Emotional reactions to music in depressed individuals

Abstract

Music is often used to alleviate depression, an affective disorder. Yet, little is known about how listeners suffering from depression respond emotionally to music. The goal of this study was to investigate whether listeners show different patterns of emotional reactions to music depending on level of depression. In previous research, depression has been linked with negative biases in cognitive processes such as memory and attention. Here we indirectly investigated whether such biases may also influence psychological mechanisms involved in the arousal of emotions during musical experiences. Seventy-seven listeners (19–65 years old) took part in an experiment which compared depressed individuals with non-depressed controls. The participants listened to music stimuli designed to target specific induction mechanisms (brain stem reflex, contagion, episodic memory), and were asked to rate felt emotions. Based on previous studies on cognitive bias, we made predictions about how depression would affect reactions to each stimulus. The predictions received partial support: depressed listeners reported significantly lower levels of happiness in the memory condition and non-significantly higher levels of anxiety in the brain stem condition, than did controls. Conversely, no difference in reported sadness was found in the contagion condition. Observed differences were mainly attributable to the severely depressed listeners.

Keywords

cognitive bias depression emotions mechanisms music experience

Depression is the most prevalent psychiatric condition in the Western world, believed to afflict nearly 20% of the American population (Gotlib & Joorman, 2010). Epidemiological data from Sweden indicate that, at any given point, approximately 10% of the population experience clinically significant depression (Johansson, Carlbring, Heedman, Paxling, & Andersson, 2013). At its core, depression is a disorder of persistent negative affect and impaired emotion regulation ability. Music can be used to alleviate depressive symptoms in therapy (Maratos, Gold, Wang, & Crawford, 2008; for a randomized controlled trial study, see Erkkilä et al., 2011). However, little is known about how people with depression respond to music. In this study, we explore one way in which depression could have an impact on musical emotions: biases in information processing.

Depression and cognitive biases

Depression is a mood disorder marked by “a despair that can be painfully persecuting and can drain all meaning from life” (Keltner, Oatley, & Jenkins, 2013, p. 327). Yet symptoms can also be motivational (e.g., loss of interest, lack of drive), physical (e.g., loss of appetite, weight loss, sleep difficulties), and cognitive (e.g., negative thoughts about the self, world, and future; Beck & Alford, 2014). Similarly, there are multiple causes of depression, which might be both biological (e.g., genes, brain chemistry) and psychological (e.g., learning, sociocultural effects).

According to cognitive theories of depression (e.g., Beck, 1976), the key to understanding depression is the way that individuals construe or represent personally relevant events. Negative cognitions are at the core of both onset and maintenance of the disorder, because they induce the depressed affect and promote the associated symptoms (Gotlib & Joorman, 2010). The negative cognitions are often referred to as cognitive biases, and can be observed in at least four domains of information processing.

First, depression is associated with interpretation bias (Mathews & MacLeod, 2005). It has been shown that depressed individuals are negatively biased when interpreting ambiguous events, including those that involve surprise (Kan, Mimura, Kamijima, & Kawamura, 2004).

Second, depressed individuals are shown to have a negative attention bias, specifically manifested in their difficulty with disengaging from negative information, once having attended to it (Gotlib & Joormann, 2010; Joormann & Arditte, 2014; Mathews & MacLeod, 2005; Power & Dalgleish, 2008).

Third, and related to interpretation bias, several studies suggest that depressed people are impaired in perceiving and recognizing emotions in faces (Bistricky, Ingram, & Atchley, 2011) and voices (Naranjo et al., 2011). Recent studies have demonstrated similar biases in perception of emotions with music (Naranjo et al., 2011; Punkanen, Eerola, & Erkkilä, 2011).

Finally, the most prominent information-processing bias associated with depression relates to memory. Two consistent biases have been found that concern the retrieval of autobiographical (episodic) memories. The first is mood-congruent memory (Lloyd & Lishman, 1975): Depressed patients are more likely to remember negative events (Joorman & Gotlib, 2008) and also have an impaired ability to recall positive events (e.g., Werner-Seidler & Moulds, 2011). The second bias is termed overgeneral autobiographical memory (Williams et al., 2007): Depressed patients have difficulties recalling specific autobiographical memories.

Depression and musical emotions

A relatively large body of literature suggests a possible link between aesthetic activities and psychopathology (Kemp, 1996). This includes depression, which has been linked to both artistic creativity and appreciation (Thomas & Duke, 2007). In music, it has been argued that some of the most prominent composers (e.g., Berlioz, Rachmaninoff, Schumann, Tchaikovsky) suffered from depression (Storr, 1992). Recent studies also suggest that many musicians suffer from depression (Help Musicians UK). Depressed people thus seem to have a propensity towards music creativity and involvement. However, depression has not been investigated in relation to music experience. Because depression is an affective disorder, one would expect it to influence mainly the emotion component of music experience (Gabrielsson, 2001).

