Spontaneous Music-Evoked Autobiographical Memories in Individuals Experiencing Depression

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Spontaneous Music-Evoked Autobiographical Memories in Individuals Experiencing Depression © The Author(s) 2020 Published version Sakka, Laura S.; Saarikallio, Suvi Sakka, L. S., & Saarikallio, S. (2020). Spontaneous Music-Evoked Autobiographical Memories in Individuals Experiencing Depression. Music and Science, 3, 1-15. https://doi.org/10.1177/2059204320960575 2020 Music and autobiographical memory - Research Article Spontaneous Music-Evoked Autobiographical Memories in Individuals Experiencing Depression Laura S. Sakka 1 and Suvi Saarikallio 2 Abstract Listening to music often triggers strong memories of events from our past, which influence how we affectively experience music listening and can therefore contribute to music’s therapeutic capacity. The aim of this study was to examine the valence and content of spontaneous music-evoked autobiographical memories (MEAMs) in listeners with self-reported depression, who typically demonstrate negatively biased autobiographical memory. Eighteen depressed and 21 controls participated in a music-listening experiment where they listened to a personalized music stimulus, described their memories, and thereafter rated the valence of these memories and of their induced affect. Participants’ ratings were statistically analysed, while the memory content was analysed with the use of a computerized text-analysis method and with a qualitative thematic analysis. Quantitative ratings of valence revealed a significant difference between groups: half of the depressed, compared to none of the controls, recalled a negative memory, and these were experienced with negative induced affect. The qualitative thematic analysis of the memory descriptions revealed that both depressed and control participants’ memories could be categorized into three first-level themes: (1) personal, (2) relationships, and (3) activities. Depressed participants’ negative memories were mainly located in the ‘relationships’ theme and included memories about loss and dysfunctional relationships, such as bullying, and in the ‘personal’ theme, including memories of mental health struggles and coping with music. Approximately a third of depressed participants recalled positive memories, and these were either related to loving family relationships or to activities. Limitations concerning the small sample size and implications regarding the function of music listening for depressed individuals are discussed. Keywords Autobiographical memory, depression, emotional memories, memory bias, music-evoked memories, spontaneous autobiographical memories Submission date: 24 April 2020; Acceptance date: 30 August 2020 Literature Music is ubiquitous, accompanying us in activities as ordinary as driving and exercising (Juslin et al., 2008), to significant events such as weddings and celebrations (Gregory, 1997). Consequently music, as our life’s ‘soundtrack’, is strongly linked to autobiographical memories. These memories influence how we affectively experience music listening and can consequently contribute to music’s healing potential, the capacity of music to serve as a resource for our emotionality, health and wellbeing (Fancourt & Finn, 2019; MacDonald et al., 2012). People experiencing depression typically tend to remember more negative personal events (Joormann & Arditte, 2014) and have difficulty recalling positive memories (Werner-Seidler & Moulds, 2011). If this is also the case with autobiographical memories evoked by music, then personal music listening may not always be a beneficial activity for mental health promotion in this population. 1 Department of Psychology, Uppsala University, Uppsala, Sweden 2 Department of Music, Art and Culture, University of Jyva ¨skyla ¨, Jyva ¨skyla ¨, Finland Corresponding author: Laura S. Sakka, Department of Psychology, Uppsala University, Box 1225, SE-751 42 Uppsala, Sweden. Email: [email protected] Music & Science Volume 3: 1–15 ªThe Author(s) 2020 DOI: 10.1177/2059204320960575 journals.sagepub.com/home/mns Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). l The aim of this study is to answer this question by investigating the valence and content of music-evoked autobiographical memories (MEAMs) in individuals experiencing depression. Music-evoked Autobiographical Memories MEAMs play an important role in the music-listening experience. First, the potential of music to evoke memories functions as an important motive for engaging in music listening (Sloboda & O’Neill, 2001). Furthermore, the retrieval of MEAMs often leads to an emotional reaction, acting as an important emotion-induction mechanism (Janata et al., 2007; Juslin et al., 2015). Typically, these emotions are positive in valence, as indicated by research on listener samples drawn from typical populations (Jakubowski & Ghosh, 2019; Janata