- Research article
- Open Access
- Open Peer Review
The importance of work conditions and health for voluntary job mobility: a two-year follow-up
© Reineholm et al.; licensee BioMed Central Ltd. 2012
- Received: 22 December 2011
- Accepted: 13 August 2012
- Published: 21 August 2012
Changing jobs is part of modern working life. Within occupational health, job mobility has mainly been studied in terms of employees’ intentions to leave their jobs. In contrast to actual turnover, turnover intentions are not definite and only reflect the probability that an individual will change job. The aim of this study was to determine what work conditions predict voluntary job mobility and to examine if good health or burnout predicts voluntary job mobility.
The study was based on questionnaire data from 792 civil servants. The data were analysed using logistic regressions.
Low variety and high autonomy were associated with increased voluntary job mobility. However, the associations between health and voluntary job mobility did not reach significance. Possible explanations for the null results may be that the population was homogeneous, and that the instruments for measuring global health are too coarse for a healthy, working population.
Voluntary job mobility may be predicted by high autonomy and low variety. The former may reflect that individuals with high autonomy have stronger career development motives; the latter may reflect the fact that low variety leads to job dissatisfaction. In contrast to our results on job content, global health measurements are not strong predictors of voluntary job mobility. This may be because good health affects job mobility through several offsetting channels, involving the resources and ability to seek a new job. Future work should use more detailed measurements of health or examine other work settings so that we may learn more about which of the offsetting effects of health dominate in different contexts.
- Work conditions
- Voluntary job mobility
- Two-year follow-up
Since the 1990s, working life has undergone several changes. As a result of globalization, new technology, and a gradual shift from production to service jobs, new work tasks and new types of jobs have evolved . Today, changing jobs is part of modern working life. In the literature, a number of concepts have been used for defining this, such as turnover, job change, job separation and job mobility. In this study, the focus is on employees changing jobs voluntarily, defined as voluntary job mobility.
Bad work conditions increase peoples’ willingness to change jobs, but it seems that the decision to actually change jobs is more complex and depends on several factors. Poor health may lead to downward mobility or redundancy, but it is also suggested that poor health increases the risk of being “locked in”, i.e. non-mobility. Changing jobs seems to lead to increased job satisfaction and increased health, but good health may also be a condition for having the ability or strength to actually change jobs. Given this background, the objective of the present study is twofold: 1) to determine what work conditions predict voluntary job mobility and 2) to examine if good health or burnout predicts voluntary job mobility.
Voluntary job mobility and work conditions
Within occupational health, voluntary job mobility has mainly been studied in terms of the intention of employees’ to leave their jobs. In contrast to actual job mobility, turnover intentions are not definite. Intention to leave is an attitude that reflects the individual’s propensity to change jobs [2, 3]. High turnover intentions are related to negative factors at work, such as high work load , job dissatisfaction , and limited opportunities for advancement : i.e., bad work conditions seem to affect peoples’ willingness to change jobs. For example, Brannon, Barry, Kemper, Schreiner, and Vasey  found that low skill variety was related to an increased intention to leave the job. Other studies have found associations between high turnover intentions and low autonomy, low feedback [8, 9], and a low level of social support . Although turnover intentions are often considered to be a strong predictor of future job mobility [3, 11, 12], a direct association between turnover intentions and job mobility is only weakly supported, possibly because of the cross-sectional design of most studies.
Changing jobs increases job satisfaction  and health , but few studies have investigated causes of actual job mobility. In a study by Jaros , job satisfaction and organizational commitment were found to be negatively related to voluntary job mobility. Among nurses leaving their jobs, Skytt, Ljunggren, and Carlsson  found that lack of social support from supervisors and heads of department was a common reason for leaving, and changing jobs increased job satisfaction. The traditional view is that people change jobs due to dissatisfaction , and Castle and Engberg  claim that the decision to quit a job consists of cognitive stages where job dissatisfaction is the initial state. In addition to job dissatisfaction, Mobley, Griffeth, Hand, and Megliano  suggest that job mobility may also be due to the opportunity to change to a more attractive job. According to Mitchell, Holtom, Lee, Sablynski and Erez , the combination of job attitudes and job alternatives predicts intention to leave, and if an alternative job is better than their current one, people will change. Thus, according to present knowledge, changing jobs may increase job satisfaction, but knowledge is essentially lacking concerning what work conditions predict voluntary job mobility in a longitudinal perspective.
