Skip to main content

Musculoskeletal pain among medical residents: role of workplace safety climate and sexual harassment

Abstract

Background

Workplace factors are important predictors of occurrence of musculoskeletal pain among different occupational populations. In healthcare, a psychologically unsafe work environment can negatively affect the emotional, physical and psychological well-being of physicians. This study aimed to examine the relationship between workplace violence, sexual harassment and musculoskeletal pain among Egyptian physicians in their years of residency.

Methods

We distributed an online self-administered questionnaire to 101 residents working in various healthcare sectors in Egypt. It included sections on demographic data, working conditions, widespread pain index (WPI), pain interference short-form, workplace violence and harassment questionnaire, psychosocial safety climate questionnaire (PSC) and sexual harassment climate questionnaire.

Results

All residents had at least one painful site on the WPI (range 1–11). The mean WPI was 3.5 ± 2.4, and 39.6% satisfied the criteria of having widespread pain by having at least 4 pain sites. Widespread pain index showed a weak statistically significant negative correlation with workplace PSC score (rho = − 0.272, p = 0.006), and a statistically significant weak positive correlation with the calculated total abuse index (rho = 0.305, p = 0.002). Workplace violence and abuse, as measured by a calculated abuse index was the only significant predictors of widespread pain among residents.

Conclusion

WPV was found to be a predictor of musculoskeletal pain among medical residents. Healthcare organizations need to address WPV by employing preventive strategies to minimize its hazardous effects and ensure a safe working environment for physicians.

Peer Review reports

Background

Musculoskeletal pain is a common symptom among healthcare workers, including physicians. Several studies have reported a high prevalence of musculoskeletal pain among physicians across different specialties [1,2,3,4,5]. Various workplace risk factors have been implicated in the occurrence of musculoskeletal pain among healthcare workers. These include ergonomic factors and physical job demands [6, 7], long working hours and night shifts [8], psychosocial and emotional burdens of the profession [3] and perceptions about workplace support [7]. A recent study conducted in Egypt found the prevalence of musculoskeletal disorders among physicians to be as high as 74% [9]. In addition to the previously mentioned factors, workplace violence (WPV) seems to play a role in the occurrence of musculoskeletal pain among healthcare workers [10]. A large survey in United States among nurses revealed that the prevalence of low back pain was as high as 70% among those who experienced WPV, compared to 40% among non-victimized workers [11].

Workplace violence (WPV) is a distinguished global occupational hazard that faces workers in the health care system, whether from the patients or their relatives, or even from other physicians and co-worker [12, 13]. The International Labour Organization defines WPV as “a range of unacceptable behaviours and practices, or threats thereof, that aim at, result in, or are likely to result in physical, psychological, sexual or economic harm…”. WPV also encompasses gender-based violence and harassment, which means violence and harassment directed at persons because of their sex or gender, or affecting persons of a particular sex or gender disproportionately [14].

Nearly all forms of WPV are prevalent among physicians. For example, a systematic review in 2019 reported that the overall prevalence of various types of WPV (physical, verbal and sexual) among physicians was 69%; 38% of them were classified as severe forms of violence [13]. In the same line, a study conducted in the United States found that 20 to 30% of the physicians endured racially and sexist offensive remarks, or unwanted sexual intimidations by patients, their relatives and other visitors [15]. It was noted that violence against healthcare workers has increased during the COVID-19 pandemic and has been increasing still since then [16, 17]. A recent study conducted in Egypt reported that approximately 43% of physicians were victims of psychological violence and 10% were victims of physical violence during the COVID-19 pandemic. The study also reported that the majority of physicians did not report the violent incidents [18].

Workplace violence is a significant problem worldwide, and more so in developing countries. A systematic review on WPV in African countries found the prevalence of WPV against physicians to range from 9 to 100%, where the highest reports were from South Africa (54–100%) and Egypt (60–86%) [19]. The study also reported that most African countries lacked policies addressing management strategies. Another Egyptian study indicated that about 80% of physicians who reported incidents of WPV were not satisfied with the actions taken by the authorities [20]. Despite the fact that the Egyptian law penalizes WPV against government officials, including healthcare workers, lack of polices at the institutional level, fear of punishment, and long legal procedures maintain low reporting rates [21, 22].

WPV can lead to profound negative consequences for physicians including burnout, depression, increasing anxiety, and emotional distress [23, 24]. In addition, it affects the quality of service and was found to motivate early retiring from work [25, 26]. Surprisingly, this could happen not just to the victimized physicians, but also to their co-workers who are in-directly assaulted [27]. In addition to mental health issues, previous studies have mentioned the occurrence of physical symptoms as a response to WPV [22, 28]. One of the reported physical symptoms by victims of violence is musculoskeletal pain. Studies have shown that most of those who are being repeatedly violated suffered moderate to severe pain, where the pain in more than half of them affected their work and/or sleep. Moreover, the musculoskeletal pain outcomes were 1.5 to 2.5 times more frequent in those subjected frequently to physical violence than their colleagues who were not [10].

Despite the high prevalence of musculoskeletal pain and WPV among physicians, few studies have examined the relation between the two phenomena. Additionally, the local context in Egypt represents a unique context, and thus warrants further investigation. For example, in the last few years, an alarming number of Egyptian residents have emigrated to other countries. The Egyptian Medical Syndicate reports that Egypt has lost more than 5% of its working physicians in a period of 3 years (2015–2018) [29]. Among the factors that were listed as negative motivators, were verbal and physical assault of physicians [30]. As mentioned previously, estimates of WPV among healthcare workers in Egypt range from 27 to 86% [18, 19, 31, 32]. Therefore, we conducted this study to investigate the relationship between workplace violence, including sexual harassment, and musculoskeletal pain among Egyptian medical residents. We also aimed to explore the association between musculoskeletal pain and different demographic and work-related determinants.

