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. 2022 Jan 19;41:107831. doi: 10.1016/j.dib.2022.107831

Dataset on the safety behavior among Pakistani healthcare workers during COVID-19

Muhammad Awais-E-Yazdan a,, Muhammad Awais Ilyas b, Muhammad Qamar Aziz c, Muhammad Waqas d
PMCID: PMC8767930  PMID: 35071698

Abstract

The dataset includes the particulars of 515 respondents on safety behavior during COVID-19. The questionnaires were adapted using Social Learning Theory and Social Exchange Theory. The variables included in dataset are Transactional Leadership (TSL), Transformational Leadership (TFL), Employee Well-Being (EWB) and Safety behavior (SB). Moreover, the dataset also contains the demographic profile of the respondents. Data was collected with the help of self-administered questionnaire from eight public hospitals in Punjab, Pakistan, namely Services Hospital Lahore, Sir Ganga Ram Hospital Lahore, Government General Hospital Faisalabad, DHQ Hospital Chiniot, Municipal General Hospital Sargodha, DHQ Hospital Jhang, DHQ Hospital Multan and Sulehri Children & General Hospital Sialkot. This dataset could provide a significant insight for future research in employee safety behavior.

Keywords: Safety compliance, Workplace safety, Safety management, Leadership styles

Specifications Table

Subject Organizational behavior
Specific subject area Human resource management
Type of data Table
How data was acquired Data was collected through self-administered questionnaire using five point likert scale. The data also includes demographic features of respondents.
Data format Raw, analyzed
Description of data collection Data was collected via self-administered questionnaire in Punjab province. Total 550 questionnaires were distributed and after removing incomplete questionnaires only 515 were used in data analysis. It took 3 months for data collection.
Data source location Hospitals: Services Hospital Lahore, Sir Ganga Ram Hospital Lahore, Government General Hospital Faisalabad, DHQ Hospital Chiniot, Municipal General Hospital Sargodha, DHQ Hospital Jhang, DHQ Hospital Multan and Sulehri Children & General Hospital Sialkot.
Country: Pakistan
Data Accessibility Repository name: Mendeley data
Data identification number:
Direct URL to data: https://data.mendeley.com/datasets/wt2dbjcgc8/draft?a=703cfd69-8e84-47f1-884f-8df3e61a0774

Value of the Data

  • The dataset provide the evidence that organizations should implement workplace policies and procedures that influence safety behavior.

  • The dataset is useful to address other related issues. For instance: safety climate, safety culture and safety citizenship behavior.

  • The dataset is helpful to predict the attitude and behavior of employees at early stage of employment.

  • The dataset focused on the hurdles which slow down the leadership practices in order to achieve a safe work environment.

  • The dataset advocates that management must invest to satisfy the psychological needs of the workers to shine their basic workplace skills.

  • The dataset could be used by other researchers in order to compare this data with other data obtain from related studies but different geographic regions.

1. Data Description

The dataset includes the questions related to four constructs:

Transactional leadership (TSL), Transformational leadership (TFL), Employee well-being (EWB) and Safety behavior (SB). Definitions of all constructs and references relating to instrument are given in Table 1.

Table 1.

Variables, code, definition and reference of each instrument.

Variable Code Definition References of the instrument
Transactional leadership TSL It refers to an exchange process where leaders and followers exchange valuable information with each other. [2,3]
Transformational leadership TFL A type of leadership which morally and ethically support both leaders and their followers in a mutual consent. 1,3]
Employee well-being EWB Refers to the physical (tiredness, muscular pain & headache) and mental (anxiety, self-respect & depression) factors of the individuals. [4,5]
Safety behavior SB It refers to maintain the safe working standard by wearing personal protective equipment. [6,7]

The SPSS sheet along with questionnaire are given as a supplementary file. The questionnaires for TSL and TFL were adapted [3] to explain the relationship by incorporating social learning theory. Similarly, the questionnaires for SB and EWB are also adapted [5,7]. The relationship between EWB and SB were explained by social exchange theory. Five-point Likert scale ranging (1= strongly dis-agree, 2= dis-agree, 3= neutral, 4= agree, 5= strongly agree) was incorporated which enhance the quality of responses and lower the tiredness of the respondents. TSL consist of five items, whereas TFL consist of six items. Items for TSL and TFL were adapted from previous study [3]. In addition, items for EWB and SB were adapted from different studies [5,7] with three and seven items respectively. Structural Equation Modeling technique using smart PLS 3.2.6 has been incorporated to explain the measurement and structural model.

