Psychometric evaluation of the Moral Distress Scale

Abstract

Background:

Experiencing moral distress is traumatic for nurses. Ignoring moral distress can lead to job dissatisfaction, improper handling in the care of patients, or even leaving the job. Thus, it is crucial to use valid and reliable instruments to measure moral distress.

Objective:

The purpose of this study was to determine the reliability and the validity of the Persian version of the Moral Distress Scale–Revised among a sample of Iranian nurses.

Research design:

In this methodological study, 310 nurses were recruited from all hospitals affiliated with the Qazvin University of Medical Sciences from February 2014 to April 2015. Data were collected using a demographic questionnaire and the Moral Distress Scale–Revised. The construct validity of the Moral Distress Scale–Revised was evaluated using principal component analysis and confirmatory factor analysis. Internal consistency reliability was assessed with Cronbach’s alpha.

Ethical considerations:

This study was approved by the Regional Committee of Medical Research Ethics. The ethical principles of voluntary participation, anonymity, and confidentiality were considered.

Findings:

The construct validity of the scale showed four factors with eigenvalues greater than one. The model had a good fit (χ²(162) = 307.561, χ²/df = 1.899, goodness-of-fit index = .904, comparative fit index = .927, incremental fit index = .929, and root mean square error of approximation (90% confidence interval) = .049 (.040–.057)) with all factor loadings greater than .5 and statistically significant. Cronbach’s alpha coefficients were .853, .686, .685, and .711for the four factors. Moreover, the model structure was invariant across different income groups.

Discussion and conclusion:

The Persian version of the Moral Distress Scale–Revised demonstrated suitable validity and reliability among nurses. The factor analysis also revealed that the Moral Distress Scale–Revised has a multidimensional structure. Regarding the proper psychometric characteristics, the validated scale can be used to further research about moral distress in this population.

Keywords

Confirmatory factor analysis moral distress psychometric properties reliability validity

Introduction

Due to its nature, nursing is a profession which is faced with several ethical issues.¹ “Moral and ethical dilemmas are an inherent component of nursing practice” (p. 885).² Thus, moral distress (MD) has become one of these ethical challenges that has attracted the attention of many researchers.³ Andrew Jameton introduced moral distress for the first time in 1984. He claims that moral distress is a phenomenon that limits a person to do act in an ethical way, despite him or her having the knowledge about his or her moral obligations.⁴ Following Jameton, Wilkinson⁵ set out to develop the concept of moral distress and defines it as “the existence of negative emotion and mental imbalance which is made due to the individual’s inability to enforce ethical decisions.” In general, moral distress can be considered as mental and emotional pain. In this situation, nurses have the knowledge and the ability to use moral judgment, but they commit moral error due to actual or mental limitations.⁶

Moral distress is traumatic for nurses⁷ and can have negative consequences for a nurse, his or her patients, and the overall health system.⁸ A nurse who is experiencing moral distress can demonstrate symptoms such as sadness, frustration, and anxiety. However, over time moral distress can lead to dissatisfaction, burnout, and a tendency to leave one’s job among nurses.^9

–12 These outcomes not only affect nurses but also influence patients due to the fact that nurses provide poor and inadequate care, which consequently leads to an increased duration in one’s hospital stay.¹³ Corley⁸ has stated that moral distress is a factor which causes one to avoid exposure to sick patients, which therefore decreases the quality of care provided. McCarthy and Deady¹² have also found that fearing to face a patient is a serious and a dangerous complication in situations of moral distress. So, it can be said that moral distress increases the recovery period in patients, which in turn extends the patients’ hospital stay.⁸

Different risk factors can contribute to the onset of moral distress in nurses including the lack of human resources available in clinical environments, poor quality of care provided by doctors and nurses, medical errors and negligence, incompetence of colleagues, and conflicts between medical teams.¹⁴ Also, the condition of a patient and his or her family, receiving insults and contradictory demands, and being mistrusted by a patient and his or her family can all increase levels of moral distress in nurses.¹⁵ Some studies have shown that age, income, work experience, and educational level influence levels of moral distress in nurses.^10,11,16,17 Moreover, investigations at intensive care units (ICUs) and in clinical settings suggest that women experience more moral distress than men.^18,19 Conflicting results have been reported about the severity of moral distress in different wards, but the highest and the lowest levels of moral distress were found at ICUs and surgical wards, respectively.^20
–22