Methods

This was a cross-sectional survey study on medical residents working in the private and public sector hospitals in Egypt. We used an online self-administered structured questionnaire. We shared the questionnaire on social media platforms that are dedicated to residents all over Egypt. An informed consent form was included on the first page of the online survey for all participants. Participants were directed to the questionnaire after agreeing to participate. Proceeding beyond the first page implied consent.

Participants and procedure

We recruited physicians in their residency training years who work in public and private Egyptian Hospitals. Public hospitals included university hospitals as well as hospitals affiliated to the Egyptian ministry of health and population. We used convenience sampling technique, since it was not possible to obtain a sampling frame. An online survey was disseminated through a link shared on different social media platforms from March 2021 to August 2021. The platforms included Facebook and Whatsapp groups dedicated to residents working in hospitals and primary care facilities of the ministry of health all over Egypt as well as social media groups whose members were residents in university hospitals including Cairo, Ain Shams and Alexandria Universities (located in northern Egypt), Suez Canal and Portsaid Universities (located in East Egypt), Sohag and Assiut Universities (located in the South of Egypt). In addition, participants who completed the survey were asked to share the link with their colleagues. We included medical residents of both genders, who have been on the job at least 3 months, so that they would have enough experience to answer the questionnaire. The study excluded those who were known to have a psychiatric diagnosis, or chronic pain disorders (fibromyalgia, Rheumatoid Arthritis, chronic back pain, etc.) before entering the residency program, to ensure that the musculoskeletal pain reported by the participants occurred after starting their residency.

Sample size determination

We used G*Power application version 3.1.9.7 using Correlation bivariate normal model method, with significance level 95%, a power of 80%, using an effect size (correlation coefficient) 0.3 (medium correlation). Calculation revealed sample size of 84, adding 20% (17 subjects) counting for non-response rate, the sample size was 101 [33].

Ethical considerations

Ethical Approval: The study was approved by the research ethics committee of the Faculty of Medicine, Suez Canal University, Egypt (Reference: 4485#),

Informed Consent: The Google forms link included an information page about the purpose and methods of the study. An informed consent was secured by clicking the “agree to participate” button at the end of the information sheet.

Study tools

We used an online questionnaire that consisted of 4 sections:

Section 1: socio-demographic data

These included age, sex, marital status, type of workplace, medical specialty, level of postgraduate education, working hours, and employment status.

Section 2: musculoskeletal pain

  1. A.

    Widespread Pain Index

For assessment of musculoskeletal pain, we used the Widespread Pain Index (WPI) which is employed in the diagnosis of chronic pain syndromes. The index was originally developed as part of the 2010 American College of Rheumatology classification criteria for Fibromyalgia [34]. Since then, it has been used more widely to assess widespread pain in studies of general pain conditions [35]. The index was shown to be highly sensitive and accurate in assessment of widespread chronic pain [36, 37]. The WPI includes a list of 19 possible painful body areas. It gives a total score that ranges from 0 to 19 [35]. In addition to identifying separate pain sites, the index can also identify subjects with widespread pain. Those are subjects with a minimum of 4 painful sites [38].

  1. B.

    Patient reported outcomes measurement information – pain interference (PROMIS-PI) short form [39]

The PROMIS-PI short form was developed using Item Response Theory [39]. The 6 items of the short form were chosen from the original PROMIS- PI 41 item bank. Each item is scored on a 5-point Likert scale ranging from “not at all” to “very much”, except for the last item which enquires about socializing with others and ranges from “never” to “always”. The questionnaire has good construct validity and precision [40].

Section 3: violence and harassment

This section was adopted from previous research [41, 42]. Al-Shafaee et al. (2013) used this set of items to quantify the frequency of different forms of violence, including verbal abuse, physical abuse, sexual harassment, and academic misuse of power in a cohort of medical interns. The same items were used for the purpose of quantifying violence in this study. A 7- point Likert Scale was used with score assigned to each response where “Not at all” =0; “Less than once a month” =1; “Once a month” =2; Few times a month” =3; “Once a week” =4; and “Few times a week” =5; and “Everyday” =6.

We calculated a unique index for each type of abusive behaviors by adding the total score of its component divided by the total number of items multiplied by 6. A total abuse index was calculated by adding the indices for the 4 types of abusive behaviors (verbal abuse, physical abuse, sexual abuse or harassment and academic misuse of power).

Section 4: workplace climate

This section assessed the residents’ perception towards workplace environment regarding the psychosocial aspect and the extent of feeling secure in their workplace. For this section, we used 2 questionnaires.

  1. A.

    Psychosocial Safety Climate (PSC) Questionnaire [43]:

This questionnaire is a 12-item short instrument that is used to measure the main four domains of safety climate, namely Senior management commitment, Management priority, Organizational participation, and Organizational communication with employees regarding their psychosocial safety and well-being. The items are measured using a 5-point Likert format ranging from 1 (strongly disagree) to 5 (strongly agree). Total scores range from 12 to 90, and are classified as low-risk (≥ 41), medium risk [37,38,39,40], high risk [26,27,28,29,30,31,32,33,34,35,36] and very high risk (< 26) [43]. This tool can be used for different occupations and within organizations, with accepted internal consistency (Cronbach’s α of 0.94 for the 12 items) as shown in previous research [44].

  1. B.

    Sexual harassment climate questionnaire [45, 46]

This section assessed the residents’ perception about the psychological climate for sexual harassment through a questionnaire composed of 9 items inquiring about two main topics. The first is their risk perception to report an incident of sexual harassment (3 questions), while the second topic inquiries about whether they think the report will be taken seriously within the organization (6 questions), with Cronbach’s α for these items ranges from 0.59 to 0.7 for internal consistency as shown in prior research [45, 46]. The items were measured using a 5-point Likert format ranged from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating a greater intolerance of sexual harassment.

