The effect of nurses’ Machiavellian and deontic justice personality on the tendency to make medical errors and other factors: a cross-sectional study

Abstract

Objective

This study was conducted to investigate the effect of nurses’ Machiavellian and deontic justice personality on the tendency to make medical errors. Additionally, conducted to investigate the other factors associated with nurses’ tendency to make medical errors.

Methods

This cross-sectional study consisted of 345 nurses working in a state university medical faculty health application and research hospital, and data were collected using the Medical Error Tendency in Nursing Scale, the Machiavellian Personality Scale, and the Deontic Justice Scale.

Results

Machiavellian and deontic justice personality of nurses effect in low level their tendency to make medical errors (R = 0.284, p = 0.001). As the nurses’ Machiavellian tendencies increased, their propensity toward making medical errors also increased. The increase in Nurses’ deontic justice reduced their tendency toward medical errors (p < 0.05). A significant difference was found between nurses’ mean tendency to medical errors scores and their age, working life/years, the number of night shifts, the daily number of patients provided with care, the status of working in the COVID-19 service, and the status of having received education on medical errors (p < 0.05).

Conclusions

Nurses’ Machiavellian tendencies and deontic justice approach affect their propensity to make medical errors. Nurses who have a Machiavellian tendency and poor deontic justice have a high tendency to make medical errors. Nurses’ age, working life/years, the number of night shifts, the daily number of patients they provide care for, working in the COVID-19 service, and having received education on medical errors were the other factors affecting their tendency to make medical errors. This study demonstrated that nurses’ personality traits can cause medical errors. Generations are changing in the world and personality are also changing. Therefore, including personal development in nursing education could be a positive approach for medical errors.

Introduction

Medical error is a topic in which the service provided by healthcare professionals is questioned, and that is discussed and studied globally with its ethical, legal, medical, educational, and managerial dimensions. At the same time, medical errors are practices that harm the patient and may even lead to death [1, 2]. The World Health Organization has emphasized that approximately 10 million people globally die or become disabled every year due to medical errors. Medical errors are actually more frequent than anticipated. In a study, the risk of being harmed due to a medical error for a person entering a healthcare facility was found as one out of 300 [3]. The Joint Commission on Accreditation of Healthcare Organization defines medical error as giving harm to a patient as a result of a healthcare professional’s inappropriate and unethical behavior or inadequate and negligent behavior in professional practices. Medical errors have two main components, namely human and system, and human errors account for 15% of all errors, while the latter account for 85% [4]. To err is human. Healthcare professionals can make honest err, and that doesn’t make them bad. However, in order to reduce medical errors, it is essential to examine the factors that cause them. This is necessary for patient safety [5, 6] The causes of human-induced medical errors generally include consciously or unconsciously conducted unethical behaviors, such as lack of knowledge, negligence, indifference, and willful misconduct [1, 7].

Machiavellianism is an approach that is based on Machiavelli’s thoughts rooted in politics and shaped by theoretical studies. This approach argues that one can keep their individual interests above everything else and that the end justifies the means in the context of manipulative and self-seeking behaviors, insincerity, and insensitivity. Machiavellianism is also defined as a personality trait characterized by making use of and exploiting others and emotionally manipulative behaviors for individual interests [8–10]. It is a concept related to morality. The negativities in Machiavellianism praise amorality. Machiavellian individuals lack moral values [11, 12]. Every individual may have a different level of Machiavellian personality tendencies [9]. According to a study, individuals with a high level of Machiavellianism exhibit more damaging behaviors. In addition, it has been argued in some studies that Machiavellian individuals violate ethical norms and moral rules more, tell lies, are prone to deceptive and unethical behaviors, prioritize their individual interests, and are emotionally cold individuals [11, 13–16]. It has also been reported that Machiavellian individuals pay less attention to principles and criteria [16].

The deontic justice approach puts that it is a moral obligation for individuals to fulfill their duties and responsibilities with a justice understanding [17]. Deontic justice is also defined as individuals’ caring for themselves and others. In the deontic justice approach, justice is a moral virtue and people should see justice as an end in itself [18]. According to Beugre, deontic justice has three dimensions: moral obligation, moral accountability, and moral outrage [17]. Moral obligation asserts that an action must be consistent with core moral beliefs. Moral accountability affirms that the individual tries to control his/her behavior following moral beliefs. Moral outrage shows that perceived injustice can develop a sense of moral outrage and restore justice [19]. In this context, deontic justice is closely related to the essence of nursing. It is a moral obligation to ensure justice in the service provided in nursing. Accordingly, nurses’ deontic justice understanding will inevitably affect their behavior while they are working.