In this study, we adopt a working definition of emotions offered by Juslin (2011), which states that:

Emotions are relatively brief, intense, and rapidly changing reactions to potentially important events (subjective challenges or opportunities) in the external or internal environment – often of a social nature – which involve a number of subcomponents (cognitive changes, subjective feelings, expressive behavior and action tendencies) that are more or less ‘synchronized’ during an emotional episode. (Juslin, 2011, p. 114)

As previously noted, there is some indication that depression affects perception of emotions in music – similarly to other nonverbal communication channels (Naranjo et al., 2011). However, hardly any studies have explored whether depressed listeners react differently to music from non-depressed controls. As far as we know, only one music study to date has investigated aroused (as opposed to perceived) emotions in depressed individuals. Bodner et al. (2007) reported that major depressive disorder (MDD) patients selected a larger number of emotional labels to describe their emotions in response to sad music, as compared to angry, happy and scary music, but the authors did not consider the underlying causes of this difference in response. It thus seems relevant to further explore the link between depression and musical arousal of emotions.

Why should depression affect emotional reactions to music? We argue that the cognitive biases discussed earlier could have an impact on the psychological mechanisms through which music arouses emotions – thus leading to differences in experienced emotions, which might be shown in listening tests. Much research and prevention aimed at mental health conceives of the emotion induction process in terms of a single mediating mechanism (e.g., a negative appraisal style), though it has recently been argued that scholars need to consider a range of mechanisms in a more process-specific manner (Juslin, 2015).

Underlying mechanisms

To understand how depression might influence music experiences, we need a theoretical framework, describing the mechanisms that mediate between musical features and experienced emotions. Classic “appraisal theories” (Scherer, 1999) assume that emotions are caused by multi-dimensional appraisals of events relative to goals. However, because purely instrumental music appears remote from our ongoing plans or life goals (cf. Ellsworth, 1994), several authors have suggested other potential mechanisms, such as musical expectancy (Meyer, 1956), conditioning (Dowling & Harwood, 1986), episodic memory (Baumgartner, 1992), and emotional contagion (Juslin, 2000). For overviews, see Sloboda and Juslin (2001) and Scherer and Zentner (2001).

In this article, we adopt a more recent and extensive framework, termed the BRECVEMA model, which currently features eight mechanisms in addition to the default mechanism cognitive appraisal. The mechanisms range from simple reflexes to complex judgments (e.g., Juslin, 2005, 2013; Juslin & Västfjäll, 2008; for a different approach, see Scherer & Coutinho, 2013):

Brain stem reflex – a hard-wired response to a simple acoustic feature such as extreme or increasing loudness or speed (e.g., Brandao, Melo, & Cardoso, 1993).

Rhythmic entrainment – a gradual adjustment of an internal body rhythm (e.g., heart rate, breathing) toward an external rhythm in the music, which affects the listener’s emotions through proprioceptive feedback (e.g., Harrer & Harrer, 1977).

Evaluative conditioning – the repeated pairing of a piece of music with other positive or negative stimuli, leading to a conditioned association (e.g., Blair & Shimp, 1992).

Contagion – an internal “mimicry” of the perceived voice-like emotional expression of the music, which induces a matching emotion in the listener (e.g., Juslin, 2000).

Visual imagery – inner images of an emotional character, which are conjured up by the listener through a metaphorical mapping of the musical structure (e.g., Osborne, 1980).

Episodic memory – a conscious recollection of a particular event from the listener’s past, which is triggered by a musical pattern (e.g., Baumgartner, 1992).

Musical expectancy – a response to the gradual unfolding of the syntactical structure of the music and its expected or unexpected continuation (e.g., Meyer, 1956).

Aesthetic judgment – a subjective evaluation of the aesthetic value of the music based on an individual set of weighted criteria (e.g., Juslin, 2013).

The prevalence of these mechanisms has been explored, using more or less representative samples of music (Juslin, Sakka, Barradas, & Liljeström, 2017), situations (Juslin, Liljeström, Västfjäll, Barradas, & Silva, 2008), and listeners (Juslin, Liljeström, Laukka, Västfjäll, & Lundqvist, 2011) – including a cross-cultural sample (Juslin, Barradas, Ovsiannikow, Limmo, & Thompson, 2016). More crucially for the present study, some mechanisms have been tested in experimental studies, which manipulated musical pieces to obtain evidence of cause and effect (Janata, 2009; Juslin, Barradas, & Eerola, 2015; Juslin, Harmat, & Eerola, 2014; Steinbeis, Koelsch, & Sloboda, 2006). However, no study thus far has examined how depression influences emotional reactions associated with specific mechanisms.

Rationale for the present experiment

The aim of the present study was to investigate whether depressed listeners show different patterns of emotional response to music from those of non-depressed controls, as expected if the “cognitive biases” linked to depression also influence mechanisms active during music listening. For both theoretical and methodological reasons, we focused on three of the eight BRECVEMA mechanisms: brain stem reflex, contagion, and episodic memory. These mechanisms have been successfully manipulated in previous experimental studies (Juslin et al., 2014, 2015). It was also possible to develop depression-related hypotheses for each mechanism.

Psychological processes (e.g., underlying mechanisms) cannot be observed “directly”, but have to be inferred from behavioral output. In this study, given cognitive biases in information-processing, we would expect to find that depressed listeners differ from controls in terms of the quality and quantity of emotion aroused by music. Furthermore, because different mechanisms involve distinct types of information processing, the precise nature of the differences may vary depending on the mechanism activated.

