Relationship Between Emotions,Emotion Regulation,and Well-Being of Professional Caregivers of People With Dementia

Emotion Felt by Caregivers at Work

Professional caregivers interact on a daily basis, mostly face to face, with troubled patients. During these interactions, the caregivers are at risk of experiencing intense negative emotions and emotional depletion (Erickson & Grove, 2007; Maslach, 1982). In particular, in their study on emotional experiences, empathy, and burnout among professional caregivers, Kuremyr, Kihlgren, Norberg, Astrom, and Karlsson (1994) showed that, despite their concerns and deep care for PwD, caregivers feel negative emotions such as guilt. Additionally, professional caregivers for people with Alzheimer reported that the caregiving process is emotionally draining by nature (McCarty & Drebing, 2003).

Many research studies have also focused on the emotions of family members caring for PwD and showed that caregiving contributes to psychiatric morbidity, particularly for emotional distress (Mafullul & Morriss, 2000) and depression (Schoenmakers, Buntinx, & De Lepeleire, 2010). Even more dramatically, caregivers are at risk for increased mortality (Schulz & Beach, 1999).

As important as evaluating family caregivers is, professional caregivers of PwD also deserve research attention as they are a valuable and sometimes unique human resource for PwD. Despite their less close relationship with the patients, their emotional involvement remains very high while performing their job. So far, however, very little research has targeted the emotional spectrum experienced by professional caregivers in nursing homes.

Well-Being of Professional Caregivers

Well-being in the workplace of nursing staff has become a major concern in the past decade (e.g., Begat, Ellefsen, & Severinsson, 2005; Burke & Greenglass, 2001), being evaluated in different contexts such as critical care nursing staff (Poncet et al., 2007), palliative care staff (van Staa, Visser, & van der Zouwe, 2000), and acute mental health settings (Jenkins & Elliott, 2004). Well-being has been broadly described as a multidimensional and heterogeneous construct integrating psychological, physical, and social dimensions (Diener & Chan, 2011; Yarcheski, Scoloveno, & Mahon, 1994). A narrowed approach of well-being was also proposed as “subjective well-being” and focused on the subjective perception of “good” quality of life (Diener, 2000, 2009). In examining the relationship between subjective well-being and experienced emotions, Diener (2000) pointed out that people feeling many positive emotions and little unpleasant emotions, experienced abundant subjective well-being. When measuring work-related well-being, health factors, that is, physical and psychological health, have been very often considered as important subcomponents of well-being (Danna & Griffin, 1999). For physical health, indicators such as cardiovascular conditions (e.g., Shockley & Allen, 2013) or general physical symptoms (Bech, Olsen, Kjoller, & Rasmussen, 2003) are seen as reliable indicators. Among the literature on working population health, psychological or mental health indicators are generally referred to as psychiatric symptoms (Bourbonnais, Comeau, & Vezina, 1999; Michie & Williams, 2003) or as affective components, such as burnout (Chou, Hecker, & Martin, 2012) and, in particular, emotional exhaustion (e.g., de Jonge, Bosma, Peter, & Siegrist, 2000; Van Der Hulst & Geurts, 2001).

Emotional exhaustion is viewed as “a chronic state of physical and emotional depletion that results from excessive job demands” (Wright & Cropanzano, 1998, p. 486). Emotional exhaustion can be measured, thanks to a subscale of the Maslach Burnout Inventory (MBI; Maslach & Jackson, 1981). Schaufeli and Van Dierendonck (1993) assessed the construct validity of the MBI on a large population of nurses and found that emotional exhaustion was the strongest factor in the MBI and “conceptually and psychometrically speaking, the most prominent and robust feature of burnout” (p. 644). Emotional exhaustion is also considered as the first stage and the core dimension of burnout experience (e.g., Cordes & Dougherty, 1993; Gaines & Jermier, 1983; Maslach, 1982; Shirom, 1989). In professional health caregivers, emotional exhaustion has been considered as a prominent factor associated with different aspects of the nursing care, such as emotional labor (Näring, Briët, & Brouwers, 2007), leadership (Stordeur, D’Hoore, & Vandenberghe, 2001), psychological capital (Spence Laschinger & Fida, 2014), as well as resilience and emotional annoyance component to measure well-being, particularly in professional caregivers.

