Home Medicine Relationship of musculoskeletal pain and well-being at work – Does pain matter?
Article Publicly Available

Relationship of musculoskeletal pain and well-being at work – Does pain matter?

  • Kirsi Malmberg-Ceder EMAIL logo , Maija Haanpää , Päivi E. Korhonen , Hannu Kautiainen and Seppo Soinila
Published/Copyright: April 1, 2017
Download Article (PDF)
Become an author with De Gruyter Brill
Author Information Explore this Subject
Scandinavian Journal of Pain
From the journal Scandinavian Journal of Pain Volume 15 Issue 1

Abstract

Background and aims

Musculoskeletal pain is a common symptom and many people even with chronic pain continue to work. The aim of our study is to analyze how musculoskeletal pain affects work wellbeing by comparing work engagement in employees with or without pain, and how pain-related risk of disability is associated with work engagement. In a separate analysis, we also studied, how psychosocial factors are related to work engagement.

Methods

This is a cross-sectional study of Finnish female employees of the city of Pori, Finland (PORi To Aid Against Threats (PORTAAT) study). Data was collected by trained study nurses and self-administrated questionnaires. Work well-being was measured by work engagement using Utrecht Work Engagement Scale (UWES-9) questionnaire and the burden of pain was measured by using the short version of Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ). Study population was divided into four groups: those without pain and the groups with low (I), medium (II) or high (III) ÖMPSQ score, reflecting increasing risk of long term disability due to musculoskeletal pain. The study nurse assessed psychosocial risk factors using defined core questions.

Results

We evaluated 702 female employees, 601 (86%) had suffered from musculoskeletal pain over the past 12 months, whereas 101 (14%) reported no pain at all. Pain was chronic (duration at least 3 months) in 465/601 (77%) subjects. Subjects with musculoskeletal pain were older, had higher BMI and were on sick leave more often than subjects without pain. Of the psychosocial risk factors, depression, type D personality, anxiety and hostility were significantly more common among subjects with musculoskeletal pain. Hypertension and the use of non-steroidal anti-inflammatory drugs were significantly more frequent in the musculoskeletal pain group. Quality of sleep and working capability were significantly better among persons without pain. Average weekly working hours were slightly higher among those with musculoskeletal pain.

In crude analysis, work engagement (UWES-9) was similar in women without pain and those with musculoskeletal pain (4.96 vs. 4.79; p = 0.091). After adjustment for age, education years, BMI, working hours and financial satisfaction, the difference between the groups became statistically significant (p = 0.036). Still, there was no difference between the groups of no-pain and low burden of pain (p = 0.21, after adjustment). Work engagement was significantly lower in the groups of medium (p = 0.024, after adjusted) and high (p < 0.001, after adjustment) burden of pain. Linearity across the Linton tertiles was significant (p < 0.001). In univariate and multivariate ordered logistic regression analyses relating study variables to the work engagement musculoskeletal pain per se did not enter in the model to explain work engagement. Work and family stress, type D personality and duration of sick leave due to pain reduced work engagement, whereas financial satisfaction, moderate and high leisure time physical activity and higher BMI improved it.

Conclusions

Among women with musculoskeletal pain psychosocial and lifestyle factors significantly correlate with work engagement, while the pain itself does not.

Implications

Special attention should be paid to the psychosocial aspects in female employees with musculoskeletal pain to improve work well-being and maintain work ability.

Keywords: Musculoskeletal pain; Work engagement; Work well-being; UWES (Utrecht Work Engagement Scale); ÖMPSQ (Örebro Musculoskeletal Pain Screening Questionnaire)

1 Introduction

Musculoskeletal pain is a common symptom, which upon prolongation into a chronic pain state often becomes a reason for disability and causes impaired work ability [1,2]. Despite the high prevalence of musculoskeletal pain in the workforce, many people with pain continue to work [3,4]. Only few studies have investigated the factors determining experienced work ability [5,6] by persons with pain. de Vries et al. assessed 119 workers, who stayed at work despite nonspecific musculoskeletal pain, and their results suggest that personal and work-related factors, rather than the pain itself, may have significant impact on experienced work ability and work performance. In a recent systematic review and meta-analysis [7] Lee et al., by using mediation analysis, found evidence to suggest that psychological stress, poor self-efficacy and fear explain the correlation between pain and disability. More thorough understanding of the complex interrelationships between musculoskeletal pain, work well-being and work ability is needed for designing individualized treatment and adjusting measures for employees with chronic pain to retain better daily functioning at and outside work.

Work engagement is a positive, fulfilling, affective-motivational state of work-related well-being [8]. Work engagement can be assessed by a validated questionnaire containing three subscales concerning vigor, dedication and absorption [8]. Work engagement reflects occupational satisfaction and is associated with experienced work ability [9]. Thus, it has been suggested that high work engagement is a predictor of maintained work ability among people with chronic pain [10]. However, to our knowledge, no studies comparing work engagement among people with or without pain have been published.

Chronic pain involves several factors in addition to the pain itself, which all contribute the cumulative burden of pain. Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) is a self-administered instrument developed to identify those people with musculoskeletal pain who are at risk for chronicity and long term disability [11]. In its short version [12], only two of the ten questions assess the pain itself, while the rest pertain to emotional stress and functional ability.