The brain stem reflex mechanism is thought to be activated by extreme features, such as high sound level, quick attack, and sharp timbre that occur locally and cannot be predicted from the syntactical structure of the music (e.g., Juslin, 2013). Brain stem reflexes during listening to music have previously been found to arouse mainly surprise in listeners (e.g., Juslin et al., 2014, 2015), consistent with an “early” reaction that occurs before any elaborate classification of the sound event has taken place (Simons, 1996). However, based on findings that depressed people are negatively biased in their interpretations of ambiguous stimuli (Mathews & MacLeod, 2005), showing increased negative responses towards surprising events (Kan et al., 2004), including an increased fear-potentiated startle (see Ballard et al., 2014), we predicted that depressed listeners would report higher levels of anxiety-fear in the brain stem reflex condition than would controls.

The contagion mechanism presupposes that an emotion expressed in the music has been perceived by the listener, who then “mimics” it internally (Juslin, 2000). Furthermore, this effect will be especially strong if the music features an expressive human voice, or instruments that are highly reminiscent of a human voice. In the present experiment, we used as contagion stimulus a piece of music with a sad expression (e.g., minor mode, slow tempo, low pitch), which had managed to produce matching sadness responses in listeners in a previous experiment (Juslin et al., 2015). However, as noted above, depressed individuals may be negatively biased in their perception of emotions in music (Naranjo et al., 2011). In addition, they have difficulties in disengaging from mood-congruent information (Joormann & Arditte, 2014; Mathews & MacLeod, 2005; Power & Dalgleish, 2008), and show increased responses of personal distress to other people’s suffering (e.g., Schreiter, Pijnenborg, & Aan Het Rot, 2013; Thoma et al., 2011). Hence, we predicted that depressed listeners would report higher levels of sadness-melancholy in the contagion condition than would controls.

The episodic memory mechanism occurs when the music evokes a personal memory of a specific event from the listener’s life and also arouses the emotion associated with the memory. Several studies have indicated that music can be a powerful cue for evoking episodic memories (Baumgartner, 1992; Cady, Harris, & Knappenberger, 2008; Janata, Tomic, & Rakowski, 2007; Juslin et al., 2008, 2011, 2014, 2015, 2017). In this experiment, we used a piece assumed to be associated with happy memories of fun, holidays, and summer for most people. We would thus expect listeners to experience happiness and nostalgia, due to the positive memories evoked by the familiar music (Juslin et al., 2015). However, since depressed individuals show difficulties recalling positive memories and suffer from overgeneral autobiographical memory, which may lead to less vivid memories and thus a blunted response (Ford, Addis, & Giovanello, 2011), we predicted that depressed listeners would report lower levels of happiness-elation in the episodic memory condition than would controls.

Method

Participants

Seventy-seven listeners (38 females and 39 males, 19–65 years old, M = 32.7, SD = 13.1) took part in the study. They received either two movie tickets or course credits as compensation for their anonymous and voluntary participation in the experiment. The target populations were depressed people and non-depressed controls. The depressed group was defined as individuals with mild, moderate, or severe depression, as indicated by their scores on the Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown, 1996; described further below). The control group was defined as individuals with minimal depression, based on the same test. The control group featured 40 listeners and the depressed group 37 listeners (11 scoring mild, 13 moderate, and 13 severe). Statistical tests (i.e., Mann–Whitney U-test for age; chi-square tests for gender, musical training, and music education) showed no significant differences between depressed individuals and non-depressed controls regarding these variables. However, 27% of the depressed and 10% of the control participants reported receiving psychotherapy, and 54% of the depressed and 10% of the controls reported taking psychotropic medication at the time of the study; 19% of the depressed participants and 2% of the controls reported receiving both psychotherapy and medication. The participants were recruited through advertisements in newspapers, social media, the mailing list of the Uppsala Music Psychology Group, and posters throughout the city of Uppsala (university campus, library, shopping malls, healthcare centers, the psychiatric department of the Uppsala University Hospital). Two different advertisements were used – one targeting depressed and the other non-depressed individuals. All participants except one were Swedish. Ethical approval for the study was provided by the Regional Ethical Review Board in Uppsala (Dnr 2015/165).

Design

The experiment used a mixed design, with depression as between-subjects independent variable (quasi-experimental; two levels: depressed, control), and target-mechanism condition as within-subjects independent variable (four levels: brain stem reflex, contagion, episodic memory, control). The dependent variables were ratings on 15 emotion scales (to test predictions) and eight mechanism scales (for manipulation checks).

Musical stimuli

We used four instrumental pieces of music, which had been previously tested and found to successfully activate intended target mechanisms. A more detailed description of the general experimental paradigm and the musical stimuli can be found in Juslin et al. (2014, 2015).

Brain stem reflex

To activate the brain stem reflex mechanism, we employed a previously validated excerpt from Juslin et al. (2014). This is a manipulated version of a digital rendition by Jay Bacal of a short composition written by Ernest Bloch titled Prayer (from Jewish Life No. 1). A sudden loud chord with a broad spectrum and a sharp attack has been inserted at the beginning of the 10th bar of the piece. (The goal was to mimic naturally-occurring brain stem reflex events, such as the drum stroke in Joseph Haydn’s Symphony No. 94, ‘Surprise’.) The sound level of the target event was carefully calibrated, and a peak sound level of 75 dBa was regarded as sufficient to produce a reliable effect on listeners (stimulus length 37 s).