Research has shown that context and culture play an essential role in ethical dilemmas and moral distress.^2,23

–27 This makes each country a unique case to study. Shorideh et al.²⁶ stated that “since moral stressors should be identified in the cultural context, it is necessary to perform national and international research” (p. 465). Thus, recognizing that nurses from different social and cultural backgrounds have different ethical and religious knowledge which influences on their moral distress and ethical dilemmas, this study introduces Iran as an Islamic context that has specific cultural and ethical values, and a healthcare system that all differ from those of other countries.^{6
–8,26
–28} Shahriari et al.²⁷ stated that “The religious discipline and cultural beliefs of the Iranian people have entered the realm of the healthcare system, where moral and ethical issues dominate patient care protocols.”

Islam is the religion of 99.4% of Iranians and among them 90%–95% are Shi’a.²⁹ Iran became an Islamic republic after the Islamic Revolution of 1979. Today, Iran is the only “clerically-ruled” government in the world that mixes religion and state more thoroughly than any other country.³⁰ It is because there is no room for the separation of the “church” and the “state” in the Shiite Islam. The healthcare system was no exception. Immediately after the Islamic revolution, the healthcare system was modified by adopting Islamic ethical values and principles. For example, healthcare providers and nurses were required to provide gender appropriate care in compliance with the laws of the Islamic Republic.^27,31

Moreover, following the revolution, the 8-year Iran–Iraq war, and the US and UN sanctions against Iran, this developing country faced unique challenges with limited resources to manage its healthcare needs. Although there was not any direct sanction on pharmaceuticals and medical equipment, as Iran was not allowed to use the international payment systems, the country faced shortages of drugs for the treatment of more than 30 serious illnesses (e.g. cancer, heart and breathing problems, and thalassemia).^32
–34 In addition, western pharmaceutical companies refused to sell any medical equipment to Iran such as autoclaves which are essential for producing different types of drugs.³⁵ The shortage and limitation of resources increased the pressure on nurses and negatively impacted on their efficiency and effectiveness which in turn led to more ethical dilemmas.^26,31

Furthermore, the work environment and the cultural organization as factors that contribute to moral distress should be considered. Nurses in Iran experience job description ambiguity, heavy workloads, and a serious nursing shortage that affect their levels of moral distress.^26,36 In the meantime, nurses are assigned many different tasks and responsibilities which do not allow them to be engaged in the areas of policy development and governance.²⁶ In addition, the relationship between physicians and nurses in Iran is characterized by a rigid hierarchy of authority:

Nursing is often considered as subordinate to medicine. In addition, most physicians are males, and most of the nurses are females. In accordance with traditional sex roles, physicians are encouraged to be decisive and to act with authority. Studies indicate that physicians view themselves as omnipotent. Nurses are often expected to follow decisions or recommendations given by physicians.²⁶

Finally, although ethics is embedded in the nursing curriculum, there is less of an emphasis on the different aspects of moral distress in the Iranian nursing programs. So, nursing students graduate with little knowledge about this issue.²⁶ Also, in the hospitals there is no specific ethics committee and nurses do not have access to ethics consultation when facing moral dilemmas.

Special instruments are required to measure moral distress.³⁷ The Moral Distress Scale (MDS) is a commonly used tool in this field. For the first time in 2001, this scale was designed by Corley et al.³⁸ to measure moral distress in nurses working in the ICU. It also takes into account the way nurses make critical decisions in clinical settings. On the other hand, Hamric et al.³⁹ attempted to develop and test the Moral Distress Scale–Revised (MDS-R). This scale is in accordance with the standard Corley questionnaire. It was designed to achieve three goals: (1) assessing the main factors of moral distress, (2) using the scale in other wards other than the ICU, and (3) ensuring that the scale is in line with various healthcare laws and regulations. Initially, the MDS was a scale with 32 items, each assessed using a 7-point Likert scale. It was then shortened to 21 items, which were evaluated using a 5-point Likert scale, in the revised version (MDS-R).

The validity of the MDS has been assessed in some countries (e.g. Turkey,⁴⁰ Italy,⁴¹ the United States,^38,39 India,⁴² China,⁴³ and Brazil⁴⁴). However, due to the significant role of culture and context in moral distress in nurses, it is necessary to validate the moral distress measurement instruments in Iran as well.^23

–27 Although researchers have conducted many studies on moral distress in Iran, in most of these studies, the original version of the MDS has been used and the research on the revised version of the scale (MDS-R) is scarce.^1,18,45 Therefore, this study aimed to determine the psychometric properties (i.e. reliability, validity, and factor structure) of the Persian version of the MDS-R in a sample of nurses.