Although job mobility is often seen as an opportunity to find a better job , employees do not always choose to quit even if they are dissatisfied with their present job and have the opportunity to change. This means that additional factors may affect job mobility and the relationship between turnover intentions and job mobility may vary . Thus, job dissatisfaction does not necessarily lead to actual job mobility . Individual characteristics such as age, education level and having a family are well-known indicators associated with job mobility [20–22]. Having a family is also negatively related to job seeking behaviour, as found by van Hooft, Born, Taris, van der Flier and Blonk . These factors should therefore be taken into consideration when studying voluntary job mobility. Naturally, opportunities for changing jobs are dependent on additional factors such as recession, high unemployment rates , and geographic factors .
Voluntary job mobility and health
Voluntary job mobility seems to improve job satisfaction [13, 15] and reduce physical and mental strain [26, 27], possibly because this type of mobility may involve career development or positive choices. Poor health, on the other hand, may increase the risk of downward mobility to lower qualified jobs and unhealthy employees are also more likely to be redundant than healthy employees [28–30]. At the structural level, low mobility in the labour market may be a possible explanation for ill health and long-term sick leave , due to a mismatch between job demands and individual capacity. However, a low degree of job mobility is not necessarily predictive of job satisfaction or a healthy organizational environment, as pointed out by Strolin-Goltzman .
Compared with other countries, Sweden has low job mobility and a possible explanation may be found in the Swedish labour market regulations . The Employment Protection Law  protects employees with long employment tenure from being laid off. According to von Otter , the law may also lock people into permanent but not preferred jobs because it makes employees hesitate to change jobs due to the risk of being first in line to be redundant at the new workplace due to short work tenure. Low job mobility may also increase the risk of becoming embedded or in a locked-in position, which increases the risk of ill health [35, 36].
A questionnaire was sent by post to all employees (N = 1010), including those on sick leave and on leave of absence, at three different regional organizations of the Swedish National Labour Market Administration (AMV). Of the 1010 employees, 602 (60%) were women and 408 (40%) were men. The average age was 48.7 years (SD 9.28 years), ranging from 25 to 65 years, and most of the respondents were working as employment officers in different local employment agencies. A total of 792 employees (78%) responded to the questionnaire. Forty-five percent of the respondents had a university degree and 43% had graduated from upper secondary school. Most (80%) were married or living with a partner and 46% had children living at home.
Information regarding job mobility for the two years after the baseline questionnaire was provided by the organization where the respondents were employed. Respondents who had retired between baseline and the follow-up (n = 15) were excluded from the analysis.
Ethical principles for social science have been observed, in that the purpose of the research was explained, informed consent was received, confidentiality was maintained, no individual response could be recognized etc. The questionnaires were sent by post to each individual; they were returned by the respondent in an enclosed response envelope and were only read by the researchers.
The study was approved by the Ethics Committee at Linkoping University.
Sex, age, education level, civil status, and having children living at home were used as demographic variables.
Work conditions were measured by the Job Characteristic Inventory (JCI) . The JCI was developed to measure how job characteristics relate to productivity and job satisfaction in different organizations. Variety, autonomy, task identity, and feedback are suggested as core dimensions because employees will be able to obtain satisfaction and perform well if they experience variation in work tasks, can plan and decide how work should be carried out, can identify the results of their efforts, and get feedback on how they are performing. One example item for measuring variety is: “How much variety is there in your job?” The response options on a 5-point Likert scale range from very little (1) to very much (5). Cronbach’s alpha was 0.84 for the variety scale, 0.82 for the feedback scale, 0.79 for the task identity scale, and 0.69 for the autonomy scale.