et al., 2007). Memories may also boost the emotional experience of music listening regardless of the affective valence; when compared to musical features as an emotion induction mechanism, memories were more strongly linked to higher pleasure of social emotions (e.g. kinship, tenderness) and to higher displeasure of sadness (Maksimainen et al., 2018). Consequently, MEAMs contribute to our emotional experiences with music and can therefore cumulatively influence music-related mental health outcomes. Musical Experience in Depression Major depression is a highly prevalent psychiatric disorder. According to the World Health Organization (WHO), depression is the leading cause of disability worldwide (World Health Organization [WHO], 2017). Depression is classified as a mood disorder and is per definition a condition of negative affect. However, the disorder is not characterized solely by increased negative, but also by reduced positive affect (Singer & Salovey, 1988; Werner- Seidler & Moulds, 2011). This impaired ability to experience positive emotions, also called anhedonia, is key in the disorder, as positive affective experiences function as a buffer against depressed mood (Singer & Salovey, 1988). Therefore, one way of approaching the treatment of depression, applied for instance in behavioural activation, is by encouraging patients to engage in pleasurable activities (Cuijpers et al., 2007). One such activity could be everyday personal music listening, which can provide cumulative health benefits (Miranda et al., 2012). However, the effect of music listening on mental health is not always positive, and in certain cases unhealthy music-listening behaviours, such as maladaptive emotion regulation with music, may promote psychopathology (Marik & Stegemann, 2016). This is especially observed in people with internalizing symptoms (Miranda et al., 2012). Depressed adolescents, for instance, have been shown to be prone to couple their music listening with ruminative tendencies, social isolation, and an inability to improve their mood (Saarikallio et al., 2015). With regards to MEAMs, Sakka & Juslin (2018a) found that participants with high depression levels reported lower induced happiness to music evoking episodic memories compared to non-depressed participants, while Garrido (2018) found that people with tendencies for depression experience nostalgic remembering with music with negative emotional responses. It therefore appears that memories with music play a unique role in how depressed people experience music. However, no research, to our knowledge, has directly investigated the content of MEAMs in depressed people, who typically demonstrate autobiographical memory alterations (Joormann & Arditte, 2014). Depressed individuals are biased towards recalling negative information, including autobiographical memories (Joormann & Arditte, 2014; Mathews & MacLeod, 2005). This bias appears to remain even after depression has remitted, suggesting that it contributes to the disorder as a vulnerability factor (Joormann & Arditte, 2014). Research also shows that these negative memories contribute to the maintenance of depression, as they prolong the experience of negative affect (Singer & Salovey, 1988). Besides demonstrating a preferential recollection of negative information, depressed individuals also show an impaired ability to retrieve positive memories (Werner- Seidler & Moulds, 2011). The Present Study To reiterate, music is capable of triggering autobiographical memories, typically associated with positive emotions. Depression is characterized by negatively biased autobiographical memory recollection and an increased tendency to experience negative affect during music listening. The aim of the present study was to investigate the valence and content of memories evoked by music in people experiencing depression. This aim was approached in two ways: (1) hypothesis-driven analysis of memory valence and valence of induced affect, based on quantitative ratings; and (2) exploratory analysis of memory content, based on the memory descriptions, using a computerized text-analysis method and a qualitative thematic analysis. The study focuses exclusively on spontaneous (contrary to voluntarily retrieved) memories, as these are typically the type that best describe MEAM experiences in everyday life (El Haj et al., 2012; Jakubowski & Ghosh, 2019). To this end, participants were asked to listen to a personalized music stimulus, without any further instructions, and to then describe and rate their eventual memories. We hypothesized that, compared to controls, depressed participants would retrieve (1) more negative MEAMs, and would experience (2) more negative induced affect. In addition, we explored the content of these memories, based on the participants’ qualitative descriptions. Finally, we explored 2Music & Science the time-period of the MEAMs, defined as age of participant during the event. Method