Methods

Design

This methodological study was conducted in all hospitals affiliated to Qazvin University of Medical Sciences between February 2014 and April 2015. The study’s sample consisted of nurses who worked in different wards of hospitals (cardiac care unit, ICU, medical, surgical, operation room, etc.). The overall survey response rate was 81%. In order for a participant to be included in this study, he or she was required to meet the following criteria: (1) he or she must have been working as a nurse for a minimum of 6 months and (2) he or she must not have a history of severe stress (death of relatives, experiencing an accident resulting in the death of a family member, divorce, etc.). The minimum sample size required for conducting a principal component analysis (PCA) is equal to 5–10 times more than the number of items of the intended instrument.⁴⁶ Therefore, 310 nurses were recruited. A demographic questionnaire and the MDS-R were used to collect the data. A demographic and work-related sheet was used to elicit information about nurses’ age, sex, marital status, educational level, job experiences (years), workplaces (wards), monthly income from nursing, shift work, job satisfaction, and tendency to leave the job. Job satisfaction and one’s tendency to leave his or her job were measured using an analogue scale ranging from 0 to 10. On the other hand, the MDS-R was used to assess moral distress in nurses.

First, the English version was translated into Persian after obtaining permission from the developer of the MDS-R. Two bilingual translators with Persian mother tongue independently translated the English MDS-R into Persian. Two other translators, along with the local project manager, then compared these translations and reconciled them into one Persian version. The Persian Version of MDS-R is provided in Appendix 1. The next step involved a backward translation into English. Two native English-speaking translators (bilingual with Persian) translated the Persian version back into English. These translators were unfamiliar with the original version of the MDS-R or its intention or concept. Third, the backward-translated versions were then compared with the original English version by the local project manager to ensure that the Persian version reflected the same item content as the original English version. In the end, this English version of the MDS-R was sent to Dr Hamric. She confirmed the accuracy of the translations and confirmed the similarity of our English MDS-R with the original English version of the MDS-R.

Instruments

The MDS-R consisted of 21 items. It measures an individual’s perceptions to a situation based on (1) intensity of moral distress and (2) frequency of the encountered situation. It includes six parallel versions, three of which focus on adult clinical settings (nurses, physicians, and other healthcare professionals) and three that focus on pediatric clinical settings (nurses, physicians, and other healthcare professionals). For the purpose of this study, the adult version was used. The MDS-R includes two subscales: (1) frequency that ranges from 0 (never) to 4 (very frequently) and (2) intensity that ranges from 0 (none) to 4 (great extent). The data are then computed into a composite score of actual moral distress using a two-part procedure. First, the frequency score is multiplied by the intensity score f × i for each item, and values can range from 0 to 16. Items that are less distressing have low (f × i) scores versus more distressing items, which have higher (f × i) scores.²⁸ Reporting f × i scores allows us to identify individual items or situations that are distressing. Second, the composite or actual moral distress score is obtained by summing each item’s f × i score, resulting in a range of 0–336, where less actual distress is indicated by low composite scores and more actual moral distress is indicated by higher composite scores.

Face validity assessment

The face validity of the Persian version of MDS-R was assessed both qualitatively and quantitatively.

Qualitative face validity assessment

For assessing the qualitative face validity of the Persian version of MDS-R, 10 nurses were invited to assess and comment on the appropriateness, difficulty, relevance, and ambiguity of the items. Moreover, the time required for completing the scale was determined in this step. The scale was amended according to nurses’ comments.

Quantitative face validity assessment

The item impact technique was adopted for assessing the quantitative face validity of the Persian version of MDS-R. Consequently, the same 10 nurses were asked to determine the importance of the items on a Likert-type scale that ranged from 1 (Not important) to 5 (Completely important). The item impact score of each item was calculated using the following formula: Importance × Frequency (%). In this formula, frequency is equal to the number of patients who had ascribed a score of 4 or 5 to the intended item and importance was equal to scores 4 or 5. If the impact score of the item was greater than 1.5, the item was considered to be suitable and was therefore maintained in the scale.^47,48

Content validity assessment

The content validity of the Persian version of MDS-R was also assessed both qualitatively and quantitatively as explained below.