Contagion

To activate the contagion mechanism, we used an excerpt featured in Juslin et al. (2015), consisting of the beginning of Concerto for Two Violins in A minor, Op. 3, No. 8, II. Larghetto e Spiritoso, written by Antonio Vivaldi and performed by Accademia Ziliniana. It has been noted that the cello and the violin are the closest-sounding instruments to the human voice, and previous data show that “sad” performances are heard as particularly expressive by listeners (Juslin, 1997, Exp 2). The “sad” expression of the piece is reflected in the slow tempo, the minor mode, the slow tone attacks, and the subtle dynamics (stimulus length 122 s).

Episodic memory

To evoke music-associated episodic memories, without having to encode them during the actual study, we used another excerpt from Juslin et al. (2015) featuring the piece Sommar, Sommar, Sommar, written by Sten Carlberg and Erik Sandström, and performed by Åke Jelvings Orchestra. For more than 50 years, the piece has been the signature song of a very popular radio program in Sweden that is broadcast daily during the summer months. It is highly familiar to most people in Sweden, and is usually associated with happy memories of holidays, relaxation, summer, and fun (stimulus length 39 s).

Control condition

As a control condition, we also included a “neutral” stimulus in the form of a piece titled “minimalist music”, composed under the alias “Mihangeliago” and downloaded from the Internet. The piece does not feature any type of information considered necessary to evoke an emotion through any of the mechanisms in the BRECVEMA framework. Previous findings have confirmed that the piece is “emotionally incompetent” (Juslin et al., 2015). It may be described as moderately slow, soft, and monotonous (stimulus length 38 s).

Measures

Emotions

To measure felt emotions in listeners, we relied on 12 rating scales, which have been used at Uppsala University specifically for measuring musical emotions (see Appendix A; e.g., Juslin et al., 2014). The list includes the emotions reported as most common in prevalence studies (Juslin et al., 2008, 2011, 2017) and covers all four quadrants of the circumplex model in terms of valence and arousal (i.e., high pleasure and high arousal, high pleasure and low arousal, low pleasure and low arousal, low pleasure and high arousal; Russell, 1980). For each piece, the participants were asked to indicate, on a scale from 0 (not at all) to 4 (a lot), the extent to which they experienced each of the 12 emotions. In addition, the participants rated the overall intensity of their emotion, their liking for the music, and their familiarity with the music.

Mechanisms

As a manipulation check, we obtained subjective measures of the induction mechanisms that occurred, using the MecScale (Juslin et al., 2014). This consists of eight items (see Appendix B), each targeting one of the induction mechanisms featured in the BRECVEMA framework. The idea is that, although many processes are implicit in nature, they may co-occur with subjective impressions that can be reported by listeners. For instance, a music listener who becomes aroused through the episodic memory mechanism may report a conscious recollection of a previous event. Self-reports cannot be taken as “veridical”. Notably, however, the MecScale items have been found to be highly predictive of both target-mechanism conditions (Juslin et al., 2014) and experienced emotions (Juslin et al., 2015) in previous studies. Listeners in the present experiment were asked to respond to each of the eight questions with a simple yes or no answer. Further, if they responded affirmatively to the episodic memory or evaluative conditioning item, they were asked to indicate if the memory or conditioned association had a “positive”, “negative”, or “mixed” affective valence (to control for mood-congruent memory effects).

Depression

Levels of depression were measured using the Beck Depression Inventory-II (BDI-II; Beck et al., 1996), which has good internal-consistency reliability and test-retest reliability (Arnau, Meagher, Norris, & Bramson, 2001). The inventory is composed of 21 multiple-choice items, relating to symptoms of depression such as hopelessness and irritability, feelings of guilt and of being punished, and physical symptoms such as fatigue and weight loss. Cronbach’s alpha in the present sample was α = .94.

Anxiety

Due to the high comorbidity rates in depressive and anxiety disorders observed in previous research (e.g., Lamers et al., 2011), we also measured anxiety with the 21-item Beck Anxiety Inventory (BAI; e.g., Beck, Epstein, Brown, & Steer, 1988). This scale has shown high internal consistency (α = .92) and test-retest reliability (r = .75). Cronbach’s alpha in the present sample was α = .93. As might be expected, BDI-II and BAI scores were significantly correlated, r (75) = .63, p < .001. BAI scores were significantly lower for the controls (M = 5.88, SD = 7.17) than for depressed group (M = 16.41, SD = 8.10), t(75) = −6.05, p < .001.

Procedure

When the participants arrived at the music laboratory, they were seated in a comfortable armchair, in front of a computer monitor. A brief introduction and instructions concerning the experiment were presented on the monitor. The participants were told that they would listen to four excerpts of music, and that after each piece they should rate their experience of the music by means of the rating scales on the computer screen. Once they had read the instructions and given informed consent, the listening test began.

All participants were tested individually in a soundproofed room and listened to the music through a pair of high-quality loudspeakers (Dali Ikon 6 MK2). The sound level was pre-set to a comfortable level, which was held constant across listeners. Stimulus order was randomized for each listener, whereas the order of rating scales was kept constant. The clinical inventories and a short questionnaire concerning demographic variables (e.g., age, gender, music education) were administered after the experiment. Stimulus administration and data collection were handled by means of the MediaLab© software. An experimental session lasted approximately 20 minutes.

