Period pain presenteeism: investigating associations of working while experiencing dysmenorrhea

Figures & data

Table 1. Descriptives and bivariate correlations of the study variables.

	M(SD)	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.
1. Gender (female)
2. Age	29.89(6.04)	0.05
3. Hours/week	35.56(6.46)	0.09*	−0.02
4. Leader gender male		0.00	0.04	0.09
5. Gender distribution industry	55.85(26.06)	−0.01	−0.01	−0.15**	−0.37**
6. Symptom severity	4.07(0.80)	0.01	−0.04	0.00	0.06	0.06
7. Medical diagnosis (present)		0.09*	0.15**	0.02	−0.07	0.04	0.30**
8. Public attitude concealment	3.68(0.75)	−0.01	−0.01	0.06	0.03	−0.11**	0.05	0.03
9. LMX	3.40(0.81)	0.07	0.00	0.07	−0.09*	0.03	−0.10*	−0.05	0.00
10. Disclosure to leader	2.24(1.11)	−0.05	0.07	0.00	−0.11**	0.11*	0.31**	0.32**	0.00	0.17**
11. Days/week remote work	1.90(2.00)	0.08*	0.14**	0.12**	0.05	−0.28**	−0.04	0.04	0.02	0.21**	−0.04
12. Presenteeism	4.22(0.78)	−0.06	−0.04	0.09*	0.00	0.03	0.23**	0.09*	0.07	−0.09*	−0.08*	−0.11*

N = 668, Gender (female) coded: 1 = identifying as female, 0 = not identifying as female; Medical diagnosis coded: 1 = medical diagnosis present, 0 = no medical diagnosis; Leader gender male coded: 1 = male, 0 = not male; Gender distribution in the industry assed: 0 = completely male-dominated, 100 = completely female-dominated.

*p < .05.

**p < .01.

Table 2. Results of models regressing standardized period pain presenteeism on the standardized covariates and predictors.

	Full dataset (N = 668)		Endometriosis (N = 383)		No medical diagnosis (N = 236)		Endometriosis and no diagnosis (N = 619)
	Model 1a	Model 1b	Model 2a	Model 2b	Model 3a	Model 3b	Model 4
Intercept	0.53	0.74*	0.03	0.10	0.57	0.71	0.64*
Gender (female)	−0.55	−0.66*	−0.02	−0.04	−0.67	−0.80*	−0.65
Age	−0.03	<0.01	−0.07	−0.02	−0.03	0.02	−0.01
Hours/week	0.10**	0.11**	0.13*	0.14**	0.04	0.08	0.12**
Leader gender (male)	0.02	−0.07	−0.01	−0.13	0.16	0.13	−0.02
Industry gender distribution	0.05	0.02	0.05	0.03	0.08	0.05	0.04
Symptom severity		0.27**		0.12*		0.43**	0.43**
Medical diagnosis (present)		0.15					0.10
Public attitude concealment		0.05		0.02		0.03	0.03
LMX		−0.01		−0.01		0.01	< −0.01
Disclosure to leader		−0.20**		−0.23**		−0.11	−0.13
Days/week remote work		−0.10*		−0.09		−0.06	−0.08
Symptom severity × medical diagnosis							−0.31**
Disclosure to leader × medical diagnosis							−0.09
R^2	0.01	0.10	0.01	0.06	0.003	0.16	0.12

Gender female: 1 = identifying as female, 0 = not identifying as female, Medical diagnosis: 1 = present, 0 = absent, Leader gender male: 1 = male, 0 = not male, industry gender distribution: 0 = completely male-dominated, 100 = completely female-dominated * p < .05 ** p < .01.

Figure 1. Plot of the association between degree of disclosure to the supervisor and period pain presenteeism moderated by the presence or absence of a medical diagnosis. N = 619, Figure based on unstandardized coefficients

Table 3. Results of models regressing standardized disclosure to leader on the standardized covariates and predictors.

	Model 5a	Model 5b
Intercept	0.57	1.00
Gender (female)	−0.49	−0.76**
Age	0.08*	0.06
Hours/week	0.02	<0.01
Leader gender (male)	−0.18*	−0.16*
Industry gender distribution industry	0.08	0.03
Symptom severity		0.27**
Medical diagnosis (present)		0.51**
Public attitude concealment		−0.01
LMX		0.22**
Days/week remote work		−0.05
R^2	0.02	0.21

N = 668, Gender female: 1 = identifying as female, 0 = not identifying as female, Medical diagnosis: 1 = present, 0 = absent, Leader gender male: 1 = male, 0 = not male, industry gender distribution: 0 = completely male-dominated, 100 = completely female-dominated * p < .05 ** p < .01.

Figure 2. Path analysis Model of associations between the standardized predictors, disclosure to the leader, and period pain presenteeism. N = 668, only significant estimates (p < .05) stated.

Table 4. Results of the analysis of the indirect associations between the standardized predictors and period pain presenteeism via disclosure to the leader.

	Estimate	SE	95%CI
Severity → Disclosure → Presenteeism	−0.05	0.01	[−0.073; −0.023]
Medical diagnosis → Disclosure → Presenteeism	−0.07	0.02	[−0.112; −0.035]
Leader gender male → Disclosure → Presenteeism	−0.04	0.01	[−0.055; −0.016]
LMX → Disclosure → Presenteeism	0.03	0.01	[0.004; 0.050]

N = 668, Medical diagnosis: 1 = present, 0 = absent, Leader gender male: 1 = male, 0 = not male.

Data availability statement

The data that support the findings of this study are openly available in the Open Science Framework at https://osf.io/5j6h8/?view_only=034fda59add448278154dd14eeb106ac (anonymous view-only link for peer-review – will be made publicly accessible after publication).