Qualitative content validity assessment

In this step, the Persian version of MDS-R was provided to 15 experts (five practitioner nurses, six nursing doctorates, two psychiatrists, and two clinical psychologists) and they were asked to assess and comment on the wording, item allocation, and scaling of the items.⁴⁹ They provided feedback regarding discrepancies found in certain items between the English and the Persian versions. Based on their comments, a final translation was created.

Quantitative content validity assessment

The quantitative content validity of the scale was assessed through calculating content validity ratio (CVR) and content validity index (CVI) for the items (Table 1). CVR reflects whether the items are essential or not. Accordingly, 15 experts (who were mentioned above) were asked to rate the essentiality of the MDS-R items on a 3-point scale as follows: 1: Not essential; 2: Useful but not essential; and 3: Essential.⁵⁰ The CVR of each item was calculated using the following formula: CVR = (n_e − (N/2))/(N/2). In this formula, N and n_e are, respectively, equal to the total number of experts and the number of experts who score the intended item as “Essential.” According to Lawshe,⁵¹ when the number of panelists is 15, the minimum acceptable CVR is equal to .49.

Table 1.

The CVR and I-CVI for the MDS-R items.

Items	CVI			CVR
Items	Simplicity (1–4)	Relevancy (1–4)	Clarity (1–4)	Essential (1–3)
1. Reduction of the quality of care to the lower level than the optimal level as a result of the pressures from administrators or insurers to reduce costs	.86	.8	.93	.86
2. I witnessed healthcare providers giving “false hope” to a patient or family	.86	1	.8	1
3. Follow the family’s wishes to continue life support even though I believe it is not in the best interest of the patient	.86	.93	.8	.86
4. Initiate extensive life-saving actions when I think they only prolong death	.86	1	.93	1
5. Follow the family’s request not to discuss death with a dying patient who asks about dying	1	1	1	1
6. To carry out the physician’s orders even in the cases when I know the test and required treatments are unnecessary (or the required tests and treatments …)	.86	.93	.8	1
7. To continue to take care of a patient for whom there is no hope to survive and who kept alive by ventilator while no decision is made to disconnect them from the ventilator	.86	.8	.8	.86
8. Not to take action when I know that a physician or the nurse colleague has made a medical error and not report it	.93	1	.93	1
9. To assist a physician who, in my opinion, does not have the skills to provide the appropriate level of care	.93	1	.8	.86
10. Be required to care for patients when I feel I do not have the adequate competence in the care	.86	1	.93	1
11. I have witnessed that medical students perform painful procedures on patients solely to increase their skill	.86	1	.8	.86
12. Provide care that does not relieve the patient’s suffering because the physician fears that increasing the dose of pain medication will cause death	1	1	1	1
13. Follow the physician’s request not to discuss the patient’s prognosis with the patient or family	.86	1	.86	1
14. Increase the dose of sedatives/opiates for an unconscious patient that I believe could hasten the patient’s death	.86	.93	.86	1
15. Take no action about an observed ethical issue because the involved staff member or someone in a position of authority requested that I do nothing	.86	1	.8	1
16. Follow the family’s wishes for the patient’s care when I do not agree with them, but do so because of fears of a lawsuit	.93	1	.8	.86
17. To work with nurses and other members of the team of healthcare providers who do not have the adequate competence to satisfy the patient’s care needs	.86	1	.93	1
18. I have witnessed that the quality of care is reduced due to poor team communication	.86	1	.8	.86
19. To ignore the situations in which adequate information was not given to the patient for informed consent	1	1	1	1
20. Watch patient care suffer because of a lack of provider continuity	.86	1	.86	1
21. To work with other levels of nursing or care providers that, in my opinion, are unsafe	.86	.93	.86	1

CVI: content validity ratio; CVR: content validity index.

On the other hand, CVI shows the degree to which the items of the intended scale are simple, relevant, and clear. CVI can be calculated for each item of a scale (Item-level or I-CVI) and for the overall scale (Scale-level or S-CVI). Accordingly, we asked the same 15 panelists to rate the simplicity, relevance, and clarity of the MDS-R items on a 4-point scale from 1 to 4. For instance, the four points for rating the relevance of the items were “Not relevant,” “Somewhat relevant,” “Quite relevant,” and “Highly relevant” which were scored as 1, 2, 3, and 4, respectively. The I-CVI of each item was calculated by dividing the number of panelists who had rated that item as 3 or 4 by the total number of the panelists. Lynn et al.⁵² noted that when the number of panelists is equal to 15, the items which acquire an I-CVI value of .79 or greater are considered to be appropriate.