Nursing is a difficult profession that requires working altruistically in a fast-paced environment [20]. Many systemic factors, such as the intense workload caused by the working environment, the stress experienced due to patients’ problems, the low number of employees, the severity of the general condition of patients, and the high number of patients, can cause medical errors in patient care [7]. In addition, medical errors may occur due to the moral approach and individual personality characteristics of many health professionals. It is a fact that nurses do not aim to be moral in the environment where they work. However, it is an important virtue and necessity for nurses to be moral in the service they provide. While working, nurses are expected to be moral, adopt compassionate care, and create an ethical working environment. In studies on the causes of nurses’ medical errors, generally working conditions and system-related factors have been mentioned. However, whether the individual characteristics of nurses related to morality affects medical errors has not been addressed. Nurses’ Machiavellian tendency, which is related to morality, and their understanding of deontic justice may affect their propensity to make medical errors. In this context, do nurses who have a Machiavellian tendency and poor deontic justice have a high tendency to make medical errors? This study takes its starting point from this question. Reflecting on this question, this study was conducted to the effects of the Machiavellian and deontic justice personality on the tendency to make medical errors, as well as examine the other factors related to nurses’ tendency to make medical errors.

Methods

Study design and time

This cross-sectional study was conducted between April 11 and July 18, 2022 with the participation of nurses working at a state university medical faculty health application and research hospital.

Study sampling

The population of the study consisted of 620 nurses working in the clinical services of a state university medical faculty health application and research hospital during the study. Power analysis has been used to determine the sample of the study. A pre-application has been done and data has been computed with G-power 3.1.9.2 software. When the effect size |ρ|) = 0,2, II. type error probability α = 0,05 and test power 1-β=%95 have been acquired, minimum sample number to be included in the study has been calculated as 327 [21]. The study has been completed with 345 nurses.

Instruments

A questionnaire, the Medical Error Tendency in Nursing Scale, the Machiavellian Personality Scale, and the Deontic Justice Scale were used as data collection tools.

The questionnaire

This form has 12 questions about nurses’ descriptive characteristics and variables that are thought to affect their tendency to medical errors [7, 20, 21].

The Medical Error Tendency in Nursing Scale (METNS)

This scale was developed by Özata and Altunkan (2010) to measure nurses’ tendency to medical errors. There are 49 five-point Likert-type items and five sub-dimensions on the scale. The sub-dimensions of the scale are “medication and transfusion applications (items 1–18)”, “hospital infections (items 19–30)”, “patient monitoring and material safety (items 31–39)”, “falls (items 40–44)”, and “communication (items 45–49)”. High mean scores on the total scale are interpreted as a decrease in the tendency to make medical errors. In the original study, Cronbach’s alpha coefficient for the total scale was 0.95 [1]. In this study, the alpha coefficient was found as 0.95 for the total scale, and 0.88, 0.90, 0.86, 0.87, and 0.86 for the sub-dimensions, respectively.

The Machiavellian Personality Scale (MPS)

This scale was developed by Dahling et al. (2009) to measure the level of Machiavellian personality traits that one has, and its Turkish validity and reliability study was performed by Akın et al. (2014) and later by Ülbeği (2016). It has 16 seven-point Likert-type items and four sub-dimensions: “amorality (items 1, 2, 3, 4, and 5)”, “desire for status (items 6, 7, and 8)”, “desire for control (items 9, 10, and 11)”, and “distrust of others (items 12, 13, 14, 15, and 16)”. Sub-dimension and total scale scores give information about the level of Machiavellian personality traits. As the mean score on the total scale and sub-dimensions increases, the Machiavellian tendency increases, as well. Ülbeği found Cronbach’s alpha coefficient as 0.88 for the total scale, 0.86 for amorality, 0.82 for the desire for status, 0.80 for the desire for control, and 0.83 for distrust of others [12–14]. In this study, Cronbach’s alpha coefficient was found as 0.87 for the total scale, 0.78 for amorality, 0.70 for the desire for status, 0.80 for the desire for control, and 0.79 for distrust of others sub-dimensions.

The Deontic Justice Scale (DJS)

The Turkish validity and reliability study of this scale, which was developed by Beugre (2012) to measure individuals’ deontic justice understanding, was carried out by Akın et al. (2013). The scale has 18 items and three sub-dimensions, namely “moral obligation (items 1, 2, 3, 4, 5, 6, 7, and 8)”, “moral accountability (items 9, 10, 11, 12, 13, and 14)”, and “moral outrage (items 15, 16, 17, and 18). Each item is scored on a five-point Likert-type scale and there are no reverse-scored items. The higher the total score on the scale and sub-dimensions is, the higher the level of deontic justice understanding is. In the original study of the scale, Cronbach’s alpha coefficients were 0.93 for the total scale, and 0.89, 0.89, and 0.85 for the sub-dimensions, respectively [17, 22]. In this study, the alpha coefficient was found as 0.96 for the total scale, and 0.95, 0.92, and 0.95 for the sub-dimensions, respectively.