Results

In the following, we first report manipulation checks, which ensured that the experimental conditions evoked the target mechanisms and emotions largely as intended, then we present the between-group comparisons between depressed listeners and non-depressed controls.

Manipulation checks

Mechanisms

In order to evaluate the effect of target-mechanism condition on self-reported mechanism indices, we computed the non-parametric Spearman’s rho (ρ) correlation between the target-mechanism conditions and the items included in MecScale. The results are shown in Table 1. If the MecScale items have predictive value, and the experimental conditions were effective in discriminating between the mechanisms, we would expect only a small subset of the correlations to be both statistically significant and positive in direction – more specifically, those correlations that involve items corresponding to the respective target-mechanism conditions.

Table 1.

Spearman rank-order correlations between target-mechanism conditions and MecScale items.

MecScale item	Target-mechanism condition
	Control	Brain stem reflex	Contagion	Episodic memory
Brain stem reflex	−.28	.80	−.23	−.28
Rhythmic entrainment	−.08	−.23	−.02	.34
Episodic memory	−.23	−.19	−.01	.43
Evaluative conditioning	−.20	−.14	.08	.26
Visual imagery	−.25	−.06	.10	.20
Contagion	−.41	.15	.36	−.09
Musical expectancy	.08	.38	−.11	−.35
Aesthetic judgment	−.49	.11	.34	.04

Note. Correlations that are both statistically significant (Bonferroni-corrected for n = 32, from α = .05 to α = .0016) and positive in direction are set in bold. The complete MecScale items are shown in Appendix B. All variables were coded dichotomously.

Inspection of Table 1 shows that the results largely follow this pattern. Note that none of the correlations was positive and statistically significant in the Control condition (the left-most column), confirming that the condition did not activate any of the mechanisms. In the remaining conditions, the correlations were also mostly as expected. In the Brain stem condition, there was a large correlation with the Brain stem reflex item, as well as a smaller correlation with the Expectancy item. In the Contagion condition, the largest correlation was with the Contagion item. Finally, in the Episodic memory condition, the largest correlations involved the Episodic memory item and, to a lesser degree, the other memory-related items (Evaluative conditioning and Visual imagery).

However, two of the correlations deviated slightly from the expected pattern: a significant correlation with the Aesthetic judgment item in the Contagion condition, and a significant correlation with the Rhythmic entrainment item in the Episodic memory condition.

To determine whether the treatments given to the participants were fully comparable across depression levels, we computed the point-biserial correlation (r_pb) between individual depression scores (BDI-II, continuously coded) and each of the mechanism items (MecScale, dichotomously coded) for each of the experimental conditions (Bonferroni-corrected for n = 32 from α = .05 to α = .0016). None of the correlations was statistically significant. Mean variance accounted for (r_pb²) in the MecScale ratings by the BDI scores was .01. In none of the correlations did the BDI scores account for more than 6% of the variance. We conducted a chi-square test to compare frequencies of reported negative, positive, and mixed memories in the Episodic memory condition between the two listener groups. The test was non-significant, χ²(2) = 1.48, p = .48, Cramer’s V = .17.

Emotion ratings

To evaluate the effect of target mechanism on listeners’ self-reports, we conducted an analysis of variance (ANOVA) across groups, with mechanism as within-subject factor (four levels: brain stem reflex, contagion, episodic memory, control) on each rating scale. However, the Kolmogorov–Smirnov test revealed that the assumption of normality was violated for the dependent variables. Thus we used instead the non-parametric Friedman test (Bonferroni-corrected for n = 15, from α = .05 to α = .0033). The results indicated a significant overall effect of target-mechanism condition on all scales (χ²_F = 23.59–186.31, all ps < .0033), except interest-expectancy (χ²_F = 0.42, p = .94).

Recall that the paradigm predicts, based on the BRECVEMA model (Juslin, 2013), that the Brain stem condition will arouse surprise-astonishment; that the Contagion condition will arouse sadness-melancholy; and that the Episodic memory condition will arouse both happiness-elation and nostalgia-longing.

To verify that the conditions discriminated between emotions as intended, we performed Wilcoxon signed-rank tests. (Because of the low statistical power of non-parametric tests, we did not Bonferroni-adjust our planned comparisons.) Results indicated that the mean ratings of surprise-astonishment were higher for the Brain stem condition (M = 2.36, Mdn = 3.00, SD = 1.40) than for the Contagion (M = 0.43, Mdn = 0.00, SD = 0.75; Z = −6.78, p < .001, r = .55), Episodic memory (M = 0.69, Mdn = 0.00, SD = 0.96; Z = −6.36, p < .001, r = .51), and Control (M = 1.03, Mdn = 1.00, SD = 1.05; Z = −5.37, p < .001, r = .43) conditions.

The mean ratings of sadness-melancholy were higher for the Contagion condition (M = 2.45, Mdn = 3.00, SD = 1.24) than for the Brain stem (M = 1.97, Mdn = 2.00, SD = 1.28; Z = −2.59, p = .010, r = .21), Episodic memory (M = 0.44, Mdn = 0.00, SD = 0.73; Z = −7.02, p < .001, r = .57), and Control (M = 0.49, Mdn = 0.00, SD = 0.70; Z = −6.83, p < .001, r = .55) conditions.