Construct validity assessment

The construct validity of the Persian version of the MDS-R was assessed by conducting PCA with oblique rotation. The Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity were used to check the appropriateness of the study sample and the model. The number of components was determined based on eigenvalues and scree plot. Items with absolute loading values of .3 or greater were regarded as appropriate.⁵³ Next, the results from the PCA were confirmed and validated using confirmatory factor analysis (CFA) (36).

Reliability assessment

The reliability of the Persian MDS-R was assessed by evaluating its internal consistency and by calculating Cronbach’s alpha. Alpha values of .7 or greater show satisfactory internal consistency.⁵⁴

Ethical consideration

The study was approved by the Ethics Committee of Qazvin University of Medical Sciences, Qazvin, Iran (QUMS.REC.1394.11). Nurses were informed about the study’s aims and procedures. Moreover, they were ensured that participation was voluntary and that it would not affect the course of their work. The confidentiality of the nurses’ information was guaranteed. Informed consent was obtained from all participants.

Statistical analysis

All statistical analyses were performed using SPSS v. 22.0 (SPSS Inc., Chicago, IL, USA). Missing values were replaced with the mean. A p value of less than .05 was considered to be statistically significant.

Results

The demographic profile of the participants is shown in Table 2. The dataset consisted of 310 male (n = 71) and female (n = 239) Iranian nurses, aged between 20 and 59 years (M = 33.82, SD = 8.06) with BSc (74.5%). In total, 59.4% of the participants were married and 40% were single.

Table 2.

Characteristics of the respondents.

Characteristic	N (%) or mean (SD)
Gender
Male	71 (22.9%)
Female	239 (77.1%)
Age	33.82 (8.06)
Marital status
Single	124 (40%)
Married	184 (59.4%)
Widow	2 (.6%)
Education
Associate degree	20 (6.5%)
BSc	231 (74.5%)
MSc	50 (16.1%)
PhD	9 (2.9%)
Job experience	10.35 (7.95)
Workplace
CCU	44 (14.2%)
ICU	73 (23.5%)
Emergency	41 (13.2%)
Medical	63 (20.3%)
Surgical	27 (8.7%)
Pediatric	9 (2.9%)
Dialysis	4 (1.3%)
Nursing office as supervisor	23 (7.4%)
Operation room	26 (8.4%)
Income	1,798,000 (654,620)
Shifts
Morning fix	59 (19%)
Evening fix	17 (5.5%)
Night fix	36 (11.6%)
Rotation	198 (63.9%)

SD: standard deviation; CCU: cardiac care unit; ICU: intensive care unit.

Table 3 shows the results of a PCA with oblique rotation on the moral distress scale. Oblique rotation allows components to be correlated.⁵⁵ Using the eigenvalue greater than one criterion, PCA extracted five components consisting of a 6-item component (comprising items 11, 17, 18, 19, 20, and 21; eigenvalue = 6.736), a 5-item component (comprising items 3, 4, 5, 7, and 10; eigenvalue = 1.697), a 4-item component (containing items 6, 8, 9, and 15; eigenvalue = 1.372), another 4-item component (containing items 12, 13, 14, and 16; eigenvalue = 1.206), and a 2-item component (comprising items 1 and 2; eigenvalue = 1.105), together accounting for 57.696% of the variance.

Table 3.

Exploratory factor loadings of items in the MDS-R.