Procedure

The study data were collected online due to the ongoing COVID-19 pandemic process. The data collection forms used in the study were delivered to the participants online via a survey link. Participants were invited to the study on online platforms, and volunteer participants filled out the forms online via the questionnaire link provided. Nurses who volunteered to participate in the study and worked in clinical services were included. Nurses who were not actively working in the clinics were excluded in the study.

Data analysis

Statistical analyses were performed on the SPSS (IBM SPSS Statistics 24). Frequency tables and descriptive statistics were used to interpret the findings. The “Mann-Whitney U” test and the “Kruskal-Wallis H” test were employed to compare the measurement values of two independent groups with non-normal measurement values. Bonferroni correction was applied for paired comparisons of variables with a significant difference in three or more groups. Multiple linear regression analysis was employed to examine the effects of the DJS and MPS on the METNS. Variables with a non-normal distribution were transformed and normality was achieved. In addition, the examination of VIF and Tolerance values indicated that there was no multicollinearity between the variables. The Durbin-Watson value was examined for autocorrelation, and it was determined that the independence of the errors was achieved. p < 0.05 was accepted as a statistical significance value.

Ethical considerations

The written permission of the relevant health institution (number/date: E-31568761-804.01-291877/17.02.2022) and the approval of Eskişehir Osmangazi University Non-Interventional Clinical Research Ethics Committee (number/date: E-25403353-050.99-313320 / 05.04.2022) were obtained to conduct the study. Permission of the authors who adapted (MPS and DJS) and developed (METNS) the scales used in the study was obtained via email. Written informed consent was obtained from all participants who wanted to participate in the study. During the data collection phase, the principles of the Declaration of Helsinki (as revised in Brazil 2013) were followed.

Results

The mean age of the nurses was 33.52 ± 7.35 years, and 33.6% of them were in the 28–33 age group. In the study, 83.5% of the nurses were female, 87.2% had an undergraduate/graduate degree, 31.3% had been working for 6–10 years, and 38.6% worked ≤ 160 h a month. 64.3% of the nurses worked both day and night shifts, 51.0% worked shifts 6–10 times a month, and 36.6% provided care for > 10 patients a day. In the study, 87.5% of the nurses stated that medical errors were likely to occur due to intense work schedules (Table 1).

Table 1.

Nurses characteristics

Variables (N = 345)		n	%
Age
	< 28	76	22.0
	28–33	116	33.6
	34–39	78	22.6
	≥ 40	75	21.8
Gender	Male	57	16.5
	Female	288	83.5
Education degree	Associate degree	25	7.3
	Graduate / undergraduate	301	87.2
Marital status	Married	227	65.8
	Single	118	34.2
Working time
	≤ 5 year	86	24.9
	6–10 year	108	31.3
	11–15 year	65	18.9
	> 15 year	86	24.9
Monthly working time
	≤ 160 h	133	38.6
	170–180 h	125	36.2
	190–200 h	49	14.2
	> 200 h	38	11.0
Number of night shifts/monthly	Not	88	25.5
	1–5	46	13.4
	6–10	176	51.0
	> 10	35	10.1
Number of patients cared for/day	< 5	124	35.9
	5–10	95	27.5
	> 10	126	36.6
Clinics	Emergency	24	7.0
	Intensive care units	93	27.0
	COVID-19 clinics	26	7.5
	Internal medicine clinics	125	36.2
	Surgical clinics	77	22.3
Causes of medical errors †	Carelessness	267	77.4
	Inadequate education	149	43.2
	Communication problems	183	53.0
	Not liking the profession	104	30.1
	Lack of motivation	180	52.2
	Intense work	302	87.5
	Fatigue	267	77.4
	Irresponsibility	104	30.1
	Selfishness	49	14.2
	Negative personality traits	72	20.9
Status of receiving medical error training	Yes	276	80.0
	No	69	20.0
Place medical error training received †	In-service training	225	65.2
	Internet/social media	53	15.4
	Congress/symposiums	59	17.1
	Publications such as books/journal etc.	36	10.4
	Certificate training	55	15.9
	Graduated school	193	55.9

^† More than one answer was given to this question and percentages were determined based on the total number of samples

Statistical estimations of the regression model, which was established to reveal the effect of the mean scores of the total DJS and MPS on the mean scores of the total tendency to medical errors showed that the model was significant and usable. Accordingly, these two variables together had a significant effect on the mean scores of the total METNS (F = 14.983; p < 0.000) and explained 8.1% of the total variance. The regression equation for the model is as follows:

According to the regression equation obtained, a one-unit increase in the DJS score caused a 0.128 unit increase in the METNS score, and a one-unit increase in the MPS score caused a 0.098 unit decrease in the METNS score. Therefore, it was observed that the increase in participants’ DJS score statistically increased the METNS score, while the increase in the MPS score decreased it (p = 0.000) (Table 2).