The aim of our study is to analyze how musculoskeletal pain affects work well-being by comparing work engagement in employees with or without pain, and how pain-related risk of disability is associated with work engagement. In a separate analysis, we also studied, how psychosocial factors, characterized in this study as anxiety, depression, social isolation, work and family stress, and certain personality traits, characterized as hostility and type D personality, are related to work engagement.

2 Methods

2.1 Participants

PORTAAT (PORi To Aid Against Threats) is a study conducted among employees of the city of Pori (83 497 inhabitants in 2014) in southwestern Finland. The study population comprised workers from ten work units, which were selected by the chief of welfare unit of Pori. Invitation and study information letters were sent to the employees as an email attachment by the managers of the work units. We cannot report the exact participation rate for the study, because some employees may have ignored the invitation and information letter sent by e-mail notifications. There was also information events organized for employees concerning PORTAAT-study. There were no exclusion criteria. Librarians, museum employees, groundkeepers, computer workers, social workers, nurses, physicians, administrative officials, and general office staff were invited to an enrolment appointment with the study nurse. Altogether 836 employees (104 males, 732 females) consented to participate in the study. Because of overwhelming predominance of females, which corresponds the gender distribution of employees of Pori, males were excluded from the study cohort. For the analyses described here, we included women with musculoskeletal pain and women without any pain. In order to create a cohort with musculoskeletal pain only, we excluded subjects with pain other than musculoskeletal (17 women) and those who did not answer the pain questionnaire (13 women). Hence, 702 female were included in the analyses.

2.2 Measurements

The baseline examination was performed by trained study nurses. Height and weight were measured with the subjects in standing position without shoes and outer garments. Body mass index (BMI) was calculated as weight (kg) divided by the square of height (m2). Blood pressure was measured with an automatic validated blood pressure monitor with subjects in a sitting posture, after resting at least for 5 min.

2.3 Questionnaires

Data were collected using self-administrated questionnaires. Their comprehensiveness was tested in a group of volunteers. They included questions about diseases diagnosed by a physician, medication used regularly, years of education, marital status (cohabiting or not), quality of sleep (good or not good), work ability with self-reported numerical rating scale (NRS 0–10), weekly working hours, alcohol consumption (the 3-item Alcohol Use Disorders Identification Test (AUDIT-C) [13]. Financial satisfaction was assessed with the question “Do I have to spare expenditures?” (yes or no). Smoking status was assessed by a questionnaire. Nonsmoking was defined as having never smoked or having quit smoking >12 months ago. Leisure-time physical activity (LTPA) was classified as follows: high: LTPA for ≥30 min at a time for four or more times a week; moderate: LTPA for ≥30 min at a time for two to three times a week; low: LTPA for ≥30 min at a time for maximum of one times a week. The amount of sick leave was measured by question “How many days of work have you missed (sick leave) because of pain during the past 12 months”.

Work well-being was measured by work engagement using Utrecht Work engagement Scale (UWES-9) questionnaire [8], which consists of three sub-scales focusing on vigor, dedication and absorption, which were rated on a 7-point Likert scale ranging from 0 (strongly disagree) to 6 (strongly agree). Items were summed and divided by the number of items in each scale. The higher each item was rated, the higher the overall work engagement. In our study work engagement tertiles were 1; <4.5, 2; 4.6–5.2 and 3; >5.3.

Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) is a self-administered instrument containing 25 items of which 21 are scored [11]. We used the short version of this questionnaire containing 10 items from the original questionnaire [12]. ÖMPSQ has been developed to identify those people with musculoskeletal pain who are at risk for chronicity and long term disability. The higher the score, the bigger is the burden of pain. We divided our study population into four groups: those without pain and the group with musculoskeletal pain with low (I), medium (II) or high (III) risk of long term disability due to musculoskeletal pain determined by tertiles of the ÖMPSQ score.

At the clinic, the study nurse assessed psychosocial risk factors by core questions suggested by the European 2012 guidelines on cardiovascular disease prevention in clinical practice [14].

  • Work and family stress: Do you have enough control over how to meet the demand at work? Is your reward appropriate for your effort? Do you have serious problems with your spouse?

  • Social isolation: Are you living alone? Do you lack a close confidant?

  • Depression: Do you feel down, depressed and hopeless? Have you lost interest and pleasure in life?

  • Anxiety: Do you frequently feel nervous, anxious or on edge? Are you frequently unable to stop or control worrying?

  • Hostility: Do you frequently feel angry over little things? Do you often feel annoyed about habits other people have?

  • Type D personality: In general, do you often feel anxious, irritable, or depressed? Do you avoid sharing your thoughts and feelings with other people?

A “yes” answer to any of these questions was interpreted to refer to the presence of psychosocial risk factors.

2.4 Statistical methods

The statistical comparisons between groups were performed by using the t test, the chi-square test, or Fisher’s exact test when appropriate. When adjusting for confounding factors, analysis of covariance (ANCOVA) with an appropriate contrast was applied. The bootstrap (10 000 replications) method was used when the theoretical distribution of the test statistics were unknown or in the case of violation of the assumptions (e.g., non-normality). To determine characteristics associated with work engagement, univariate and multivariate forward stepwise (probability for entry 0.05; probability for removal 0.10) ordered logistic regression analysis were applied; because of prominent negatively skewed distribution, the results of work engagement were concentrated at high values. We evaluated for multicollinearity using the variance inflation factor (VIF) diagnostic. STATA 14.1, StataCorp LP (College Station, TX, USA) statistical package was used for the analyses.