Questions	Factors
Questions	F1	F2	F3	F4	F5
18. Witness diminished patient care quality due to poor team communication	.881
21. Work with levels of nurse or other care provider staffing that I consider unsafe	.874
20. Watch patient care suffer because of a lack of provider continuity	.872
17. Work with nurses or other healthcare providers who are not as competent as the patient care requires	.837
19. Ignore situations in which patients have not been given adequate information to insure informed consent	.561
11. Witness medical students perform painful procedures on patients solely to increase their skill	.366
4. Initiate extensive life-saving actions when I think they only prolong death		.744
5. Follow the family’s request not to discuss death with a dying patient who asks about dying		.708
7. Continue to participate in care for a hopelessly ill person who is being sustained on a ventilator, when no one will make a decision to withdraw support		.698
3. Follow the family’s wishes to continue life support even though I believe it is not in the best interest of the patient		.693
10. Be required to care for patients I don’t feel qualified to care for		.453
9. Assist a physician who, in my opinion, is providing incompetent care			.838
8. Avoid taking action when I learn that a physician or nurse colleague has made a medical error and does not report it			.804
6. Carry out the physician’s orders for what I consider to be unnecessary tests and treatments			.540
15. Take no action about an observed ethical issue because the involved staff member or someone in a position of authority requested that I do nothing			.383
14. Increase the dose of sedatives/opiates for an unconscious patient that I believe could hasten the patient’s death				.908
16. Follow the family’s wishes for the patient’s care when I do not agree with them, but do so because of fears of a lawsuit				.642
12. Provide care that does not relieve the patient’s suffering because the physician fears that increasing the dose of pain medication will cause death				.507
13. Follow the physician’s request not to discuss the patient’s prognosis with the patient or family				.457
1. Provide less than optimal care due to pressures from administrators or insurers to reduce costs					.811
2. Witness healthcare providers giving “false hope” to a patient or family					.489

Table 4 presents the correlations between the extracted components (which vary from −.028 to .563). Thus, maximum overlap between the five components was 31.7%, indicating that these components should be conceptualized as distinct components. Using Cronbach’s alpha, reliability coefficients for F1 (.853) and F3 (.711) indicate a good reliability. Moreover, Cronbach’s alpha coefficients for F2 (.686) and F3 (.685) indicate an acceptable reliability.^56
–58 According to Kline,⁵⁶ a Cronbach’s alpha coefficient below .7 in psychological constructs can be due to the diversity of the constructs being measured. However, the unacceptable Cronbach’s alpha for F5 (.385) suggests deleting the 2-item construct.

Table 4.

Correlation between MDS-R factors.

Factors	F1	F2	F3	F4	F5	Cronbach’s alpha
F1	–					.853
F2	.462	–				.686
F3	.563	.431	–			.685
F4	.447	.367	.362	–		.711
F5	.091	.001	−.028	.157	–	.385

Subsequently, this study developed the factor structure based on the results obtained from the PCA and validated the model using maximum likelihood CFA.⁵⁸ Based on the modification indices, two pairs of measurement errors between measured items of the first factor, one pair of the third factor items, and one pair of the measurement errors from the fourth factor were allowed to freely covary. The results showed that, after reviewing model modification indices for sources of model misfit, the measurement model consisting of five factors has a good fit (χ²(175) = 370.850, p < .05, χ²/df = 2.119, goodness-of-fit index (GFI) = .901, comparative fit index (CFI) = .905, incremental fit index (IFI) = .906, and root mean square error of approximation (RMSEA) (90% confidence interval (CI)) = .060 (.052–.069)). Most item loadings were greater than .5; however, items 5, 10, 14, and 1 loaded weakly on the second (.49), second (.40), fourth (.42), and fifth (.44) factors, respectively. After deleting the weak items from their respective factors, the fifth factor only comprised two items (items 1 and 2); therefore, it was deleted from the model as well. In the new model, item 15 from the third factor was deleted due to a factor loading of .48.

Finally, CFA was rerun with only 4 factors and 15 items. The results showed that the final model fit improved considerably (Δχ² (Δdf = 13) = 63.289, p < .05). The final model factor loadings were greater than .5 and statistically significant (z-value range = 7.473–10.776). Moreover, the model showed a good fit (χ²(162) = 307.561, χ²/df = 1.899, GFI = .904, CFI = .927, IFI = .929, and RMSEA (90% CI) = .049 (.040–.057)).

In order to assess the ability to replicate the results and to test the invariance of the model across different groups, this study ran multi-group analysis comparing the final model among participants with a low income (n = 167) and a high income (n = 143). The median level of income was used to split the samples into two groups. The prerequisite for assessing the invariance of the model was that the unconstrained model fits each sub-sample separately. The results indicate a good fit for both low income (χ²(81) = 131.314, p < .05, χ²/df = 1.621, GFI = .910, CFI = .945, IFI = .947, Tucker–Lewis index (TLI) = .929, and RMSEA (90% CI) = .061 (.041–.080)) and high income (χ²(81) = 129.331, p < .05, χ²/df = 1.597, GFI = .896, CFI = .935, IFI = .937, TLI = .916, and RMSEA (90% CI) = .065 (.043–.085)) participants. Next, the unconstrained and constrained models were compared. The results showed that both unconstrained (χ ²(162) = 260.655, p < .05, χ ²/df = 1.609, GFI = .903, CFI = .941, IFI = .942, TLI = .923, and RMSEA (90% CI) = .044 (.034–.053)) and constrained (χ ²(173) = 294.228, p < .05, χ ²/df = 1.588, GFI = .898, CFI = .939, IFI = .940, TLI = .926, and RMSEA (90% CI) = .044 (.034–.053)) models fit the data well and therefore there is no significant difference in goodness of fit between them (χ ²(11) = 14.064, p = .229). This shows that the model structure was invariant across different income groups.

