (ref.=No)
Yes	-0.291	< 0.001	-0.195	0.010	-0.313	< 0.001
Occupations (ref.=Nurses)
Non-medical citizens	0.417	< 0.001	0.650	< 0.001	0.393	< 0.001
Coef.: Regression Coefficient
Ref.: Reference
Q4: “Do you think that some people will have severe side effects even if they take the same medicine, while others will not?”
Q5: “Do you think that sudden deterioration (sudden worsening of the condition) or death that medical professionals cannot predict will occur?”
Q6: “What do you think is the probability of neuropathy (numbness, sensation, movement abnormalities, etc.) from blood collection?”

A negative association was noted between male participants and Q1 (coef.=-0.332, p < 0.001), but junior high school/high school education was positively associated with Q1 (coef.=0.337, p < 0.001). The variable without children was negatively associated with the scores of items Q3 and Q5 (Q3: coef.=-0.256, p = 0.010; Q5: coef.=-0.304, p = 0.003).

[Insert Tables 2 and 3 here]

This study examines the perceptions of medical uncertainty among non-medical citizens and nurses in Japan. Health care is affected by uncertainty in structures and processes in care, and not all situations in medical institutions can be strictly controlled [9]. Patient-centered care assures quality health care [19, 20] and is linked with personal, professional, and organizational factors [20]. However, a gap exists in the perceptions of patients’ health beliefs between medical care professionals and patients [21]. Street et al. reported that physicians may not necessarily be good judges of patients’ health beliefs and recommended the implementation of partnership-building strategies to encourage active patient participation [21]. Our results revealed that, compared with nurses, non-medical citizens are less tolerant of uncertainty regarding four points: 1) people making mistakes; 2) diagnosis, treatment, or drug uncertainty; 3) sudden deterioration; and 4) injury from blood collection.

To fill the gap between citizens and healthcare providers, the latter should inform the former regarding any issues of uncertainty in medical care provision, and the government should educate citizens to achieve a sustainable provision of medical care.

Non-medical citizens are less tolerant of human error

We found that non-medical citizens’ scores on perceptions of medical uncertainty were higher than those of nurses for item Q1, suggesting that citizens were less accepting of medical uncertainty due to human errors than were nurses. Item Q1 includes the terms “humans make mistakes,” stated as a common saying in the fields of health and safety, indicating that human error is natural [4, 5]. The probability of human error occurrence cannot be zero; however, we noted a gap of 1.2 points in the scores for item Q1 between non-medical citizens and nurses. In the multiple regression model, after adjusting for other variables, non-medical citizens appear to be less tolerant than nurses of uncertainty in health care. A policy for preventing human error focused on maximizing attention to one’s oversight or neglect (e.g., by double-checking or maintaining a high index of suspicion), but this increased emotional distress among health care providers [22]. Further, informed consent involves processes through which health care providers educate patients about the risks and benefits of and alternatives to treatment procedures or interventions [23]. However, informed consent does not include explanations regarding errors that can occur because health care providers are human. As such, general citizens may be unaware that human error can occur in health care. Therefore, citizens must be educated that errors cannot be completely prevented, even if health care providers confront human errors from an individual or organizational standpoint.

Compared to nurses, non-medical citizens are less tolerant of diagnostic, treatment, or drug uncertainty

Our findings revealed an association between medical care users and tolerance of medical uncertainty. Meanwhile, regarding population size of residential areas, small towns were positively associated with diagnostic uncertainty and side effects of drugs, and the age group of 20−39 years and non-medical citizens, were positively associated with diagnostic uncertainty, effect of treatment and drugs, and side effects of drugs.

Medical litigation includes issues such as intraoperative negligence, inadequate informed consent, ineffective explanations regarding complications, and poor teamwork or communication [24, 25]. It is important that medical providers communicate with their patients about uncertainties in medical care. Dahm et al. reported that physicians used two main communication strategies to manage diagnostic uncertainty, and patient-centered communication was associated with positive patient reactions [26]. A study of physicians’ tolerance in medical care indicated that tolerance of uncertainty is associated with the characteristics and experience of physicians and that less tolerance is associated with burnout [27], which has been prominently displayed during the coronavirus (COVID-19) pandemic. Although the medical situation in the early days of the COVID-19 pandemic was dire and a standard treatment was lacking, medical care had to be provided. In addition, there was uncertainty about when this situation would end. The ability to tolerate uncertainty was needed to prevent burnout among health care providers [28, 29]. Outside of the COVID-19 pandemic, medical care is generally fraught with uncertainty. All treatments and drugs have individual differences in efficiency, and some patients develop serious complications and side effects. To prevent burnout and conflicts related to medical issues, health care providers must communicate with patients about uncertainty in medical care.

Prior research has reported an association between tolerance of uncertainty in medical care and the size of residential area, demonstrating how access to health information and its use differ between rural and urban areas [30]. This also shows that differences in health literacy between rural and urban populations are not atypical and are associated with social factors [31]. Differences based on population size of residential areas should be examined further in future research.