Statistical analysis

Data was analyzed using the Statistical Package for Social Sciences (SPSS) version 23. Quantitative variables were presented as either mean ± standard deviation or median and interquartile range; qualitative data were presented as frequency and percentage. We tested association of demographic and work-related variables with the widespread pain index and abuse indices using either Mann-Whitney or Kruskal- Wallis tests with pairwise comparisons for significant differences performed by Dunn Bonferroni test. Spearman correlation was used to test the relation between WPI, duration of residency, abuse index and psychosocial safety climate score. Finally, we performed a backward linear regression analysis for predictors of WPI including abuse index. Factors entered into the model included those showing significant statistical relation to WPI in univariate statistical analysis. P-value < 0.05 was considered statistically significant.

Results

The study included 101 medical residents working in Egyptian hospitals. About (54.5%) of the participants were older than 28 years and females were more represented than males (86.1%). Regarding occupational characteristics, 93.1% of the participants worked in the public sector while only 6.9% worked in the private sector. About three quarters (75.2%) of the study participants worked both morning and night shifts. Work shift duration was mostly 12 hours (37.6%) followed by 6 hours (34.7%). Family medicine residents were the most represented specialty (23.8%) while obstetrics and gynecology were the least frequent specialty (2%). Other specialties included clinical pathology, emergence medicine, anesthesia, and intensive care unit residents (13.9% each). Most participants held a master’s degree (47.5%), and about 13.9% finished their medical doctorate. More than one third (38.6%) of the participants were fresh graduates. The mean duration of residency was 3.1 ± 2.1 ranging from 0.5 to 12 years. Table 1 shows the sociodemographic characteristics of the study participants.

Table 1 Basic characteristics of study participants

Measurement of physical pain and pain interference

All participants had at least one painful site (range 1 to 11, the maximum possible number of pain sites is 19). The mean widespread pain index was 3.5 ± 2.4, with a median of 3.0 and IQR of 3.5 (These results are not tabulated). Forty of the 101 participants (39.6%) satisfied the definition of having widespread pain by having 4 or more pain sites. The most reported site of pain was the lower back (65.3%), and the least reported site was the jaw (2%). Frequency for each pain site is shown in Fig. 1. Regarding pain interference, the highest percentage for interference was recorded for the item “Pain a little bit interfered with day-to-day activities (34.7%), while the lowest percentage was recorded for “Pain interference very much with day-to-day activities” and “Pain interfered very much with enjoyment and recreational activities” (8.9% each). PROMIS – PI scores for pain interference with activities as reported by the study participants are presented in Table 2.

Fig. 1
figure 1

Frequency of pain sites reported by study participants

Table 2 Pain interference with activities (PROMIS – PI) during the preceding 7 days (n = 101)

Frequency and forms of abuse

The most common reported verbal abuse was “shouting and yelling” being reported daily by 26.7% and few times a week by 24.8% of participants. The most common form of harassment was discrimination on the basis of age, gender or religion occurring daily in 6.9% of participants and a few times per week to 5% of participants. Regarding academic abuse, shifting of responsibilities (i.e., where more responsibilities are unjustly assigned to the resident) was the most common form reported by 12.9% on daily basis and 11.9% a few times per week (results are not tabulated).

Workplace psychological climate and well-being

According to the PSC score, 36.6% of the residents perceived their work environment to be high-risk of PSC and 35.6% scored very high-risk PSC. The category with the highest mean was Senior Management Commitment, and the category with the lowest score was Organizational Communication with Employees. Workplace psychological climate total and category scores are presented in Table 3.

Table 3 Workplace psychosocial safety climate scores among study participants (n = 101)

Sexual harassment climate and reporting of sexual abuse

Almost half of the study participants (47.6%) agreed (either agreed or strongly agreed) that a sexual harassment complaints would be thoroughly investigated. Less than half (40.6%) thought they would be comfortable reporting a sexual harassment complaint. However, a similar percentage (41.6) perceived that individuals who sexually harass others get away with it. Additionally, about one third (31.6%) thought it would be risky to file a sexual harassment complaint (results are not tabulated).

Risk perception to report a sexual harassment was assessed by scoring three questions about how safe the resident feels reporting a sexual harassment. The mean score for risk perception to report a sexual harassment was 3.2 ± 1.0 with a median of 3.3 and interquartile range (IQR) of 1.2. On the other hand, seriousness of organization towards report was assessed by four questions about how the organization will deal with a reported sexual harassment. The mean score for organizational seriousness towards harassment reports was 3.1 ± 0.7 with a median of 3.2 and IQR of 0.7. The overall mean sexual harassment climate score was 3.1 ± 0.7 with a median of 3.1 and IQR of 0.8 (Figs. 2, 3 and 4).

Fig. 2
figure 2

Sexual harassment climate score among studied residents (n = 101)

Fig. 3
figure 3

Organizational seriousness towards harassment reports as reported by studied residents (n = 101)

Fig. 4
figure 4

Risk perception to report a sexual harassment among studied residents (n = 101)

Associations of WPI with demographic and work-related characteristics

Widespread pain index did not show any significant relation to demographic and occupational characteristics of the study participants (Table 4).