3 Results

We evaluated 702 female employees. The mean (SD) age was 48 (10) years. Of the subjects, 601 (86%) had suffered from musculoskeletal pain over the past 12 months, whereas 101 (14%) reported no pain at all. Pain was chronic (duration at least 3 months) in 465/601 (77%) subjects. The baseline characteristics of the subjects are shown in Table 1. Subjects with musculoskeletal pain were older, had higher BMI and were on sick leave more often than subjects without pain. Of the psychosocial risk factors, depression, type D personality, anxiety and hostility were significantly more common among subjects with musculoskeletal pain. Hypertension and the use of non-steroidal anti-inflammatory drugs were significantly more frequent in the musculoskeletal pain group. Quality of sleep and working capability were significantly better among persons without pain. Average weekly working hours were slightly higher among those with musculoskeletal pain.

Table 1

Baseline characteristics of study subjects.

Musculoskeletal pain p-value
Not present N = 101 Present N = 601
Age, years, mean (SD) 46 (10) 49 (10) 0.014
Body mass index, kg/m2, mean (SD) 25.2 (4.7) 27.0 (4.8) <0.001
Smoking, n (%) 10 (10) 79 (13) 0.36
Living with spouse, n (%) 71 (70) 473 (79) 0.057
Financial satisfaction, n (%) 72 (71) 371 (62) 0.066
Education years, mean (SD) 14.3 (2.7) 13.8 (2.7) 0.13
Sick leave (days ≥3) due to pain last 12-month period, n (%) 11 (11) 158 (26) <0.001
Leisure time physical activity (%) 0.45
 Low 31 (31) 158 (26)
 Moderate 37 (37) 259 (43)
 High 33 (32) 184 (31)
Good sleep quality, n (%) 86 (85) 410 (68) <0.001
AUDIT-C score, mean (SD) 2.96 (1.78) 2.89 (1.73) 0.73
Psychosocial risk factors, n (%) 49 (49) 399 (66) <0.001
 Depression 8 (8) 123 (20) 0.003
 Type D personality 16 (16) 168 (28) 0.010
 Work and family stress 26 (26) 195 (32) 0.18
 Social isolation 19 (19) 103 (17) 0.68
 Anxiety 15 (15) 208 (35) <0.001
 Hostility 11 (11) 136 (23) 0.007
Work ability (NRS), mean (SD) 8.7 (1.0) 8.1 (1.3) <0.001
Weekly working hours, mean (SD) 40.8 (3.4) 41.7 (4.1) 0.044
Morbidity, n (%)
 Diabetes 2 (2) 23 (4) 0.56
 Hypertension 8 (8) 104 (17) 0.017
 Thyreoid disorder 5 (5) 60 (10) 0.11
 Coronary heart disease 0 (0) 2 (1) 0.56
 Asthma 5 (5) 34 (6) 0.77
 Depression 3 (3) 13 (2) 0.62
 Cancer 1 (1) 10 (2) 0.61
 Musculoskeletal disorder 3 (3) 113 (19) <0.001
 Gastrointestinal disorder 5 (5) 44 (7) 0.39
 Headache 2 (2) 37 (6) 0.090
Medication for pain, n (%)
 NSAID 0 (0) 26 (4) 0.023
 Paracetamol 0 (0) 7 (1) 0.60
 Opioid 0 (0) 5 (1) 0.99
 Tricyclic antidepressant 3 (3) 30 (5) 0.38
 Gabapentin or pregabalin 0 (0) 9 (2) 0.22
Antidepressant for mood disorder, n (%) 3 (3) 31 (5) 0.34
Benzodiazepines, n (%) 3 (3) 9 (2) 0.29

In crude analysis, work engagement measured by UWES-9 was similar in women without pain and those with musculoskeletal pain (4.96 vs. 4.79; p = 0.091). However, after adjustment for age, education years, BMI, working hours and financial satisfaction, the difference between the groups became statistically significant (p = 0.036). Still, there was no difference between the groups of nopain and low burden of pain (p = 0.21, after adjustment). However, work engagement was significantly lower in the groups of medium (p = 0.024, after adjusted) and high (p < 0.001, after adjustment) burden of pain. Linearity across the Linton tertiles was significant (p < 0.001) (Fig. 1).

Fig. 1 Work engagement (95% confidence intervals) as a function of the burden of pain and no pain. The level of burden of pain is based on the ÖMPSQtertiles (I <59, II 59-81, III >81).
Fig. 1

Work engagement (95% confidence intervals) as a function of the burden of pain and no pain. The level of burden of pain is based on the ÖMPSQtertiles (I <59, II 59-81, III >81).

Table 2 shows the results of univariate and multivariate ordered logistic regression analyses relating study variables to the work engagement. BMI, financial satisfaction, duration of sick leave due to pain, high leisure time physical activity, type D personality and work and family stress were entered into the forward ordered logistic regression model as explanatory variables.

Table 2

Ordered logistic regression analysis for relationships between work engagement and study variables.