Emotion Regulation

The Present Research

The purpose of the current study was, first, to describe the emotions experienced at work by professional caregivers of PwD. Second, we wanted to examine the interplay between these emotions and (a) the caregiver’s well-being and (b) the use of different emotion regulation strategies. Third, we thought to benefit from the recorded data to investigate the association between the emotion regulation strategies used by the caregivers and their well-being. Fourth, given the potential strong link between the emotions experienced at work, specific strategies of cognitive reappraisal and expressive suppression, and the caregiver’s exhaustion level, we wondered whether the reappraisal and suppression strategies play a moderating role between experienced emotions and exhaustion.

To fulfill these four goals, we used a set of standardized questionnaires to record (a) the frequency of different positive and negative emotions as experienced at work, (b) some of the main indicators of well-being (i.e., physical health, psychological health, and emotional exhaustion), and (c) the use of general emotion regulation strategies (adaptive and maladaptive) as well as specific strategies (i.e., cognitive reappraisal and expressive suppression).

Concerning the relationship between emotions and well-being, positive emotions seemed to be associated with higher level of subjective well-being and few negative emotions (Diener, 2000). In addition, it has been suggested that burnout is rooted in negative emotions felt by caregivers (Erickson & Grove, 2007). Therefore, we hypothesized that positive emotions are related to better well-being and negative emotions associated with poorer well-being in professional caregivers for PwD. As to the relationship between experienced emotions and emotion regulation strategies, in line with previous results (Garnefski, Kraaij, & Spinhoven, 2001; Garnefski et al., 2002; John & Gross, 2004), we suggested that positive emotions are associated with cognitive reappraisal and adaptive coping strategies, whereas negative emotions are linked to expressive suppression and maladaptive coping styles. Concerning the relationship between well-being indicators and emotion regulation strategy use, we assumed that higher well-being is linked to adaptive emotion regulation strategies, including cognitive reappraisal, whereas poorer well-being is associated with maladaptive coping strategies and expressive suppression.

Among emotion regulation strategies, adaptive and maladaptive strategies are composed of multiple cognitive strategies, each of these groups giving a broad overview on emotion regulation strategies. However, cognitive reappraisal and expressive suppression are distinct, specific strategies, and have been associated with psychological well-being in previous studies (Abler, Hofer, & Viviani, 2008; John & Gross, 2004; Wong & Fielding, 2013). Consequently, only these two particular emotion regulation strategies were chosen to be tested as moderator variables. Emotional exhaustion is considered to be the best indicator of burnout (Donahue et al., 2012; Koeske & Koeske, 1989) and a consistent variable of psychological well-being in professional caregivers. Therefore, we chose emotional exhaustion as a unique measure of well-being for testing the moderation effect. Although it had been shown that positive and negative emotions are important to well-being (Diener, 2009; Diener & Chan, 2011), and specifically emotional exhaustion (Chou et al., 2012; Johnson & Spector, 2007), the way in which emotion regulation, that is, cognitive reappraisal and expressive suppression, impacts this association has not been examined in professional caregivers caring for PwD. Hence, we expected that cognitive reappraisal or expressive suppression would moderate the link between the emotions experienced at work and the emotional exhaustion reported by professional caregivers. Particularly, cognitive reappraisal should enhance the positive effects of positive emotions on exhaustion and expressive suppression should maximize the impact of negative emotions on exhaustion.

Participants

Data were collected from a sample of 43 professional caregivers who volunteered to participate in our study. Caregivers were 9 men and 34 women, with a mean age of 42.02 years (standard deviation [SD] = 9.61), recruited from nine nursing homes and a psychogeriatric hospital in the French-speaking part of Switzerland. Inclusion criteria consisted of caring for PwD and fluently speaking and understanding French. There were no exclusion criteria. Sociodemographic information is shown in Table 1.

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Table 1.

Participants’ Sociodemographic Variables.

	Percentage (%)	N
Women	79	34
Job title
Registered head nurses	13.95	6
Registered nurses	37.21	16
Nurse aides	46.51	20
Community care aides	2.33	1
Employment rate (%)
100	41.86	18
60–90	48.84	21
40–50	9.30	4
Years of experience
More than 10	55.81	24
6–10	20.93	9
Less than 6	23.26	10
Years of experience caring for PwD
More than 10	37.21	16
6–10	16.28	7
Less than 6	46.51	20

Note. N = 43. PwD = People with Dementia.