Table 4 Association between WPI and demographic and work-related characteristics of the study participants (n = 101)

Associations of workplace PSC, sexual harassment index and abuse index with demographic and work-related characteristics

Workplace safety climate scores showed significant difference between participants in relation to their marital status where married participants had a median of 29.5 and IQR of 15.5, single residents (median = 27, IQR = 13.3) and the divorced residents had a median score of 12 (p = 0.047). Pairwise comparison between marital statuses did not show any significant difference between pairs. There was no significant difference in the PSC, sexual harassment and abuse index scores in relation to the remaining demographic characteristics. On the other hand, workplace PSC was significantly higher among those working morning shift only (median = 35, IQR = 20.5) than those working both morning and night shifts (median = 27, IQR = 14.8) (p = 0.016). There was a significant relation between residents’ specialty and workplace PSC; the highest score was recorded among emergency medicine, intensive care unit (ICU) and Anesthesia residents (median = 31, IQR = 16.3) followed by family medicine (median = 30, IQR = 19.3) and clinical pathology (median = 30, IQR = 12.5); the least score was recorded for obstetrics and gynecology residents (median = 12.5, IQR = 0.5) (p = 0.047). Pairwise comparisons did not show statistically significant differences between different specialties as regard workplace PSC score. Regarding the abuse index, there was a significant difference between residents working morning shifts only (median = 0.7, IQR = 0.7) and those working both morning and night shifts (median = 1, IQR = 1) (p = 0.018). Additionally, there was a significant difference in Abuse score between residents working 6-hour shifts (median = 31.0, IQR = 17.0), 12-hour shifts (median = 27.5, IQR = 16.5), and 18–24-hour shifts (median = 25.5, IQR = 12.8) (p = 0.034). Pairwise comparison showed significant difference in Abuse index between residents working 6-hours shifts and those working 12-hour shifts (p = 0.021), and 18–24-hours shifts (p = 0.031). Once more, there were significant differences across specialties (p < 0.01), where the highest scores belonged to obstetrics and gynecology residents (Median = 1.9, IQR = 0.7), followed by Surgery (Median = 1.3, IQR = 1) (Table 5). Pairwise comparisons showed significant difference in Abuse index between family medicine residents and each of surgery residents (p = 0.023) and residents of EM, Anesthesia and ICU specialty (p = 0.001).

Table 5 Associations between demographic and work-related characteristics of the study participants and Workplace psychological safety climate; Sexual harassment climate scores; and Abuse index

Correlation between WPI and workplace PSC and abuse index

Widespread pain index showed a statistically significant weak negative correlation with workplace PSC score (rho = − 0.272, p = 0.006). Conversely, there was a statistically significant weak positive correlation between WPI and the calculated total abuse index (rho = 0.305, p = 0.002). In addition, a weak non-significant correlation was found between WPI and sexual harassment climate score (Table 6).

Table 6 Correlation between Widespread pain index and duration of work; Workplace psychosocial safety climate score; and Sexual harassment climate score

Predictors of WPI score

Regression analysis of predictors of WPI was performed. Results are presented in Table 7, where factors entered into the model were duration of residency, sexual harassment climate score, workplace psychosocial safety climate and abuse index. Abuse index was found to be the only predictor of WPI (p = 0.002).

Table 7 Regression analysis of predictors of Widespread pain index

Discussion

We aimed to explore the relationship between workplace factors, namely workplace violence (WPV) and musculoskeletal pain among Egyptian medical residents. Results of the current study confirm the presence of an association between the two phenomena. In addition, our results show a high prevalence of musculoskeletal pain among residents, where about 40% of our sample experienced widespread musculoskeletal pain, with low back pain being the most prevalent pain site. Previous studies worldwide report high prevalence rates of musculoskeletal symptoms among physicians [5, 47], with reported prevalence of low back pain as high as 68% [2]. Previous studies in Egypt, studies show similar prevalence rates of musculoskeletal pain among physicians [9, 48]. With the alarming increase of prevalence of chronic pain among the general population and among physicians, factors that contribute to such pain warrant in-depth investigation and prompt preventive actions [49].

Models that explain work-related musculoskeletal pain have evolved over time from ones that recognize mechanical factors as the sole determinant for musculoskeletal complaints to those that appreciate the complex nature of pain as a biopsychosocial phenomenon [50,51,52]. Despite these recent models, most studies still focus on either physical (including structural, ergonomic and biomechanical factors) and psychological factors, with less focus on the social and work-related components [53, 54]. Previous studies have explored the effects of job strain [55], long working hours [56], and overexertion at work [57], while studies that focus on WPV as a risk factor for chronic pain among physicians are few.

Our results show that medical residents in Egypt work in a challenging environment, where the risks of violence, sexual harassment and abuse are high, and the sense of safety and perception of support against such violence are low. Previous studies conducted in Egypt also show high a high prevalence of violence. Mahmoud et al. (2022) reported that in a sample of 445 physicians, 82.5% reported exposure to violence [58]. Other studies reported prevalence rates ranging from 59.7 and 72.6% [59,60,61]. In the current study, residents working night shifts, and those working 12–24 hour-shifts were found to be more exposed to violence compared to physicians who work morning shifts only and 6–12-hour shifts. Similar results were found by Mahmoud et al. (2022), where exposure to violence was associated with higher working hours/week, as well as number of staff/work setting. A higher work load can lead to physician exhaustion, coupled with long patient waiting time, which could explain the increase in incidences of violence [58]. As with our results, previous studies also show that Emergency physicians are more prone to violence than other specialties [59, 62].

Regarding sexual harassment and reporting of abuse, we found that more than half of our sample would not feel comfortable reporting harassment complaints. There is a similar global lack of reporting of incidences of violence and sexual harassment, and a subsequent state of inaction which will only serve to aggravate the consequences of WPV [13, 63]. Lack of reporting is attributed to absence of trust in the reporting system, lack of action from the authorities [20, 64]. One study indicated that the reason for not reporting violence was that healthcare workers have become accustomed to violence, to the extent that they no longer report it [31].

Our results show a significant, although weak, correlation between the degree and magnitude of workplace abuse and musculoskeletal pain. Similar results were reported among nurses and other clinical staff [10, 65, 66]. Moreover, a dose-response relationship was found between incidences of assault and musculoskeletal pain [11]. Additionally, women exposed to workplace violence were found to show significantly higher pain levels than other workers [67]. The relationship between violence and physical pain is somewhat complex. Studies show that the perception of pain, the transition to chronicity and the degree of pain interference with the quality of life are not driven merely by the initial injuries causing the pain (i.e. trauma or sprain), but by a set of underlying psychological processes and environmental triggers that account for persistence, chronicity and disability [68]. The continuous or recurrent exposure to violence, including physical and emotional traumas, serves as triggers that exacerbate underlying vulnerabilities such as distress and anxiety, and exhaust protective mechanisms, such as coping and resilience [69].

