title: [The natural story of a mega selection for nurses: a case study].
abstract: BACKGROUND
  In the Italian National Health Service, it has been documented recently a new phenomenon called 'mega-selection' where thousands of newly graduates submit their application and compete for the few positions available. However, scarce scientific information is available on mega - selections and their outcomes.
  
  
  OBJECTIVE
  To evaluate the nurses candidates profile attending the public selections, the factors affecting their likelihood of success and the duration of the entire selection process.
  
  
  METHODS
  Administrative data of the public selection of nurses performed by 4-health trusts in Friuli Venezia Giulia (Italy) has been obtained: the number and characteristics of the candidates admitted, as well as of those who passed the competition.
  
  
  RESULTS
  Over 3.901 applications, 3.880 candidates were admitted to the selection; only 1.690 (43.3%) attended the public selection, 417 (10.6%) passed the first examination and 217 (7%) passed the competition (7%). The winners were, on average, 27 years old, graduated from approximately 1.5 years, lived and obtained their nursing degree in the northern Italian regions.
  
  
  CONCLUSIONS
  With the hiring freezing documented in recent years in the health sector, a large number of candidates are expected in the public selections; however a limited number succeed in the selection process. Some recommendations are proposed to streamline the public selection process.
authors.affiliation: Responsabile infermieristico AAS 4 Friuli Centrale.
authors.forename: Michele
authors.initials: M
authors.lastname: Picogna
authors.affiliation: Tutor didattico, Università di Udine.
authors.forename: Stefano
authors.initials: S
authors.lastname: Fabris
authors.affiliation: Professore associato infermieristica, Università di Udine Per corrispondenza: Michele Picogna, michele.picogna@aas4.sanita.fvg.it.
authors.forename: Alvisa
authors.initials: A
authors.lastname: Palese
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D007558:Italy; D008297:Male; D008875:Middle Aged; D009726:Nurses / Q000706:statistics & numerical data; D010560:Personnel Selection / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D013222:State Medicine / Q000706:statistics & numerical data