Literature DB >> 21631936

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units.

Adriana P A van Beek1, Cordula Wagner, Peter P M Spreeuwenberg, Dinnus H M Frijters, Miel W Ribbe, Peter P Groenewegen.   

Abstract

BACKGROUND: The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction.
METHODS: We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account.
RESULTS: Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model.
CONCLUSIONS: Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction.

Entities:  

Mesh:

Year:  2011        PMID: 21631936      PMCID: PMC3133544          DOI: 10.1186/1472-6963-11-140

Source DB:  PubMed          Journal:  BMC Health Serv Res        ISSN: 1472-6963            Impact factor:   2.655


  11 in total

1.  Factors influencing satisfaction and anticipated turnover for nurses in an academic medical center.

Authors:  K Shader; M E Broome; C D Broome; M E West; M Nash
Journal:  J Nurs Adm       Date:  2001-04       Impact factor: 1.737

2.  Health care for older persons, a country profile: The Netherlands.

Authors:  J F Hoek; B W Penninx; G J Ligthart; M W Ribbe
Journal:  J Am Geriatr Soc       Date:  2000-02       Impact factor: 5.562

3.  Hierarchies and cliques in the social networks of health care professionals: implications for the design of dissemination strategies.

Authors:  E West; D N Barron; J Dowsett; J N Newton
Journal:  Soc Sci Med       Date:  1999-03       Impact factor: 4.634

Review 4.  Multilevel modelling and public health policy.

Authors:  Alastair H Leyland; Peter P Groenewegen
Journal:  Scand J Public Health       Date:  2003       Impact factor: 3.021

5.  Informal networks: the company behind the chart.

Authors:  D Krackhardt; J R Hanson
Journal:  Harv Bus Rev       Date:  1993 Jul-Aug

6.  "We decide, you carry it out": a social network analysis of multidisciplinary long-term care teams.

Authors:  C Cott
Journal:  Soc Sci Med       Date:  1997-11       Impact factor: 4.634

7.  Analysis of non-response bias in a mailed health survey.

Authors:  J F Etter; T V Perneger
Journal:  J Clin Epidemiol       Date:  1997-10       Impact factor: 6.437

8.  Networked for change? Identifying obstetric opinion leaders and assessing their opinions on caesarean delivery.

Authors:  Richard L Kravitz; David Krackhardt; Joy Melnikow; Carol E Franz; William M Gilbert; Andra Zach; Debora A Paterniti; Patrick S Romano
Journal:  Soc Sci Med       Date:  2003-12       Impact factor: 4.634

9.  Understanding communication networks in the emergency department.

Authors:  Nerida Creswick; Johanna I Westbrook; Jeffrey Braithwaite
Journal:  BMC Health Serv Res       Date:  2009-12-31       Impact factor: 2.655

10.  Is networking different with doctors working part-time? Differences in social networks of part-time and full-time doctors.

Authors:  Phil J M Heiligers; Judith D de Jong; Peter P Groenewegen; Lammert Hingstman; Beate Völker; Peter Spreeuwenberg
Journal:  BMC Health Serv Res       Date:  2008-10-04       Impact factor: 2.655

View more
  11 in total

1.  Job dissatisfaction as a predictor of poor health among middle-aged workers: a 14-wave mixed model analysis in Japan.

Authors:  Takashi Oshio
Journal:  Scand J Work Environ Health       Date:  2021-09-14       Impact factor: 5.492

Review 2.  Social network analysis in healthcare settings: a systematic scoping review.

Authors:  Duncan Chambers; Paul Wilson; Carl Thompson; Melissa Harden
Journal:  PLoS One       Date:  2012-08-03       Impact factor: 3.240

3.  Evidence-based design in an intensive care unit: end-user perceptions.

Authors:  Mauricio Ferri; David A Zygun; Alexandra Harrison; Henry T Stelfox
Journal:  BMC Anesthesiol       Date:  2015-04-25       Impact factor: 2.217

4.  Factors associated with high job satisfaction among care workers in Swiss nursing homes - a cross sectional survey study.

Authors:  René Schwendimann; Suzanne Dhaini; Dietmar Ausserhofer; Sandra Engberg; Franziska Zúñiga
Journal:  BMC Nurs       Date:  2016-06-06

5.  Professional advice for primary healthcare workers in Ethiopia: a social network analysis.

Authors:  Kate Sabot; Karl Blanchet; Della Berhanu; Neil Spicer; Joanna Schellenberg
Journal:  BMC Health Serv Res       Date:  2020-06-17       Impact factor: 2.655

6.  Could the connectedness of primary health care workers involved in social networks affect their job burnout? A cross-sectional study in six counties, Central China.

Authors:  Yiqing Mao; Hang Fu; Zhanchun Feng; Da Feng; Xiaoyu Chen; Jian Yang; Yuanqing Li
Journal:  BMC Health Serv Res       Date:  2020-06-18       Impact factor: 2.655

7.  Nursing Unit Design, Nursing Staff Communication Networks, and Patient Falls: Are They Related?

Authors:  Barbara B Brewer; Kathleen M Carley; Marge Benham-Hutchins; Judith A Effken; Jeffrey Reminga
Journal:  HERD       Date:  2018-06-19

8.  Factors associated with patient information sharing among home-visiting nurses in Japan: a cross-sectional study.

Authors:  Akiyo Nonogaki; Tomoko Nishida; Kazunari Kobayashi; Kayoko Nozaki; Haruka Tamura; Hisataka Sakakibara
Journal:  BMC Health Serv Res       Date:  2019-02-04       Impact factor: 2.655

9.  Indian Society of Critical Care Medicine Experts Committee Consensus Statement on ICU Planning and Designing, 2020.

Authors:  Narendra Rungta; Kapil Gangadhar Zirpe; Subhal B Dixit; Yatin Mehta; Dhruva Chaudhry; Deepak Govil; Rajesh C Mishra; Jeetendra Sharma; Pravin Amin; B K Rao; G C Khilnani; Kundan Mittal; Pradip Kumar Bhattacharya; A K Baronia; Yash Javeri; Sheila Nainan Myatra; Neena Rungta; Ranvir Tyagi; Sanjay Dhanuka; Mahesh Mishra; Srinivas Samavedam
Journal:  Indian J Crit Care Med       Date:  2020-01

10.  Exploring the structure of social media application-based information-sharing clinical networks in a community in Japan using a social network analysis approach.

Authors:  Junji Haruta; Sho Tsugawa; Kazunari Ogura
Journal:  Fam Med Community Health       Date:  2020-09
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.