Sensory Processing Sensitivity and Compassion Satisfaction as Risk/Protective Factors from Burnout and Compassion Fatigue in Healthcare and Education Professionals

International Journal of Environmental Research and Public Health Article Sensory Processing Sensitivity and Compassion Satisfaction as Risk/Protective Factors from Burnout and Compassion Fatigue in Healthcare and Education Professionals Manuela Pérez-Chacón1, Antonio Chacón1, Mercedes Borda-Mas 2,* and María Luisa Avargues-Navarro 2,*   Citation: Pérez-Chacón, M.; Chacón, A.; Borda-Mas, M.; Avargues- Navarro, M.L. Sensory Processing Sensitivity and Compassion Satisfaction as Risk/Protective Factors from Burnout and Compassion Fatigue in Healthcare and Education Professionals. Int. J. Environ. Res. Public Health 2021,18, 611. https://doi.org/10.3390/ ijerph18020611 Received: 19 December 2020 Accepted: 10 January 2021 Published: 12 January 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1International Doctoral School of the University of Seville, University of Seville, 41013 Seville, Spain; [email protected] (M.P.-C.); [email protected] (A.C.) 2Department of Personality, Assessment, and Psychological Treatment, University of Seville, 41018 Seville, Spain *Correspondence: [email protected] (M.B.-M.); avar[email protected] (M.L.A.-N.) Abstract: The study analyzes sensory processing sensitivity and the compassion satisfaction as risk/protective factors against burnout and compassion fatigue, during the first period of the COVID- 19 health emergency. A sample of 1566 Spanish adult healthcare (n = 694) and education (n = 872) professionals was evaluated. An ad hoc questionnaire for sociodemographic data, and the highly sensitive person scale (HSPS), Maslach burnout inventory (MBI) and professional quality of life scale (ProQOL-vIV) were administered. Burnout and compassion fatigue were observed in the healthcare and education professionals, where personal realization and depersonalization were higher in healthcare and compassion fatigue in education. The protective role of compassion satisfaction was confirmed, as was sensory processing sensitivity as a risk factor, except for its low sensory threshold dimension, which positively influenced personal realization. The findings of this study demonstrate the presence of burnout and compassion fatigue in healthcare and education professionals, displaying compassion fatigue as an emerging psychosocial risk in education, which was made more severe under the conditions of study, which is at the beginning of the COVID-19 pandemic. The importance of incorporating adequate management strategies for high sensitivity, empathy and compassion satisfaction in prevention programs is emphasized. Keywords: burnout; compassion fatigue; compassion satisfaction; sensory processing sensitivity; healthcare workers; educators; risk/protective factors; COVID-19 1. Introduction In recent decades, studies have reported that healthcare and education professionals are the groups most at risk of developing burnout because of their work in social service. In healthcare, professional activity is very emotionally demanding [ 1 ] due to its strong involvement in a job concentrating on human suffering. This is due to the emotional expectations generated and the need to constantly manage emotions adequately. The progressive state of stress experienced becomes a risk factor for developing burnout, depending on the working conditions and personal characteristics of the professionals [ 2 ]. Professional activity in education is also very physically and emotionally demanding. Today, the work of education professionals goes beyond teaching a subject matter. There is also a relationship in which they help with problems and concerns not directly related to education but also other areas (e.g., family and peers), and give