Authors of articles published in Journal for Person-Oriented Research retain the copyright of their articles and are free to reproduce and disseminate their work.
The pleasure derived from helping others is referred to as compassion satisfaction (CS). When a psychologist feels a too heavy demand to be compassionate and effective in helping, however, this may result in compassion fatigue (CF). CF may take the form of burnout or secondary traumatic stress (STS). The present paper focuses on two factors that may possibly protect against the development of CF, and facilitate the development of CS: (1) access to supervision and (2) a reflective stance. An online survey was distributed to two closed Swedish Facebook groups of psychologists, and complete data were obtained from 374 psychologists (320 women and 63 men). Both variable-oriented and person-oriented analyses were carried out. Correlational analysis showed that both supervision and reflection was associated with more CS, whereas only supervision but not reflection was significantly associated with less CF. Cluster analysis gave a more nuanced picture, suggesting a non-linear and multi-faceted association between reflection and CF. Some clusters of psychologists showed the expected association between level of reflection and level of CF. This was balanced, however, by other clusters that showed an association in the opposite direction, indicating high levels of reflection in clinicians with high levels of CF, and low levels in clinicians with low levels of CF. The results are discussed in terms of these differences in associative patterns possibly being due to different patient populations being involved. Among the limitations of the present study are its cross-sectional design, absence of data on patient characteristics, and a crude measure of supervision and reflection.
Keywords: Compassion fatigue, compassion satisfaction, supervision, reflective stanceWhen psychologists listen to patients’ experiences of trauma, anxiety, pain, depression, or some other kind of distress, with an intention to understand the suffering of these patients and to be of help for them, they will often tend to feel these emotions themselves to some degree. This kind of emotional contagion is a basic characteristic of human psychological functioning, and also a basic constituent of the empathic concern and compassion that lies at the root of human helping behavior.
The concept of compassion fatigue (CF) has been in use since 1992, when Joinson (1992) used the term to describe the experience of nurses who were worn down by the stress of attending to daily hospital emergencies, and Kottler (1992) emphasized the importance of compassion in dealing with particularly challenging patients. Two closely related concepts are those of secondary traumatic stress (STS; Solomon, 1988) and vicarious traumatization (Pearlman & Saakvitne, 1995). Although these terms refer more explicitly to traumas and traumatization than the concept of CF does, the phenomena that are referred to seem to be rather similar. In Stamm’s (2010) conceptualization, however, CF is seen as consisting of two components: STS and burnout.
On a more positive note, clinicians who work with suffering patients may also experience compassion satisfaction. Compassion satisfaction (CS) is defined as the amount of pleasure derived from helping others (Stamm, 2005), and has been found to correlate positively with resilience, that is, the ability to cope, learn and grow from difficult experiences (Burnett & Wahl, 2015). CS and CF, however, do not seem to correlate negatively in any simple linear way, but may coexist (Barr, 2017). For example, according to Bride, Radey and Figley (2007), “a clinician may experience both compassion fatigue and compassion satisfaction simultaneously, though as compassion fatigue increases it may overwhelm the clinician’s ability to experience compassion satisfaction” (p. 156). Stamm (2010) describes a pattern where high CS is combined with high scores on one of the CF components (STS) and low scores on the other (burnout); according to her, this pattern is typically seen in clinicians who work in high-risk situations and are “highly effective at their work because they feel that their work matters”, but at the same time experience strong fear because of their engagement.
A wide range of variables have been found to be associated with higher CF, including female gender (Mangoulia, Koukia, Alevizopoulos, Fildissis, & Katostaras, 2015; Mooney, Fetter, Gross, Rinehart, Lynch, & Rogers, 2017; Sprang, Clark, & Whitt-Woosley, 2007), lower age (Berger, Polivka, & Smoot, 2015; Craig & Sprang, 2010; Mooney et al., 2017; Sprang et al., 2007), and less clinical experience (Kolthoff & Hickman, 2017; Mangoulia et al., 2015; Mooney et al., 2017; Ray, Wong, White, & Heaslip, 2013; Sprang et al., 2007). As to CS, research indicates that it may be higher among older professionals (Berger et al., 2015; Sprang et al., 2007), among professionals with longer clinical experience (Berger et al., 2015), and among those who have received specialized trauma training (Craig & Sprang, 2010; Linley & Joseph, 2007; Sprang et al., 2007).
