Quality of Life in Nurses Working in Neyshabur Hospitals

The world health organization (WHO) has defined quality of life (QOL) as “an individual’s perception of his/her position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” (1). Recently, many general instruments have been used to measure QOL in different groups (i.e., population, patients, workers, etc). One of such instruments is the SF-36 questionnaire, a generic instrument translated and validated in Iran by Montazeri (2). In this regard, QOL of people with a health problem (i.e., cancer, diabetes, hypertension, etc) was evaluated in many studies (3-29); But there are few studies that have evaluated the QOL of health care workers, for example nurses, who provide health care services for patients.

Nurses are among the greatest providers of services in the health care system and in their work settings, they may be exposed to a wide array of chemical, biological, psychosocial (i.e., stress, depression, etc) and physical hazards (i.e., injuries, transmission of infectious diseases, etc). Consecutively, such conditions may affect the QOL of nurses. It is noteworthy that nurses provide higher quality services for their patients when they are healthy and possess desirable QOL. Therefore, it is important to pay particular attention to nurses’ general health conditions and QOL.

The objective of this study was to assess the QOL in nurses working in Neyshabur hospitals and some factors associated with it, with the use of the SF-36 scale.

In this cross-sectional study, data were collected from February to April 2012 in Neyshabur hospitals (22 Bahman and Hakim) in Neyshabur (A city in Northeast of Iran). Of all nurses (n = 220), 22 were excluded because they refused to participate in the study. Therefore, 198 questionnaires were collected (response rate = 90%). All of participants provided informed consent after the purpose of study was explained for them. Inclusion criteria for participating in the study included the nurses who work in Neyshabur hospitals in addition to their agreement for participation.

In total, 198 nurses filled out the SF-36 questionnaire in this study. Ten questionnaires had more than 20% of missing data and thus were excluded from the study. The analysis was restricted for the remaining 188 respondents. Some of the characteristics of study population are shown in Table 1. The mean age of female and male participants was 29.5 and 36.2 years respectively and this difference was statistically significant (P < 0.001) .

Table 2 presents correlations between eight subscales of SF36; as observed, there were statistically significant correlations between all subscales (P < 0.05). There was also relations between all subscales (P < 0.05). There was also a significant correlation between PCS and eight subscales in addition to MCS and eight subscales of SF36. As Table 3 shows, the total mean score of SF-36 was 64.7 and among the different subscales of SF-36, the lowest and the highest mean scores were found for RE subscale (Mean = 55.9) and PF subscale (Mean = 77.3 ), respectively. The mean scores of the PCS, MCS, eight subscales and total of SF-36 according to sex, age, marital status, employment status, income level, years in occupation, chronic disease existence, family size, number of children, shift type and house ownership are presented in Table 3. As Table 3 shows, there were significant differences between different states of some variables (age, marital status, employment status, years in occupation, chronic disease existence and house ownership) in six subscales of SF-36 (P < 0.05) . Table 4 presents the results of Backward Multiple Linear Regression model; variables with significant relations were as follows: years in occupation, employment status and house ownership. Table 4 shows the positive and negative relations in this study. Positive relations included: between RP subscale and employment status, between the PCS and employment status. Negative relations included: between PF, VT, SF, BP, GH subscales and years in occupation, between the MCS and years in occupation, between RP subscale and house ownership. We did not observe any significant relation between various factors and RE or MH subscales after use of regression model.

The present study was designed to assess the QOL in nurses working in Neyshabur hospitals and some factors associated with it, with the use of the SF-36 scale. According to our findings, the total mean score of SF-36 was 64.7 that indicates a relatively moderate QOL in Neyshabur’ nurses. In a study conducted by Assarrodi, which was conducted to investigate the relation between spiritual well-being and QOL in nurses, they observed that the mean score of QOL was 64.38 (32). In another study conducted by Allaf Javadi in order to compare the QOL in nurses of special care and internal surgical wards, they observed that mean scores of QOL were 69.66 and 62.17, respectively (33).

Among the different subscales of SF-36, the lowest mean score was found for RE subscale (55.9%), implying that more than 44% of Neyshabur’ nurses, had problems with their work or other regular daily activities as a result of emotional problems (such as feeling depressed or anxious) in the last four weeks. Moreover, the highest mean score was shown for PF subscale (77.3%) indicating that lower than 23% of physical activities of Neyshabur’ nurses, was limited a lot or limited a little. In a study conducted by Aghamolaei in order to investigate the determinants of health-related quality of life (HRQOL) in general population living in Bandar Abbas, the lowest and the highest mean scores were found for GH and RE subscales, respectively (34). Additionally, assarrodi showed that the lowest and the highest mean scores were observed for RE and RP subscales, respectively (32). Daher et al performed another study to assess the HRQOL among Iraqis living in Malaysia, and they observed that the lowest and the highest mean scores were found for VT and PF subscales, respectively (35). In this study, we observed that the mean score of PCS is more than the mean score of MSC, implying that participants in this study had fewer problems in physical component in compare with mental component. This findings confirm the results of Assarrodi, Allaf Javadi and Daher’ studies (32, 33, 35). But the report of Aghamolaei showed that the mean score of PCS is lower than the mean score of MSC (34).

As Table 3 shows, single/divorced participants reported higher QOL in compare to married participants in the PCS, MCS and eight subscales of SF-36, and the differences were statistically significant (except in RE and MH sub-scales). In the report of Aghamolaei, they observed that marital status could not significantly decrease the scores of SF-36 in both mental and physical aspects (34). But in Tajvar’s report married participants had higher HRQOL in compare to single people (36).

As Table 4 shows, years in occupation was the most important factor affecting the QOL of study population in total and also in MCS and five subscales (PF, VT, SF, BP and GH) of SF-36. Years in occupation was negatively related to MCS and subscales such as: PF, VT, SF, BP and GH. This subject indicates that having more work experience reduced QOL in some physical and mental subscales. Employment status was the other factor that was associated with PCS and RP subscales. Such results indicate that employment status was related only with physical subscale. House ownership was another factor that was associated with RP subscale. In the study conducted by Aghamolaei, sex, age, education and employment status were significantly related to the PCS and MCS (34). Sex was significantly associated with PCS and marital status was associated with MCS in the study conducted by Daher (35). Thumboo observed that educational level and housing type (markers of socio-economic status) were also associated with SF-36 scores (37).

This study has several limitations: First, causality between the compared variables could not be concluded due to the cross-sectional design of the study. Second, most variables were assessed by self-report and desirable responses might have been given. Third, 22 persons were excluded from the study because of refusal to participate in the study and 10 persons were also excluded because their questionnaires had more than 20% of missing data.

From the findings of this study, it appears that Neyshabur’ nurses have SF-36 scores that might indicate a relatively moderate QOL and the findings also confirm that years in occupation is the major factor that affects their QOL. Thereby, interventional programs should be designed and implemented by Neyshabur Faculty of Medical Science, in order to help nurses to improve their QOL and general well-being, especially among nurses with more work experience.