The Impact of the Employee’s Personal Characteristics on the Abuse of Sickness Absence: Empirical Evidence From Poland

Jurek, Łukasz

doi:10.2478/wrlae-2022-0008

Figures & Tables

Results of the predictive model estimates for the abuse of compulsion sickness absenceSource: Own elaborationNote: The error whisker bars present 95% of the confidence interval for estimate B. Lines that cross one another represent the lack of differences between the predictors in the effect on the level of Compulsion. However, lines that do not cross one another represent important differences in the effect on the level of the Compulsion variable.

Results of the predictive model estimates for the abuse of escape sickness absenceSource: Own elaborationNote: The error whisker bars present 95% of the confidence interval for estimate B. Lines that cross one another represent the lack of differences between the predictors in the effect on the level of Escape. However, lines that do not cross one another represent important differences in the effect on the level of the Escape variable.

Results of the predictive model estimates for the abuse of recreation sickness absenceSource: Own elaborationNote: The error whisker bars present 95% of the confidence interval for estimate B. Lines that cross one another represent the lack of differences between the predictors in the effect on the level of Recreation. However, lines that do not cross one another represent important differences in the effect on the level of the Recreation variable.

Abuse of sick leave absence and personal characteristic of respondents (in %)

Characteristic	Description	Circumstance
Characteristic	Description	CIR1	CIR2	CIR3	CIR4	CIR5	CIR6	CIR7	CIR8	CIR9	CIR10	CIR11
General		19.4	17.7	10.6	8.4	9.2	11.2	22.9	14.3	9.7	18.6	19.4
Gender	Female	7.7	18.1	9.0	6.2	6.8	7.9	18.4	10.3	7.0	16.5	19.2
Gender	Male	12.7	17.4	12.2	10.7	11.6	14.4	27.3	18.1	12.3	20.6	19.6
Age	18–24	12.2	21.2	12.2	10.6	9.0	12.2	27.0	13.8	11.1	20.6	23.3
	25–34	9.0	19.4	8.3	6.8	9.6	8.3	23.8	12.0	9.6	17.6	18.2
	35–44	10.6	15.0	12.5	10.3	9.5	11.0	16.9	14.7	9.2	15.4	15.4
	45–54	10.1	14.6	10.6	8.5	8.5	14.1	26.6	19.6	10.6	21.1	22.1
	55–64	9.8	19.5	9.8	3.7	8.5	13.4	20.7	9.8	6.1	22.0	22.0
Education	Primary	20.0	45.0	15.0	25.0	0.0	15.0	25.0	10.0	20.0	15.0	15.0
	Secondary	12.3	17.2	13.1	11.5	11.5	11.5	32.8	28.7	12.3	29.5	28.7
	Vocational	9.2	17.2	10.7	8.0	8.3	14.1	25.2	14.4	11.7	18.7	19.3
	Post-secondary	9.9	13.7	12.2	8.4	9.9	9.2	15.3	10.7	13.0	15.3	15.3
	Bechelor	11.2	23.8	14.7	11.2	8.4	11.9	22.4	18.2	9.1	18.9	18.9
	Graduate and higher	9.5	15.7	6.8	5.5	9.9	8.3	20.0	8.6	4.9	15.7	18.2
Place of living	Village	8.5	21.8	10.6	8.5	11.2	11.2	30.3	23.4	9.6	24.5	27.1
	Small town	17.2	24.2	12.5	18.0	15.6	21.9	28.9	17.2	14.8	25.0	26.6
	Medium city	11.2	13.4	9.2	7.3	7.0	10.2	19.8	11.2	8.6	15.0	13.7
	Big city	7.5	16.3	11.7	7.1	7.9	7.5	19.2	12.9	8.3	13.8	20.4
	Metropolis	9.1	18.3	10.2	5.6	8.1	10.2	21.3	10.2	9.6	20.3	15.2
Marital status	Single	10.9	20.5	14.1	8.7	9.0	11.5	29.5	15.1	12.5	21.5	22.8
	Married	9.6	15.6	9.6	9.0	7.9	11.6	21.8	14.1	8.4	18.2	18.0
	Divorced	12.1	19.7	10.6	12.1	10.6	12.1	19.7	16.7	7.6	22.7	24.2
	Separation	18.8	25.0	18.8	25.0	25.0	12.5	25.0	25.0	25.0	18.8	31.3
	Widowed	6.3	31.3	18.8	0.0	25.0	25.0	12.5	37.5	18.8	25.0	25.0
	Partnership	9.5	15.8	5.8	4.7	9.5	7.9	16.3	9.5	6.8	12.6	14.2
Number of children	None	9.5	17.1	9.5	6.8	8.3	9.0	19.9	11.1	8.4	16.9	16.7
	02-sty	8.9	18.4	10.8	8.7	9.2	12.5	25.4	15.1	8.9	19.3	21.4
	04-mar	18.9	20.3	16.2	18.9	16.2	18.9	28.4	31.1	21.6	27.0	25.7
	5 and more	36.4	9.1	18.2	9.1	9.1	18.2	36.4	27.3	18.2	18.2	36.4
Financial situation	Definitely good	11.0	14.4	10.5	11.0	10.5	10.5	23.4	18.2	10.5	16.3	18.7
	Rather good	8.0	15.8	9.4	6.3	7.8	9.4	21.6	12.8	8.4	17.6	18.1
	Average	12.8	22.0	11.4	9.9	11.0	14.5	25.5	13.8	12.1	22.0	22.3
	Rather bad	16.3	25.6	20.9	9.3	4.7	11.6	16.3	11.6	2.3	14.0	18.6
	Definitely bad	11.1	33.3	11.1	22.2	22.2	22.2	33.3	33.3	22.2	44.4	22.2
Health	Very good	12.4	18.1	10.2	11.3	9.0	13.6	24.3	15.3	12.4	18.6	14.7
	Good	7.5	14.6	11.8	8.2	7.9	11.4	20.4	13.6	9.3	16.1	18.6
	Average	9.7	17.1	9.5	7.8	9.9	9.7	23.9	15.2	8.2	20.4	20.0
	Bad	13.0	25.9	13.0	7.4	9.3	11.1	21.3	9.3	11.1	14.8	26.9
	Very bad	31.3	31.3	12.5	6.3	12.5	25.0	31.3	18.8	18.8	31.3	18.8