Participants Participants were recruited via two advertisements targeting individuals with high levels of depression (defined as individuals with a BDI-II score 14, indicating mild, moderate and/or severe depression) and controls (individuals with a BDI-II score < 14, indicating minimal depression, and no diagnosis of a psychiatric disorder). These were distributed to healthcare professionals and were posted at the campus of Uppsala University and on the Internet (via social media). Participation was voluntary and anonymous and did not offer any monetary compensation; psychology students could however receive course points for participating. Seventy-three individuals applied via the registration form (see Procedure) to participate in the study. From these, 11 participants reported having a diagnosis of depression, but their BDI-II scores were sub-threshold, indicating no depression. These individuals were excluded, as they did not fit the inclusion criteria for either the depressed or the control group. The remaining 62 participants were contacted via email with the weblink to the study. From these, 23 did not submit their responses. The final sample thus consisted of 39 participants (Swedish nationality; 7 males; age: 18–55 years, M¼29.87, SD ¼10.35). Eighteen participants (1 male) formed the depressed group, with average age M¼ 28.52 years (SD ¼9.34) and a mean BDI-II score of M¼ 32.44, which corresponds to ‘severe’ depression (SD ¼9.33). Fifteen of the depressed participants had a diagnosis and 13 were on psychotropic medication and/or in psychotherapy. The remaining 21 participants (6 males) formed the control group (age: M¼31.44, SD ¼11.50; BDI-II scores: M¼4.86, SD ¼4.14). The two groups did not differ significantly in terms of gender (w 2 (1) ¼3.49, p¼.06) or age (t(37) ¼-.88, p¼.39). Six participants from the control group and seven from the depressed reportedly played a musical instrument, while five control and two depressed participants reported that they had received musical education. Groups did not differ significantly with regards to either musical instrument (w 2 (1) ¼.46, p¼.50) or musical education (w 2 (1) ¼1.06, p¼.30). Musical Compilation Stimulus To maximize the probability of MEAM evocation and to create a balance between ecologically valid and experimentally controlled stimuli, a combination of both experimenterselected music (cf. Belfi et al., 2016; Janata et al., 2007; Schulkind et al., 1999) and personal music (cf. El Haj et al., 2012) was used. An individualized set of music pieces was thus assembled for each participant, including 5–10 personal (participants’ favourite music, which they provided during the registration) and 20 experimental (popular ‘hits’ from participants’ youth, that is, the period when they were approximately 10–25 years old, which corresponds to the time when the ‘reminiscence bump’ occurs; Conway & Holmes, 2005) pieces. The participants in the current sample covered a wide age range (18–55) and were thus distributed across four age groups (i.e. 18–25, 26–35, 36–45, 46–55 years old). Ten of the most popular ‘hits’ from five eras were selected: 1970s, 1980s, 1990s, 2000s, 2010s. Popular hits represented pieces that were high on Swedish billboards, according to the data from Swedish websites such as ‘Sverige topp listan’ and ‘Sveriges radio’. For each participant (and corresponding age group) music from the two eras corresponding to their youth was selected. For example, participants aged 18–25 listened to popular pieces from the 2000s and 2010s, whereas participants aged 36–45 listened to pieces from the 1980s and 1990s. Therefore, for each participant (and corresponding age group) there was a set of 20 pieces from their youth. In addition to these, each individualized stimuli set also featured 5–10 personal pieces, which participants provided during their registration (see Procedure). The goal of the task was to maximize the probability of participants retrieving spontaneous (i.e. involuntary) memories. It was thus important that participants listened to a sufficient number of pieces, while still remaining unaware that their memories would be measured, by avoiding the repetition of memory questions after each stimulus. To achieve this, 10 pieces (5 experimental and 5 personal) were drawn from each participant’s individualized stimuli set, segmented into 30-sec fragments, and combined into a single compilation stimulus. Measures Depression. The Beck Depression Inventory-II (BDI-II; Beck et al., 1996) was administered during registration for measuring depression. The BDI-II is a widely used instrument for measuring level of depression and has been shown to demonstrate good internal consistency reliability and test-retest reliability (Arnau et al., 2001). In the present sample, Cronbach’s alpha reliability was a¼.97, indicating excellent internal consistency reliability. Self-report. The valence of memory and of induced emotion were measured with one item each, asking: ‘Is this memory positive or negative?’ and ‘How does this memory make you feel?’ respectively. These were rated on a 5-point scale each, ranging from 0 (very negative) to 4 (very positive). Participants were also asked how old they were when the event described in the memory took place (analysed as period) with an open-ended question. Sakka and Saarikallio 3 Procedure All data were collected online. During registration, participants received information about the study. After providing informed consent, they submitted background information, a selection of 5–10 pieces of their all-time favourite music (defined as ‘pieces that have stuck with them over the years, from childhood until today, which have an important meaning for them and which they have listened to often’ 1 ), as well as one piece that always makes them feel good. 2 Finally, they completed the BDI-II depression test. The study was approved by the Swedish Ethical Review Authority and participation was voluntary and anonymous. Experimental Task. People who registered their interest in participating received an email with a weblink to the study together with instructions, requesting them to choose a convenient time when they would be able to sit alone and undisturbed at their personal computer for approximately 30 min to complete the music-listening experiment. Once they were directed to the study and after providing informed consent, participants were instructed to listen to the music by clicking on a link. Because the objective was to measure spontaneous memories, it was important that participants were not aware that their memories were being measured. Thus, the instructions did not reveal any further explanation at this point. After listening to the music, participants were asked if the music evoked any memory of an event from their lives. If they answered ‘yes’, they were given 5 min to write down the memory with as much detail as possible (cf. El Haj et al., 2012). In case the music evoked more than one memory, the instructions specified that participants should describe the one they remembered the best. Following their memory description, participants responded to the self-report items. Data Treatment The self-report items were statistically analysed, and ratings were compared between the two participant groups. The memory valence and induced emotion valence data are ordinal (5-point Likert-type scales) and were thus analysed with the non-parametric Mann-Whitney test. The period data (age of participant during event) were categorized into age groups, and between-group differences were analysed with Fisher’s exact test. The content of the memory descriptions was first analysed with the use of Linguistic Inquiry and Word Count (LIWC2015; Pennebaker et al., 2015), a widely used and validated computerized text analysis software (Tausczik & Pennebaker, 2010). LIWC codes words according to approximately 90 variables belonging to different categories, such as language and linguistic dimensions, psychological constructs and personal concern categories. This software is particularly useful for analysing verbal expression of emotion (Kahn et al., 2007) and has also been used in previous studies for measuring MEAM characteristics (e.g. Jakubowski & Ghosh, 2019; Janata et al., 2007). Because the content analysis in the present study was exploratory, we decided to analyse the memories based on LIWC variables that have been previously investigated in relation to MEAMs (e.g. Jakubowski & Ghosh, 2019; Janata et al., 2007), enabling the comparability of our findings. MEAMs were thus analysed according to (1) affective processes, (2) social processes, and (3) personal concerns. The memory descriptions were next analysed qualitatively following Braun and Clarke’s (2006) thematic analysis principles. The analysis was conducted by the first author with consultation on the procedure and on the interpretations by the second author and was performed in two phases: (1) data familiarization and generation of initial codes, and (2) identification, revision and definition of themes. The analysis employed an inductive, data-driven approach, as there were no specific theoretical hypotheses regarding memory content. In order to avoid researcher bias, the first phase of the analysis was performed simultaneously for all participants so that the researcher was blind to participant group (depressed versus controls). The generation of initial codes consisted of detecting codes for (1) content and (2) emotional terms. The coding focused on ‘semantic’ coding, although in certain cases codes were constructed to give an abstract representation of an underlying phenomenon. For instance, a memory description with verbatim content ‘it felt like I had taken one step further in life somehow’ was given the code ‘personal growth’. The data were then categorized according to participant group for the second