Variables Univariate Multivariate[a]
OR (95% Cl) p-value OR (95% Cl) p-value
Musculoskeletal pain 0.83 (0.56–1.23) 0.35
Age 1.00 (0.99–1.02) 0.82
Body mass index 1.02 (0.99–1.05) 0.098 1.04 (1.01–1.07) 0.005
Smoking 1.18 (0.78–1.81) 0.43
Financial satisfaction 1.60 (1.20–2.12) <0.001 1.38 (1.03–1.86) 0.032
Education years 0.97 (0.92–1.02) 0.28
Sick leave (days ≥3) due to pain last 12-month period 0.54 (0.39–0.75) <0.001 0.57 (0.41–0.79) <0.001
Weekly working hours 1.03 (1.00–1.07) 0.078
Leisure time physical activity <0.001[b] <0.001[b]
 Low 1 (reference) 1 (reference)
 Moderate 1.28 (0.92–1.79) 1.25 (0.89–1.76)
 High 2.09 (1.45–3.01) 2.08 (1.42–3.04)
AUDIT-C score 0.95 (0.88–1.03) 0.21
Depression 0.45 (0.31–0.65) <0.001
Type D personality 0.49 (0.36–0.68) <0.001 0.64 (0.46–0.89) 0.008
Work and family stress 0.50 (0.37–0.67) <0.001 0.62 (0.45–0.85) 0.003
Social isolation 0.74 (0.51–1.07) 0.11
Anxiety 0.56 (0.42–0.75) <0.001
Hostility 0.60 (0.43–0.84) <0.001
Good sleep quality 1.40 (1.03–1.89) 0.027

4 Discussion

The main result of our study is that although work engagement, quite expectedly, shows significant negative correlation with burden of pain as measured by ÖMPSQ, musculoskeletal pain per se did not enter in the model to explain work engagement in multivariate ordered logistic regression analysis. Work and family stress, type D personality and duration of sick leave due to pain reduced work engagement, whereas financial satisfaction, moderate and high leisure time physical activity and higher BMI improved it.

According to our study, musculoskeletal pain is a very common complaint among city employees: five out of six subjects in our study reported musculoskeletal pain over the last year. Of them, 77% had chronic pain. High prevalence of pain in people at working age has been reported by others, although the figures are not comparable due to difference in socioeconomic factors, health care systems and data collection strategies. In a large European survey based on working population, the prevalence of musculoskeletal pain varied remarkably between countries. Neck and upper arm pain prevalence was the highest in Finland (68%), and that of back pain was highest in Portugal (64%), while both pain types had the lowest prevalence in Ireland [15]. In an Estonian study [16], the prevalence of overall musculoskeletal pain in female nurse population was 84% over the past year and 69% over the past month.

In our material, certain psychosocial risk factors, namely depression, anxiety, type D personality and hostility were significantly more common in females with musculoskeletal pain as compared to those without pain, while no such difference was observed in terms of stress and social isolation. In line with the present observations, earlier studies have shown that chronic pain is clearly associated with depression and anxiety [17].The association of pain and emotions has also been revealed by brain imaging studies with functional MRI [18]. Spontaneous chronic back pain intensity is strongly related to activity in the medial prefrontal cortex, a region known to associate with negative emotions, response to conflict, and detection of unfavorable outcomes, especially in relation to the self.

Type D personality is described as the tendency to experience a joint occurrence of negative affectivity and social inhibition [19]. It is a well-known risk factor for many health problems, although its relation to pain is less clear [20,21]. Type D personality increases the risk of back pain in cancer survivors [22] and it is a risk factor for musculoskeletal pain in adolescents [23]. Barnett et al. [20] concluded that chronic pain patients with type D personality are more prone to anxiety, depression and social discomfort.

Hostility denotes antagonistic attitudes and cynical expectations regarding others’ motives. It is characterized by extensive experience of mistrust, anger and rage and the tendency to engage in aggressive, maladaptive social relationships. Although hostility is considered primarily as a personality trait, it has a neurophysiological correlate, demonstrated by differences in EEG response to pain stimulus between hostile and non-hostile men [24]). Hostility is a known risk factor for cardiovascular diseases [14,25,26]. To our knowledge, only few studies conducted on adults have examined type D personality and hostility in relation to chronic pain in general [20,27] and none on the relationship of type D personality and musculoskeletal pain specifically. According to Burns et al. [27] spousal criticism or hostility may be factors contributing to maintenance and even worsening of chronic pain. No studies have been published on the relation of patient’s own hostility to pain or to the risk of pain chronicity.

Work engagement is a relatively new concept to characterize well-being at work. Work engagement is associated with perceived work ability and person’s desire to continue to work [9]. Factors compiling work engagement are both person- and work-related [28]. Personal elements include personality and personal situation outside work, including health factors. de Vries et al. [6] reported that workers with chronic musculoskeletal pain tend to stay at work, if they have high beliefs in self-efficacy of pain. de Vries et al. [29] pointed out that perceived low physical disability, low emotional distress, flexibility to make personal adjustments and workplace interventions are significant factors to improve the work ability of people with musculoskeletal pain. Our study showed that musculoskeletal pain itself has no association to work engagement. Instead, financial satisfaction, high leisure time physical activity, low amount of sick leaves, work or/and family stress and presence of type D personality are independently associated to work engagement.

Our results are in line with a recent study [30] performed mainly on female employees, which showed that communication between musculoskeletal pain patients and their supervisors and consecutive problem solving significantly lowered health care visits and sick leaves due to pain. Taken together, these conclusions point out that organizational contributions focusing on psychosocial factors lead to reinforcement of the musculoskeletal pain patients’ own estimation of maintained work ability and are expected to strengthen work engagement, improve work well-being and consequently maintain work ability and prevent absenteeism despite lowered functional capacity caused by the pain.