Discussion

The purpose of this study was to evaluate the psychometric properties of the Persian version of the MDS-R in Iranian nurses. Exploratory and confirmatory factor analyses were used to investigate and then confirm the underlying structure of the scale. Exploratory factor analysis showed that the MDS-R is a multidimensional construct among nurses. Based on PCA and oblique rotation, a five-factor solution was selected, explaining 57.696% of the variance. Karagozoglu et al.,⁴⁰ who investigated the construct validity using factor analysis, showed that the present scale is a one-dimensional structure. Hamric et al.³⁹ also confirmed the one-dimensionality of the scale.

CFA suggested that one of the factors should be deleted to improve the model fit and the validity of the factors. The confirmed four factors contributed significantly to their respective items. Moreover, the final four-factor model was invariant across different groups.

One of the five factors identified in the exploratory factor analysis was the role of healthcare providers. In fact, factors such as the poor collaboration of the medical team, presence of insecure nurses who do not have enough control to provide care to patients, can be effective in creating and exacerbating moral distress. Many studies have stated that the team members and managers of health services are often faced with problems involving patient care and treatment decision-making. These issues may be related to economic or political factors present in the medical center.^59,60 On the other hand, Gutierrez⁶¹ showed that the inability of nurses to demonstrate courageous behaviors in the medical team makes it difficult for them to communicate effectively with patients and other members of the treatment team. Thus, they experience moral distress.⁶¹ Another study showed that an increased risk of harming the patient and the inadequacy of the responsibilities of nurses can lead to increases in moral distress in nurses and their colleagues.⁶²

The results of an exploratory factor analysis showed that the second factor is associated with the futile care provided by members of the healthcare team. In fact, issues related to ethical decisions, do not resuscitate (DNR), and death with dignity impose the highest levels of moral distress on nurses. These factors play a role in causing or exacerbating moral distress in nurses.⁶³ In this regard, Rice et al.⁶⁴ state that providing care to maintain life, despite awareness of its ineffectiveness, promotes moral distress in nurses. In another study, issues related to keeping transplant patients alive, contrary to patients and their families, are stressful for nurses.⁶⁵ Hamric and Blackhall⁶⁶ claimed that the most stressful situations are when medical care is delayed in dying patients and when nobody makes a decision to end his or her life. As it was shown, items 5 and 10 weakly contributed to the second factor and were therefore deleted from the structural model. Item 5 was about a situation where the patient’s family requested that the nurse not discuss death with their dying patient. Indeed, in Iranian culture, giving hope even if it is unrealistic is admired.²⁶ Thus, following the patient’s family’s request to provide incomplete information to the patient in order to keep him or her hopeful is not against Iranian nurses’ culture which in turn may weaken the factor loading on this item. Item 10 was about situations where nurses were required to care for a patient that he or she did not feel qualified to care for. The weak factor loading on this item can be due to the job description ambiguity, a serious nursing shortage, and lack of human resources in Iran. Moreover, because of a rigid hierarchy between nurses and physicians, physicians do not consult nurses about the patients’ treatment and/or condition.^26,36 Thus, caring for a patient when one is not qualified to do so has become a common practice and an accepted organizational culture norm in hospitals in Iran.