Measurements of health were chosen to capture a range of good health to bad health. The SF-36  is a generic instrument designed to be applicable to a wide range of physical and mental health conditions. Vitality, as a component of good health, was measured by the vitality scale from the SF-36. The vitality scale captures health states ranging from feeling tired and worn out to feeling full of pep and energy. One example item for measuring vitality is: “How much of the time during the four past weeks did you have a lot of energy?” The response options on an 8-point Likert scale range from all of the time (1) to none of the time (8). Cronbach’s alpha was 0.85 for the vitality scale.
Overall health was measured by the Visual Analog Scale from the EuroQol instrument (EQ-VAS) . The purpose of the self-rating scale is to capture overall health; the respondents rate their current physical and mental health state ranging from the worst state you can imagine (0) to the best state you can imagine (100).
The Copenhagen Burnout Inventory (CBI) was developed to measure burnout, anxiety, and fatigue . Only the generic part of the CBI, personal burnout, was used in the present study as an indicator of general burnout. One example item for measuring burnout is: “How often do you feel worn out?” and the response options on a 5-point Likert scale range from always (1) to never/almost never (5). The scale ranges from 0 to 100, where the first category, always, is scored 100 and the fifth category, never/almost never, is scored 0. Cronbach’s alpha was 0.90 for the personal burnout scale.
Voluntary job mobility
Voluntary job mobility was defined as voluntarily changing jobs, i.e. leaving the organization. Information about job mobility between baseline and two years later was provided by the organization where the respondents were employed. Voluntary job mobility was coded as non-mobile (still at original workplace or internal mobility) or mobile (changing organization/employer).
Mobility and non-mobility were examined with cross-tabulation and the chi-squared test. The distribution of the means and standard deviations for work conditions and self-rated health and burnout in relation to non-mobility and mobility were calculated using the t-test. To investigate how demographic variables, work conditions and health predict voluntary job mobility, logistic regressions were performed. The results are presented as odds ratios (OR) with 95% confidence intervals (CI). SPSS version 17.0 was used for the statistical analyses.
The response rate was 78%. Non-responders and dropouts were analysed with the available data (sex and age). The response rate did not differ significantly between the sexes. The responders were older than the non-responders (p < .01).
Descriptive statistics for voluntary job mobility between baseline and the two-year follow-up distributed among sex, age, education level, civil status, and having children living at home ( N = 1010)
55years and older
9-years compulsory school
2years upper secondary school
3/4years upper secondary school
Descriptive statistics (means and standard deviations) and results of t -test for work conditions and health distributed among non-mobile and mobile
Work conditions, health, burnout, and voluntary job mobility
Associations between work conditions, health, burnout at baseline, and voluntary job mobility at follow-up (OR, p -value and 95% CI), controlled for sex, age, education, civil status and having children living at home
Health and burnout
In Model 1, work conditions were adjusted for each other to determine the association with voluntary job mobility. Low variety (OR 0.62, CI 0.42–0.91) and high autonomy (OR 1.71, CI 1.00–2.89) were associated with voluntary job mobility.
In Model 2, the associations between work conditions and voluntary job mobility were adjusted for health variables. Low variety and high autonomy remained associated with voluntary job mobility. The associations between health and voluntary job mobility were not significant, but burnout was close to significance (OR 1.02, CI 1.00–1.04).
The purpose of this study was to examine what work conditions predict voluntary job mobility, and whether good health or burnout predicts voluntary job mobility. The respondents in this study had a high degree of job mobility. After two years, 12% had left their organization compared with the average workplace mobility in Sweden of 8% during the same period . The study population was not only well-educated; in all likelihood they also had a good knowledge of the labour market, since they worked as employment officers. High employability and good opportunities for changing jobs may therefore be a possible explanation for the high degree of job mobility in the study population.
Younger individuals were more mobile. It can be assumed that trying different types of jobs or occupations while building up a career is more common among younger individuals. As individual characteristics are important for being able to change jobs , sex, age, education level, civil status, and having children living at home were controlled for in the analysis.