How is it possible to decrease the risk for compassion fatigue, and to facilitate the development of compassion satisfaction? One prominent suggestion is that clinicians need to rely on self-care strategies as a protection from the deleterious effects of empathic engagement. Examples of such self-care practices mentioned by Figley and Ludick (2017) are “eating regularly and healthily, getting sufficient exercise, spending time in nature, getting enough sleep” (p. 582) as well as “[d]eveloping interests and an identity outside of the work domain” (p. 582). This approach is based on the assumption that clinicians “need to cultivate and create a fulfilling personal life as a positive counterpoint to their work” (p. 582).
As an alternative or complement to the self-care approach, Miller and Sprang (2017) outlines an approach that focuses on skills during clinical practice that may protect clinicians from compassion fatigue. They list five categories of such skills: (1) experiential engagement, defined as “a cluster of skills used by the therapist to establish, balance, and maintain a connection to a client and the client’s experience and to acknowledge and experience the feelings that arise as a result of this engagement” (p. 154), so that emotions can be metabolized; (2) regulating rumination, so that a repetitive processing of events does not detract from the metabolizing of emotions that may occur through experiential engagement; (3) developing a conscious narrative about the clinical work being done; (4) reducing emotional labor by communicating authentically; and (5) skills for parasympathetic recovery during the workday. An important aspect of their model is also that this may be “facilitated greatly by a regular supervision process focused on reflection about the effect of the work on the therapist” (p. 158)
The importance of clinical supervision and reflection about the clinician’s emotional experiences in relation to clients is emphasized in many forms of psychotherapy. In psychoanalytic tradition, this is often referred to under the heading of countertransference. Freud (1910) observed that the therapist may sometimes respond emotionally to the patient in a way that can interfere with the treatment, and named it “countertransference”. Originally, this was assumed to be due to unresolved issues in the therapist’s past experiences with significant others. Later psychoanalysts and psychotherapists, however, have broadened the focus, recognizing that the therapist’s reactions to the patient may, in fact, also carry important information about the kind of responses which the client tends to evoke in others, and can thereby be used to facilitate treatment. This means that the concept of “countertransference” has shown a drift in meaning, from Freud’s original conceptualization (which saw countertransference as a threat to the treatment) to modern conceptualizations (which see it also as a source of information about the patient), and to models that integrate both of these aspects (Gabbard, 2001). The important thing for the present purposes is that, wherever these emotional processes may have their roots, reflection about these emotional processes in combination with clinical supervision may be assumed to be important both for the quality of the treatment and for the clinician’s well-being.
In the cognitive-behavioral tradition, the importance of reflection on, and analysis of the emotional aspects of the therapeutic relationship is emphasized especially in treatments that focus on patients with severe personality disorders and other interpersonal problems that may be expressed in the therapeutic relationship. In dialectical behavior therapy (Linehan, 1993), for example, the therapists are part of a consultation team who meet regularly to help one another and manage the high stress and potential burnout that may result from treating clients at high risk for suicide.
The present study focuses on these two factors: clinical supervision, and reflection about emotional experiences in relation to clients. There is little research done on these topics. With regard to clinical supervision, Linley and Joseph (2007) found that therapists who had formal supervision reported more personal growth than those who did not have supervision; however, they found no significant effects on compassion fatigue or compassion satisfaction. Other research, however, has documented that the perceived quality of clinical supervision is associated with less emotional exhaustion among counsellors who work with patients suffering from substance use disorders (Knudsen, Ducharme, & Roman, 2008; Knudsen, Roman, & Abraham, 2013). Peled-Avram (2017) also found that social workers who reported receiving a more relational-oriented supervision and evaluated their supervision as more effective had lower levels of vicarious traumatization.
The present study
The purpose of this study was to investigate how the availability of supervision/collegial support (from now on referred to as “supervision”) and the degree and the perceived importance of reflection about relational processes (together referred to as a reflective stance, or “reflection”) are associated with compassion fatigue (CF) and compassion satisfaction (CS) among psychologists. This question was approached not only in terms of associations between individual variables, but also and primarily in terms of person-oriented analyses of patterns of values on these variables.