Regarding workplace safety climate, our results show a negative correlation between perception of psychological safety and presence of musculoskeletal pain. A somewhat similar finding was reported by Zadow et al. who found that low workplace psychological safety climate was strongly associated with low psychological health and high incidence of work injuries in healthcare workers [70]. Specifically, workplace safety climate is the result of the different dynamics of the various levels of an organization. Such dynamics include how decisions are made, tasks are assigned, goals are set, and mistakes are dealt with. These organizational processes could ultimately decide the workloads, job demands, degree of work engagement and, in part, the psychological health of workers [71], and ultimately the safety and satisfaction of the end users (i.e. patients and their relatives) [72]. Unfortunately, studies report that the workplace safety climate in healthcare report various degrees of poor safety climates, with subsequent negative effects on job stress, low job satisfaction and high job-quitting intent [73,74,75].

Regarding sexual harassment, we found no correlation between musculoskeletal pain and sexual harassment climate score. Although to our knowledge, no studies have reported an association between sexual harassment and pain among physicians, studies on the general population show a relationship between exposure to sexual abuse and chronic pain [76, 77]. The lack of association in our study could be related to the tool we used, which enquires about reporting of sexual harassment, rather than the occurrence of actual incidences of sexual abuse at the workplace.

Finally, our study found that exposure to abuse predicts physical pain among our sample of physicians. This alarming finding was also reported in nurses, where exposure to violence was found to predict physical symptoms, including back pain, upper body pain and lower extremity pain. Moreover, a change in the exposure to violence, whether by an increase or a decrease, led to a change in physical symptoms in the same direction [67]. Similarly, Miranda et al. found that a combination of poor workplace safety and violent assaults increased the risk of widespread pain among nursing home workers [11]. Unlike exposure to abuse, workplace safety climate did not predict physical pain in our study, but did show a significant negative correlation with widespread pain.

The current study supports the presence of an association between WPV and musculoskeletal pain among physicians. However, several limitations should be kept in mind when interpreting results of the current study. First, the inquiry about incidences of abuse during the whole period of residency may raise the possibility of recall bias, which could lead to either over or under-reporting of forms of abuse. Second, the convenient sample and the absence of a sampling frame did not allow for calculation of a response rate. Also, volunteer bias could have occurred, where physicians who were subjected to violence might have been more eager to participate in the study. Third, the use of the widespread pain index allowed for quantification of the number of sites of pain, however, it did not give an indication for the severity of pain in each site. Finally, due to the cross-sectional design of the study, we were unable to examine whether a temporal relationship exists between variables.

Conclusions

The current study provides evidence of an association between WPV and widespread musculoskeletal pain among physicians. The study also shows that both WPV and musculoskeletal pain are alarmingly prevalent among medical residents in Egypt. These two phenomena should be the targets of preventive strategies that enhance workplace safety climate and physical wellbeing of physicians to reduce incidences of violence and all its hazardous effects, including musculoskeletal pain.

Availability of data and materials

The dataset generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

ICU:

Intensive care unit

PROMIS-PI:

Patient reported outcomes measurement information – pain interference

PSC:

Psychosocial safety climate

WPI:

Widespread pain index

WPV:

Workplace violence

References

  1. Vijendren A, Yung M, Sanchez J, Duffield K. Occupational musculoskeletal pain amongst ENT surgeons–are we looking at the tip of an iceberg? J Laryngol Otol. 2016;130(5):490–6.

    Article  CAS  PubMed  Google Scholar 

  2. Oude Hengel KM, Visser B, Sluiter JK. The prevalence and incidence of musculoskeletal symptoms among hospital physicians: a systematic review. Int Arch Occup Environ Health. 2011;84:115–9.

    Article  PubMed  Google Scholar 

  3. Wang M, Ding Q, Sang L, Song L. Prevalence of pain and its risk factors among ICU personnel in tertiary Hospital in China: a cross-sectional study. J Pain Res. 2022:1749–58.

  4. Jadhav AP, Dharmapuri VM, Ashok S, Sancheti PK. Prevalence, severity and characteristics of work related musculoskeletal disorders amongst obstetrics and Gynaecology professionals. Int J Commun Med Public Health. 2019;6(6):2605.

    Article  Google Scholar 

  5. Epstein S, Sparer EH, Tran BN, Ruan QZ, Dennerlein JT, Singhal D, et al. Prevalence of work-related musculoskeletal disorders among surgeons and interventionalists: a systematic review and meta-analysis. JAMA Surg. 2018;153(2):e174947-e.

    Article  Google Scholar 

  6. Ganiyu SO, Olabode JA, Stanley MM, Muhammad I. Patterns of occurrence of work-related musculoskeletal disorders and its correlation with ergonomic hazards among health care professionals. Nigerian J Exp Clin Biosci. 2015;3(1):18.

    Article  Google Scholar 

  7. Keyaerts S, Godderis L, Delvaux E, Daenen L. The association between work-related physical and psychosocial factors and musculoskeletal disorders in healthcare workers: moderating role of fear of movement. J Occup Health. 2022;64(1):e12314.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Yizengaw MA, Mustofa SY, Ashagrie HE, Zeleke TG. Prevalence and factors associated with work-related musculoskeletal disorder among health care providers working in the operation room. Ann Med Surg. 2021;72:102989.

    Article  Google Scholar 

  9. Senosy SA, Anwar MM, Elareed HR. Profession-related musculoskeletal disorders among Egyptian physicians and dentists. J Public Health. 2020;28:17–22.