Work conditions and voluntary job mobility
The results showed that work conditions were related to voluntary job mobility. Low variety (i.e. a low degree of variety in work tasks or procedures) was associated with high voluntary job mobility. According to the activation theory, stimulation by variety and complexity of tasks increases the activation level, which is suggested to improve motivation and job satisfaction . Repetitive tasks may decrease motivation, job satisfaction, and performance [42, 43]. Low variety has been associated with increased turnover intentions in several studies [7, 8], and according to Castle and Engberg  job dissatisfaction is the first step towards the decision to change jobs. Thus, as high variety is related to job satisfaction , low variety may be assumed to predict voluntary job mobility due to job dissatisfaction.
Employees scoring high on autonomy, i.e. the extent to which employees have a major say in planning, performing, and controlling their work, had higher voluntary job mobility. In previous research, low autonomy was associated with high turnover intentions [8, 9] and decreased job satisfaction . It is reasonable to assume that respondents who scored high on perceived autonomy in this study changed jobs for other reasons than dissatisfaction with their current job, such as career development and advancement to higher skilled jobs. This confirms the statement by Mobley, Griffeth, Hand and Megliano , that in addition to job dissatisfaction, voluntary job mobility may be related to the decision to change to a more attractive job. According to the gravitational theory [27, 46, 47], people move to a job that matches their ability level, but some people may have higher goals and strive for advancement that matches their future goals and career plans. Changing jobs seems to be triggered by individual motives and people change jobs in the expectation that the new job will be an improvement on their current job, in terms of better work conditions, career development, etc. . This may also gain support from the expectancy theory, which perceives individuals as rational beings who choose between action options in order to maximize outcomes and minimize costs , or to maximize pleasure or minimize pain . The expectancy theory also proposes that individuals’ choices about a certain act depend on their beliefs in their own capabilities and the reward from it . Thus, voluntary job mobility may be due to different reasons: job dissatisfaction but also career development and new challenges.
Voluntary job mobility and health
Despite using instruments that were expected to capture the spectrum from good health to bad health, the associations between health and voluntary job mobility did not quite reach significance. One possible explanation for the null results is that the instruments for measuring global health are too coarse for a healthy, working population. Furthermore, they are also designed to capture symptoms. As the respondents in this study were all white-collar workers with no physically demanding work tasks, this may also have affected the null results.
Voluntary job mobility is most likely due to two forces for mobility: job dissatisfaction and career development. These forces may, in turn, define individuals who are able to act and mobilize themselves to a new job. According to a holistic approach to health, health is related to an individual’s ability to act, and an individual has full health if, in a given standard situation, he or she has the ability to fulfil vital goals . Drawing on this health approach, work itself may be important for health, which, in turn, may be important for voluntary job mobility.
A weakness of this study is the homogeneous population. The respondents were all well-educated white-collar workers and worked in the same organization with similar work tasks. This may have caused imprecise estimation of associations, compared with a more heterogeneous population.
The strength of this study is the two-year follow-up data and the high response rate.
We find that voluntary job mobility is predicted by high autonomy and low variety. The former may reflect that individuals with high autonomy have stronger career development motives; the latter may reflect the fact that low variety leads to job dissatisfaction. In contrast to our results on job content, global health measurements are not strong predictors of voluntary job mobility. This may be because good health affects job mobility through several offsetting channels, involving the resources and ability to seek a new job. Future work should use more detailed measurements of health or examine other work settings so that we may learn more about which of the offsetting effects of health dominate in different contexts.