In terms of individual variables, it was hypothesized that both supervision and reflection are associated with less of CF and more of CS. In terms of patterns, it was hypothesized that the combination of a good availability of supervision and the use of a reflective stance is the most beneficial pattern, whereas the combination of poor availability of supervision with little reflection is the worst pattern (best and worst being measured in terms CF and CS).
In addition, patterns of CF and CS were analyzed for their associations with supervision and reflection. Here it was expected that the analysis would identify the patterns described by Stamm (2010): (1) high CS combined with moderate to low CF; (2) low CS combined with high CF; (3) high burnout combined with moderate to low CS and STS; (4) high STS combined with low CS and burnout; and (5) high CS and high STS combined with low burnout. It was also expected that the high CS/low CF pattern, which is described by Stamm (2010) as the most beneficial combination, would be most clearly associated with a good availability of supervision and a reflective stance. Conversely, it was expected that the combination of low CS and high CF, which is described by Stamm (2010) as the most distressing combination, would be associated with a poor availability of supervision and little reflection.
The study used a cross-sectional survey design, with a questionnaire constructed in the digital tool Sunet (Swedish University computer Network) and administered during one week over the Internet on two closed Swedish Facebook groups: Psykologer (with around 6500 members who are licensed psychologists) and PTP-psykologer (with around 1500 members, who are not yet licensed but are doing their practice [PTP] to receive their license).
The participants were 384 psychologists (320 women and 63 men); 44.5% of them were 20-34 years old, and 47.9% were 35-54 years old. All participants reported that they had contact with patients suffering from mental ill-health as part of their work; 46,6% reported that they had 0-5 years of experience; 24,2 % reported 6-10 years of experience; 15,1% reported 11-15 years of experience; 8,9% reported 16-25 years of experience; and 5.2% reported more than 25 years of experience.
The questionnaire contained 100 questions, and included both standardized psychometric instruments and some questions that were constructed specifically for the present study. The first page of the questionnaire provided information about the purpose of the study, contact information to the researchers, and informed the participants that they were anonymous, and that they were free to interrupt their participation at any time.
(ProQOL; Stamm, 2010) is a 30-item instrument using a five-point Likert-type scale from 1 (never) to 5 (very often) that yields composite scores on the three subscales: Compassion Satisfaction, Burnout, and Secondary Traumatic Stress. A score on Compassion Fatigue is computed by summarizing the scores on Secondary Traumatic Stress and Burnout. Good reliability and validity has been established (Stamm, 2010). Although Stamm (2010) provides cut-offs for high and low values on the ProQOL scales, she strongly suggests that the continuous scores should be used, and she also advises against using ProQOL for diagnostic purposes. The Swedish translation was made by Gerge (2011).
The Compassion Satisfaction subscale contains ten items. Examples of items are “I get satisfaction from being able to help people”, “I feel invigorated after working with those I help”, “I have happy thoughts and feelings about those I help and how I could help them”, and “I believe I can make a difference through my work”. No items are reversed. Cronbach’s alpha in the present study was .90.
The Burnout subscale also contains ten items. Examples of items are “I feel trapped by my job as a helper”, “I feel worn out because of my work as a helper”, “I feel overwhelmed because my case load seems endless”, and “I feel connected to others” (reversed). Four items on this subscale are reversed before summarizing the total score. Cron-bach’s alpha in the present study was .75.
The Secondary Traumatic Stress subscale contains ten items. Examples of items are “I jump or am startled by unexpected sounds”, “I find it difficult to separate my personal life from my life as a helper”, “I think that I might have been affected by the traumatic stress of those I help”, and “I feel depressed because of the traumatic experiences of the people I help”. No items are reversed. Cronbach’s alpha in the present study was .74.
Availability of supervision was measured by the participants’ responses to the item “I have access to supervision and collegial support where I can get emotional relief in relation to my work, in case I would need it.” A reflective stance was measured by the following two items: “I reflect actively about how I am influenced emotionally in the meeting with clients”, and “I feel that what is evoked in me emotionally in the meeting with clients can be useful information in treatment.” All three of these items were rated on a 5-grade Likert scale, ranging from 1 (never) over 2 (seldom), 3 (sometimes), 4 (often), to 5 (very often).
The questionnaire also contained a number of other psychometric scales, the results on which have been reported elsewhere (Dehlin, 2017; Sandberg, 2017).