attention to those students with special education needs (e.g., psychological, physical or sensory disability and/or behavior disorders, as well as highly gifted students) or in disadvantaged economic, sociocultural or health situations. Therefore, education involves an excessive emotional demand in the form of assistance, converting it in a risk factor for development of burnout [3]. In addition to burnout, recent studies on the quality of life of professionals devoted to helping others have referred to the concept of compassion fatigue. Compassion fatigue Int. J. Environ. Res. Public Health 2021,18, 611. https://doi.org/10.3390/ijerph18020611 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2021,18, 611 2 of 15 arises suddenly as the result of investing high levels of energy and compassion, or empathic care of others during an extended period of time. It is, therefore, not surprising that this syndrome has been widely studied in teaching [4] and healthcare [5]. Compassion fatigue has been described as a psychological state of anxiety or physical and mental distress associated with the stress of helping [ 6 ]. Not acting in time can affect one’s professional life by making it hard to care for patients/clients, and when empathy is not as strong, can evolve into burnout. Some authors have suggested that compassion fatigue is a syndrome related to emotional exhaustion, a basic component of burnout in labor [ 2 ], as a consequence of being exposed and absorbing the suffering of the patient/client for an extended period along with the professional’s own empathic predisposition. The high demand of performing service work in healthcare and education can also be of benefit, as it is compensated by the satisfaction of contributing one’s professional and human capacity to helping and social service. This benefit, called compassion satisfaction [ 6 ], becomes a protective factor against developing burnout and compassion fatigue by increasing the capacity to support the emotional cost of concern for patients/clients [ 7 ]. In addition, as the choice of professions in healthcare and teaching tends to be vocational, intrinsic motivation predisposes to greater satisfaction from helping and caring for others. Some authors [ 8 ] have found a direct relationship between burnout and compassion fatigue and the opposite with compassion satisfaction [1]. Healthcare and education professionals who suffer from these syndromes show differences in personality variables when interacting with the persons they care for or provide service to. Several personal variables have been studied with regard to burnout and compassion fatigue [ 9 ]. These variables (e.g., personality, problems relating to and understanding patients/clients and/or coping strategies) could explain individual differences with respect to susceptibility to syndromes such as burnout or compassion fatigue. Along this line, numerous studies in recent decades have related stress with personal risk and protection variables. Thus, a personality type characterized, among other factors, by the cognitive ability to perceive what the other person would feel in that situation is highly sensitive. Such people have sensory processing sensitivity, a trait which is related to feeling stressed by new or intense environmental or social stimuli. This trait represents a stronger awareness of sensory stimulation, inhibition of behavior and deeper cognitive awareness of environmental stimuli, leading to stronger emotional and physiological reactivity [10]. Although high sensitivity has been studied in recent years, its relationship to burnout or compassion fatigue has not received as much attention. However, a relationship has been found between highly sensitive individuals and reactivity to stress in traumatic situations [ 11 ], which leads us to wonder whether in