Sample characteristics according to a personal characteristics of respondents

Characteristic	Description	%
Gender	Female	49.9
Gender	Male	51.1
Age	18–24	17.7
	25–34	30.4
	35–44	25.6
	45–54	18.7
	55–64	7.7
Education	Primary	1.9
	Secondary	11.4
	Vocational	30.6
	Post-secondary	12.3
	Bechelor	13.4
	Graduate and higher	30.5
Place of living	Village	17.6
	Small town (up to 20k citizens)	12.0
	Medium city (between 20k and 100k citizens)	29.4
	Big city (between 100k and 500k citizens)	22.5
	Metropolis (more than 500k citizens)	18.5
Marital status	Single	29.2
	Married	43.8
	Divorced	6.2
	Separation	1.5
	Widowed	1.5
	Partnership	17.8
Number of children	None	52.2
	1–2	39.8
	3–4	6.9
	5 and more	1.0
Subjective assessment of own financial situation	Definitely good: I have enough for living and I am saving	16.6
	Rather good: I have enough for living but I am not saving	26.2
	Average: I live frugally, so I can afford to buy everything	45.5
	Rather bad: I can afford only the most basic expenses	10.1
	Definitely bad: I cannot afford even the most basic expenses	1.5
Subjective assessment of health condition	Very good	19.6
	Good	49.1
	Average	26.4
	Bad	4.0
	Very bad	0.8

The direction of the effect of personal factors on particular categories of sick leave absence abuse