- Näswall K, Hellgren J, Sverke M: The individual in the changing working life. 2008, Cambridge University Press: CambridgeView ArticleGoogle Scholar
- Allen DG, Weeks KP, Moffitt KR: Turnover intentions and voluntary turnover: the moderating roles of self-monitoring, locus of control, pro-active personality, and risk aversion. J Appl Psychol. 2005, 90: 980-990.View ArticlePubMedGoogle Scholar
- Sousa-Poza A, Henneberger F: Analyzing job mobility with turnover intentions: an international comparative study. J Econ Issues. 2004, 38: 113-137.View ArticleGoogle Scholar
- Conklin MH, Desselle SP: Job turnover intentions among pharmacy faculty. Am J Pharm Educ. 2007, 71: 62-10.5688/aj710462. articleView ArticlePubMedPubMed CentralGoogle Scholar
- Coomber B, Barriball KL: Impact of job satisfaction components on intent to leave and turnover for hospital-based nurses: a review of job-related and non-related factors. Int J Nurs Stud. 2007, 44: 297-314. 10.1016/j.ijnurstu.2006.02.004.View ArticlePubMedGoogle Scholar
- Flinkman M, Laine M, Leino-Kilpi H, Hasselhorn H-M, Salanterä S: Explaining young registered Finnish nurses’ intentions to leave the profession: a questionnaire survey. Int Arch Environ Health. 2008, 45: 727-739.Google Scholar
- Brannon D, Barry T, Kemper P, Schreiner A, Vasey J: Job perceptions and intent to leave among direct care workers: evidence from the better jobs better care demonstrations. Gerontologist. 2007, 47: 820-829. 10.1093/geront/47.6.820.View ArticlePubMedGoogle Scholar
- Lin B-Y, Yeh Y-C, Lin W-H: The influence of job characteristics on job outcomes of pharmacists in hospital, clinical, and community pharmacies. J Med Syst. 2007, 31: 224-229. 10.1007/s10916-007-9059-y.View ArticlePubMedGoogle Scholar
- Spector PE, Jex SM: Relations of job characteristics from multiple data sources with employee affect, absence, turnover intentions, and health. J Appl Psychol. 1991, 76: 46-53.View ArticlePubMedGoogle Scholar
- Acker GM: The effect of organizational conditions (role conflict, role ambiguity, opportunities for professional development, and social support) on job satisfaction and intention to leave among social workers in mental health care. Comm Ment Health J. 2004, 40: 65-73.View ArticleGoogle Scholar
- George JM, Jones GR: The experience of work and turnover intentions: interactive effects of value attainment, job satisfaction, and positive mood. J Appl Psychol. 1996, 81: 318-325.View ArticlePubMedGoogle Scholar
- Jaros SJ: An assessment of Meyer and Allen’s (1991) Three-Component Model of Organizational Commitment and Turnover Intentions. J Vocat Behav. 1997, 51: 319-337. 10.1006/jvbe.1995.1553.View ArticleGoogle Scholar
- Kalleberg AL, Mastekaasa A: Satisfied movers, committed stayers. The impact of job mobility on work attitudes in Norway. Work Occup. 2001, 28: 183-209. 10.1177/0730888401028002004.View ArticleGoogle Scholar
- Liljegren M, Ekberg K: Job mobility as predictor to health and burnout. J Occup Organ Psychol. 2009, 82: 317-329. 10.1348/096317908X332919.View ArticleGoogle Scholar
- Skytt B, Ljunggren B, Carlsson M: Reasons to leave: the motives of firstline nurse managers’ for leaving their posts. J Nurs Manage Stud. 2007, 15: 294-302. 10.1111/j.1365-2834.2007.00651.x.View ArticleGoogle Scholar
- Mitchell TR, Holtom BC, Lee TW, Sablynski CJ, Erez M: Why people stay: using job embeddedness to predict voluntary turnover. Acad Manage J. 2001, 44: 1102-1121. 10.2307/3069391.View ArticleGoogle Scholar