highly sensitive people it is acting as a protective factor from stress, burnout and compassion fatigue due to susceptibility to their own personal resources [ 12 ]. Furthermore, highly sensitive people are characterized by showing higher levels of empathy [ 10 , 13 , 14 ]. However, unlike what occurs with empathic individuals who show compassion satisfaction [ 15 ], their high sensitivity trait could be acting as a risk factor, since in such people, empathy is associated with more suffering from dramatic or problematic situations experienced by others. All of the above, along with prevalence data supplied in studies on high sensitivity, where it has been demonstrated that around 15–20% of the population could have this trait [ 16 ], leads us to suggest the need to continue its study. At the present time, the situation generated by the COVID-19 pandemic cannot be ignored. In Spain, healthcare workers and educators have had to absorb unexpected changes in their work, not only making it more demanding, but requiring them to adapt to new demands, and work in the context of uncertainty generated by the pandemic, with the imminent urgency of needing to have the resources to help patients/clients. Therefore, the professionals exposed to the effects of this virus have been showing symptoms of stress and burnout [17]. Int. J. Environ. Res. Public Health 2021,18, 611 3 of 15 In brief, the situation of the healthcare emergency and changes occurring over time are leading to an increase in professional demands, which could generate the appearance of burnout or compassion fatigue [ 18 ] or worsen the distress professionals already feel. In addition, as mentioned above, the personal variables of healthcare workers and educators have an important role. Empathy, a characteristic which can be found in highly sensitive individuals [ 10 ], as well as in those who show compassion satisfaction in their work [ 15 ] should be emphasized. In this scenario, research advancing knowledge of these syndromes and variables that could be acting as risk or protective factors is required for design of effective intervention strategies adapted to a changing and uncertain context. Recent studies have demonstrated the efficacy of burnout and/or compassion fatigue intervention and prevention programs, showing decrease in burnout and compassion fatigue and increase in compassion satisfaction [ 19 ]. Intervention programs have traditionally focused mostly on contextual variables or stressful work conditions [ 20 ]. However, in recent years, interest has increased in variables such as compassion satisfaction, personal characteristics, resilience or self-efficacy [ 4 , 21 ]. It has also been observed that training highly sensitive people in intervention programs based on mindfulness, could reduce their stress and increase their sense of personal realization [22]. In view of the above, three objectives were posed for this study: (1) to find out the extent to which healthcare and education professionals showed burnout (BO), that is, high scores in emotional exhaustion (EE) and depersonalization (DP) and low in personal accomplishment (PA), and high compassion fatigue (CF) at the beginning of the healthcare emergency caused by the COVID-19 pandemic; (2) to determine whether there were any differences in sensory processing sensitivity (SPS), burnout dimensions, compassion fatigue and compassion satisfaction (CS) by the sector they belonged to; (3) to find out to what extent compassion satisfaction, sensory processing sensitivity and sector influenced their experience of these syndromes as risk and/or protective factors. The final purpose is to advance in designing burnout and compassion fatigue intervention programs for these labor groups. 