Permanent Nurse Outcomes In Swiss Psychiatric by Kaggle | Demographics and Population Studies

About this Dataset

Permanent Nurse Outcomes In Swiss Psychiatric

Permanent Nurse Outcomes in Swiss Psychiatric Hospitals

Staffing Levels and Job Satisfaction, Burnout and Intention to Leave

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About this dataset

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How to use the dataset

This dataset contains invaluable information that can help us to better understand how staffing levels, as well as the deployment of temporary nurses, affect outcomes in Swiss psychiatric hospitals. This data can be used to answer important questions and gain insight into the impact of nurse staffing levels on permanent nurse outcomes such as job satisfaction, burnout, and intention to leave the organization or profession.

In this dataset you will find information on 79 psychiatric units and 651 nurses from 2019-2020. The columns included are unit_code (a unique ID for each psychiatric unit), A.2 (Frequency of temporary nurse deployment in the unit), A.3 (Number of permanent nurses in the unit), A.4 (Number of temporary nurses in unit), A.8.* (Overall job satisfaction, burnout, and intention to leave organization or profession for permanent nurses in the unit) ,A.1.(Number of permanent nurses with specific degrees such as Bachelor's degree or PhD), D.2.(number of permanent nurses with specific qualifications).

To get started working with this data we suggest downloading it first and importing it into your chosen software program for analysis purposes – Python is a popular choice among data analysts due to its easy usage.(Refer user tutorials below) If analyzing relationships between variables across different units within Switzerland is part a more complex scenario, then importing this dataset within SQL might also be an option depending on personal preferences/knowledge; feel free check out our SQL tutorial if you they require further guidance here!

Analyzing how variables interact by studying correlation across different cohorts is most likely going to be interesting charting shows clearly ‘hot spots’ where there correlations are strong – don’t forget bar-charts may also help show differences between variable distributions! We wish you luck understanding this dataset– Hopefully answering key questions about “Associationof Temporary Nurse Deployment Permanent Nurse Outcomes Swiss Psychiatric Hospitals becomes much easier now with access to this meaningful resource!

Research Ideas

Developing a predictive model for nurse outcomes based on temporary nurse deployment and staffing levels across all 79 Swiss psychiatric units.

Comparing how different contexts and settings affect the job satisfaction, burnout, and intention to leave of permanent nurses in various psychiatric units.

Investigating the impact of different types of permanent nurses (i.e., with bachelor’s degrees, master’s degrees, post-doctoral degrees) on their overall outcomes in Swiss psychiatric hospitals to inform better recruitment decisions based on educational attainment in nursing staff levels

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: MRNP_NURSES.csv

Column name	Description
unit_code	Unique identifier for each psychiatric unit represented in this dataset. (String)
A.2	Frequency of temporary nurse deployment. (Integer)
A.3	Number of permanent nurses in the unit. (Integer)
A.4	Number of temporary nurses in the unit. (Integer)
A.8.1	Job satisfaction of permanent nurses. (Integer)
A.8.2	Burnout of permanent nurses. (Integer)
A.8.3	Intention to leave the organization of permanent nurses. (Integer)
A.8.4	Intention to leave the profession of permanent nurses. (Integer)
A.8.5	Number of permanent nurses who left the unit. (Integer)
A.1.2	Number of permanent nurses with a bachelor's degree. (Integer)
A.1.6	Number of permanent nurses with a master's degree. (Integer)
A.1.8	Number of permanent nurses with a doctoral degree. (Integer)
A.1.12	Number of permanent nurses with a nursing assistant diploma. (Integer)
D.2.1	Number of permanent nurses with a bachelor's degree from abroad. (Integer)
D.2.8	Number of permanent nurses with a master's degree from abroad. (Integer)
D.2.9.c	Number of permanent nurses with a bachelor's degree from a domestic university. (Integer)
D.2.9.e	Number of permanent nurses with a master's degree from a domestic university. (Integer)
D.2.10	Number of permanent nurses with a doctoral degree from abroad. (Integer)
D.2.11	Number of permanent nurses with a nursing assistant diploma from abroad. (Integer)
D.2.12	Number of permanent nurses with a nursing assistant diploma from a domestic university. (Integer)

File: MRNP_UNIT.csv

Column name	Description
unit_code	Unique identifier for each psychiatric unit represented in this dataset. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Mrnp Nurses

@kaggle.thedevastator_permanent_nurse_outcomes_in_swiss_psychiatric_ho.mrnp_nurses

37.4 KB
1185 rows
26 columns


CREATE TABLE mrnp_nurses (
  "unnamed_0" BIGINT,
  "unit_code" VARCHAR,
  "a_2" DOUBLE,
  "a_3" DOUBLE,
  "a_4" DOUBLE,
  "a_8_1" DOUBLE,
  "a_8_2" DOUBLE,
  "a_8_3" DOUBLE,
  "a_8_4" DOUBLE,
  "a_8_5" DOUBLE,
  "a_1_2" DOUBLE,
  "a_1_6" DOUBLE,
  "a_1_8" DOUBLE,
  "a_1_12" DOUBLE,
  "d_2_1" DOUBLE,
  "d_2_8" DOUBLE,
  "d_2_9_c" DOUBLE,
  "d_2_9_e" DOUBLE,
  "d_2_10" DOUBLE,
  "d_2_11" DOUBLE,
  "d_2_12" DOUBLE,
  "h_1" DOUBLE,
  "h_2" DOUBLE,
  "h_3" DOUBLE,
  "h_8" DOUBLE,
  "h_8_1" DOUBLE
);

Mrnp Unit

@kaggle.thedevastator_permanent_nurse_outcomes_in_swiss_psychiatric_ho.mrnp_unit

3.91 KB
115 rows
3 columns


CREATE TABLE mrnp_unit (
  "unnamed_0" BIGINT,
  "unit_code" VARCHAR,
  "u_e_3" DOUBLE
);