Table 2.

Distribution of the mean scores and regression analysis of the nurses from scales (N = 345)

Scales	Sub-dimension	Mean	S.D.	Median	Min.	Max.
METNS	Medication and transfusion	4.76	0.33	4.9	3.0	5.0
	Hospital infections	4.75	0.36	4.9	2.9	5.0
	Patient monitoring and material safety	4.57	0.45	4.7	3.0	5.0
	Falls	4.66	0.47	4.8	3.0	5.0
	Communication	4.68	0.50	5.0	2.8	5.0
	Total	4.70	0.30	4.7	3.0	5.0
DJS	Moral obligation	4.58	0.61	4.9	1.0	5.0
	Moral accountability	4.48	0.63	4.7	1.0	5.0
	Moral outrage	4.50	0.68	5.0	1.0	5.0
	Total	4.53	0.57	4.7	1.0	5.0
MPS	Amorality	1.87	1.17	1.4	1.0	7.0
	Desire for status	2.91	1.40	3.0	1.0	7.0
	Desire for control	3.24	1.66	3.0	1.0	7.0
	Distrust of others	2.83	1.40	2.6	1.0	7.0
	Total	2.62	1.02	2.5	1.0	7.0
Independent Variables		B	Std. Error	β	t	p
Constant		0.127	0.013		9.523	0.001
DJS		0.128	0.034	0.193	3.725	0.001
MPS		-0.098	0.025	-0.200	3.850	0.001
Dependent Variable: METNS R = 0.284; R2 = 0.081; F = 14.983; p < 0.05; Durbin Watson = 1.846

A statistically significant difference was found between nurses’ mean tendency to medical errors scores on the medication and transfusion, hospital infections, and falls sub-dimensions according to their age groups (p = 0.002, p = 0.000, and p = 0.008, respectively). Accordingly, the mean tendency to medical errors score of those aged ≥ 40 years was significantly higher than the scores of those in the 28–33 and 34–39 age groups. There was a statistically significant difference between nurses’ mean tendency to medical errors scores on the hospital infections sub-dimension by their marital status (p = 0.033). The mean hospital infections-related tendency to medical errors scores of married nurses were significantly higher than those of single nurses. A statistically significant difference was determined between nurses’ mean tendency to medical errors scores on the hospital infections and falls sub-dimensions by the duration of their working life (p = 0.001 and p = 0.020, respectively). The mean hospital infections and falls-related tendency to medical errors scores of nurses who had been working for > 15 years were significantly higher than the scores of others. The difference between nurses’ mean tendency to medical errors scores on the medication and transfusion, hospital infections, patient monitoring and material safety, and falls sub-dimensions was statistically significant according to their the monthly number of shifts (p = 0.014, p = 0.000, p = 0.001, and p = 0.033, respectively). The mean tendency to medical errors scores of nurses who did not work shifts on medication and transfusion sub-dimension was significantly higher than the scores of those who did.

There was a statistically significant difference between nurses’ mean tendency to medical errors scores on the hospital infections sub-dimension by the daily number of patients provided with care (p = 0.032). The mean tendency to medical errors scores of nurses who provided care for > 10 patients a day on the hospital infections sub-dimension was significantly higher than the scores of those who provided care for < 5 patients daily. A statistically significant difference was determined between nurses’ mean tendency to medical errors scores on the hospital infections sub-dimension by their department (p = 0.002). The mean tendency to medical errors scores of nurses who worked in COVID-19 clinics on the hospital infections sub-dimension was significantly lower than the scores of those who worked in other services. The difference between nurses’ mean tendency to medical errors scores on the hospital infections sub-dimension was statistically significant according to their status of having received education on medical errors (p = 0.024). The mean tendency to medical errors scores of nurses who had received education on medical errors on the hospital infections sub-dimension was significantly higher than the scores of those who had not (Table 3).

Table 3.