Non-medical citizens are less tolerant of sudden deterioration

The gap between health care providers’ and patients’ perceptions of prognostic uncertainty can be attributed to poor communication between patients and care providers. Examples of poor communication include physicians’ reluctance to communicate the uncertain circumstances that can lead to a patient’s death, while the family prefers to acquire all necessary details regarding the loss of their loved one [32, 33]. Akiyama et al. reported that health care providers did not have risk perceptions of patients’ accidental choking, although choking has caused severe disabilities or even led to patient deaths [34]. Medical care users demonstrated a tolerance of sudden deterioration, but all occupations, excluding self-employment, and those living in small towns were associated with intolerance of uncertainty in medical care. We believe that the reasons for this trend are similar to those for the population’s low tolerance of diagnosis, treatment, or drug uncertainty. Health care providers cannot fully anticipate all the sudden changes a patient may experience. However, in some cases, preventive efforts can be taken by providing appropriate explanations to patients and their families, or by predicting risks and taking necessary measures.

In Japan, a new system related to medical accidents was introduced in October 2015 under the Medical Care Act. When a medical accident occurs, the hospital conducts an internal investigation and submits a report to a third-party public health center [35]. The center recommends improvements and educates both the professionals and citizens about medical accidents.

Compared to nurses, non-medical citizens are less tolerant of injuries during blood collection

Nerve injury during venipuncture can be caused by direct puncture or compression [36]. The incidence of nerve injury during venipuncture can vary, with estimates in the range of 0.02ཞ0.03% [37, 38]. Although the incidence is very low and recovery may occur after a few months, venipuncture is a common medical procedure; hence, public awareness about neuropathy is an important matter to be addressed by health care providers. Participants aged 20−39 years, those living in a small town, and those with non-medical occupations demonstrated lower tolerance of uncertainty in medical care than did other participants. Tolerance of uncertainty in medical care was associated with medical care usage. Younger generations might be perceived as less tolerant because they have less experience using medical care. Non-medical citizens’ tolerance of uncertainty in blood collection is very low in comparison to that of nurses; thus, it is necessary to carefully explain the possibility of neuropathy to non-medical citizens.

Limitations

Our study has some limitations. First, the characteristics of non-medical citizens and nurses were different. In general, most nurses are female, with research reporting 92.2% female nurses and 8.1% male nurses [39]. Thus, it was not possible to avoid biases related to sex and education level due to occupational characteristics.

Second, we implemented an online survey method. While this approach is convenient to collect information from many citizens, information about the population distribution could not be obtained from the internet survey monitors. In addition, Andrade et al. reported the possibility of respondents having biases toward this type of survey [40]. Thus, our findings may have limitations in terms of generalization. However, collecting data from non-medical citizens using controlled sampling strategies presents some difficulties. Despite these limitations, our study provides a different perspective on citizens’ tolerance of uncertainty in medical care.

Our results revealed that non-medical citizens are less tolerant of uncertainty in medical care than nurses are regarding the following four points: 1) people making mistakes; 2) diagnosis, treatment, or drug uncertainty; 3) sudden deterioration; and 4) injury from blood collection.

Further, the results demonstrate that patients who receive medical care are more tolerant of medical uncertainty than non-patients. In addition, young people were generally less tolerant than older respondents. The younger generation, those who are likely to be family members of patients, have a low tolerance for medical care uncertainty, and may even become involved in medical conflicts through their families. Therefore, to reduce conflicts related to medical issues, health care providers need to improve education for general citizens on the perception of uncertainty in medical care.

COVID-19: coronavirus disease 2019

Ethics approval and consent to participate

This study was approved by the ethics committee at the Gifu University of Health Sciences (approval number: 2022_19). We outsourced the internet survey administration to an online research company, which contacted the survey monitors and collected the study data. The purpose of the survey was shown at the beginning of the questionnaire, and only those who agreed with this study were allowed to proceed to the questions. Informed consent was taken from participants to participate in the study through the internet system. All methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not declared

Availability of data and materials

If you intend to use the data for research purposes, please contact the authors.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by a Grants-in-Aid for Scientific Research grant number 20K18889, 20H01598, 20H04147. The funder had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.

Authors’ contributions

KH, JS, and MM supervised the work. NA, SK, and TA developed the questionnaire and conducted the pilot study. NA, SK, and RU were responsible for data analysis and interpretation. NA wrote the main body of the manuscript. All authors contributed to writing the final manuscript. All authors read and approved the final manuscript.

Acknowledgements

We would like to thank the respondents of this internet survey.

Authors’ information

NA is a nurse and a patient safety manager. Her research fields include patient safety and fundamental nursing.

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No competing interests reported.

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Perceptions of uncertainty in medical care among non-medical citizens and nurses in Japan: A cross- sectional internet-based survey

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Abstract

Background

Methods

Results

Conclusions

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Background

Methods

Participants

Eligibility criteria

Study setting

Ethical considerations

Measures

Sample size

Analysis

Results

Participants’ flowchart

Study characteristics

Discussion

Non-medical citizens are less tolerant of human error

Compared to nurses, non-medical citizens are less tolerant of diagnostic, treatment, or drug uncertainty

Non-medical citizens are less tolerant of sudden deterioration

Compared to nurses, non-medical citizens are less tolerant of injuries during blood collection

Limitations

Conclusion

Abbreviations

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References

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