2. Materials and Methods

Data was gathered through convenience sampling. It is a type of non-probability technique in which the data is collected from the people easily to approach. Data is collected from the public hospitals of Punjab Pakistan. Province Punjab is selected for data collection as it is the second most populous province and is known for quality hospitals. Data was entered and coded in SPSS software. All the preliminary tests were conducted on SPSS. For the main analysis Smart PLS 3.2.6 was used.

2.1. Loadings, composite reliability and average variance extracted

Individual item reliability of construct above 0.30 can be retained [8]. Similarly, items must be removed if the removal increase the value of average variance extracted (AVE) and composite reliability (CR). Therefore, the present dataset removed one item (SC2) as the removal increase the value of AVE and CR. In addition, the value of AVE is above than 0.5 which means convergent validity is established.

Table 2 shows the adequate, individual item reliability, CR and AVE of the study's constructs.

Table 2.

Loadings, average variance extracted and composite reliability.

Constructs Items Loadings AVE CR
Transactional leadership TSL1 0.728 0.552 0.860
TSL2 0.729
TSL3 0.813
TSL4 0.753
TSL5 0.688
Transformational leadership TFL1 0.587 0.515 0.863
TFL2 0.796
TFL3 0.793
TFL4 0.744
TFL5 0.713
TFL6 0.649
Employee well-being EWB1 0.820 0.655 0.850
EWB2 0.801
EWB3 0.806
Safety compliance SC1 0.658 0.514 0.863
SC3 0.819
SC4 0.786
SC5 0.725
SC6 0.661
SC7 0.633

Note: AVE = Average Variance Extracted, CR = Composite Reliability.

Discriminant validity is considered valid as the values in Tables 3, 4 and 5 were in acceptable range.

Table 3.

Latent variable correlations and square roots of (AVE).

EWB SC TFL TSL
EWB 0.809
SC 0.314 0.717
TFL 0.457 0.612 0.718
TSL 0.258 0.656 0.673 0.743

Note: Entries in the boldface represent the square root of average variance extracted (AVE).

Table 4.

Cross loadings.

EWB SC TFL TSL
EWB1 0.820 0.294 0.488 0.284
EWB2 0.801 0.179 0.328 0.176
EWB3 0.806 0.261 0.266 0.147
SC1 0.384 0.658 0.515 0.376
SC3 0.293 0.819 0.511 0.513
SC4 0.245 0.786 0.482 0.450
SC5 0.097 0.725 0.389 0.545
SC6 0.128 0.661 0.337 0.410
SC7 0.186 0.633 0.378 0.510
TFL1 0.227 0.430 0.587 0.561
TFL2 0.287 0.549 0.796 0.639
TFL3 0.296 0.428 0.793 0.642
TFL4 0.415 0.440 0.744 0.380
TFL5 0.406 0.421 0.713 0.327
TFL6 0.366 0.317 0.649 0.256
TSL1 0.170 0.491 0.394 0.728
TSL2 0.203 0.497 0.418 0.729
TSL3 0.232 0.565 0.664 0.813
TSL4 0.149 0.426 0.534 0.753
TSL5 0.195 0.440 0.476 0.688

Table 5.

HTMT correlation matrix for discriminant validity.

EWB SC TFL TSL
EWB -
SC 0.385 -
TFL 0.583 0.741 -
TSL 0.322 0.810 0.808 -

Ethics Statement

It is stated that the consent was taken from each individual who participated in this survey.

CRediT authorship contribution statement

Muhammad Awais-E-Yazdan: Conceptualization, Data curation, Writing – review & editing, Methodology. Muhammad Awais Ilyas: Visualization, Software. Muhammad Qamar Aziz: Investigation, Validation. Muhammad Waqas: Supervision.

Declaration of Competing Interest

The authors declared that there is no conflict of interest either financial or personal among them.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.dib.2022.107831.

Appendix. Supplementary materials

mmc1.docx (20.5KB, docx)
mmc2.csv (26.8KB, csv)
mmc3.zip (5.1KB, zip)

References

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx (20.5KB, docx)
mmc2.csv (26.8KB, csv)
mmc3.zip (5.1KB, zip)

Articles from Data in Brief are provided here courtesy of Elsevier

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