Cluster analysis was used to identify groups of participants with similar profiles of scores, first on the supervision/reflection variables, and then on the ProQOL variables. The cluster analyses were carried out in four steps in accordance with the LICUR procedure (Bergman, Magnusson, & El-Khouri, 2009), by means of the statistical software ROPstat (Varga, Torma, & Bergman, 2015). First, multivariate outliers were identified by means of a residue procedure and removed from further analysis. Second, Ward’s hierarchical clustering method was applied. Four criteria described by Bergman et al. (2009) were used to decide on the optimal cluster solution: (a) theoretical meaningfulness of the cluster solution; (b) a cluster solution with k clusters is preferable to one with k-1 if a sharp decrease in explained error sum of squares (EESS) occurs between the solution with k clusters and the one with k-1 clusters; (c) the number of clusters should not be more than 15 and should not be expected to be less than five; (d) the size of the EESS for the chosen cluster solution should preferably not be less than 67% and at the very least exceed 50%. In addition, the homogeneity coefficient of each cluster should preferably be 1. Third, a data simulation was undertaken to verify that the EESS was higher than what could be expected on a random data set with the same general properties as the data set used in the real analysis. Fourth, a non-hierarchical relocation procedure was carried out in order to improve the homogeneity of the clusters and to increase the variance explained by the cluster solution.
From the total number of participants (n=384), 10 individuals were excluded because they had indicated that the questions about supervision/collegial support and/or reflection were not relevant to them. This means that 374 individuals remained for statistical analyses.
Table 1 shows descriptive data on the ProQOL variables. Comparison by independent samples t-test showed only one difference between genders: women reported higher scores than men on STS, t(371) = 1.52, p < .05. As to age, CS showed a weak positive correlation with age, rho = .11, p < .05. Similarly, years of clinical experience showed a weak positive correlation with CS, rho = .16, p < .01.
Descriptive data on the ProQOL variables, and the supervision and reflection variables.
| M (SD) | Women | Men | |
|---|---|---|---|
| Compassion Satisfaction | 37.1 (5.8) | 37.3 (5.8) | 36.7 (5.7) |
| Burnout | 23.8 (4.8) | 23.7 (4.8) | 24.1 (4.8) |
| Secondary Traumatic Stress | 20.6 (5.2) | 20.9 (5.4) | 19.4 (4.4) |
| Availability of supervision/collegial support | 3.3 (1.0) | 3.3 (1.0) | 3.3 (1.1) |
| Reflection | 3.7 (0.8) | 3.7 (0.8) | 3.8 (0.9) |
| Relevance of reflection | 3.7 (0.9) | 3.7 (0.8) | 3.6 (1.2) |
Table 1 also shows descriptive data on the supervision and reflection variables. There were no gender differences on these variables. Age correlated negatively with the availability of supervision, rho = -.12, p < .05, but positively with perceived relevance of reflection, rho = .13, p < .05. Years of clinical experience also correlated positively, rho = .16, p < .01, with perceived relevance of reflection.
Because there are several versions of ProQOL, with different response formats (for example, previous versions have used a 6-scale Likert format from 0 to 5, rather than the 5-point format from 1 to 5 which is used by ProQOL version 5), results should be compared only between studies that use the same version. Table 2 shows a comparison with three other studies that have used ProQOL version 5. Although the psychologists in the present study scored slightly lower on CS than the nurses in these three studies, they did not differ much on the burnout and STS scales.
Comparison with three other studies that have used the ProQOL version 5 in other populations.
| Study | Participants | CS | Burnout | STS |
|---|---|---|---|---|
| Wu et al. (2016) | Oncology nurses (N=486; US) | 42.4 (5.3) | 22.7 (5.7) | 22.7 (5.8) |
| Mooney et al (2017) | Nurses in an intensive care unit (N=68; US) | 38.3 (6.1) | 25.5 (5.9) | 20.5 (6.1) |
| Kolthoff et al (2017) | Geriatric nurses (N=42; US) | 37.4 (5.2) | 26.7 (6.1) | 23.0 (6.2) |
As seen in Table 3 , CF showed a negative correlation with the availability of supervision, although it showed no significant correlation with the measures of a reflective stance. CS, on the other hand, showed significant positive correlations both with access to supervision and with the two aspects of a reflective stance. Of the two components of CF, only burnout showed significant correlations with supervision. It may also be noted that, with regard to the reflection variables, burnout and STS showed weak correlations in opposite directions – whereas both reflection variables tended to correlate weakly negatively with burnout they tended to show weak positive correlations with STS.