2. Materials and Methods 2.1. Participants The sample came from another study in which 10,821 adults from Spanish-speaking countries (Mexico, Argentina, Colombia, Chile, Peru, Dominican Republic, Costa Rica, Venezuela, Guatemala, Honduras, and others) and countries where the Spanish language is strongly implanted (the United States and Brazil) participated. The inclusion criteria were Spanish nationality, over 18 years of age and currently employed. The exclusion criteria were although from a Spanish-speaking country, not having Spanish nationality, being unemployed, not filling in the data and/or the test battery properly and not giving express informed consent. Thus, following Beaton [ 23 ], questionnaires of participants from different cultures and countries, although they spoke the same language, were rejected. Therefore, after applying these criteria, and leaving only participants with Spanish nationality, the sample was reduced to 8358 adults. The sample selection procedure is shown in Figure 1. From the sample of participants with Spanish nationality, only professionals in the healthcare (n = 694) and education (n = 872) sectors were selected. Therefore, the final sample was made up of 1566 participants aged 22 to 70, of whom 165 were men (10.54%) and 1401 women (89.46%). Of these, 69 men (4.40%) (mean age = 43.58; SD = 11.88) and 625 women (39.91%) (mean age = 37.79; SD = 9.77) were working in healthcare and 96 men (6.14%) (mean age = 40.04; SD = 9.57) and 776 women (49.55%) (mean age = 37.50; SD = 9.62) in education. Int. J. Environ. Res. Public Health 2021,18, 611 4 of 15 The participants were from all of the autonomous regions of Spain, but mostly from Catalonia (20.11%), Madrid (19.41%), Andalusia (14.18%), Valencia (8.56%) and Galicia (6.58%). Figure 1. Sample selection procedure. 2.2. Procedure The study was performed following the code of ethics of the World Medical Association (Helsinki Declaration). All of the participants signed their informed consent. Sampling was by convenience, by accessibility. The sample was recruited in a community context. The procedure was: (a) contact the population and associations of highly sensitive people interested in the subject and professionals and workers in Spanish universities, for its diffusion, and (b) fill in the anonymous online tests in 45 to 60 min. The participants had access to the online application. After reading a brief introduction with the study objectives, they accepted participation and the research conditions. Then they proceeded to the tests which were presented in the same order for all of the participants. Participation was voluntary and received no economic compensation. The sample was collected in April and May of 2020, coinciding with the beginning of the COVID-19 pandemic, specifically the first two months of confinement derived from the national health emergency. 2.3. Measures An ad hoc questionnaire for sociodemographic and occupational information. This consisted of 12 questions with several answer choices referring to sociodemographic variables (sex, age, marital status, education, number of children, place and autonomous region of residence, occupation, occupation sector, job and time working at present job). The highly sensitive person scale (HSPS) [ 24 ] by Smolewska [ 25 ] adapted to Spanish by Chacón and Pérez-Chacón (2020) [ 26 ]. Developed to measure sensory processing sensitivity (SPS), this scale evaluates high sensitivity in adults. The scale consists of 27 items. The items have seven answer choices (0 = totally disagree, 6 = totally agree). This scale has a unidimensional structure with a reliability coefficient of 0.85. In the version by Smolewska et al. [ 25 ] three factors were found: ease of excitation, that is, being easily overwhelmed Int. J. Environ. Res. Public Health 2021,18, 611 5 of 15 by external and internal stimuli (EOE: items 3, 4, 13, 14, 16, 17, 20, 21, 23, 24, 26 and 27), aesthetic