    Article  Google Scholar 

  10. Miranda H, Punnett L, Gore RJ, Team PR. Musculoskeletal pain and reported workplace assault: a prospective study of clinical staff in nursing homes. Hum Factors. 2014;56(1):215–27.

    Article  PubMed  Google Scholar 

  11. Miranda H, Punnett L, Gore R, Boyer J. Violence at the workplace increases the risk of musculoskeletal pain among nursing home workers. Occup Environ Med. 2011;68(1):52–7.

    Article  PubMed  Google Scholar 

  12. Phillips JP. Workplace violence against health care workers in the United States. N Engl J Med. 2016;374(17):1661–9.

    Article  CAS  PubMed  Google Scholar 

  13. Nowrouzi-Kia B, Chai E, Usuba K, Nowrouzi-Kia B, Casole J. Prevalence of type II and type III workplace violence against physicians: a systematic review and meta-analysis. Int J Occup Environ Med. 2019;10(3):99.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Beghini V, International Labour Office, Gender E, Department I. Violence and harassment in the world of work : a guide on Convention No. 190 and Recommendation No. 206, Geneva: ILO; 2022. Retrieved from https://policycommons.net/artifacts/1804382/violence-and-harassment-in-the-world-of-work/2536119/.

  15. Dyrbye LN, West CP, Sinsky CA, Trockel M, Tutty M, Satele D, et al. Physicians’ experiences with mistreatment and discrimination by patients, families, and visitors and association with burnout. JAMA Netw Open. 2022;5(5):e2213080-e.

    Article  Google Scholar 

  16. Devi S. COVID-19 exacerbates violence against health workers. Lancet. 2020;396(10252):658.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Yang Y, Li Y, An Y, Zhao Y-J, Zhang L, Cheung T, et al. Workplace violence against Chinese frontline clinicians during the COVID-19 pandemic and its associations with demographic and clinical characteristics and quality of life: a structural equation modeling investigation. Front Psych. 2021;12:649989.

    Article  Google Scholar 

  18. Arafa A, Shehata A, Youssef M, Senosy S. Violence against healthcare workers during the COVID-19 pandemic: a cross-sectional study from Egypt. Arch Environ Occup Health. 2022;77(8):621–7.

    Article  CAS  PubMed  Google Scholar 

  19. Njaka S, Edeogu OC, Oko CC, Goni MD, Nkadi N. Work place violence (WPV) against healthcare workers in Africa: a systematic review. Heliyon. 2020;6(9).

  20. Salem H, Nafad R, Taha S. Legal response of physicians towards workplace violence during COVID-19 pandemic in Egypt: a cross sectional study. Zagazig J Forensic Med. 2022;20(2):29–46.

    Google Scholar 

  21. Safety O, Administration H. Workplace violence in healthcare: understanding the challenge. OSHA. 2015;3826(12):2105.

    Google Scholar 

  22. El-Zoghby SM, Ibrahim ME, Zaghloul NM, Shehata SA, Farghaly RM. Impact of workplace violence on anxiety and sleep disturbances among Egyptian medical residents: a cross-sectional study. Hum Resour Health. 2022;20(1):1–16.

    Article  Google Scholar 

  23. Hacer TY, Ali A. Burnout in physicians who are exposed to workplace violence. J Forensic Leg Med. 2020;69:101874.

    Article  PubMed  Google Scholar 

  24. Shi L, Li G, Hao J, Wang W, Chen W, Liu S, et al. Psychological depletion in physicians and nurses exposed to workplace violence: a cross-sectional study using propensity score analysis. Int J Nurs Stud. 2020;103:103493.

    Article  PubMed  Google Scholar 

  25. Vento S, Cainelli F, Vallone A. Violence against healthcare workers: a worldwide phenomenon with serious consequences. Front Public Health. 2020;8:570459.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Zafar W, Khan UR, Siddiqui SA, Jamali S, Razzak JA. Workplace violence and self-reported psychological health: coping with post-traumatic stress, mental distress, and burnout among physicians working in the emergency departments compared to other specialties in Pakistan. J Emerg Med. 2016;50(1):167–77 e1.

    Article  PubMed  Google Scholar 

  27. Di Marco D, López-Cabrera R, Arenas A, Giorgi G, Arcangeli G, Mucci N. Approaching the discriminatory work environment as stressor: the protective role of job satisfaction on health. Front Psychol. 2016;7:1313.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Crofford LJ. Violence, stress, and somatic syndromes. Trauma Violence Abuse. 2007;8(3):299–313.

    Article  PubMed  Google Scholar 

  29. AlSawahli H. Physicians' motivation in the Ministry of Health and population-Egypt: challenges and opportunities. [Master's Thesis, the American University in Cairo]. AUC Knowledge Fountain; 2019. https://fount.aucegypt.edu/etds/761.

  30. Kabbash I, El-Sallamy R, Zayed H, Alkhyate I, Omar A, Abdo S. The brain drain: why medical students and young physicians want to leave Egypt. East Mediterr Health J. 2021;27(11).

  31. Abdellah RF, Salama KM. Prevalence and risk factors of workplace violence against health care workers in emergency department in Ismailia, Egypt. Pan Afr Med J. 2017;26(1):1–8.

    Google Scholar 

  32. Abbas MA, Fiala LA, Abdel Rahman AG, Fahim AE. Epidemiology of workplace violence against nursing staff in Ismailia governorate, Egypt. J Egypt Public Health Assoc. 2010;85(1–2):29–43.

    PubMed  Google Scholar 

  33. Faul F, Erdfelder E, Lang A-G, Buchner A. G*power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–91 Accessed at: https://download.cnet.com/g-power/3000-2054_4-10647044.html. Accessed 21 Feb 2021.

  34. Quine L. Workplace bullying in junior doctors: questionnaire survey. Bmj. 2002;324(7342):878–9.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Wolfe F, Clauw DJ, Fitzcharles M-A, Goldenberg DL, Häuser W, Katz RS, et al. Fibromyalgia criteria and severity scales for clinical and epidemiological studies: a modification of the ACR preliminary diagnostic criteria for fibromyalgia. J Rheumatol. 2011;38(6):1113–22.