Correlations between the compassion scales and the availability of supervision/ collegial support and aspects of a reflective stance.
| CF | Bu | STS | CS | |
|---|---|---|---|---|
| Availability of supervision/collegial support | -.27 ** | -.40 ** | -.08 | .32 ** |
| Reflection | -.00 | -.13 | .12 | .23 ** |
| Relevance of reflection | -.01 | -.13 | .10 | .32 ** |
Note. CF = Compassion fatigue; Bu = Burnout; STS = Secondary Traumatic Stress; CS = Compassion Satisfaction.
No outliers were identified. Ward’s hierarchical method resulted in a 5-cluster solution that explained 58.5% of the variance (ESS). After the use of Wishart’s non-hierarchical relocation procedure, the EES increased to 61.3. All homogeneity coefficients were below 1.0, ranging between 0.36 and 0.96. Figure 1 shows the five profiles of these clusters in terms of the z-scores of each cluster. To describe the clusters, we will use the following conventions: When z > 1, this is referred to as a very high score, and when z < -1 this is referred as a very low score. A z-score between 0.5 and 1 is referred to as a moderately high score, and one between -0.5 and -1 is referred to as a moderately low score. Z-scores between -0.5 and 0.5 are referred to as about average scores.
The five-cluster solution on the supervision and reflection variables, described in terms of z-scores.
The largest cluster was Cluster 1 (n = 93), which was characterized by moderately low scores both on supervision/collegial support and on aspects of reflective stance; this was labeled the Low Supervision/Low Reflection cluster. Three other clusters were almost equally large: Cluster 2 (n = 78); Cluster 3 (n = 84); and Cluster 4 (n = 85). Cluster 2 had moderately high scores on supervision/collegial support and on reflection, and average scores on relevance of reflection; this was labeled the High Supervision/Average Reflection cluster. Cluster 3 had moderately low scores on supervision/collegial support and moderately high scores on the reflection items, and was labeled the Low Supervision/High Reflection cluster. Cluster 4 had moderately high scores on supervision/collegial support, very low scores on reflection, and average scores on relevance of reflection, and was labeled the High Supervision/Low Reflection cluster. Finally, there was a smaller cluster (Cluster 5; n = 34), with high scores on supervision in combination with very high scores on aspects of a reflective stance; this was labeled the High Supervision/High Reflection cluster.
The clusters were compared by means of a series of one-way ANOVAs on the ProQOL variables. As seen in Table 4 , the two low supervision clusters (low supervision/low reflection, and low supervision/high reflection) scored higher on CF than two of the high supervision clusters (high supervision/average reflection and high supervision/low reflection). Of the two CF subscales, these differences were even more pronounced on the Burnout scale; here the two low supervision clusters scored significantly lower than most of the high supervision clusters. On the STS scale, however, the differences were small, and the post hoc tests showed no significant differences.
Comparison of the supervision/reflection clusters on the ProQOL scales by one-way ANOVA.
| 1. Low Sup/Low Refl | 2. High Sup/Average Refl | 3. Low Sup/High Refl | 4. High Sup/Low Refl | 5. High Sup/High Refl | Comparison by ANOVA F(4,374) | Tukey Post hoc test | |
|---|---|---|---|---|---|---|---|
| M(SD) | M(SD) | M(SD) | M(SD) | M(SD) | |||
| CF | 46.9 (8.9) | 41.4 (7.3) | 46.6 (8.8) | 42.8 (7.9) | 43.3 (9.2) | 6.94 *** | 1,3>2,4 |
| Bu | 26 (4.2) | 21.4 (3.8) | 25 (5.1) | 23.3 (4.3) | 21.4 (5.2) | 15.69 *** | 1>2,4,5; 3>2,5 |
| STS | 20.9 (6.1) | 20 (4.6) | 21.6 (5.1) | 19.6 (4.6) | 21.9 (5.3) | 2.42 * | |
| CS | 33.5 (5.4) | 39.5 (5.2) | 37.6 (5.6) | 37.1 (5.4) | 40.4 (4.8) | 17.42 *** | 1 |
| 4 |