phase of the analysis, and the codes for each group were organized into higher-order themes, with the help of thematic mind maps (Braun & Clarke, 2006). Results As the task measured spontaneous memories, naturally, some participants (23%) did not experience a MEAM. The analyses below are therefore based on the data from the 30 participants who did retrieve a memory with the music (Depressed group: n¼15, including 1 male, mean age M¼31.47, SD ¼12.43; BDI-II score M¼32.27, SD ¼10.17; Control group: n¼15, 4 males, mean age M¼26.13, SD ¼7.02; mean BDI-II score M¼6.00, SD ¼3.87). Quantitative Analyses Memory Valence. Figure 1a displays the distribution of memory valence per participant group, and in particular the frequency in percentage of memories for each valence rating (with 0 indicating ‘very negative’ and 4 indicating ‘very positive’). As can be seen, depressed individuals retrieved memories across the valence spectrum, while controls’ memories were skewed towards positive valence. The between-group difference in median valence scores 4Music & Science can be seen in the boxplot in Figure 1b. This difference was statistically tested with a Mann-Whitney test which revealed a significant difference, with MEAMs significantly more negative for depressed (Mdn ¼2.00, M¼ 1.93, SD ¼1.53) compared to controls (Mdn ¼4.00, M¼3.60, SD ¼.63), U¼44.50, Z¼-2.99, p¼.001, r¼-.55, indicating a large effect (Cohen, 1992). Valence of Induced Emotion. The valence of induced emotion was significantly correlated with the valence of the memory (Spearman’s rank-order correlation r S (28) ¼.95, p< .001, indicating a large effect size; Cohen, 1992). The distribution of induced valence scores per participant group and the between-group comparison of median scores can be seen in Figures 2a and 2b respectively. As was in the case of memory valence, depressed participants’ induced valence covered the whole range of scores in comparison to the controls’, which were predominately positive. A Mann- Whitney test showed that depressed participants reported feeling significantly more negative (Mdn ¼1.00, M¼ 1.73, SD ¼1.62) compared to controls (Mdn ¼4.00, M¼3.40, SD ¼.82), U¼51.50, Z¼-2.65, p¼.002, r¼-.48, a medium towards large effect (Cohen, 1992). Period of Memory. Participants were also asked how old they were during the event described in their memory. Figure 1a. Frequency in percentage of memories for each valence rating split by participant group (0: very negative – 4: very positive) Figure 1b. Boxplot of memory valence scores split by participant group (0: very negative – 4: very positive) Figure 2a. Frequency in percentage of induced affect for each valence rating split by participant group (0: very negative – 4: very positive) Figure 2b. Boxplot of induced valence scores split by participant group (0: very negative – 4: very positive) Sakka and Saarikallio 5 Memories were classified into three memory period categories: (1) childhood (younger than 13 years); (2) adolescence (13–18 years); and (3) adulthood (older than 18 years). Table 1 represents the frequencies of retrieved memories in each category for each participant group and for the total sample. As can be seen, over the whole sample, memories were roughly equally distributed across the three periods. However, when examining each group separately, we can see that depressed participants retrieved mostly childhood (46.67%) and least adulthood (20.00%) memories, while controls retrieved least childhood memories (13.33%), but recalled approximately equal number of adolescent and adulthood memories (46.67%and 40.00% respectively). The association between period and group was not significant (Fisher’s Exact Test p¼.21, Cramer’s V¼.37, indicating a large effect size [Cohen, 1988]), indicating that there was no difference in memory period between the two participant groups. Content Analysis with LIWC The memory descriptions were first analysed with LIWC2015. Over the whole sample, MEAM descriptions were on average 96 words long (range: 9 – 295, SD ¼ 73.56). Data were analysed using the LIWC internal dictionary 2015, which included 93%of the words contained in the data. LIWC codes words according to psychologically relevant categories, such as affective or social processes. Here, the MEAMs were analysed in relation to three main categories, each including several subcategories: (1) affective processes, (2) social processes, and (3) personal concerns. Table 2 presents the mean percentage of words in each category, both for the whole participant sample and for each group separately. With regards to the main categories, over the whole sample, 4.25%of words were related to affective processes and 9.63%to social processes. (LIWC does not provide a percentage for the main category ‘personal concerns’.) Regarding subcategories, the ‘personal concerns’ subcategory ‘leisure’ (4.57%) was evident in MEAM descriptions in relatively high percentages. Given the particular