The strength of our study is that it includes a well characterized and relatively large cohort of employed female population. Estimation of the relationship between work engagement and pain becomes more reliable, when subjects without pain are included. Although the participants represent different work units and widely varying tasks, they share a uniform occupational health care system, their working conditions are regulated by the same collective agreement, they receive equitable salaries and their employment status is stable. Thus, in spite of some variability, our study population consists of a sample of employees having a relatively homogeneous cultural ground. Exclusive enrollment of female participants further contributes to homogeneity of the study population and reliability of the results. This is significant, since pain sensitivity and pain-related anxiety are different in women and men [31,32]. The burden of musculoskeletal pain and work engagement were measured using internationally approved questionnaires, ÖMPSQ and UWES. We assessed psychosocial risk factors with core questions, which can be used as a preliminary assessment within clinical interview [14]. We assessed depression by two core questions. Giving an affirmative answer to either one is reportedly as effective as using longer screening instruments [33].

The major limitation of our study is its cross-sectional nature, which prevents us from assessing any causality between pain, psychosocial risk factors and work engagement. Another limitation is the fact that we are not able to report the exact participation rate for the study, because some employees may have ignored the invitation and information letter sent by e-mail notifications. Furthermore, self-reporting of diet, physical activity and smoking status may be unreliable, although we used validated questionnaires and standardized procedures to overcome this bias.

5 Conclusions

We showed that among women with musculoskeletal pain psychosocial and lifestyle factors significantly correlate with work engagement, while the pain itself does not.

6 Implications

The major implication of the present study is that special attention should be paid to the psychosocial aspects in female employees with musculoskeletal pain to improve work well-being and maintain work ability.

Highlights

  • 2/3 of Finnish female city employees suffer from chronic musculoskeletal pain.

  • Work engagement had significant negative relationship with burden of pain.

  • Musculoskeletal pain per se did not correlate with work engagement.

  • Work engagement was significantly associated with psychosocial factors.

DOI of refers to article: http://dx.doi.org/10.1016/j.sjpain.2016.12.003.

Department of Neurology, Satakunta Central Hospital, Sairaalantie, 28500 Pori, Satakunta, Finland.

  1. Ethical issues: The study protocol and consent forms were reviewed and approved by the Ethics Committee of the Hospital District of Southwestern Finland. All participants provided written informed consent for the project and subsequent medical research.

  2. Conflict of interest: The authors have no competing interests to declare.

Acknowledgements

The PORTAAT study has been supported by unrestricted grant from Mutual Insurance company Etera. Research grants from the Hospital District of Satakunta and from the Finnish Cultural Foundation, Satakunta Regional Fund to Kirsi Malmberg-Ceder are gratefully acknowledged.

References

[1] McDonald M, DiBonaventura Md, Ullman S. Musculoskeletal pain in the workforce: the effects of back, arthritis, and fibromyalgia pain on quality of life and work productivity. J Occup Environ Med 2011;53:765–70, http://dx.doi.org/10.1097/JOM.0b013e318222af81.Search in Google Scholar

[2] Miranda H, Kaila-Kangas L, Heliövaara M, Leino-Arjas P, Haukka E, Liira J, Viikari-Juntura E. Musculoskeletal pain at multiple sites and its effects on work ability in a general working population. Occup Environ Med 2010;67:449–55, http://dx.doi.org/10.1136/oem.2009.048249.Search in Google Scholar

[3] Blyth FM, March LM, Nicholas MK, Cousins MJ. Chronic pain, work performance and litigation. Pain 2003;103:41–7, http://dx.doi.org/10.1016/S0304-3959(02)00380-9.Search in Google Scholar

[4] Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain 2006;10:287–333, http://dx.doi.org/10.1016/j.ejpain.2005.06.009.Search in Google Scholar

[5] de Vries HJ, Reneman MF, Groothoff JW, Geertzen JH, Brouwer S. Workers who stay at work despite chronic nonspecific musculoskeletal pain: do they differ from workers with sick leave? J Occup Rehabil 2012;22:489–502, http://dx.doi.org/10.1007/s10926-012-9360-6.Search in Google Scholar

[6] de Vries HJ, Reneman MF, Groothoff JW, Geertzen JH, Brouwer S. Self-reported work ability and work performance in workers with chronic nonspecific musculoskeletal pain. J Occup Rehabil 2013;23:1–10, http://dx.doi.org/10.1007/s10926-012-9373-1.Search in Google Scholar

[7] Lee H, Hübscher M, Moseley GL, Kamper SJ, Traeger AC, Mansell G, McAuley JH. How does pain lead to disability? A systematic review and meta-analysis of mediation studies in people with back and neck pain. Pain 2015;156:988–97, http://dx.doi.org/10.1097/j.pain.0000000000000146.Search in Google Scholar

[8] Schaufeli WB, Salanova M, Gonzalez-Roma V, Bakker AB. The measurement of engagement and burnout: a confirmative analytic approach. J Happiness Stud 2002;3:71–92.Search in Google Scholar

[9] Airila A, Hakanen J, Punakallio A, Lusa S, Luukkonen R. Is work engagement related to work ability beyond working conditions and lifestyle factors? Int Arch Occup Environ Health 2012;85:915–25, http://dx.doi.org/10.1007/s00420-012-0732-1.Search in Google Scholar