Variables and Instruments

Procedure

A letter of information, including a list of contact information, was sent by the researchers to the head manager of several nursing homes and psychogeriatric hospitals in the French-speaking part of Switzerland. These long-term facilities had units including people with dementia. Professional caregivers working in units with 100% residents with dementia or with symptoms of dementia were informed by their director of care or their unit’s head nurse about the study. The caregivers willing to enroll in the study had to fill the list of contact information. When completed, the list was sent to the research team, and three female collectors contacted the professional caregivers and invited them to complete the five above-described questionnaires in a location of their choice (workplace, home, or public area). All the professional caregivers enrolled on the list participated in the study. The session lasted approximately 90 min. All participants signed an informed consent form ensuring anonymous and confidential treatment of data.

Data Analysis

All statistical analyses were conducted using SPSS Version 20.0 (SPSS Inc., Chicago, IL). To characterize positive and negative emotions experienced by professional caregivers at work, we computed descriptive statistics (means and medians) for each emotion. We also obtained a single measure for positive and negative emotions by averaging the values obtained on all positive and negative emotions, respectively. We then used a t-test to compare the frequency of positive and negative emotion means.

We computed means, SDs, and ranges for each subscale of the emotion regulation data (cognitive reappraisal, expressive suppression, adaptive coping, and maladaptive coping). Concerning the physical and the mental scales, we applied reversed scores for specific items. Then, we calculated the sum of scores for each participant on each subscale of the well-being (mental health, physical health, and exhaustion). Bivariate correlations (Spearman’s ρ) explored the associations between positive and negative emotions, emotion regulation strategies, and well-being subscales.

Hierarchical moderated regression analyses were applied to test the moderating effect of cognitive reappraisal and expressive suppression (Cohen & Cohen, 1983). Before performing the regression analyses, we first normalized the nonnormal targeted variables. We used Box–Cox transformation (Box & Cox, 1964; Osborne, 2010) for exhaustion (λ = −.48) and for cognitive reappraisal (λ = −.48). We used formulas suggested by Rummel (1970) for expressive suppression, log[x/(x − 1)], and for the frequency of negative emotion, (arcsin[x])^1/2. Z-scored variables were used in four moderated regression analyses for predicting emotional exhaustion. The first model considered positive emotions and cognitive reappraisal as predictors, the second model considered negative emotions and cognitive reappraisal, the third model considered positive emotions and expressive suppression, and the fourth model considered negative emotions and expressive suppression.

Emotions Experienced at Work

Table 2 reports the emotion frequency means, medians, and SDs. Participants reported experiencing positive emotions (M = 5.33, SD = 1.12), such as joy and pride, more frequently, t(42) = 11.02, p < .001, than negative emotions (M = 2.00, SD = 1.04), such as anger and sadness (see Table 2).

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Table 2.

Frequency of Emotions Experienced at Work.

Measure	Mean	Median	SD
Joy	5.65	6.00	1.43
Contentment	5.55	5.00	1.27
Happiness	5.43	5.00	1.43
Appreciation	5.24	5.50	1.57
Respect	5.00	5.00	1.66
Pride	4.40	5.00	1.78
Surprise	3.53	3.00	1.71
Tiredness	3.37	3.00	1.50
Worry	2.93	3.00	1.75
Frustration	2.86	2.00	1.92
Anger at administration	2.67	2.00	2.11
Irritation	2.43	2.00	1.52
Impatience	2.42	2.00	1.31
Loneliness	2.40	1.00	1.89
Anger at others	2.37	2.00	1.69
Sadness	2.16	2.00	1.51
Anger at self	1.95	2.00	1.21
Hostile	1.93	1.00	1.58
Disgust	1.86	1.00	1.47
Guilt	1.67	1.00	1.23
Fear	1.65	1.00	1.02
Anger	1.56	1.00	0.81
Shame	1.35	1.00	0.65
Positive emotions	5.33	5.22	1.12
Negative emotions	2.00	2.24	1.04

Note. N = 43.

Table 3 presents the means, SDs, and ranges of the well-being indicators (physical health, mental health, and emotional exhaustion) as well as of the ERQ and CERQ scores.

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Table 3.

Means and Standard Deviations of Scores for the Well-Being Indicators, the Emotion Regulation Questionnaire (ERQ) Scores, and the Cognitive Emotion Regulation Questionnaire (CERQ) Scores.