The third factor can be attributed to obeying the doctor’s orders without question and working with unsafe colleagues. In fact, providing inadequate care or prescribing tests and drugs which will not improve a patient’s quality of life were identified as factors that can contribute to nurses’ experiences of moral distress. Erlen⁶⁷ reported that moral distress is caused by organizational constraints such as the mandatory documentation of medical care and policies. Results of a study showed that regardless of the lack of skilled and trained manpower, most nurses’ moral distress includes invasive treatment, unnecessary tests, cheating in examinations, and inadequate and incomplete treatment. Obeying the physician’s orders and low functional independence in nurses decreases their level of self-confidence and motivation.¹² This can cause nurses to lose their decision-making power and job opportunities. Also, despite their professional expertise in the field, they may be unable to take action in addressing the current situation.⁶⁸ In such circumstances, the nurses’ moral distress can be intensified. The factor loading for item 15 was weak and was therefore dropped from the model. The item was about a situation in which a nurse has to refrain from taking action when he or she observes an ethical issue because someone who holds a powerful position of authority has requested that he or she do nothing. From the lens of Hofstede’s cultural model, Iran is considered to be a collectivistic society.⁶⁹ In a collectivistic culture, managers and people who hold power play the parents role of the organization members with the assumption that they are not self-serving and that they are aware of their subordinates’ (nurses here) needs and concerns. Instead, nurses as subordinates appreciate the managers’ authority and orders and interpret them as being a form of protection that takes their best interests into account.⁶⁹ Thus, item 15 had a very weak factor loading.

Based on the items in the fourth factor identified in the exploratory factor analysis, it appears that the condition of the patient and his or her family, as well as the unavailability of doctors in some areas of care, are factors that may strengthen moral distress in nurses. Actually, the lack of trust that a patient and his or her family may demonstrate to their treatment team may predispose a nurse to moral distress.¹⁵ Hanna⁷⁰ reported that a disagreement between nurses and patients’ families regarding their views about patient care is an important factor that may lead to the onset of moral distress. Moreover, sometimes, doctors may have the tendency to increase the dose of a patient’s drug because of its side effects. This may frustrate some nurses because they see the pain and suffering that their patient is going through, as a result of their medication, but they are unable to prescribe medication to alleviate these symptoms. They must therefore act in accordance with the doctor’s orders.⁷¹

In the exploratory factor analysis, the fifth factor relates to the limitations of the organization. It seems that managers’ efforts to reduce costs lead to decreases in the quality and adequacy of care provided to patients. Ersoy and Akpinar⁷² stated that the organizational situation is one of the factors that causes moral distress to occur among nurses. The lack of organizational support and budget constraints are some examples of these organizational factors.⁷² The results of a qualitative study also show that treating the patient as an object to meet organizational needs is a major factor in the onset of moral distress.⁵ Therefore, these factors all affect the quality of care provided by nurses and create conflicts in nursing care.⁸

The reliability coefficients of the MDS-R showed that the instrument has good reliability among nurses, especially when the reliability was calculated separately for each factor. It is clear that when Cronbach’s alpha is closer to 1, the internal consistency of the items will be more homogeneous. In the case of low alpha values, the items should be reviewed in order to determine which ones should be removed to increase its value.⁷³ The results of this study showed that all factors (except the fifth one) have good reliability. The unacceptable Cronbach’s alpha for F5 led us to remove the 2-item construct. In the MDS-R by Hamric et al.³⁹ the Cronbach’s alpha coefficient for nurses, physicians, and all participants were .89, .69, and .88, respectively. Test–retest reliability and the Cronbach’s alpha coefficient of the Turkish version of the scale were determined to be .82 and .85, respectively.⁴⁰ In fact, the Cronbach’s alpha value indicates good internal consistency of the scale and it also shows an adequate correlation between the questions. Therefore, it can be assumed that the items that comprise the scale assess similar concepts.

Conclusion

This study confirmed adequate psychometric properties and factor structure of the MDS-R. With this structure, the scale can be used as a valid and reliable tool for the assessment of moral distress experienced by Iranian nurses working in different wards of hospitals.

Footnotes

Acknowledgements

The authors want to extend their sincere gratitude to the nurses who helped to make this research possible.

Conflict of interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by Qazvin University of Medical Sciences, Qazvin, Iran (Grant No. QUMS.REC.1394.11) and an extension of Taylor's University Research Grant (TRGS/ERFS/1/2015/TBS/014).

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Psychometric evaluation of the Moral Distress Scale–Revised among Iranian Nurses

Abstract

Background:

Objective:

Research design:

Ethical considerations:

Findings:

Discussion and conclusion:

Keywords

Introduction

Methods

Design

Instruments

Face validity assessment

Qualitative face validity assessment

Quantitative face validity assessment

Content validity assessment

Qualitative content validity assessment

Quantitative content validity assessment

Construct validity assessment

Reliability assessment

Ethical consideration

Statistical analysis

Results

Discussion

Conclusion

Footnotes

Acknowledgements

Conflict of interest

Funding

Appendix 1

References