[10] Karoly P, Ruehlman LS, Okun MA. Psychosocial and demographic correlates of employment vs disability status in a national community sample of adults with chronic pain: toward a psychology of pain presenteeism. Pain Med 2013;14:1698–707, http://dx.doi.org/10.1111/pme.12234.Search in Google Scholar

[11] Linton SJ, Boersma K. Early identification of patients at risk of developing a persistent back problem: the predictive validity of the Orebro Musculoskeletal Pain Questionnaire. Clin J Pain 2003;19:80–6, http://dx.doi.org/10.1097/00002508-200303000-00002.Search in Google Scholar

[12] Linton SJ, Nicholas M, MacDonald S. Development of a short form of the Örebro Musculoskeletal Pain Screening Questionnaire. Spine (Phila Pa 1976) 2011;36:1891–5, http://dx.doi.org/10.1097/BRS.0b013e3181f8f775.Search in Google Scholar

[13] Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Car Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Inter Med 1998;158:1789–95, http://dx.doi.org/10.1001/archinte.158.16.1789.Search in Google Scholar

[14] Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren WMM, Albus C, Benlian P, Boysen G, Cifkova R, Deaton C, Ebrahim S, Fisher M, Germano G, Hobbs R, Hoes A, Karadeniz S, Mezzani A, Prescott E, Ryden L, Scherer M, Syvänne M, Scholte Op Reimer WJM, Vrints C, Wood D, Zamorano JL, Zannad F. European Guidelines on cardiovascular disease prevention in clinical practice (version 2012). The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice. Eur Heart J 2012;33:1635–701, http://dx.doi.org/10.1093/eurheartj/ehs092.Search in Google Scholar

[15] Farioli A, Mattioli S, Quaglieri A, Curti S, Violante FS, Coggon D. Musculoskeletal pain in Europe: the role of personal, occupational, and social risk factors. Scand J Work Environ Health 2014;40:36–46, http://dx.doi.org/10.5271/sjweh.3381.Search in Google Scholar

[16] Freimann T, Coggon D, Merisalu E, Animägi L, Pääsuke M. Risk factors for musculoskeletal pain amongst nurses in Estonia: a cross-sectional study. BMC Musculoskelet Disord 2013;14:334, http://dx.doi.org/10.1186/1471-2474-14-334.Search in Google Scholar

[17] Turk DC, Okifuji A. Psychological factors in chronic pain: evolution and revolution. J Consult Clin Psychol 2002;70:678–90.Search in Google Scholar

[18] Baliki MN, Chialvo DR, Geha PY, Levy RM, Harden RN, Parrish TB, Apkarian AV. Chronic pain and the emotional brain: specific brain activity associated with spontaneous fluctuations of intensity of chronic back pain. J Neurosci 2006;26:12165–73, http://dx.doi.org/10.1523/JNEUROSCI.3576-06.2006.Search in Google Scholar

[19] Denollet J. DS14: standard assessment of negative affectivity, social inhibition, and Type D personality. Psychosom Med 2005;67:89–97, http://dx.doi.org/10.1097/01.psy.0000149256.81953.49.Search in Google Scholar

[20] Barnett MD, Ledoux T, Garcini LM, Baker J. Type D personality and chronic pain: construct and concurrent validity of the DS14. J Clin Psychol Med Settings 2009;16:194–9, http://dx.doi.org/10.1007/s10880-009-9152-0.Search in Google Scholar

[21] Mols F, Denollet J. Type D personality among noncardiovascular patient populations: a systematic review. Gen Hosp Psychiatry 2010;32:66–72.Search in Google Scholar

[22] Mols F, Oerlemans S, Denollet J, Roukema JA, van de Poll-Franse LV. Type D personality is associated with increased comorbidity burden and health care utilization among 3080 cancer survivors. Gen Hosp Psychiatry 2012;34:352–9, http://dx.doi.org/10.1016/j.genhosppsych.2009.09.010.Search in Google Scholar

[23] Condén E, Leppert J, Ekselius L, Åslund C. Type D personality is a risk factor for psychosomatic symptoms and musculoskeletal pain among adolescents: a cross-sectional study of a large population-based cohort of Swedish adolescents. BMC Pediatr 2013;13:11, http://dx.doi.org/10.1186/1471-2431-13-11.Search in Google Scholar

[24] Mitchell GA, Harrison DW. Neuropsychological effects of hostility and pain on emotion perception. J Clin Exp Neuropsychol 2010;32:174–89, http://dx.doi.org/10.1080/13803390902889614.Search in Google Scholar

[25] Everson-Rose SA, Lewis TT. Psychosocial factors and cardiovascular diseases. Annu Rev Public Health 2005;26:469–500, http://dx.doi.org/10.1146/annurev.publhealth.26.021304.144542.Search in Google Scholar

[26] Everson-Rose SA, Roetker NS, Lutsey PL, Kershaw KN, Longstreth Jr WT, Sacco RL, Diez Roux AV, Alonso A. Chronic stress, depressive symptoms, anger, hostility, and risk of stroke and transient ischemic attack in the multi-ethnic study of atherosclerosis. Stroke 2014;45:2318–23, http://dx.doi.org/10.1161/STROKEAHA.114.004815.Search in Google Scholar

