title: Interaction among general practitioners age and patient load in the prediction of job strain, decision latitude and perception of job demands. A cross-sectional study.
abstract: BACKGROUND
  It is widely recognized and accepted that job strain adversely impacts the workforce. Individual responses to stressful situations can vary greatly and it has been shown that certain people are more likely to experience high levels of stress in their job than others. Studies highlighted that there can be age differences in job strain perception.
  
  
  METHODS
  Cross-sectional postal survey of 300 Lithuanian general practitioners. Psychosocial stress was investigated with a questionnaire based on the Reeder scale. Job demands were investigated with the Karasek scale. The analysis included descriptive statistics; logistic regression beta coefficients to find out predictors and interactions between characteristics and predictors.
  
  
  RESULTS
  Response rate was 66% (N = 197). Logistic regression as significant predictors for job strain assigned - duration of work in primary care; for job demands- age and duration of working in primary care; for decision latitude- age and patient load.The interactions with regard to job strain showed that GP's age and job strain are negatively associated to a low patient load. Lower decision latitude for older GP age is strongly related to higher patient load. Job demands and GP age are slightly positively related at low patient load.
  
  
  CONCLUSIONS
  Lithuanian GP's have high patient load and are at risk of stress, they have high job demands and low decision latitude. Older GP's perceive less strain, lower job demands and higher decision latitude in case of low patient load. Young GP's decision latitude has week association to patient load. Regarding to the changes in patient load younger GP's perceive it more sensitively as changes in job demands.
authors.affiliation: Kaunas University of Medicine, Dept. Preventive Medicine, Kaunas, Lithuania. vanagas@kmu.lt
authors.forename: Giedrius
authors.initials: G
authors.lastname: Vanagas
authors.forename: Susanna
authors.initials: S
authors.lastname: Bihari-Axelsson
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D003430:Cross-Sectional Studies; D003657:Decision Making; D005194:Family Practice / Q000706:statistics & numerical data*; D005260:Female; D006301:Health Services Needs and Demand; D006306:Health Surveys; D006801:Humans; D008097:Lithuania / Q000453:epidemiology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000453:epidemiology; D010817:Physician-Patient Relations; D010821:Physicians, Family / Q000523:psychology* / Q000706:statistics & numerical data; D012044:Regression Analysis; D013315:Stress, Psychological / Q000453:epidemiology*; D011795:Surveys and Questionnaires; D000078329:Workforce; D016526:Workload / Q000523:psychology*