sensitivity, or aesthetic awareness (AES: items 2, 8, 10, 12, 15, 22 and 5), and low sensory threshold, reflecting unpleasant sensory arousal to external stimuli (LST: items 6, 7, 9, 18, 19 and 25), excluding items 1 and 11. The Cronbach’s alpha coefficients were 0.81, 0.72, and 0.78, respectively. To calculate the total SPS score, all the items of the final scale were added. The Cronbach’s alpha coefficients, for this sample, were 0.92. A higher score reflects greater sensory processing sensitivity. The Spanish Adaptation of the Maslach burnout inventory (MBI) [ 27 , 28 ] was used to evaluate burnout (BO). The scale consists of 22 items and includes three dimensions: emotional exhaustion (EE: items 1, 2, 3, 6, 8, 13, 14, 16, 20), depersonalization (DP: items 5, 10, 11, 15, 22), and decreased personal accomplishment (PA: items 4, 7, 9, 12, 17, 18, 19, 21). The items have seven answer choices (0 = never; 6 = every day). For classification into high, medium, and low burnout, the criteria used were those of the authors applied to the Spanish population sample (N= 1.138): EE (low: <15; medium: 15–24; high: >24), DP (low: <4; medium: 4–9; high: >9), and PA (low: <33; medium: 33–39; high: >39). The reliability indices for this sample, according to the Cronbach’s alpha coefficients, were 0.90 (EE), 0.79 (DP), and 0.71 (PA). The Spanish Adaptation of the Professional Quality of Life Scale (ProQOL-vIV) [ 29 , 30 ] was used to evaluate compassion fatigue and compassion satisfaction. This scale consists of 30 items measuring positive and negative facets of empathy in professionals. The items have six answer choices (0 = never; 5 = always). It includes three dimensions: compassion fatigue (CF: items 2, 5, 7, 9, 11, 13, 14, 23, 25 and 28), compassion satisfaction (CS: items 3, 6, 12, 16, 18, 20, 22, 24, 27 and 30) and burnout (B: items 1, 4, 8, 10, 15, 17, 19, 21, 26 and 29). Items 1, 4, 15, 17 and 29 are scored in reverse. The high, medium and low score classification is: CF (low: ≤ 7; medium: 8–17; high: ≥ 18), CS (low: ≤ 32; medium: 33–41; high: ≥ 42), and B (low: ≤ 17; medium: 18–27; high: ≥ 28). The reliability of the scale was 0.88 and the internal consistency indices were 0.81, 0.84 and 0.07, respectively. This study used the compassion fatigue and compassion satisfaction dimensions. These dimensions are directly related to the objectives of this study and present very good internal consistency values. 2.4. Data Analysis Statistical analyses were performed with the Statistical Package for the Social Sciences for Windows (SPSS), version 22.0 (SPSS Statistics for Windows, Version 22.0, IBM Corp., Armonk, NY, USA). To determine the percentage of participants with burnout (BO), the presence of burnout variable was created based on the criteria: EE high >24; DP high >9; PA low <33. Descriptive analyses were done (frequencies, percentages, means and standard deviations) in the different variables for the two groups of professionals, healthcare and educators. Then the presence of high compassion fatigue was determined using the criterion above (CF high: ≥ 18). The relationship between being a healthcare or an education worker and presence/absence of BO and presence/absence of CF was evaluated using Chi square (χ2). The assumption of normality was tested using Kolmogorov–Smirnov and the assumption of homoscedasticity using the Levene statistic. Parametric tests were used in the comparison of means, except for those variables that did not comply with homogeneity of variance. According to the above, the Student’s tand Mann–Whitney (U) were used to test for the existence of significant differences in the scores of MBI (BO dimensions), HSPS (total SPS and its dimensions) and ProQOL-vIV (CF y CS) among healthcare professionals and teachers. The contingency coefficient (r 2ϕ )was used to evaluate effect