Comparison of METNS scores according to the descriptive characteristics of the nurses (N = 345)

METNS		Medication and transfusion		Hospital infections		Patient monitoring and material safety		Falls		Communication
Variables	n	± S.S	Median [IQR]	± S.D	Median [IQR]	± S.D	Median [IQR]	± S.D	Median [IQR]	± S.D	Median [IQR]
Age groups
< 28 (1)  28–33 (2)  34–39 (3)  ≥ 40 (4)	76 116 78 75	4.76 ± 0.33 4.74 ± 0.30 4.71 ± 0.33 4.86 ± 0.22	4.8 [0.3] 4.7 [0.4] 4.7 [0.4] 4.9 [0.2]	4.73 ± 0.43 4.70 ± 0.39 4.70 ± 0.36 4.89 ± 0.21	4.9 [0.3] 4.8 [0.4] 4.8 [0.5] 5.0 [0.2]	4.56 ± 0.48 4.53 ± 0.48 4.51 ± 0.46 4.69 ± 0.35	4.7 [0.8] 4.7 [0.8] 4.7 [0.9] 4.9 [0.5]	4.65 ± 0.48 4.58 ± 0.47 4.59 ± 0.48 4.77 ± 0.46	4.8 [0.7] 4.7 [0.6] 4.7 [0.9] 5.0 [0.2]	4.68 ± 0.50 4.65 ± 0.56 4.66 ± 0.45 4.75 ± 0.43	5.0 [0.4] 5.0 [0.6] 4.8 [0.7] 5.0 [0.4]
Test*; p Difference		χ2 = 14.645; p = 0.002 [2,3–4]		χ2 = 22.009; p = 0.001 [1,2,3–4]		χ2 = 5.272; p = 0.153		χ2 = 11,922; p = 0.008 [2,3–4]		χ2 = 2.619; p = 0.454
Gender
Male  Female	57 288	4.75 ± 0.36 4.76 ± 0.29	4.9 [0.4] 4.9 [0.3]	4.79 ± 0.34 4.74 ± 0.37	4.9 [0.3] 4.9 [0.4]	4.57 ± 0.42 4.56 ± 0.46	4.7 [0.7] 4.7 [0.8]	4.69 ± 0.49 4.66 ± 0.47	5.0 [0.4] 4.8 [0.6]	4.75 ± 0.45 4.67 ± 0.50	5.0 [0.4] 5.0 [0.6]
Test; p		Z=-0.059; p = 0.953		Z=-0.951; p = 0.342		Z=-0.307; p = 0.759		Z=-0.816; p = 0.414		Z=-1.057; p = 0.290
Education degree
High school  Associate degree  Graduate and up	19 25 301	4.63 ± 0.53 4.86 ± 0.18 4.76 ± 0.29	4.9 [0.7] 4.9 [0.2] 4.8 [0.3]	4.67 ± 0.49 4.87 ± 0.23 4.75 ± 0.37	4.8 [0.5] 5.0 [0.2] 4.9 [0.4]	4.41 ± 0.52 4.62 ± 0.33 4.57 ± 0.46	4.4 [1.0] 4.8 [0.7] 4.7 [0.7]	4.39 ± 0.62 4.71 ± 0.37 4.68 ± 0.46	4.4 [1.0] 4.8 [0.4] 5.0 [0.6]	4.57 ± 0.55 4.63 ± 0.49 4.69 ± 0.49	4.8 [1.0] 4.8 [0.6] 5.0 [0.4]
Test; p		χ2 = 3.775; p = 0.151		χ2 = 3.198; p = 0.202		χ2 = 1.876; p = 0.391		χ2 = 3.905; p = 0.142		χ2 = 2.679; p = 0.262
Marital status
Married  Single	227 118	4.78 ± 0.27 4.71 ± 0.35	4.9 [0.3] 4.8 [0.5]	4.78 ± 0.33 4.69 ± 0.42	4.9 [0.3] 4.8 [0.5]	4.60 ± 0.43 4.50 ± 0.50	4.7 [0.7] 4.7 [0.9]	4.68 ± 0.44 4.62 ± 0.52	5.0 [0.6] 4.8 [0.8]	4.68 ± 0.50 4.69 ± 0.48	5.0 [0.6] 5.0 [0.6]
Test; p		Z=-1.250; p = 0.211		Z=-2.131;p = 0.033		Z=-1.462; p = 0.144		Z=-0.888; p = 0.375		Z=-0.122; p = 0.903
Working time
≤ 5 year(1)  6–10 year(2)  11–15 year(3)  > 15 year(4)	86 108 65 86	4.73 ± 0.34 4.75 ± 0.29 4.73 ± 0.29 4.82 ± 0.28	4.8 [0.4] 4.8 [0.4] 4.8 [1.2] 4.9 [0.3]	4.69 ± 0.48 4.71 ± 0.35 4.76 ± 0.30 4.85 ± 0.29	4.9 [0.5] 4.8 [0.4] 4.9 [0.4] 5.0 [0.2]	4.58 ± 0.48 4.51 ± 0.47 4.52 ± 0.46 4.67 ± 0.38	4.8 [0.7] 4.7 [0.9] 4.7 [0.9] 4.8 [0.6]	4.67 ± 0.53 4.59 ± 0.45 4.68 ± 0.45 4.73 ± 0.46	4.8 [0.4] 4.7 [0.8] 4.8 [0.5] 5.0 [0.4]	4.70 ± 0.53 4.63 ± 0.55 4.70 ± 0.42 4.73 ± 0.44	5.0 [0.4] 5.0 [0.8] 4.8 [0.5] 5.0 [0.4]
Test; p Difference		χ2 = 7.485; p = 0.058		χ2 = 15.966; p = 0.001 [1,2,3–4]		χ2 = 5.097; p = 0.165		χ2 = 9.818; p = 0.020 [2–4]		χ2 = 1.394; p = 0.707
METNS		Medication and transfusion		Hospital infections		Patient monitoring and material safety		Falls		Communication
Variables	n	± S.D	Median [IQR]	± S.D	Median [IQR]	± S.D	Median [IQR]	± S.D	Median [IQR]	± S.D	Median [IQR]