    Article  PubMed  Google Scholar 

  36. Dudeney J, Law EF, Meyyappan A, Palermo TM, Rabbitts JA. Evaluating the psychometric properties of the widespread pain index and the symptom severity scale in youth with painful conditions. Can J Pain. 2019;3(1):137–47.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Evans V, Duarte FC, Linde LD, Kumbhare D. Differences and similarities among questionnaires to assess pain status in chronic widespread pain population: a quantitative analysis. Br J Pain. 2021;15(4):441–9.

    Article  PubMed  Google Scholar 

  38. Galvez-Sánchez CM, de la Coba P, Duschek S, Reyes del Paso GA. Reliability, factor structure and predictive validity of the widespread pain index and symptom severity scales of the 2010 American College of Rheumatology criteria of fibromyalgia. J Clin Med. 2020;9(8):2460.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Wolfe F, Egloff N, Häuser W. Widespread pain and low widespread pain index scores among fibromyalgia-positive cases assessed with the 2010/2011 fibromyalgia criteria. J Rheumatol. 2016;43(9):1743–8.

    Article  PubMed  Google Scholar 

  40. Askew RL, Kim J, Chung H, Cook KF, Johnson KL, Amtmann D. Development of a crosswalk for pain interference measured by the BPI and PROMIS pain interference short form. Qual Life Res. 2013;22:2769–76.

    Article  PubMed  Google Scholar 

  41. Kim J, Chung H, Amtmann D, Revicki DA, Cook KF. Measurement invariance of the PROMIS pain interference item bank across community and clinical samples. Qual Life Res. 2013;22:501–7.

    Article  PubMed  Google Scholar 

  42. Al-Shafaee M, Al-Kaabi Y, Al-Farsi Y, White G, Al-Maniri A, Al-Sinawi H, et al. Pilot study on the prevalence of abuse and mistreatment during clinical internship: a cross-sectional study among first year residents in Oman. BMJ Open. 2013;3(2):e002076.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Baldwin D Jr, Daugherty SR, Eckenfels EJ. Student perceptions of mistreatment and harassment during medical school. A survey of ten United States schools. West J Med. 1991;155(2):140.

    PubMed  PubMed Central  Google Scholar 

  44. Hall GB, Dollard MF, Coward J. Psychosocial safety climate: development of the PSC-12. Int J Stress Manag. 2010;17(4):353.

    Article  Google Scholar 

  45. Dollard MF, Dormann C, Tuckey MR, Escartín J. Psychosocial safety climate (PSC) and enacted PSC for workplace bullying and psychological health problem reduction. Eur J Work Organ Psy. 2017;26(6):844–57.

    Article  Google Scholar 

  46. Estrada AX, Olson KJ, Harbke CR, Berggren AW. Evaluating a brief scale measuring psychological climate for sexual harassment. Mil Psychol. 2011;23(4):410–32.

    Google Scholar 

  47. Siller H, Tauber G, Komlenac N, Hochleitner M. Gender differences and similarities in medical students’ experiences of mistreatment by various groups of perpetrators. BMC Med Educ. 2017;17:1–8.

    Article  Google Scholar 

  48. Hämmig O. Work-and stress-related musculoskeletal and sleep disorders among health professionals: a cross-sectional study in a hospital setting in Switzerland. BMC Musculoskelet Disord. 2020;21(1):1–11.

    Article  Google Scholar 

  49. Khairy WA, Bekhet AH, Sayed B, Elmetwally SE, Elsayed AM, Jahan AM. Prevalence, profile, and response to work-related musculoskeletal disorders among Egyptian physiotherapists. Open Access Maced J Med Sci. 2019;7(10):1692.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Cohen SP, Vase L, Hooten WM. Chronic pain: an update on burden, best practices, and new advances. Lancet. 2021;397(10289):2082–97.

    Article  PubMed  Google Scholar 

  51. Solidaki E, Chatzi L, Bitsios P, Markatzi I, Plana E, Castro F, et al. Work-related and psychological determinants of multisite musculoskeletal pain. Scand J Work Environ Health. 2010:54–61.

  52. Neupane S, Nygård C-H, Oakman J. Work-related determinants of multi-site musculoskeletal pain among employees in the health care sector. Work. 2016;54(3):689–97.

    Article  PubMed  Google Scholar 

  53. Descatha A, Evanoff BA, Leclerc A, Roquelaure Y. Occupational determinants of musculoskeletal disorders. Handbook of disability, work and health. 2020:169–88. https://doi.org/10.1007/978-3-030-24334-0_8.

  54. Puntillo F, Giglio M, Paladini A, Perchiazzi G, Viswanath O, Urits I, et al. Pathophysiology of musculoskeletal pain: a narrative review. Ther Adv Musculoskelet Dis. 2021;13:1759720X21995067.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Menzel NN. Psychosocial factors in musculoskeletal disorders. Crit Care Nurs Clin North Am. 2007;19(2):145–53.

    Article  PubMed  Google Scholar 

  56. Amiri S, Behnezhad S. Is job strain a risk factor for musculoskeletal pain? A systematic review and meta-analysis of 21 longitudinal studies. Public Health. 2020;181:158–67.

    Article  CAS  PubMed  Google Scholar 

  57. Amiri S. Longer working hours and musculoskeletal pain: a meta-analysis. Int J Occup Saf Ergon. 2022;1-16.

  58. Alnaami I, Awadalla NJ, Alkhairy M, Alburidy S, Alqarni A, Algarni A, et al. Prevalence and factors associated with low back pain among health care workers in southwestern Saudi Arabia. BMC Musculoskelet Disord. 2019;20:1–7.