size to complement the Chi square value. Similarly, the Cohen’s dwas calculated using the Lipsey and Wilson [ 31 ] formula, considering the sample sizes in the two groups (healthcare/educators workers) and the Int. J. Environ. Res. Public Health 2021,18, 611 6 of 15 Student’s t. The reference values were <0.30, 0.30–0.50, and >0.50 as small, medium and large sizes, respectively [32]. A Pearson’s rcorrelation analysis was done to find the relationship between BO dimensions, total SPS and its dimensions, CF and CS (MBI, HSPS and ProQOL-vIV, respectively). Effect size values were: small size: <0.30; medium: from 0.30 to 0.49; large: >0.49 [31]. Then, to find out the weight of SPS and each dimension as well as CS in each BO dimensions and in CF, a multiple linear regression analysis was performed using the “enter” method. 3. Results 3.1. Preliminary Analysis The groups were equivalent in sex (p= 0.495), age (p= 0.247), marital status (p= 0.198) and number of children (p= 0.412). Differences were found in education (p= 0.000) and type of professional activity (p= 0.000). Sample characteristics are presented in Table 1. Table 1. Sample characteristics. N= 1566 Type of Professional Activity Healthcare (n= 694) Education (n= 872) t/X2 F % F % F % Sex Men 165 10.54 69 4.40 96 6.14 t(1563) = 1.159 p= 0.247 Women 1401 89.46 625 39.91 776 49.55 Age <30 407 25.99 171 10.92 236 15.07 31–40 551 35.18 254 16.22 297 18.96 X2(4) = 12.667 p= 0.013 * 41–50 413 26.37 165 10.54 248 15.83 51–60 163 10.41 82 5.24 81 5.17 >61 25 1.59 17 1.08 8 0.51 Unspecified 7 0.45 5 0.32 2 0.12 Education Elementary School 4 0.25 2 0.12 2 0.12 Middle School 14 0.89 9 0.57 5 0.32 X 2(5) = 54.620 p= 0.000 ** High School 216 13.08 125 7.98 91 5.82 Graduate 688 43.93 285 18.20 403 25.73 Postgraduate 516 32.95 236 15.07 280 17.88 Doctorate 128 8.17 37 2.36 91 5.81 Marital status Single 504 32.18 214 13.66 290 18.52 Married 477 30.46 224 14.30 253 16.16 X2(6) = 9.832 p= 0.198 Living together 377 24.07 167 10.66 210 13.40 Widow/widower 9 0.57 3 0.19 6 0.38 Separated marriage 45 2.87 18 1.15 27 1.72 Divorced 103 6.58 52 3.32 51 3.26 Others 51 3.26 16 1.02 35 2.24 Number of children 0 901 57.54 394 25.16 507 32.38 X2(5) = 6.097 p= 0.412 1 235 15.00 106 6.76 129 8.24 2 303 19.35 139 8.88 164 10.47 3 55 3.51 28 1.79 27 1.72 >3 15 0.96 4 0.25 11 0.71 Unspecified 57 3.64 23 1.47 34 2.17 Occupation Outside company 1237 79.00 502 32.05 735 46.93 X 2(1) = 33.280 p= 0.000 ** Autonomous company 329 21.00 192 12.27 137 8.75 ** p≤0.01, * p≤0.05. 3.2. Presence of Burnout and Compassion Fatigue The relationship between healthcare worker and educator and presence/absence of BO and high CF was evaluated using Chi square ( χ2 ). The frequency and percentage analysis used crossed tables between presence of BO and high CF by professional sector 4.3% (n= 30) of the healthcare workers fulfilled criteria for presence of BO compared to Int. J. Environ. Res. Public Health 2021,18, 611 7 of 15 4.2% of educators, with non-significant χ2 . However, the percentages of high CF increased noticeably in both professional sectors, surpassing the criterion by a higher percentage in 71.4% (n= 623) of educators compared to 65.1% of healthcare professionals. Significant associations were found in CF (χ2= 7.161; p= 0.007; r2ϕ= 0.067). 