- Castle NG, Engberg J: Organizational characteristics associated with staff turnover in nursing homes. Gerontologist. 2006, 46: 62-73. 10.1093/geront/46.1.62.View ArticlePubMedGoogle Scholar
- Mobley WH, Griffeth RW, Hand HH, Megliano BM: Review and conceptual analysis of the employee turnover process. Psychol Bull. 1979, 86: 493-522.View ArticleGoogle Scholar
- Wheeler AR, Coleman Gallagher V, Brouer R, Sablynski C: When person-organization (mis)fit and (dis)satisfaction lead to turnover. J Manage Psychol. 2007, 22: 203-219. 10.1108/02683940710726447.View ArticleGoogle Scholar
- de Luis Carnicer M, Sanchez AM, Perez MP, Jimenez MJV: Analysis of internal and external labour mobility. A model of job-related and non-related factors. Pers Rev. 2004, 33: 222-240. 10.1108/00483480410518068.View ArticleGoogle Scholar
- Muffels R, Luijkx R: Labour market mobility and employment security of male employees in Europe: ‘trade-off’ or ‘flexicurity’?. Work Employment Society. 2008, 22: 221-242. 10.1177/0950017008089102.View ArticleGoogle Scholar
- Virjo I: Mobility between workplaces, occupations and industries. In Labour market mobility in Nordic welfare states. TemaNord 2010:515. 2010, Copenhagen: Nordic Council of Ministers; 2010:183, 183-Google Scholar
- Van Hooft EAJ, Born MPH, Taris TW, van der Flier H, Blonk RWB: Predictors and outcomes of job search behavior: the moderating effects of gender and family situation. J Vocat Behav. 2005, 67: 133-152. 10.1016/j.jvb.2004.11.005.View ArticleGoogle Scholar
- Rosenfeld RA: Job mobility and career processes. Ann Rev Sociol. 1992, 18: 39-61. 10.1146/annurev.so.18.080192.000351.View ArticleGoogle Scholar
- Wilk SI, Sackett PR: Longitudinal analysis of ability-job complexity fit and job change. Pers Psychol. 1996, 49: 937-967. 10.1111/j.1744-6570.1996.tb02455.x.View ArticleGoogle Scholar
- de Croon EM, Sluiter JK, Blonk RWB, Broersen JPJ, Frings-Dresen MHW: Stressful work, psychological job strain, and turnover: a 2-year prospective cohort study of truck drivers. J Appl Psychol. 2004, 89: 442-454.View ArticlePubMedGoogle Scholar
- Swaen GMH, Kant IJ, van Amelsvoort LGPM, Beurskens AJHM: Job mobility, its determinants, and its effects: longitudinal data from the Maastricht Cohort Study. J Occup Health Psychol. 2007, 7: 121-129.View ArticleGoogle Scholar
- Cardano M, Costa G, Demaria M: Social mobility and health in the Turin longitudinal study. Soc Sci Med. 2004, 58: 1563-1574. 10.1016/S0277-9536(03)00354-X.View ArticlePubMedGoogle Scholar
- Kivimäki M, Vahtera J, Elovainio M, Pentti J, Virtanen M: Human costs of organizational downsizing: comparing health trends between leavers and stayers. Am J Comm Psychol. 2003, 32: 57-67. 10.1023/A:1025642806557.View ArticleGoogle Scholar
- van de Mheen H, Stronks K, Schrijvers CTM, Mackenbach JP: The influence of adult ill health on occupational class mobility and mobility out of and into employment in the Netherlands. Soc Sci Med. 1999, 49: 509-518. 10.1016/S0277-9536(99)00140-9.View ArticlePubMedGoogle Scholar
- Rothstein B, Boräng F: Dags att dra in guldklockorna? Om rörlighet och sjukfrånvaro på den svenska arbetsmarknaden. Svenska strukturproblem kontra dansk dynamik. Edited by: Olshov A. 2006, ÖI förlag, Malmö, 48-74.Google Scholar
- Strolin-Goltzman J: Should I stay or should I go? A comparison study of intention to leave among public child welfare systems with high and low turnover rates. Child Welfare. 2008, 87: 125-143.PubMedGoogle Scholar
- Employment Protection Law: SFS 1982:80. 1982, Stockholm: RegeringskanslietGoogle Scholar
- von Otter C: I skuggan av marknadskrafterna – synpunkter på arbetslivsforskningens framtid. Arbetsmarknad Arbetsliv. 2007, 13: 87-104.Google Scholar