Monthly working time (hour/h)
≤ 160 h  170–180 h  190–200 h  > 200 h	133 125 49 38	4.74 ± 0.34 4.75 ± 0.28 4.79 ± 0.26 4.79 ± 0.30	4.9 [0.4] 4.8 [0.3] 4.8 [0.4] 4.9 [0.4]	4.75 ± 0.37 4.74 ± 0.40 4.80 ± 0.21 4.75 ± 0.41	4.9 [0.4] 4.9 [0.4] 4.8 [0.3] 5.0 [0.4]	4.57 ± 0.46 4.55 ± 0.46 4.62 ± 0.42 4.56 ± 0.43	4.7 [0.7] 4.7 [0.8] 4.8 [0.8] 4.7 [0.8]	4.64 ± 0.53 4.63 ± 0.45 4.72 ± 0.44 4.77 ± 0.35	5.0 [0.6] 4.8 [0.7] 5.0 [0.5] 5.0 [0.4]	4.65 ± 0.56 4.69 ± 0.44 4.69 ± 0.54 4.75 ± 0.37	5.0 [0.6] 5.0 [0.6] 5.0 [0.5] 5.0 [0.5]
Test; p		χ2 = 2.685; p = 0.443		χ2 = 0.860; p = 0.835		χ2 = 0.864; p = 0.834		χ2 = 5.166; p = 0.160		χ2 = 0.835; p = 0.841
Number of night shifts / monthly
Not (1)  1–5 (2)  6–10 (3)  > 10 (4)	88 46 176 35	4.90 ± 0.26 4.81 ± 0.28 4.72 ± 0.31 4.73 ± 0.37	4.9 [0.2] 4.8 [0.2] 4.7 [0.4] 4.8 [0.3]	4.85 ± 0.27 4.83 ± 0.33 4.69 ± 0.39 4.68 ± 0.46	5.0 [0.2] 5.0 [0.2] 4.8 [0.4] 4.8 [0.5]	4.69 ± 0.42 4.68 ± 0.40 4.51 ± 0.47 4.42 ± 0.46	4.9 [0.6] 4.9 [0.6] 4.6 [0.9] 4.4 [0.8]	4.74 ± 0.45 4.71 ± 0.45 4.64 ± 0.46 4.49 ± 0.58	5.0 [0.4] 5.9 [0.6] 4.8 [0.6] 4.6 [1.0]	4.67 ± 0.53 4.68 ± 0.51 4.71 ± 0.45 4.62 ± 0.58	5.0 [0.6] 5.0 [0.6] 5.0 [0.6] 5.0 [0.8]
Test; p Difference		χ2 = 10.608 p = 0.014 [1–3]		χ2 = 22.172 p = 0.001 [1–3,4] [2–3,4]		χ2 = 16.655 p = 0.001 [1–3,4] [2–3,4]		χ2 = 8.768 p = 0.033 [1–3,4]		χ2 = 0.350 p = 0.950
Number of patient cared for/day
<5 (1)  5–10 (2)  > 10 (3)	124 95 126	4.75 ± 0.32 4.73 ± 0.32 4.80 ± 0.27	4.9 [0.4] 4.8 [0.4] 4.9 [0.3]	4.69 ± 0.42 4.75 ± 0.34 4.81 ± 0.32	4.8 [0.5] 4.9 [0.4] 5.0 [0.3]	4.54 ± 0.50 4.55 ± 0.45 4.61 ± 0.41	4.7 [0.9] 4.7 [0.7] 4.7 [0.4]	4.64 ± 0.49 4.67 ± 0.45 4.66 ± 0.45	4.8 [0.6] 5.0 [0.6] 5.0 [0.6]	4.71 ± 0.51 4.63 ± 0.53 4.69 ± 0.46	5.0 [0.4] 4.8 [0.6] 5.0 [0.6]
Test; p Difference		χ2 = 3.514; p = 0.173		χ2 = 6.898; p = 0.032 [1–3]		χ2 = 0.716; p = 0.694		χ2 = 0.163; p = 0.922		χ2 = 4.983; p = 0.083
Clinics
Emergency (1)  Intensive care unit (2)  COVID-19 clinics (3)  Int. medicine clin. (4)  Surgical clinics (5)	24 93 26 125 77	4.79 ± 0.27 4.73 ± 0.34 4.61 ± 0.39 4.79 ± 0.28 4.79 ± 0.24	4.9 [0.3] 4.8 [0.3] 4.7 [0.7] 4.9 [0.3] 4.8 [0.3]	4.81 ± 0.30 4.67 ± 0.39 4.56 ± 0.38 4.78 ± 0.39 4.83 ± 0.30	5.0 [0.3] 4.8 [0.5] 4.6 [0.7] 5.0 [0.3] 4.9 [0.3]	4.57 ± 0.53 4.51 ± 0.48 4.37 ± 0.52 4.59 ± 0.45 4.67 ± 0.35	4.7 [0.7] 4.7 [0.9] 4.3 [1.1] 4.8 [0.7] 4.7 [0.6]	4.62 ± 0.57 4.66 ± 0.45 4.58 ± 0.53 4.65 ± 0.49 4.72 ± 0.42	5.0 [0.8] 4.8 [0.4] 4.8 [0.8] 5.0 [0.6] 5.0 [0.4]	4.77 ± 0.40 4.71 ± 0.52 4.65 ± 0.40 4.61 ± 0.54 4.76 ± 0.43	5.0 [0.5] 5.0 [0.4] 4.8 [0.6] 4.8 [0.8] 5.0 [0.4]
Test; p Difference		χ2 = 6.186; p = 0.186		χ2 = 17.324; p = 0.002 [3 − 1,4,5]		χ2 = 6.619; p = 0.157		χ2 = 2.357; p = 0.670		χ2 = 8.292; p = 0.081
Status of receiving medical err. train.
Yes  No	276 69	4.77 ± 0.29 4.73 ± 0.34	4.9 [0.3] 4.8 [0.4]	4.77 ± 0.35 4.66 ± 0.42	4.9 [0.3] 4.8 [0.6]	4.58 ± 0.45 4.52 ± 0.48	4.7 [0.7] 4.7 [0.9]	4.68 ± 0.47 4.61 ± 0.48	4.9 [0.6] 4.8 [0.8]	4.68 ± 0.52 4.70 ± 0.41	5.0 [0.6] 4.8 [0.5]
Test; p		Z=-0.591; p = 0.555		Z=-2.254;p = 0.024		Z=-0.967; p = 0.333		Z=-0.991; p = 0.322		Z=-0.798; p = 0.425