Moreover, the ratings of happiness-elation were higher for the Episodic memory condition (M = 2.69, Mdn = 3.00, SD = 1.20) than for the Brain stem (M = 1.21, Mdn = 1.00, SD = 1.10; Z = −6.28, p < .001, r = .51), Contagion (M = 1.31, Mdn = 1.00, SD = 1.07; Z = −5.86, p < .001, r = .47), and Control (M = 0.92, Mdn = 1.00, SD = 1.10; Z = −6.51, p < .001, r = .52) conditions.

The ratings of nostalgia-longing, finally, were higher for the Episodic memory condition (M = 2.64, Mdn = 3.00, SD = 1.44) than for the Brain stem (M = 1.32, Mdn = 1.00, SD = 1.37; Z = −4.93, p < .001, r = .40), Contagion (M = 2.16, Mdn = 3.00, SD = 1.38; Z = −2.00, p = .045, r = .16), and Control (M = 0.40, Mdn = 0.00, SD = 0.83; Z = −6.93, p < .001, r = .56) conditions.

The ratings of intensity, liking, and familiarity may also serve to confirm the adequacy of the experimental paradigm. Wilcoxon tests revealed that the ratings of liking were significantly lower for the Control condition (M = 0.97, Mdn = 1.00, SD = 1.00) than for the for the Brain stem (M = 2.12, Mdn = 2.00, SD = 1.21; Z = −5.28, p < .001, r = .43), Contagion (M = 2.77, Mdn = 3.00, SD = 1.25; Z = −6.70, p < .001, r = .54), and Episodic memory (M = 2.70, Mdn = 3.00, SD = 1.16; Z = −6.51, p < .001, r = .52) conditions.

The ratings of intensity were significantly lower for the Control condition (M = 1.65, Mdn = 2.00, SD = 0.98) than for the Brain stem (M = 2.42, Mdn = 2.00, SD = 0.94; Z = −4.43, p < .001, r = .36), Contagion (M = 2.64, Mdn = 3.00, SD = 0.97; Z = −5.55, p < .001, r = .45), and Episodic memory (M = 2.52, Mdn = 3.00, SD = 1.15; Z = −4.45, p < .001, r = .36) conditions.

The ratings of familiarity were significantly higher for the Episodic memory condition (M = 3.79, Mdn = 4.00, SD = 0.64) than for the Brain stem (M = 0.27, Mdn = 0.00, SD = 0.68; Z = −7.97, p < .001, r = .64), Contagion (M = 0.83, Mdn = 0.00, SD = 1.04; Z = −7.53, p < .001, r = .61), and Control (M = 0.08, Mdn = 0.00, SD = 0.27; Z = −8.11, p < .001, r = .65) conditions.

Comparisons of depressed listeners and controls

We conducted planned comparisons between groups for each of the emotions included in our predictions (anxiety-fear in the Brain stem condition, sadness-melancholy in the Contagion condition, and happiness-elation in the Episodic memory condition). However, according to the Kolmogorov–Smirnov test, the distribution of the rating variables deviated from normality. Thus we used the bootstrapping method (e.g., Efron & Tibshirani, 1993) with 1.000 bootstrap samples to report our bias-corrected and accelerated (BCa) 95% confidence intervals (CIs) and p-values.

Our predictions received partial support. Thus, as predicted, depressed participants reported significantly lower levels of happiness-elation in the Episodic memory condition (M = 2.41, Mdn = 3.00, SD = 1.28) than did controls (M = 2.95, Mdn = 3.00, SD = 1.06), t(70.16) = 2.02, p = .04, BCa 95% CI [.03, 1.09], d = .46, a marginally “medium” effect size (Cohen, 1992).

Also in the predicted direction, depressed participants reported higher levels of anxiety-fear in the Brain stem condition (M = 1.65, Mdn = 1.00, SD = 1.23) than did controls (M = 1.25, Mdn = 1.00, SD = 1.35), d = .31, a “small” effect size. This difference was not statistically significant, however, t(75) = −1.35, p = .18, BCa 95% CI [−1.03, .15].

Moreover, contrary to our prediction, depressed participants and controls showed roughly equal means in the Contagion condition (M = 2.49, Mdn = 3.00, SD = 1.28 for depressed; M = 2.43, Mdn = 3.00, SD = 1.22 for controls), t(75) = –.22, p = .83, BCa 95% CI [−.62, .54], d = .05.¹

As a follow-up analysis, we calculated the means for the predicted emotions as a function of the four BDI-levels of depression (i.e., minimal/control, mild, moderate, severe). The data are shown in Figures 1 –3. As seen in Figure 1, the low ratings of happiness-elation in the Episodic memory condition for the depressed group (mild-moderate-severe) are mainly accounted for by the severe sub-category. Figure 2 similarly illustrates that the high ratings of anxiety-fear in the Brain stem condition was mainly explained by the severe sub-category. In fact, a follow-up test adopting an “extremes-groups approach” revealed that the contrast between minimal/control and severe sub-categories was statistically significant, t(51) = −2.88, p = .006, BCa 95% CI [−2.05, −.41], d = 0.92, a “large” effect size. Similarly, the contrast between minimal/control and severe for happiness-elation in Episodic memory condition was significant t(16.20) = 2.66, p = .02, BCa 95% CI [.27, −2.10], d = 0.92. Finally, the sadness ratings in the Contagion condition were roughly equal across the four sub-categories (Figure 3).