3.3. Comparison of Sensory Processing Sensitivity, Burnout Dimensions, Compassion Fatigue and Compassion Satisfaction The mean scores, Student’s t-test and Mann–Whitney for comparison of means are shown in Table 2. Statistically significant differences were observed in high sensitivity (SPS) and its dimensions (EOE, LST and AES), where the means were highest for educators, in both total score and dimensions. Significant differences were observed in the PA and DP dimensions, with healthcare professionals scoring higher in both dimensions. Finally, significant differences in CF were found, where educators had higher mean scores, although it should be considered that the effect sizes were small (see Table 2). Table 2. Comparisons between groups. Variables Healthcare Education Comparison of Means M SD M SD t/U Sign d Cohen Sensory processing sensitivity (Total SPS) 125.86 23.25 130.35 20.99 U= 341,082 0.000 ** −0.20 Ease of excitation (EOE) 54.97 10.77 57.10 10.30 t=−3.999 0.000 ** −0.20 Low sensory threshold (LST) 34.11 6.42 35.11 5.76 U= 332,987.50 0.001 ** −0.16 Aesthetic sensitivity (AES) 33.17 6.88 34.35 6.23 U= 331,237 0.000 ** −0.18 Emotional exhaustion (EE) 26.92 12.81 27.45 12.12 U= 309,532.50 0.434 −0.04 Personal accomplishment (PA) 39.93 6.84 38.91 7.01 t= 2.880 0.004 ** 0.15 Depersonalization (DP) 5.97 5.45 4.91 4.83 U= 270,807.50 0.000 ** 0.21 Compassion fatigue (CF) 21.16 7.95 22.20 7.78 t=−2.597 0.010 * −0.13 Compassion satisfaction (CS) 37.41 7.69 38.12 7.24 t=−1.859 0.063 −0.09 ** p≤0.01, * p≤0.05. 3.4. Relationship between Sensory Processing Sensitivity, Burnout Dimensions, Compassion Fatigue and Compassion Satisfaction Regarding the relationship between total SPS and the BO dimensions (EE, DP, PA), small variations were found between sectors. Both in healthcare workers and educators, the relationships with EE were significant (r= 0.20, p= 0.000 and r= 0.28, p= 0.000, respectively), but not with PA (p= 0.635 and p= 0.800, respectively). The relationship between DP and high sensitivity was significant in the group of educators (r= 0.07, p= 0.023) (see Table 3). The relationships between BO (EE, DP and PA) and SPS (EOE, LST, AES) dimensions, were direct and significant between EE and EOE and AES in both healthcare and education sectors, but not with LST (EOE: r= 0.22, p= 0.000 and r= 0.31, p= 0.000; LST: r= 0.09, p= 0.018 and r= 0.15, p= 0.000; AES: r= 0.14, p= 0.000 and r= 0.21, p= 0.000; respectively). Similarly, the relationships established between the high sensitivity subscales with DP and PA were different in both sectors. Specifically, there was a direct significant relationship between EOE and DP in the group of educators (r= 0.09, p= 0.004). The PA dimension was significantly directly related to LST (r= 0.17, p= 0.000 and r= 0.13, p= 0.000, respectively) in both sectors, and the opposite with EOE in educators (r= − 0.07, p= 0.023) with small effect sizes. CF and total high sensitivity (SPS) (r= 0.37, p= 0.000 and r= 0.38, p= 0.000) and their dimensions were directly and significantly related in both the healthcare and education sectors (EOE: r= 0.38, p= 0.000 and r= 0.37, p= 0.000; LST: r= 0.23, p= 0.000 and r= 0.23, p= 0.000; AES: r= 0.31, p= 0.000 and r= 0.34, p= 0.000; respectively). Int. J. Environ. Res. Public Health 2021,18, 611 8 of 15 Table 3. Relationship between healthcare and education variables. Healthcare (n= 694) Education (n= 872) HSPS MBI ProQO-vIV HSPS MBI ProQOL-vIV Total SPS EOE LST AES EE DP PA CF Total SPS EOE LST AES EE DP PA CF (a) Sensory processing sensitivity (HSPS) Total SPS 1 Sensory processing sensitivity (HSPS) Total SPS 1 EOE 0.91 ** 0.000 1 0.000 EOE 0.91 ** 0.000 1 LST 0.84 ** 0.000 0.63 ** 0.000 1 0.000 LST 0.79 ** 0.000 0.56 ** 0.000 1 AES 0.87 ** 0.000 0.67 ** 0.000 0.68 ** 0.000 1 0.000 AES 0.86 ** 0.000 0.67 ** 0.000 0.60 ** 0.000 1 (b) Burnout (MBI) EE 0.20 ** 0.000 0.22 ** 0.000 0.09 * 0018 0.14 ** 0.000 1 Burnout (MBI) EE 0.28 ** 0.000 0.31 ** 0.000 0.15 ** 0.000 0.21 ** 0.000 1 DP 0.01 0.744 0.058 0.128 −0.05 0.156 0.00 0.901 0.40 ** 0.000 1 DP 0.07 * 0.023 0.09 ** 0.004 0.03 0.347 0.03 0.332 0.41 ** 0.000 1 PA 0.01 0.635 −0.06 0.088 0.17 ** 0.000 0.02 0.529 −0.39 ** 0.000 −0.31 ** 0.000 1 PA 0.00 0.800 −0.07 * 0.025 0.13 ** 0.000 0.02 0.458 −0.31 ** 0.000 −0.32 ** 0.000 1 (c) Quality of life (ProQOL-vIV) CF 0.37 ** 0.000 0.38 ** 0.000 0.23 ** 0.000 0.31 ** 0.000 0.56 ** 0.000 0.24 ** 0.000 −0.23 ** 0.000 1Quality of life (ProQOL−vIV) CF 0.38 ** 0.000 0.37 ** 0.000 0.23 ** 0.000 0.34 ** 0.000 0.56 ** 0.000 0.31 ** 0.000 −0.16 ** 0.000 1 CS −0.03 0.334 −0.09 * 0.014 0.07 0.070 −0.01 0.810 −0.53 ** 0.000 −0.40 ** 0.000 0.66 ** 0.000 −0.22 ** 0.000 CS 0.02 0.452 −0.03 0.445 0.10 ** 0.002 0.03 0.331 −0.44 ** 0.000 −0.34 ** 0.000 0.62 ** 0.000 −0.10 ** 0.000 ** p ≤ 0.01, * p ≤ 0.05 Note: effect size: small magnitude ratio: <0.30; mean: between 0.30 y 0.49; high: >0.49 (a) Sensory processing sensitivity (SPS) (EOE: ease of excitation, LST: low sensory threshold, AES: aesthetic sensitivity), (b) dimensions of burnout syndrome (BO) (EE: emotional exhaustion, DP: depersonalization, PA personal accomplishment), (c) quality of life (ProQOL-vIV) (CF: compassion fatigue, CS: compassion satisfaction). Int. J. Environ. Res. Public Health 2021,18, 611 9 of 15 With respect to CS, significant inverse relationships were found in healthcare and education professionals with CF (r= − 0.22, p= 0.000 and r= − 0.10, p= 0.002; respectively) and the EE and DP dimensions (EE: r= − 0.53, p= 0.000 and r= − 0.44, p= 0.000; DP: r=−0.40 , p= 0.000 and r= − 0.34, p= 0.000; respectively). However, with PA the relationship was direct (r= 0.66, p= 0.000 and r= 0.62, p= 0.000; respectively). Lastly, there were no significant relationships between CS and total SPS in either healthcare workers (p= 0.334) or educators (p= 0.452). A significant inverse relationship was found between the high sensitivity dimensions (SPS) and EOE (r= − 0.09, p= 0.014) in healthcare workers and direct with LST (r= 0.10, p= 0.002) in educators, with low effect sizes. 3.5. Influence of High Sensitivity and Compassion Satisfaction on Burnout Dimensions and Compassion Fatigue Linear regression analyses were done to determine the weight of high sensitivity, CS and sector on BO dimensions, as well as on CF. Four regression analyses were performed with four criterion variables, the three BO dimensions (EE, PA and DP) and CF. The predictor variables were SPS dimensions (EOE, LST and AES), CS and sector (healthcare or education). In each analysis, the dimensions of high sensitivity (SPS) which had previously been shown to have significant correlations with the criterion variables were included. The total SPS variable had to be excluded from the analyses because it caused collinearity. The “enter” method was used for the analyses. Table 4shows the four models. All of them were significant, but more variance was explained in the PA and EE models. Table 4. Regression analyses. Influence of high sensitivity and compassion satisfaction on burnout dimensions and compassion fatigue. Beta Standard Error t p Emotional exhaustion (EE) R2= 0.301 (Constant) 35.774 2.438 14.671 0.000 ** Compassion satisfaction (CS) −0.795 0.036 −22.190 0.000 ** Ease of excitation (EOE) 0.260 0.036 7.238 0.000 ** Personal accomplishment (PA) R2= 0.438 (Constant) 17.574 1.220 14.401 0.000 ** Compassion satisfaction (CS) 0.575 0.018 31.998 0.000 ** Sector −1.429 0.267 −5.345 0.000 ** Ease of excitation (EOE) −0.098 0.016 −6.135 0.000 ** Low sensory threshold (LST) 0.214 0.027 7.802 0.000 ** Depersonalization (DP) R2= 0.153 (Constant) 14.647 1.053 13.912 0.000 ** Compassion satisfaction (CS) −0.257 0.016 −15.951 0.000 ** Sector −0.939 0.242 −3.873 0.000 ** Compassion fatigue (CF) R2= 0.173 (Constant) 6.934 1.675 4.140 0.000 ** Compassion satisfaction (CS) −0.148 0.025 −6.030 0.000 ** Ease of excitation (EOE) 0.206 0.025 8.350 0.000 ** Aesthetic sensitivity (AES) 0.187 0.041 4.569 0.000 ** ** p≤0.01. The predictor variables in the model estimated for EE were the SPS dimensions (EOE, AES, LST), CS and sector. The resulting model explained 30.1% (R 2 = 0.301) of EE scores ( F= 134.173 ;p= 0.000), again resulting in significant effects of CS and EOE. As in the