[27] Burns JW, Peterson KM, Smith DA, Keefe FJ, Porter LS, Schuster E, Kinner E. Temporal associations between spouse criticism/hostility and pain among patients with chronic pain: a within-couple daily diary study. Pain 2013;154:2715–21, http://dx.doi.org/10.1016/j.pain.2013.07.053.Search in Google Scholar

[28] Bakker A, Albrecht S, Leiter M. Key questions regarding work engagement. Eur J Work Organ Psychol 2011;20:4–28, http://dx.doi.org/10.1080/1359432X.2010.485352.Search in Google Scholar

[29] de Vries HJ, Reneman MF, Groothoff JW, Geertzen JH, Brouwer S. Factors promoting staying at work in people with chronic nonspecific musculoskeletal pain: a systematic review. Disabil Rehabil 2012;34:443–58, http://dx.doi.org/10.3109/09638288.2011.607551.Search in Google Scholar

[30] Linton SJ, Boersma K, Traczyk M, Shaw W, Nicholas M. Early workplace communication and problem solving to prevent back disability: results of a randomized controlled trial among high-risk workers and their supervisors. J Occup Rehabil 2016;26:150–9, http://dx.doi.org/10.1007/s10926-015-9596-z.Search in Google Scholar

[31] Herin F, Vézina M, Thaon I, Soulat JM, Paris C, ESTEV Group. Predictive risk factors for chronic regional and multisite musculoskeletal pain: a 5-year prospective study in a working population. Pain 2014;155:937–43, http://dx.doi.org/10.1016/j.pain.2014.01.033.Search in Google Scholar

[32] Thibodeau MA, Welch PG, Katz J, Asmundson GJ. Pain-related anxiety influences pain perception differently in men and women: a quantitative sensory test across thermal pain modalities. Pain 2013;154:419–26, http://dx.doi.org/10.1016/j.pain.2012.12.001.Search in Google Scholar

[33] US Preventive Services Task Force (USPSTF). Screening for depression in adults: US Preventive Services Task Force Recommendation Statement. Ann Intern Med 2009;151:784–92, http://dx.doi.org/10.7326/0003-4819-151-11-200912010-00006.Search in Google Scholar
Received: 2016-08-29
Revised: 2016-11-22
Accepted: 2016-11-26
Published Online: 2017-04-01
Published in Print: 2017-04-01

© 2016 Scandinavian Association for the Study of Pain

Articles in the same Issue

  2. Scandinavian Journal of Pain
  3. Editorial comment
  4. Cardiovascular risk reduction as a population strategy for preventing pain?
  5. Observational study
  6. Diabetes mellitus and hyperlipidaemia as risk factors for frequent pain in the back, neck and/or shoulders/arms among adults in Stockholm 2006 to 2010 – Results from the Stockholm Public Health Cohort
  7. Editorial comment
  8. Exercising non-painful muscles can induce hypoalgesia in individuals with chronic pain
  9. Clinical pain research
  10. Exercise induced hypoalgesia is elicited by isometric, but not aerobic exercise in individuals with chronic whiplash associated disorders
  11. Editorial comment
  12. Education of nurses and medical doctors is a sine qua non for improving pain management of hospitalized patients, but not enough
  13. Observational study
  14. Acute pain in the emergency department: Effect of an educational intervention
  15. Editorial comment
  16. Home training in sensorimotor discrimination reduces pain in complex regional pain syndrome (CRPS)
  17. Original experimental
  18. Pain reduction due to novel sensory-motor training in Complex Regional Pain Syndrome I – A pilot study
  19. Editorial comment
  20. How can pain management be improved in hospitalized patients?
  21. Original experimental
  22. Pain and pain management in hospitalized patients before and after an intervention
  23. Editorial comment
  24. Is musculoskeletal pain associated with work engagement?
  25. Clinical pain research
  26. Relationship of musculoskeletal pain and well-being at work – Does pain matter?
  27. Editorial comment
  28. Preoperative quantitative sensory testing (QST) predicting postoperative pain: Image or mirage?
  29. Systematic review
  30. Are preoperative experimental pain assessments correlated with clinical pain outcomes after surgery? A systematic review
  31. Editorial comment
  32. A possible biomarker of low back pain: 18F-FDeoxyGlucose uptake in PETscan and CT of the spinal cord
  33. Observational study
  34. Detection of nociceptive-related metabolic activity in the spinal cord of low back pain patients using 18F-FDG PET/CT
  35. Editorial comment
  36. Patients’ subjective acute pain rating scales (VAS, NRS) are fine; more elaborate evaluations needed for chronic pain, especially in the elderly and demented patients
  37. Clinical pain research
  38. How do medical students use and understand pain rating scales?
  39. Editorial comment
  40. Opioids and the gut; not only constipation and laxatives
  41. Observational study
  42. Healthcare resource use and costs of opioid-induced constipation among non-cancer and cancer patients on opioid therapy: A nationwide register-based cohort study in Denmark
  43. Editorial comment
  44. Relief of phantom limb pain using mirror therapy: A bit more optimism from retrospective analysis of two studies
  45. Clinical pain research
  46. Trajectory of phantom limb pain relief using mirror therapy: Retrospective analysis of two studies
  47. Editorial comment
  48. Qualitative pain research emphasizes that patients need true information and physicians and nurses need more knowledge of complex regional pain syndrome (CRPS)
  49. Clinical pain research
  50. Adolescents’ experience of complex persistent pain
  51. Editorial comment
  52. New knowledge reduces risk of damage to spinal cord from spinal haematoma after epidural- or spinal-analgesia and from spinal cord stimulator leads
  53. Review
  54. Neuraxial blocks and spinal haematoma: Review of 166 case reports published 1994–2015. Part 1: Demographics and risk-factors
  55. Review
  56. Neuraxial blocks and spinal haematoma: Review of 166 cases published 1994 – 2015. Part 2: diagnosis, treatment, and outcome
  57. Editorial comment
  58. CNS–mechanisms contribute to chronification of pain
  59. Topical review
  60. A neurobiologist’s attempt to understand persistent pain
  61. Editorial Comment
  62. The triumvirate of co-morbid chronic pain, depression, and cognitive impairment: Attacking this “chicken-and-egg” in novel ways
  63. Observational study
  64. Pain and major depressive disorder: Associations with cognitive impairment as measured by the THINC-integrated tool (THINC-it)
https://doi.org/10.1016/j.sjpain.2016.11.018
Keywords for this article
Musculoskeletal pain; Work engagement; Work well-being; UWES (Utrecht Work Engagement Scale); ÖMPSQ (Örebro Musculoskeletal Pain Screening Questionnaire)