Figure 1.

Mean ratings of happiness-elation for the Episodic memory condition, displayed for each depression level.

Figure 2.

Mean ratings of anxiety-fear for the Brain stem reflex condition, displayed for each depression level.

Figure 3.

Mean ratings of sadness-melancholy for the Contagion condition, displayed for each depression level.

Discussion

Summary and interpretation

The aim of this study was to explore whether depressed listeners show different patterns of emotional reactions to music from those of non-depressed controls. Building on previous studies of cognitive bias in depression, we developed predictions about how depression might influence responses involving specific mechanisms. The results offered partial support for our predictions.

First, depressed listeners reported significantly lower levels of happiness than did controls in the Episodic memory condition, which was designed to arouse positive emotions via positive memories. The effect approached a “medium” size (d = 0.46). Follow-up analyses indicated that the effect was strongest for the listeners with severe depression.

We did not find a significant difference between depressed individuals and controls in the valence of the evoked memories. This indicates that the low happiness ratings were not due to a mood-congruent memory bias (as this would have been seen in the retrieval of more negative or fewer positive memories). One possible explanation for this result is that the depressed listeners’ memories were overgeneral – that is, that the memories lacked specificity. It has been suggested that overgeneral memory may be linked to an avoidance of the threat of negative affect aroused by the recall of specific events (Williams et al., 2007). It seems plausible that lack of specificity of memories might lead to a reduced happiness response (e.g., Ford et al., 2011).

One further explanation of the lower happiness in the depressed group is that it is an effect of the blunted reactivity to positive stimuli of depressed people reported previously (see Webb & Pizzagalli, 2016), if we regard retrieved memories as “internal stimuli” of sorts. On this view, the depressed listeners may have retrieved the same amount of positive memories as the controls and the retrieved memories may have been equally specific; nonetheless, these listeners may not have reacted with the same level of positive emotion, due to a generally reduced activity in the reward-related brain regions. This has been described as anhedonia (Pizzagalli, Iosifescu, Hallett, Ratner, & Fava, 2008), and is consistent with notions of reduced positive emotion-reactivity in depression (Depue & Iacono, 1989) and of reduced emotion reactivity regardless of valence (i.e., the emotion context insensitivity hypothesis; Rottenberg, Gross, & Gotlib, 2005). Future studies need to tease apart these alternative explanations.

Consistent with our theoretical predictions, depressed participants reported higher levels of anxiety than did non-depressed controls in the Brain stem condition. The difference (d = 0.31) was not statistically significant, but the non-significant trend was clarified by follow-up analyses, which revealed a significant difference between the most severe depression sub-category and the non-depressed controls (d = 0.92, a “large” effect). Notably, this result is consistent with findings that depressed individuals show an increased fear-potentiated startle (Ballard et al., 2014), and a negative interpretation bias towards ambiguous stimuli (Kan et al., 2004; Mathews & MacLeod, 2005). The majority of these studies have focused on MDD populations, which would correspond to our severely depressed subgroup. The finding that depressed individuals reacted with higher levels of anxiety would appear to speak against the emotion context insensitivity hypothesis. However, the small number of observations in the severe category should be kept in mind when interpreting the results.

Our between-group differences were predominately attributable to the severely depressed subgroup of participants. This result reflects the heterogeneity of depressive disorders (Webb & Pizzagalli, 2016). A few investigations have explored cognitive biases in dysphoric non-clinical populations (e.g., Joormann, 2004), but the majority of studies of biases focus on MDD, which is characterized by a distinct set of severe symptoms. It should be noted that BDI-II scores alone do not suffice for an MDD diagnosis. Our results suggest that these biases are selectively evident in severely depressed individuals, at least within a music context. Future studies may want to focus on specific types of depression in order to be able to offer clearer interpretations.

Finally, the most unexpected finding concerns our prediction for the Contagion condition. Contrary to what we expected, depressed listeners’ ratings of sadness did not differ from those of controls. This result may be interpreted in at least two ways: Either the depressed listeners did not perceive higher levels of sadness and thus did not experience higher levels of felt sadness through contagion, or they did perceive higher levels of sadness, but did still not feel it to a greater extent.

The first interpretation, if applicable, could be due to a so-called ceiling effect. The specific stimulus is characterized by an exceptionally sad expression, to which both depressed and control participants might have responded with as much felt sadness as could reasonably be expected in a laboratory context. We may speculate that the use of a more ambiguous-sounding stimulus would have offered enhanced opportunities for a between-groups difference due to perception bias to be revealed. However, this would arguably introduce methodological difficulties, given that in order to selectively and effectively activate the contagion mechanism, the use of music with a clear and convincing emotional expression is imperative (Juslin et al., 2015).

The second interpretation, in turn, might reflect the avoidance or suppression of depression-related information (e.g., Williams et al., 2007). That is, depressed listeners may have perceived a higher level of sadness in the music than did controls, but perhaps they did not contagiously feel it because they suppressed this information. This possibility can be explored in future studies that try to disentangle a purely perceptual bias from a bias in emotional reaction. However, the degree to which emotional contagion could actually be subject to suppression is still unclear, considering that it appears to involve subcortical and automatic processes (Juslin, 2013; cf. Wheeler, 1966).