*Z = “Mann-Whitney U” test; χ²= “Kruskall-Wallis H” test

Discussion

It has been stated that individuals with Machiavellian tendencies are inclined to put individual interests above everything else, to give harm, and to exhibit unethical behaviors [10]. This tendency is in contradiction with the nature of nursing, which is based on compassion, tolerance, and helping people. In this study, the Machiavellian tendency of nurses was found to be low. Especially the Machiavellian tendency in the amorality sub-dimension of the scale was very low. This is a positive result for the nurses and the patients they provide care for. Although there is no study on the evaluation of the Machiavellian tendency of nurses with the scale used in this study, it has been observed that the Machiavellian tendency in studies conducted in different populations and occupational groups is higher than in our study results [8–11, 15, 23]. This study, the Machiavellian tendency was found to be low compared to these studies. Because in different professions and groups, while there are situations such as desire for success and power, in nursing, helping people is at the forefront. In a study, the Machiavellian tendencies of individuals with high moral metacognition were found to be low [24]. In other studies, it was reported that the Machiavellian tendency of healthcare professionals who provided patient care was low [25], while nurses who wanted to be a manager had more Machiavellian characteristics [26]. The reason why the Machiavellian tendency was found to be low in this study is that we worked with a group of nurses who provide direct service to the patient. It is thought that helping the patient positively affects human factors and reduces the Machiavellian tendency, while the competitive environment increases the Machiavellian tendency in manager nurses. A high Machiavellian tendency is not desirable for healthcare professionals working with a focus on the quality of care and patients’ benefits. It is thought that particularly the competition in the working environment supports the Machiavellian tendency in nurses but does not support the patient care environment.