focus of this study on affective content, participants’ self-report ratings of MEAM valence were correlated with the LIWC subcategories ‘positive emotions’ and ‘negative emotions’. ‘Negative emotions’ was significantly correlated with ‘MEAM valence’ in the expected (negative) direction, r¼-.58, p¼.001, indicating a large effect size (Cohen, 1992). Though not statistically significant, the correlation between ‘positive emotions’ and ‘MEAM valence’ was also in the expected (positive) direction and represented a medium effect size (Cohen, 1992), r¼.31, p¼.096. While depressed participants’ MEAMs contained fewer positive and more negative words compared to controls’ memories, these differences were not statistically significant (positive words: t(28) ¼1.95, p¼ .061, Cohen’s d¼.71, indicating a medium-large effect size [Cohen, 1992]; negative words: t(28) ¼-1.83, p¼ .077, Cohen’s d¼.67, a medium-large effect size [Cohen, 1992]). T-tests comparing the two groups on the remaining categories revealed no statistically significant differences (ps > .05). Qualitative Thematic Analysis Themes in Depressed Participants’ Memories. After the familiarization and generation of initial codes, the codes for each group were organized into higher-order themes. Figure 3 displays a thematic map, based on the initial codes for the depressed participants’ memories. Three first-level themes were derived, each containing a number of subthemes: (1) ‘personal’, including two subthemes, (1a) ‘mental states’ and (1b) ‘emotion regulation’; (2) ‘relationships’, including (2a) ‘love’ (loving relationships), (2b) ‘dysfunctional’ (relationships), and (2c) ‘loss’; and (3) ‘activities’, including two subthemes, namely (3a) ‘music’ (musical activities) and (3b) ‘music as background’ (to other activities). Table 1. Frequencies and percentages of retrieved memories in terms of period (per participant group and for the whole sample). Participants Depressed Controls Total sample Memory category F%F% F % Period Childhood 7 46.67 2 13.33 9 30.00 Adolescence 5 33.33 7 46.67 12 40.00 Adulthood 3 20.00 6 40.00 9 30.00 Table 2. Mean percentage of words classified in LIWC categories, presented by group and for the total sample. Participant group Category Depressed Mean (SD) Control Mean (SD) Total sample Mean (SD) Affective processes 4.18 (2.96) 4.32 (3.10) 4.25 (2.98) Positive emotions 1.91 (1.62) 3.60 (2.94) 2.75 (2.48) Negative emotions 2.14 (2.50) 0.72 (1.66) 1.43 (2.21) Social processes 11.90 (5.54) 7.37 (6.14) 9.63 (6.19) Family 2.87 (5.57) 0.33 (0.88) 1.60 (4.12) Friends 0.40 (.77) 0.53 (0.90) 0.47 (0.82) Personal concerns Work 0.78 (1.30) 1.60 (2.91) 1.19 (2.25) Leisure 4.37 (2.96) 4.76 (3.25) 4.57 (3.06) Home 1.41 (1.48) 1.25 (2.15) 1.33 (1.82) Money 0.17 (0.41) 0.63 (1.90) 0.40 (1.37) Religion 0.03 (0.13) 0.00 (0.00) 0.02 (0.09) Death 0.74 (2.87) 0.00 (0.00) 0.37 (2.03) LIWC: Linguistic Inquiry and Word Count. 6Music & Science Personal. A number of participants reported that the music reminded them of a particular mental state. One participant reported that the music is connected to an experience of personal growth. For other participants, the music brought back memories of times of mental health struggles, anxiety and loneliness. One memory refers to an incident of a panic attack. In relation to difficult mental states, a common theme in the data was the memory of how music had functioned at that time as a medium for emotion regulation and coping. Here participants refer to music being ‘one’s best and only friend’ in lonely times, feelings of being understood by music, feeling soothed by music, and music being a medium for expressing emotions and thoughts. Relationships. Besides themes of personal experiences, there were several memories referring to relationships. Some of these referred to loving relationships, such as the participant who remembered listening to music with their father and feeling a ‘sense of togetherness and love’, or the participant who recalled a time when they were filled with a ‘sense of overpowering love’ for their siblings. There were also reports of dysfunctional relationships, such as the memory of being sexually assaulted or betrayed by a loved one. A recurring code within this theme was bullying, with three participants referring to memories of being bullied at school. The third subcategory in relationships contains memories of loss. Here, one participant refers to missing their stepfather, two participants refer to the end of a romantic relationship, and one describes the memory of the death of their grandfather. Activities. ‘Activities’ is the final and least prominent theme and contains memories of musical activities (going to a concert, listening to music with dad), and memories of music as background to other activities, such as travelling or watching a movie. Figure 3. Thematic map of the depressed participants’ memory content codes. First-level themes are marked with bold capital