One further interpretation is related to the finding that the Contagion condition evoked the Aesthetic judgment mechanism in addition to the Contagion mechanism. Juslin, Sakka, Barradas, and Liljeström (2016) obtained preliminary evidence of a positive link between depression and judgments of aesthetic value in music. In addition, they found that depressed listeners tended to base their judgments on the expressivity of the music to a greater extent than did non-depressed listeners. Thus, if the aesthetic judgments evoked by the Contagion condition in this experiment were based mainly on evaluation regarding the emotional expressivity (not an unlikely prospect given the moving expression of the piece), these judgments would have had a stronger effect on depressed individuals. Hence, although the music may have aroused sadness through contagion, the aesthetic pleasure derived from the aesthetic judgment might have been more pronounced in the depressed individuals, thus counteracting the sadness from the contagion process. However, speaking against this interpretation is the result that there was no significant difference between depressed listeners and controls with respect to the ratings of admiration-awe, which is strongly linked to judgments of aesthetic value (Juslin, 2013).

Implications and limitations

To the best of our knowledge, this is the first attempt to apply the BRECVEMA model to a depressed sample. One advantage of this approach is that it takes the underlying mechanisms as the point of departure. We submit that individual differences in emotional reactions to music are due to differential functioning of the induction mechanisms, and that individual differences thus must be sought at the level of these processes. The use of a validated experimental paradigm and the possibility of selectively activating mechanisms provided us with the opportunity to measure differences in reaction based on theoretical predictions for each mechanism. Our findings did, in fact, suggest that the exact nature of differences between depressed listeners and controls varied depending on target-mechanism condition.

However, our design prohibits us from drawing conclusions regarding the precise function and nature of the mechanisms, because they were assessed indirectly by measuring the outcome emotions. In order to achieve a better understanding of how music is processed in listeners with depression at the mechanism level, studies that examine more directly the biases involved in the functioning of specific mechanisms are needed.

One further limitation of the study is that the measurement of emotion relied exclusively on self-reports (as opposed to a multi-component measurement approach, including physiology and expression). Self-report can introduce a number of biases such as self-presentation bias, demand characteristics, and difficulties in recognizing or labeling emotions (cf. Zentner & Eerola, 2010). The latter problem could be particularly pronounced for people suffering from depression, which has been linked to alexithymia (see, e.g., Punkanen et al., 2011). On the other hand, depression has been linked with a dissociation between various emotion components (e.g., facial expression and feeling; see Rottenberg, Kasch, Gross, & Gotlib, 2002). Thus, a multi-component approach would perhaps have produced less interpretable findings. Moreover, it should be noted that the experimental paradigms used here have been validated in previous studies, which did use a multi-component approach and offered converging evidence of felt emotions from self-reports, expression and physiology (Juslin et al., 2014, 2015; see also Lundqvist, Carlsson, Hilmersson, & Juslin, 2009).

There are also some limitations of our sample of listeners. The sample was fairly small, limiting the statistical power of our analyses (and a non-parametric overall test did not enable testing of interaction effects between group and mechanism). Moreover, the depressed sample covered a wide range of depression levels, from mild to severe. Our findings indicate that the differences observed were mainly attributable to the severely depressed listeners. Hence, one would perhaps obtain larger and more consistent differences with a sample of listeners drawn solely from the severely depressed population. Moreover, the high comorbidity of depression and anxiety in the sample should be taken into account, considering that anxiety is associated with its own collection of cognitive biases (Mathews & MacLeod, 2005). Finally, 54% of the depressed participants reported receiving psychotropic medication. Bylsma, Morris, and Rottenberg (2008) note that antidepressant medication may influence emotion reactivity in depressed patients. Future studies should optimally attempt to exclude medicated participants, in the hope of conducting more sensitive tests of potential differences between depressed listeners and controls.

Concluding remarks

Knowledge about how depressed individuals experience music emotionally is beneficial for understanding how they might benefit from music listening in their everyday lives, and also how music can be applied in therapeutic contexts. The present results suggest that depressed listeners’ emotional reactions to music differ from those of non-depressed listeners, especially with regard to episodic memories in severely depressed listeners. Hence, a closer study of memories evoked by music in severely depressed individuals seems to be a promising direction for future research.

Footnotes

Appendix A: Emotion items

Describe how you felt when you heard the music.

		Not at all A lot
1.	happiness – elation	0 1 2 3 4
2.	sadness – melancholy	0 1 2 3 4
3.	surprise – astonishment	0 1 2 3 4
4.	calm – contentment	0 1 2 3 4
5.	interest – expectancy	0 1 2 3 4
6.	nostalgia – longing	0 1 2 3 4
7.	anxiety – nervousness	0 1 2 3 4
8.	pride – confidence	0 1 2 3 4
9.	anger – irritation	0 1 2 3 4
10.	love – tenderness	0 1 2 3 4
11.	disgust – contempt	0 1 2 3 4
12.	admiration – awe	0 1 2 3 4
13.	How intense (strong) was your emotional experience as a whole?	0 1 2 3 4
14.	How much did you like the music?	0 1 2 3 4
15.	How familiar were you with the music?	0 1 2 3 4

Appendix B: Mechanism items ( MecScale )

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The present study was supported by the Swedish Research Council through a grant to Patrik N. Juslin.

Notes

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