	Mean (SD)	Range
Well-being scores
Physical health	0.26 (0.17)	(0.00–0.67)
Mental health	0.17 (0.17)	(0.00–0.70)
Emotional exhaustion	2.40 (1.18)	(1.00–6.67)
ERQ scores
Cognitive reappraisal	4.88 (1.28)	(1.83–6.83)
Expressive suppression	3.43 (1.25)	(1.50–6.00)
CERQ scores
Adaptive coping	3.69 (0.59)	(2.35–4.80)
Maladaptive coping	2.15 (0.45)	(1.19–3.25)

Note. N = 43.

Relationship Between Emotions Experienced at Work and Well-Being

As reported in Table 4, caregivers who reported more positive emotions showed better physical (r_s = .43, p < .01) and mental health (r_s = .41, p < .01). No significant result was found between positive emotions and emotional exhaustion (r_s = −.29, p = .06). Conversely, caregivers who experienced more negative emotions reported poorer physical (r_s = −.49, p < .01) and mental health (r_s = −.67, p < .01) and were more likely to feel emotional exhaustion (r_s = .46, p < .01).

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Table 4.

Correlations of Scores for Frequency of Emotions at Work; Physical and Mental Health; Emotional Exhaustion; and Emotion Regulation Strategies.

	1	2	3	4	5	6	7	8	9
1. Positive emotions	—
2. Negative emotions	−.31*	—
3. Physical health	.43**	−.49**	—
4. Mental health	.41**	−.67**	.53**	—
5. Emotional exhaustion	−.29	.46**	−.64**	−.56**	—
6. Cognitive reappraisal	.21	−.19	.02	.07	−.04	—
7. Expressive suppression	−.07	.07	−.13	−.26	.08	.19	—
8. Adaptive coping	.15	−.18	.02	.16	−.05	.60**	.08	—
9. Maladaptive coping	−.37*	.47**	−.31*	−.47**	.47**	−.07	.07	−.04	—

Note. N = 43.

**p < .01. *p < .05.

Relationship Between Emotions Experienced at Work and Emotion Regulation Strategies

Regarding the link between the emotions experienced by caregivers and emotion regulation strategy use, results show no significant association between positive and negative emotions and cognitive reappraisal, expressive suppression, as well as adaptive coping strategies (see Table 4). However, participants who generally used maladaptive coping strategies were prone to experience more negative emotions (r_s = .47, p < .01) and less positive emotions (r_s = −.37, p < .05).

Relationship Between Well-Being and Emotion Regulation Strategies

No significant association was found between the well-being indicators on the one hand and cognitive reappraisal, expressive suppression, and adaptive coping strategies on the other hand (see Table 4). However, participants who generally used maladaptive coping strategies reported poorer physical health (r_s = −.31, p < .05), poorer mental health (r_s = −.47, p < .01) as well as a higher level of exhaustion (r_s = .47, p < .01).

Cognitive Reappraisal and Expressive Suppression as Moderator Variables

We hypothesized that cognitive reappraisal and expressive suppression would moderate the link between positive/negative emotions and exhaustion level. To test this moderation effect, hierarchical moderated regression analyses were performed with the corresponding normalized variables. In regression analyses predicting exhaustion level, the independent variables (positive or negative experienced emotions) and the moderator variables (reappraisal or suppression) were entered in the first step, followed in the second step by the addition of the interaction term Predictors (positive or negative experienced emotions) × Moderator (reappraisal or suppression). In the second step, a significant change in R ² for the interaction between the moderator (reappraisal or suppression) and positive or negative emotions signaled moderating effects. Table 5 presents the standardized regression coefficients, first for the first step of the analyses, presenting the singular impact of independent and moderator variables, and then for the second step, presenting the model with independent, moderator, and interaction variables.

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Table 5.

Results of Hierarchical Moderated Regression Analyses Predicting Exhaustion.

	β Coefficients
	Model 1a	Model 2b	Model 3c	Model 4d
Step 1
Positive emotions	−.263		−.244
Negative emotions		.594**		.581**
Cognitive reappraisal	.068	.079
Expressive suppression			.100	.075
Step 2
Positive emotions	−.302		−.291
Negative emotions		.579**		.550**
Cognitive reappraisal	.082	−.238
Expressive suppression			.149	−.208
Interaction	−.130	.353	−.361*	.313
ΔR 2 after addition of interaction	.015	.025	.125*	.016

Note. Step 1 is the regression model with the independent variable and the moderator alone, while Step 2 contains the addition of their interaction.

^aPredictors are Positive Emotions × Reappraisal. ^bPredictors are Negative Emotions × Reappraisal. ^cPredictors are Positive Emotions × Suppression. ^dPredictors are Negative Emotions × Suppression.