    Article  Google Scholar 

  59. Mahmoud A, Ezzat A. Workplace violence against physicians: an online cross-sectional study. Egypt J Occup Med. 2022;46(3):1–16.

    Article  Google Scholar 

  60. Abdel-Salam D. Violence against physicians working in emergency departments in Assiut, Egypt. J High Inst Public Health. 2014;44(2):98–107.

    Article  MathSciNet  Google Scholar 

  61. Gabr HM, Younis FE, El-Badry AS. Workplace violence against female nurses in Menoufia governorate, Egypt: an epidemiological study. Egypt Family Med J. 2021;5(1):17–27.

    Article  Google Scholar 

  62. Moustafa MS, Gewaifel GI. Work-related violence among female employees in a university hospital in Alexandria: an epidemiologic study. J Am Sci. 2013;9(3):243–50.

    Google Scholar 

  63. Abou-ElWafa HS, El-Gilany A-H, Abd-El-Raouf SE, Abd-Elmouty SM, El-Sayed Hassan El-Sayed R. Workplace violence against emergency versus non-emergency nurses in Mansoura university hospitals, Egypt. J Interpers Violence. 2015;30(5):857–72.

    Article  PubMed  Google Scholar 

  64. Chakraborty S, Mashreky SR, Dalal K. Violence against physicians and nurses: a systematic literature review. J Public Health. 2022;30(8):1837–55.

    Article  PubMed  Google Scholar 

  65. Abo-Ali EA, Zayed HA, Atlam SA. Workplace violence: effects on job performance and coping strategies among physicians. J High Inst Public Health. 2020;50(3):126–31.

    Article  Google Scholar 

  66. Rezaee M, Ghasemi M. Prevalence of low back pain among nurses: predisposing factors and role of work place violence. Trauma Mon. 2014;19(4).

  67. Yang L-Q, Spector PE, Gallant-Roman M, Powell J. Psychosocial precursors and physical consequences of workplace violence towards nurses: a longitudinal examination with naturally occurring groups in hospital settings. Int J Nurs Stud. 2012;49(9):1091–102.

    Article  PubMed  Google Scholar 

  68. Madsen IE, Gupta N, Budtz-Jørgensen E, Bonde JP, Framke E, Flachs EM, et al. Physical work demands and psychosocial working conditions as predictors of musculoskeletal pain: a cohort study comparing self-reported and job exposure matrix measurements. Occup Environ Med. 2018;75(10):752–8.

    Article  PubMed  Google Scholar 

  69. Linton SJ. A transdiagnostic approach to pain and emotion. J Appl Biobehav Res. 2013;18(2):82–103.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Linton SJ, Flink IK, Vlaeyen JW. Understanding the etiology of chronic pain from a psychological perspective. Phys Ther. 2018;98(5):315–24.

    Article  PubMed  Google Scholar 

  71. Zadow AJ, Dollard MF, Mclinton SS, Lawrence P, Tuckey MR. Psychosocial safety climate, emotional exhaustion, and work injuries in healthcare workplaces. Stress Health. 2017;33(5):558–69.

    Article  PubMed  Google Scholar 

  72. Loh MY, Zadow A, Dollard M. Psychosocial safety climate and occupational health: what we know so far. Handbook of socioeconomic determinants of occupational health: From macro-level to micro-level evidence. T. Handbook Series in Occupational Health Sciences; 2020. p. 1–27. https://doi.org/10.1007/978-3-030-05031-3_17-1.

  73. McLinton SS, Afsharian A, Dollard MF, Tuckey MR. The dynamic interplay of physical and psychosocial safety climates in frontline healthcare. Stress Health. 2019;35(5):650–64.

    Article  PubMed  Google Scholar 

  74. McGhan GE, Ludlow NC, Rathert C, McCaughey D. Variations in workplace safety climate perceptions and outcomes across healthcare provider positions. J Healthc Manag. 2020;65(3):202–15.

    PubMed  Google Scholar 

  75. Mohr DC, Eaton JL, McPhaul KM, Hodgson MJ. Does employee safety matter for patients too? Employee safety climate and patient safety culture in health care. J Patient Saf. 2018;14(3):181–5.

    Article  PubMed  Google Scholar 

  76. Paras ML, Murad MH, Chen LP, Goranson EN, Sattler AL, Colbenson KM, et al. Sexual abuse and lifetime diagnosis of somatic disorders: a systematic review and meta-analysis. Jama. 2009;302(5):550–61.

    Article  CAS  PubMed  Google Scholar 

  77. Bailey BE, Freedenfeld R, Kiser RS, Gatchel RJ. Lifetime physical and sexual abuse in chronic pain patients: psychosocial correlates and treatment outcomes. Disabil Rehabil. 2003;25(7):331–42.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB). No funding was received to conduct this study.

Author information

Authors and Affiliations

Authors

Contributions

M.E.I. contributed to conception and design of the study, acquisition of data, data interpretation, article drafting and article revision. S.M.Z. participated in conception and design of the study, acquisition of data, drafting the manuscript, data interpretation and article revision, N.M.Z. participated in conception and design, acquisition of data, data interpretation and article revision. S.A.S. participated in data interpretation, article drafting and article revision, and R.M.F. contributed to conception and design, data interpretation and data analysis and article revision. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Maha E. Ibrahim.

Ethics declarations

Ethics approval and consent to participate

The study was performed in accordance with the principles of the declaration of Helsinki (2000) and was approved by the Research Ethical Committee of the Faculty of Medicine, Suez Canal University (No. 4485#). An informed consent was obtained from all participants. All data were collected anonymously.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ibrahim, M.E., El-Zoghby, S.M., Zaghloul, N.M. et al. Musculoskeletal pain among medical residents: role of workplace safety climate and sexual harassment. BMC Musculoskelet Disord 25, 167 (2024). https://doi.org/10.1186/s12891-024-07272-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12891-024-07272-w

Keywords