Articles in the same Issue

  2. Scandinavian Journal of Pain
  3. Editorial comment
  4. Cardiovascular risk reduction as a population strategy for preventing pain?
  5. Observational study
  6. Diabetes mellitus and hyperlipidaemia as risk factors for frequent pain in the back, neck and/or shoulders/arms among adults in Stockholm 2006 to 2010 – Results from the Stockholm Public Health Cohort
  7. Editorial comment
  8. Exercising non-painful muscles can induce hypoalgesia in individuals with chronic pain
  9. Clinical pain research
  10. Exercise induced hypoalgesia is elicited by isometric, but not aerobic exercise in individuals with chronic whiplash associated disorders
  11. Editorial comment
  12. Education of nurses and medical doctors is a sine qua non for improving pain management of hospitalized patients, but not enough
  13. Observational study
  14. Acute pain in the emergency department: Effect of an educational intervention
  15. Editorial comment
  16. Home training in sensorimotor discrimination reduces pain in complex regional pain syndrome (CRPS)
  17. Original experimental
  18. Pain reduction due to novel sensory-motor training in Complex Regional Pain Syndrome I – A pilot study
  19. Editorial comment
  20. How can pain management be improved in hospitalized patients?
  21. Original experimental
  22. Pain and pain management in hospitalized patients before and after an intervention
  23. Editorial comment
  24. Is musculoskeletal pain associated with work engagement?
  25. Clinical pain research
  26. Relationship of musculoskeletal pain and well-being at work – Does pain matter?
  27. Editorial comment
  28. Preoperative quantitative sensory testing (QST) predicting postoperative pain: Image or mirage?
  29. Systematic review
  30. Are preoperative experimental pain assessments correlated with clinical pain outcomes after surgery? A systematic review
  31. Editorial comment
  32. A possible biomarker of low back pain: 18F-FDeoxyGlucose uptake in PETscan and CT of the spinal cord
  33. Observational study
  34. Detection of nociceptive-related metabolic activity in the spinal cord of low back pain patients using 18F-FDG PET/CT
  35. Editorial comment
  36. Patients’ subjective acute pain rating scales (VAS, NRS) are fine; more elaborate evaluations needed for chronic pain, especially in the elderly and demented patients
  37. Clinical pain research
  38. How do medical students use and understand pain rating scales?
  39. Editorial comment
  40. Opioids and the gut; not only constipation and laxatives
  41. Observational study
  42. Healthcare resource use and costs of opioid-induced constipation among non-cancer and cancer patients on opioid therapy: A nationwide register-based cohort study in Denmark
  43. Editorial comment
  44. Relief of phantom limb pain using mirror therapy: A bit more optimism from retrospective analysis of two studies
  45. Clinical pain research
  46. Trajectory of phantom limb pain relief using mirror therapy: Retrospective analysis of two studies
  47. Editorial comment
  48. Qualitative pain research emphasizes that patients need true information and physicians and nurses need more knowledge of complex regional pain syndrome (CRPS)
  49. Clinical pain research
  50. Adolescents’ experience of complex persistent pain
  51. Editorial comment
  52. New knowledge reduces risk of damage to spinal cord from spinal haematoma after epidural- or spinal-analgesia and from spinal cord stimulator leads
  53. Review
  54. Neuraxial blocks and spinal haematoma: Review of 166 case reports published 1994–2015. Part 1: Demographics and risk-factors
  55. Review
  56. Neuraxial blocks and spinal haematoma: Review of 166 cases published 1994 – 2015. Part 2: diagnosis, treatment, and outcome
  57. Editorial comment
  58. CNS–mechanisms contribute to chronification of pain
  59. Topical review
  60. A neurobiologist’s attempt to understand persistent pain
  61. Editorial Comment
  62. The triumvirate of co-morbid chronic pain, depression, and cognitive impairment: Attacking this “chicken-and-egg” in novel ways
  63. Observational study
  64. Pain and major depressive disorder: Associations with cognitive impairment as measured by the THINC-integrated tool (THINC-it)
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 30.12.2025 from https://www.degruyterbrill.com/document/doi/10.1016/j.sjpain.2016.11.018/html
Scroll to top button