**p < .01. *p < .05.

As shown in Table 5, only the results including positive emotions experienced at work and expressive suppression to explain emotional exhaustion was significant (ΔR ² = .125, p < .05, η _p ² = .20). To better understand this effect, median splits were performed for frequency of positive emotions and expressive suppression. An analysis of variance was then performed with these two factors and predicted emotional exhaustion. Results showed that participants having low frequency of positive emotion and high expressive suppression level showed the highest level of emotional exhaustion, F(1, 32) = 17.75, p < .01, η _p ² = .36 (see Figure 1). Thus, the results of the hierarchical moderated regressions showed that low frequency of positive emotion experienced at work was associated with higher emotional exhaustion level, but only when expressive suppression was frequently performed.

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Figure 1.

Exploration of the moderating effect of expressive suppression on the relationship between the frequency of positive emotions experienced at work and emotional exhaustion (**p < .01 with all other groups).

Emotions Felt at Work by Professional Caregivers

There is evidence in the literature that professional caregivers of dementia residents experience burden (McCarty & Drebing, 2003) and emotional exhaustion (e.g., Cocco, Gatti, de Mendonça Lima, & Camus, 2003), which are in some ways linked to negative affects (Morris & Feldman, 1996). When considering employment outcomes, negative feelings, emotional exhaustion, and feeling of not being respected were found to be associated with job dissatisfaction (Bishop, Squillace, Meagher, Anderson, & Wiener, 2009) and high turnover (Tourangeau, Cranley, Spence Laschinger, & Pachis, 2010). We were thus expecting in the present pilot study to encounter high frequency of negative emotions, given the prevalence of such affects described in the literature. Contrary to expectation, however, our results indicated that the most frequent emotions are all positive (joy, contentment, happiness, appreciation, respect, and pride). In their study of emotional experience in everyday life in the Swiss population, Scherer, Wranik, Sangsue, Tran, and Scherer (2004) also found that happiness was the most frequently reported emotion. However, in their research, they also found that happiness was closely followed by anger, while in our findings, anger is one of the less frequent emotion experienced by professional caregivers. This discrepancy could partly be explained by the characteristics of our selective sample, which included caregivers who voluntarily participated. Since they had to actively reply to our letter, we suppose they were strongly committed to the topic, contrary to a random sample, which could include participants less involved in the topic of interest (Ganguli, Lytle, Reynolds, & Dodge, 1998; Martinson et al., 2010; Rosenthal & Rosnow, 1975) and having different emotional experiences for the same work assignment. Another explanation is that our results can be driven by socially desirable responding, which is generally defined as the tendency to present a favorable image of oneself (Van de Mortel, 2008). As a further explanation, we could interpret our result from the perspective of the emotional labor theories (Hochschild, 1979, 1983; Wharton, 1993), which brings into light underlying emotional mechanisms of the professional caregivers. Emotional labor refers to the emotional work undertaken to regulate emotional display in order to fit the organization expectations (Brotheridge & Lee, 2003). Emotional labor is a process of coordination between mind and feelings, giving rise to a sense of being cared for and safe in others. It is expressed through two strategies: surface acting (i.e., modifying emotion through facial and body expression, e.g., by faking or simulating) and deep acting (i.e., shaping the inner feeling; Hochschild, 1983). In the nurse–patient relationship, the emotional labor is strengthened by the intrinsic nature of caring (McQueen, 2004; Swanson, 1993). Moreover, as pointed out by McQueen (2004), professional caregivers are encouraged throughout their education and training to conceal negative emotions and maintain a professional barrier. On the one hand, thus, cognitive and behavioral symptoms and emotional liability of PwD may induce negative emotions in the professional caregiver, emotions that are being repressed. On the other hand, PwD, mostly frail and vulnerable, may elicit positive emotional and technical aspects in the caring process, such as protection and patient safety, which we mainly highlight in the present pilot study through the report of frequent positive emotions.