letters. Subthemes are marked with italic capital letters. Content codes are marked with lowercase letters. Marked with dark text on light background are content codes belonging to negative memories, as rated by participants. Sakka and Saarikallio 7 Emotional terms. The quantitative analysis revealed that the main difference between depressed and controls was in the occurrence of negative memories. Approximately half of depressed participants’ memories but none of controls’ were rated as negative (0: very negative or 1: negative), while 60%of memories induced a negative emotion in depressed participants, in comparison to one memory (6%) in the control group. We were therefore interested in further investigating the content of the negative memories. The codes belonging to negative memories are marked with dark text in the thematic map (Figure 3). As can be seen, there is a clear distinction of negative valence within different themes: most of the memories relating to ‘personal’ experiences (such as mental states and emotion regulation) were negative memories. As expected, memories of dysfunctional relationships and loss were negative, but not memories of loving relationships. Finally, memories related to activities were not negative. The emotional terms used in the negative memories were: missing (father/father), anxiety, loneliness, feeling horrible, love (for music/romantic), shame, crying, feeling life was over, serious, sad, and strong feeling. The emotional terms used in the remaining memories were: content, happy, sense of togetherness, love, feels fun, overpowering love, happiness, special feeling, crying (from love). Themes in Control Participants’ Memories. A thematic map for the control participants’ memory content is shown in Figure 4. As can be seen, the first-level themes identified were similar to those of depressed participants, and were namely (1) ‘activities’, (2) ‘personal’, and (3) ‘relationships’. Contrary to the depressed, though, the most prominent theme was ‘activities’, which includes the subthemes of (1a) ‘music’ (musical activities, such as making music at home, singing and dancing, being at a concert) and (1b) ‘music as background’ (to other activities, such as working out, travelling, planning a school performance). The ‘personal’ theme includes two subthemes, namely (2a) ‘emotional’ and (2b) ‘achievements’. Two participants remembered events related to personal achievements, namely the memory of winning a competition and a memory of carrying out a successful speech at Figure 4. Thematic map of the control participants’ memory content codes. First-level themes are marked with bold capital letters. Subthemes are marked with italic capital letters. Content codes are marked with lowercase letters. 8Music & Science Taylor,G.J.,Bagby,R.M.,&Parker,J.D.A.(1991).The alexithymia construct. Psychosomatics,32, 153–164. Thomson, C. J., Reece, J. E., & Di Benedetto, M. (2014). The relationship between music-related mood regulation and psychopathology in young people. Musicae Scientiae,18(2), 150– 165. https://doi.org/10.1177/1029864914521422 Tran, T. B., Hertel, P. T., & Joormann, J. (2011). Cognitive bias modification: Induced interpretive biases affect memory. Emotion, 11(1), 145–152. https://doi.org/10.1037/a0021754 Tunnard, C., Rane, L. J., Wooderson, S. C., Markopoulou, K., Poon, L.,Fekadu, A., Juruena, M.,& Cleare, A.J. (2014). The impactof childhood adversity on suicidality and clinical course in treatment-resistant depression. Journal of Affective Disorders, 152–154, 122–130. https://doi.org/10.1016/j.jad.2013.06.037 Vasileiou, K., Barnett, J., Thorpe, S., & Young, T. (2018). Characterising and justifying sample size sufficiency in interviewbased studies: Systematic analysis of qualitative health research over a 15-year period. BMC Medical Research Methodology, 18(1), 148. https://doi.org/10.1186/s12874-018-0594-7 Werner-Seidler, A., & Moulds, M. L. (2011). Autobiographical memory characteristics in depression vulnerability: Formerly depressed individuals recall less vivid positive memories. Cognition & Emotion,25(6), 1087–1103. https://doi.org/10. 1080/02699931.2010.531007 Wilhelm, K., Gillis, I., Schubert, E., & Whittle, E. L. (2013). On a blue note: Depressed peoples’ reasons for listening to music. Music and Medicine,5(2), 76–83. https://doi.org/10.1177/ 1943862113482143 Williams, A. D., & Moulds, M. L. (2007). An investigation of the cognitive and experiential features of intrusive memories in depression. Memory,15(8), 912–920. https://doi.org/10.1080/ 09658210701508369 Witheridge, K. S., Cabral, C. M., & Rector, N. A. (2010). Examining autobiographical memory content in patients with depression and anxiety disorders. Cognitive Behaviour Therapy,39(4), 302–310. https://doi.org/10.1080/16506073.2010.520730 World Health Organization (WHO). (2017). Depression (Fact sheet). http://www.who.int/mediacentre/factsheets/fs369/en/ Sakka and Saarikallio 15