Unethical behaviors are mentioned among human factors affecting the tendency to make medical errors [27]. The Machiavellian tendency emphasizes unethical individual behaviors. Therefore, in this study, the Machiavellian tendency was considered as a human factor that was thought to affect making medical errors. The increase in nurses’ Machiavellian tendency in the study also increased their tendency to make medical errors. The rise of Machiavellian tendencies in nurses may be a risk factor for medical errors and may affect making medical errors. Developing technology, changing living conditions, and generational differences alter individual characteristics. People act more focused on their personal interests. This may support the Machiavellian tendency and the tendency to make medical errors.

The deontic justice approach is that individuals fulfill their duties and responsibilities with justice understanding and it is a moral obligation. In this study, it was determined that nurses’ understanding of deontic justice was very high. The reflection of nurses’ understanding of justice in care is a very valuable virtue. Therefore, this is a positive, natural result for nursing. In the study, it was found that the increase in nurses’ deontic justice approach had an effect on decreasing their tendency to make medical errors. Although there are no studies examining these two factors together, this reveals a significant result that the tendency of nurses, who work with justice and an awareness of their responsibilities, to make medical errors will decrease.

The factors affecting nurses’ tendency to make medical errors included age, working life, the status of working night shifts, the daily number of patients provided with care, department, and the status of having received education on medical errors. In the study, nurses with higher age and longer working life had a lower tendency to make medical errors. These two factors revealed that experience in nursing was important. Consistent with the literature, as age increased, work experience also increased, and the tendency to make medical errors decreased [7, 21, 28].

In the study, nurses who had a high number of night shifts and a daily number of patients had a higher tendency to make medical errors. Night shifts and intense work schedules are among the factors that cause medical errors [29]. Working night shifts is a tiring situation that disrupts the sleep pattern and attention of employees. Similarly, a high number of patients is a factor that can reduce the quality of care and cause errors. In a similar study, nurses with a high daily number of patients had a high tendency to make medical errors regarding hospital infections [30]. In this context, we think that when the number of patients is high, nurses who have to move faster and therefore get more tired in their busy work schedule are inadequate to take precautions regarding hospital infections.

In this study, the tendency of nurses working in COVID-19 clinics to make medical errors regarding hospital infection was found to be high. The COVID-19 clinics that were opened during the pandemic caused nurses to have busy work schedules in addition to the risk of contracting the COVID-19 disease. Therefore, we think that the COVID-19 disease may have been a stress factor for nurses and that this factor may have increased the tendency to make medical errors.

In this study, nurses stated that the most common causes of medical errors might have been due to intense work schedules, carelessness, and fatigue. These statements overlap with the factors associated with medical errors in the literature [20, 23, 31]. In the study, nurses who had received education on medical errors were less likely to make medical errors in terms of hospital infections. This result is compatible with the literature [32]. It is thought that updating the knowledge of nurses who have received education on medical errors has a positive effect on reducing the tendency to make medical errors.

Limitations

Owing to manpower, time and geographical area limitations, only the nurses of one Medical Faculty Hospital were surveyed. Therefore, its generalizability to nurses at the national level was low. The measurement tools that evaluate personal characteristics used in the study do not have a diagnostic feature, they provide a preliminary evaluation. There is a need for better scales that can be evaluate nurses’ deontic personal characteristics.

Conclusions

Nurses’ Machiavellian tendencies and deontic justice approach affect their propensity to make medical errors. Nurses with increased Machiavellian tendencies tend to make more medical errors. Nurses with a high deontic justice understanding tend to make fewer medical errors. In this study, it was found that some factors related to nurses’ professional characteristics and working conditions were associated with the tendency to make medical errors. Nurses’ age, working life/years, the number of night shifts, the daily number of patients they provide care for, working in the COVID-19 service, and having received education on medical errors were factors affecting their tendency to make medical errors. Personal development should be included in the nursing education curriculum. Working for the well-being of the patient and deontic justice should be emphasized in education. If nurses have positive personality, they will reduce the tendency towards medical errors. It is recommended that practices that positively support the personal development of healthcare professionals be implemented and that future studies be conducted to investigate their effects on medical errors.

Author contributions

N.Ç. wrote the main manuscript text, N.Ç. prepared tables, N.Ç. reviewed the manuscript.

Funding

No funding.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The approval of Eskişehir Osmangazi University Non-Interventional Clinical Research Ethics Committee (number/date: E-25403353-050.99-313320 / 05.04.2022) were obtained to conduct the study. Written informed consent was obtained from all participants who wanted to participate in the study. During the data collection phase, the principles of the Declaration of Helsinki (as revised in Brazil 2013) were followed.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.