Relationship Between Emotion, Well-Being, and Emotion Regulation Strategies Use

Positive and negative emotions of professional caregivers of PwD were globally significantly related to their well-being. These preliminary results support our hypotheses and seem to be in line with previous studies that have largely demonstrated the association between positive emotions and good health in different populations (Danner, Snowdon, & Friesen, 2001; Fredrickson & Joiner, 2002; Fredrickson & Levenson, 1998) or between negative emotions and (a) poor health (Tugade, Fredrickson, & Feldman Barrett, 2004; Watson, 1988) or (b) greater emotional exhaustion (Zapf & Holz, 2006) and association between positive emotions and good health in different populations (Danner et al., 2001; Fredrickson & Joiner, 2002; Fredrickson & Levenson, 1998). Therefore, expecting positive emotions to be negatively associated with the level of exhaustion would have been in line with these past results but does not appear in our data. This tends to show that the level of emotional exhaustion could be potentially more targeted by actions on negative emotions than on positive emotions. Future studies should address this hypothesis, as it may be that reducing the emotional exhaustion level in the context of caring for PwD could be achieved by reducing the frequency of negative emotions, their display (Kovacs, Kovacs, & Hegedu, 2010), or the workload (Deery, Iverson, & Walsh, 2002), rather than by trying to augment the frequency of positive emotions.

Contrary to expectations, positive and negative emotions were not found to be associated with cognitive reappraisal and expressive suppression, as measured by the ERQ. It is possible that the habitual regulation strategies asked by the questionnaire are significantly different than the regulation strategies performed in the context of professional caregivers of PwD in their work environment. Future studies could focus on the strategies specifically performed in this context, as they could thereafter better relate to the emotional landscape observed at work. Results show however that caregivers who used maladaptive coping (as measured by the CERQ) were likely to experience negative emotions, which is congruent with previous studies on the negative consequences of the use of maladaptive coping strategies (Garnefski & Kraaij, 2007; Martin & Dahlen, 2005).

No significant results were found between cognitive reappraisal and expressive suppression (ERQ) and well-being indicators as well as between adaptive coping strategies (CERQ) and health and exhaustion. However, we found a positive relationship between maladaptive coping strategies and poorer well-being in professional caregivers of PwD. This could signal that using maladaptive coping strategies leads to a decrease in well-being or that a low well-being does not leave sufficient resources to attempt adaptive coping strategies. Together with the relationship found between maladaptive strategy use and frequency of emotions, these results seem nevertheless to indicate that at least part of the maladaptive strategies that are tackled by the CERQ play an important role in the emotions experienced at work and the well-being of professional caregivers of PwD (Clinton et al., 1995; Rodney, 2000). Those strategies would benefit to be separately addressed to observe their individual contribution to health and emotions of professional caregivers of PwD.

Suppression as a Moderator Variable

Specific emotion regulation strategies were hypothesized to be moderator variables between emotions and exhaustion level, given their consistent association with experienced emotions on the one hand (Butler et al., 2003; Goldin, McRae, Ramel, & Gross, 2008; Gross, 1998) and with well-being on the other hand (Gross, 2002; Gross & John, 2003). Our results indicated that, in our sample, expressive suppression enhanced the negative relationship between experienced positive emotions and the level of exhaustion. More specifically, for professional caregivers with low level of reported positive emotions, high use of suppression enhanced their emotional exhaustion. Thus, expressive suppression, considered as a less efficient emotion regulation strategy, could play a more complex role than expected when testing its moderating effect on the relationship between positive emotions and emotional exhaustion. In order to tackle emotional exhaustion in professional caregivers, future studies should verify if individuals who have low positive emotions and high expressive suppression are more likely to experience high level of exhaustion. If corroborated, this could lead to important recommendation for practice.

Limitations and Future Directions

This pilot study offers a promising attempt to evaluate the complex interplay between emotions, emotion regulation, and well-being in professional caregivers. Nevertheless, the study suffers from limitations common with pilot studies. These limitations include a small sample size and nonrandomization. Therefore, conclusions drawn for this sample might be restricted. However, this pilot study is a fundamental step for further research on emotion regulation of professional caregivers of PwD, which is innovative. Future research would benefit from a larger sample size and better fitting the population of professional caregivers of PwD working in Swiss long-term facilities.

Another limitation is how physical and mental health was here operationalized by using negative characteristics of health (i.e., symptoms). It would be interesting to see if the promotion of good health at work can also relate with the emotional variables into play.

One particularly difficult problem in our study regards the measures, which were all based on self-reports. Although self-report measures are valid to a certain degree, researchers have long highlighted some biases, such as social desirability, differences in awareness and willingness to report emotional states (Mauss & Robinson, 2009), and memory biases (Diener, 2000). Our results speak for this analysis, the desirability bias seeming to have a particularly powerful impact in the context of caring for PwD.