- Aronsson G, Göransson S: Permanent employment but in a non-preferred occupation: psychological and medical aspects, research implications. J Occup Health Psychol. 1999, 4: 152-163.View ArticlePubMedGoogle Scholar
- Fahlén G, Goine H, Edlund C, Arrelöv B, Knutsson A, Richard P: Effort-reward imbalance, “locked-in” at work, and long-term sick leave. Int Arch Environ Health. 2009, 82: 191-197. 10.1007/s00420-008-0321-5.View ArticleGoogle Scholar
- Sims HP, Szilagyi AD, Keller RT: The measurement of job characteristics. Acad Manage J. 1976, 19: 195-212. 10.2307/255772.View ArticlePubMedGoogle Scholar
- Sullivan M, Karlsson J, Ware JE: The Swedish SF-36 health survey – I. Evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med. 1995, 41: 1349-1358. 10.1016/0277-9536(95)00125-Q.View ArticlePubMedGoogle Scholar
- Rabin R, de Charro F: EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001, 33: 337-343. 10.3109/07853890109002087.View ArticlePubMedGoogle Scholar
- Kristensen TS, Borritz M, Villadsen E, Christensen KB: The Copenhagen Burnout Inventory: a new tool for the assessment of burnout. Work Stress. 2005, 19: 192-207. 10.1080/02678370500297720.View ArticleGoogle Scholar
- Scott WE: Activation theory and task design. Organ Behav Human Perf. 1966, 1: 3-30. 10.1016/0030-5073(66)90003-1.View ArticleGoogle Scholar
- Oldham JR, Hackman GR, Pearce JL: Conditions under which employees respond positively to enriched work. J Appl Psychol. 1976, 61: 395-403.View ArticleGoogle Scholar
- Van Veldhoven M, de Jonge J, Broersen S, Kompier M, Meijman T: Specific relationships between psychosocial job conditions and job-related stress: a three-level analytic approach. Work Stress. 2002, 16: 207-228. 10.1080/02678370210166399.View ArticleGoogle Scholar
- Humphrey SE, Nahrgang JD, Morgeson FP: Integrating motivational, social, and contextual work design features: a meta-analytic summary and theoretical extension of the work design literature. J Appl Psychol. 2007, 92: 1332-1356.View ArticlePubMedGoogle Scholar
- Warr P: Well-being and the workplace. Well-being: the foundation of hedonic psychology. Edited by: Kahnemann D, Diener E, Schwarz N. 1999, New York: Russell Sage FoundationGoogle Scholar
- McCormick EJ, DeNisi AS, Shaw JB: Use of the Positions Analysis Questionnaire for establishing the job component validity of tests. J Appl Psychol. 1979, 64: 51-56.View ArticleGoogle Scholar
- McCormick EJ, Jeanneret PR, Mecham RC: Study of job characteristics and job dimensions as based on the Position Analysis Questionnaire (PAQ). J Appl Psychol. 1972, 56: 347-368.View ArticleGoogle Scholar
- Hertel G, Wittchen M: Work motivation. An introduction to work and organizational psychology. A European perspective. Edited by: Chmiel N. 2008, Malden: Blackwell Publishing, 29-55. 2Google Scholar
- Donovan JJ: Work motivation. Handbook of industrial, work & organizational psychology. Organizational psychology. Edited by: Andersson N, Ones DS, Sinangil HK, Visvesvaran C. 2001, London: Sage Publications, 53-76. Volume 2View ArticleGoogle Scholar
- Arnold J, Silvester J, Patterson F, Robertson I, Cooper C, Burnes B: Work psychology. Understanding human behaviour in the workplace. 2004, New York: Financial Times/Prentice Hall, 319-322. 4Google Scholar
- Nordenfelt L: On the nature of health. An action-theoretic approach. 1995, Dordrecht: Kluwer, 35-80.Google Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/682/prepub
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