Detail
Článek
Článek online
FT
Medvik - BMČ
  • Je něco špatně v tomto záznamu ?

Datamining techniques - decision tree: new view on nurses' intention to leave

Jiří Vévoda, Šárka Vévodová, Štěpánka Bubeníková, Helena Kisvetrová, Kateřina Ivanová

. 2016 ; 7 (4) : 518-526.

Jazyk angličtina Země Česko

Typ dokumentu pozorovací studie, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc17023090

Aim: The aim of the survey is to identify factors of the work environment which are important for general nurses when they are considering whether or not to leave their current employer. Design: The research consists of an observational and a crosssectional study. Methods: Based on a modified interpretation of Herzberg's theory, we created a structured interview to investigate environmental factors. Interviewers carried out 1,992 interviews with hospital nurses working in the Czech Republic, between 2011 and 2012. The data gathered were analyzed with data mining tools – a decision tree and nonparametric tests. Results: If a good opportunity arose, 34.7% of nurses would leave their current employer. The analysis of the decision tree identified the factor “Patient care”, i.e. a factor concerning the nature of the work itself, as the most important. Data mining offers a new view of the data and can reveal valuable information existing within the primary data. Conclusion: Data mining has great potential in nursing. In this research, the decision tree shows that the essence of the nursing profession is the nursing work itself and it is also the most significant stabilizing factor. The management of healthcare providers should create and maintain a work environment which will ensure nursing work can be performed without impediment, thus minimizing staff turnover.

Bibliografie atd.

Literatura

000      
00000naa a2200000 a 4500
001      
bmc17023090
003      
CZ-PrNML
005      
20200317101049.0
007      
cr|cn|
008      
170720s2016 xr d fs 000 0|eng||
009      
eAR
024    7_
$2 doi $a 10.15452/cejnm.2016.07.0024
040    __
$a ABA008 $d ABA008 $e AACR2 $b cze
041    0_
$a eng
044    __
$a xr
100    1_
$a Vévoda, Jiří $7 hka2013783529 $u Department of Healthcare Management, Faculty of Health Sciences, Palacký University, Czech Republic
245    10
$a Datamining techniques - decision tree: new view on nurses' intention to leave / $c Jiří Vévoda, Šárka Vévodová, Štěpánka Bubeníková, Helena Kisvetrová, Kateřina Ivanová
504    __
$a Literatura
520    9_
$a Aim: The aim of the survey is to identify factors of the work environment which are important for general nurses when they are considering whether or not to leave their current employer. Design: The research consists of an observational and a crosssectional study. Methods: Based on a modified interpretation of Herzberg's theory, we created a structured interview to investigate environmental factors. Interviewers carried out 1,992 interviews with hospital nurses working in the Czech Republic, between 2011 and 2012. The data gathered were analyzed with data mining tools – a decision tree and nonparametric tests. Results: If a good opportunity arose, 34.7% of nurses would leave their current employer. The analysis of the decision tree identified the factor “Patient care”, i.e. a factor concerning the nature of the work itself, as the most important. Data mining offers a new view of the data and can reveal valuable information existing within the primary data. Conclusion: Data mining has great potential in nursing. In this research, the decision tree shows that the essence of the nursing profession is the nursing work itself and it is also the most significant stabilizing factor. The management of healthcare providers should create and maintain a work environment which will ensure nursing work can be performed without impediment, thus minimizing staff turnover.
650    12
$a zdravotní sestry $x ekonomika $x klasifikace $x psychologie $x statistika a číselné údaje $7 D009726
650    _2
$a zaměstnanost $7 D004651
650    12
$a pracovní uspokojení $7 D007588
650    _2
$a mzdy a přídavky $7 D012456
650    _2
$a péče o pacienta $x psychologie $7 D005791
650    _2
$a pracovní stres $7 D000073397
650    _2
$a motivace $7 D009042
650    _2
$a rozhodovací stromy $7 D003663
650    _2
$a data mining $7 D057225
650    _2
$a lidé $7 D006801
650    _2
$a ženské pohlaví $7 D005260
655    _2
$a pozorovací studie $7 D064888
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Vévodová, Šárka, $d 1976- $7 xx0101697 $u Department of Humanities and Social Sciences, Faculty of Health Sciences, Palacký University Olomouc, Czech Republic
700    1_
$a Bubeníková, Štěpánka $7 osd2016912926 $u Department of Midwifery, Faculty of Health Sciences, Palacký University Olomouc, Czech Republic
700    1_
$a Kisvetrová, Helena $7 hka2010569765 $u Department of Nursing, Faculty of Health Sciences, Palacký University Olomouc, Czech Republic
700    1_
$a Ivanová, K, $d 1955- $7 _AN118063 $u Department of Social Medicine and Public Health, Faculty of Medicine and Dentistry, Palacký University Olomouc, Czech Republic
773    0_
$t Central European Journal of Nursing and Midwifery $x 2336-3517 $g Roč. 7, č. 4 (2016), s. 518-526 $w MED00183333
856    41
$u https://cejnm.osu.cz/ $y domovská stránka časopisu
910    __
$a ABA008 $b online $y 4 $z 0
990    __
$a 20170719183927 $b ABA008
991    __
$a 20200317101513 $b ABA008
999    __
$a ok $b bmc $g 1238771 $s 984003
BAS    __
$a 3 $a 4
BMC    __
$a 2016 $b 7 $c 4 $d 518-526 $i 2336-3517 $m Central European Journal of Nursing and Midwifery $x MED00183333
LZP    __
$c NLK197 $d 20190303 $a NLK 2017-33/vt

Najít záznam

Citační ukazatele

Možnosti archivace