Predictor	Abuse category
Predictor	COMPULSION	ESCAPE	RECREATION
Gender: male	↑*	↑*	↑*
Age: mature	↓*	-	↓*
Age: old	↑	↑	↓
Number of children: with children	↑*	↑*	↑*
Place of living: metropolitan	↑	↑	↑
Place of living: provincial	↑*	↑*	↑*
Education: higher	↓	↓	↑
Marital status: in a relationship	↓*	↓*	↓*
Health	↑	↑*	↑*
Financial situation	↑	-	↑

Categories of sick leave absence abuse

Abuse category	Circumstances of abuse
RECREATION	CIR1. extending the period free from work
RECREATION	CIR2. overtiredness and/or overwork
ESCAPE	CIR3. refusal to grant regular leave
	CIR5. escape from problematic work tasks and/or cooperation with unliked persons
	CIR6. spontaneous escapade
	CIR9. other paid work
COMPULSION	CIR7. situation of higher necessity
	CIR8. renovation or other important work on the home
	CIR10. need to arrange an important administrative matter
	CIR11. providing care for a loved one or animal

The list and description of independent variables

Characteristic	Independent variable
Characteristic	Name	Description
Gender	gender: male	➢ male
Gender	gender: female*	➢ female
Age	age: young*	➢ 18–24 ➢ 25–34
	age: mature	➢ 35–44
	age: old	➢ 45–54 ➢ 55–64
Number of children	number of children: childless*	➢ none
Number of children	number of children: with children	➢ 1–2 ➢ 3-4 ➢ 5 and more
Education	education: lower*	➢ primary ➢ secondary ➢ vocational ➢ post-secondary
Education	education: higher	➢ bachelor ➢ graduate or higher
Place of living	place of living: provincial	➢ village ➢ small town
	place of living: medium-city*	➢ medium city
	place of living: metropolitan	➢ big city ➢ metropolis
Marital status	marital status: single*	➢ single ➢ divorced ➢ separation ➢ widowed
Marital status	marital status: in a relationship	➢ married ➢ partnership
Subjective assessment of own financial situation	financial situation**	➢ definitely good ➢ rather good ➢ average ➢ rather bad ➢ definitely bad
Subjective assessment of health condition	health**	➢ very good ➢ good ➢ average ➢ bad ➢ very bad

Results of structural model estimates for the dependent variable according to the three categories of abuse (recreation, escape, and compulsion)

Latent	□	Circumstance	B	s.e.	Z	DPU	GPU	R²
COMPULSION	->	CIR10	0.63	0.04	15.38***	0.55	0.72	0.40
COMPULSION	->	CIR7	0.57	0.04	15.18***	0.50	0.65	0.33
COMPULSION	->	CIR8	0.58	0.05	12.83***	0.49	0.67	0.34
COMPULSION	->	CIR11	0.53	0.04	13.30***	0.45	0.60	0.28
ESCAPE	->	CIR3	0.38	0.05	7.28***	0.28	0.49	0.15
ESCAPE	->	CIR5	0.43	0.05	8.01***	0.33	0.54	0.19
ESCAPE	->	CIR9	0.52	0.05	9.71***	0.42	0.63	0.27
ESCAPE	->	CIR6	0.47	0.05	9.47***	0.38	0.57	0.23
RECREATION	->	CIR1	0.48	0.06	7.96***	0.36	0.60	0.23
RECREATION	->	CIR2	0.48	0.06	8.65***	0.37	0.59	0.23

The Impact of the Employee’s Personal Characteristics on the Abuse of Sickness Absence: Empirical Evidence From Poland

Figures & Tables

Figure 1:

Figure 2:

Figure 3:

Abuse of sick leave absence and personal characteristic of respondents (in %)

Sample characteristics according to a personal characteristics of respondents

The direction of the effect of personal factors on particular categories of sick leave absence abuse

Categories of sick leave absence abuse

The list and description of independent variables

Results of structural model estimates for the dependent variable according to the three categories of abuse (recreation, escape, and compulsion)

Paradigm

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