572795
research-article2015
IJOXXX10.1177/0306624X15572795International Journal of Offender Therapy and Comparative CriminologyChen et al.
Article
Randomized Trial of Group Music Therapy With Chinese Prisoners: Impact on Anxiety, Depression, and Self-Esteem
International Journal of Offender Therapy and Comparative Criminology 1–18 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0306624X15572795 ijo.sagepub.com
Xi-Jing Chen1, Niels Hannibal1, and Christian Gold2
Abstract This study investigated the effects of group music therapy on improving anxiety, depression, and self-esteem in Chinese prisoners. Two-hundred male prisoners were randomly assigned to music therapy (n = 100) or standard care (n = 100). The music therapy had 20 sessions of group therapy compared with standard care. Anxiety (State and Trait Anxiety Inventory [STAI]), depression (Beck Depression Inventory [BDI]), and self-esteem (Texas Social Behavior Inventory [TSBI], Rosenberg Self-Esteem Inventory [RSI]) were measured by standardized scales at baseline, mid-program, and post-program. Data were analyzed based on the intention to treat principle. Compared with standard care, anxiety and depression in the music therapy condition decreased significantly at mid-test and post-test; self-esteem improved significantly at mid-test (TSBI) and at post-test (TSBI, RSI). Improvements were greater in younger participants (STAI-Trait, RSI) and/or in those with a lower level of education (STAIState, STAI-Trait). Group music therapy seems to be effective in improving anxiety, depression, and self-esteem and was shown to be most beneficial for prisoners of younger age or with lower education level. Keywords group music therapy, prisoners, anxiety, depression, self-esteem
Introduction The high prevalence of mental health problems in prisons has become a global problem (Bureau of Justice Statistics, 2006; Stewart, 2008). Imprisonment has been found
1Aalborg 2Uni
University, Denmark Research, Bergen, Norway
Corresponding Author: Xi-Jing Chen, Fu Yuan Xiao Qu 10-3-601, Da Xing district, Beijing, China 102628. Email: [email protected]
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to negatively influence prisoners’ psychological well-being by disconnecting them from family and the outside world (Picken, 2012). In recent decades, results from prison surveys in China (Fu et al., 2012; Qian, 2001; Zhang, Wang, & Yang, 2007) have shown high rates (53%-80%) of Chinese prisoners suffering from mental health problems. In addition to other common mental health problems among prisoners, several studies (Unver, Yuce, Bayram, & Bilgel, 2013; Værøy, 2011) found the high prevalence and levels of anxiety and depression in prisoners are thought to be related to histories of domestic violence and substance abuse. Furthermore, affective problems may increase the risks of suicide and self-harm, and influence the development of psychosis (Hartley, Barrowclough, & Haddock, 2013; Unver et al., 2013). Moreover, level of self-esteem seems to play a role in prisoners’ experience of anxiety and depression. Castellano and Soderstrom (1997) suggested that low self-esteem in prisoners is often related to high anxiety and depression. This co-occurrence is likely to result in a seriously compromised state of mental health in prisoners (Gullone, Jones, & Cummins, 2000). The close relationship between self-esteem and emotions needs to be taken into consideration in prisoners’ mental health treatments and correctional programs for promoting their overall mental health well-being and correcting related inappropriate behaviors. The rehabilitation of offenders in correctional systems usually involves criminogenic and mental health domains. A variety of interventions and programs for diverse offender populations which are typically group programs based on risk–need–responsivity (RNR) principles have been applied mainly focusing on reducing the risk of criminality, and several therapy models (e.g., cognitive behavioral therapy, family therapy, multisystemic therapy, group counselling) have proved to be effective (Jolliffe & Farrington, 2007; Lipsey & Cullen, 2007). The variability of the intervention effects is linked with the types of the intervention, therapy intensity, quality of implementation, and types of offenders. However, there are some studies focusing on improving offenders’ mental health issues, which may or may not be related to offending behavior (Leigh-Hunt & Perry, 2014). In the decades of music therapy’s application in correctional systems, various music therapy approaches based on active music therapy (e.g., improvisation, song writing, performing music) or receptive music therapy (e.g., music imagery, music relaxation) have been applied to help offenders improve mental health in terms of mood states, empathy, social relationships, connections with reality (Chambers, 2008; Compton Dickinson & Gahir, 2013; O’Grady, 2011; Thaut, 1989). In receptive music therapy, the client focuses on perceiving and experiencing music; in active music therapy, the client is actively involved in the process of music creation. The distinguishing features of these two music therapy modalities may each contribute to meet the client’s personal preference and various therapeutic needs at different therapy stages. Combining the two modalities may therefore be advantageous. The psychological and neurological influences of music on mental health are well documented in the research literature (Blood & Zatorre, 2001; Lin et al., 2011). Brain research has shown that music can elicit various emotional and physiological responses based on the area of the brain in which it is processed (Koelsch, Fritz, Cramon, Müller,
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& Friederici, 2006; Menon & Levitin, 2005). As a “language of emotion” (Juslin & Sloboda, 2010), music not only influences people’s emotional experiences but also provides a means for people to explore and express emotions, build up relationships, and experience autonomy, which are necessary pre-requisites for mental health improvement. With respect to its application in music therapy for offenders, music may support offenders to identify, explore, and express emotions in a positive way (Loth, 1994); it also provides multimodal experiences, including images, sensations, and feelings to facilitate offenders’ action-oriented forms of musical expression instead of verbal discussion (Nolan, 1983). Studies show that music therapy can be beneficial for prisoners, especially for those with restricted ability of emotional expression caused by the prison setting or the individual’s own limited verbal skills (Erickson & Young, 2010); as well as for those with negative emotions and low motivation who are unable to benefit sufficiently from psychotherapy (Gold, Mössler, et al., 2013; Howells, 2006). Research has shown that music therapy is effective in improving depression (Maratos, Gold, Wang, & Crawford, 2008), psychiatric symptoms, and psychosocial functioning (Erkkilä et al., 2011; Ulrich, Houtmans, & Gold, 2007). Several qualitative studies also suggested the potential benefits of music therapy for offenders (Chambers, 2008; Compton Dickinson, Odell-Miller, & Adlam, 2013; Daveson & Edwards, 2001; Tuastad & O’Grady, 2013). Yet, only a few controlled trials have explored the effects of music therapy on the mental health and psychosocial functioning of people in correctional services, either with or without diagnosed mental disorder (Gold, Assmus, et al., 2013; Hakvoort, Bogaerts, Thaut, & Spreen, 2013; Johnson, 1981; Thaut, 1989). Most of these studies contained a small sample size (N = 13-50) with a low test power or no calculation of test power. One study utilized only non-standardized measures (Thaut, 1989). For one study with a larger sample size (N = 113) and more rigorous study design (a randomized-controlled trial, music therapy vs. standard care, analysis based on intention to treat principle, sufficient test power), the result was inconclusive because of the high rate of dropout (Gold, Assmus, et al., 2013). The effects of music therapy on mental health in prisoners therefore remain unclear.
Aims of the Study This study aimed to investigate the effects of group music therapy on reducing anxiety and depression, and improving self-esteem in Chinese prisoners. The research question was the following: Can music therapy contribute to the mental health improvement of prisoners in terms of anxiety, depression, and self-esteem? Study hypothesis was formulated as follows: Music therapy can alleviate anxiety and depression of prisoners as well as improve their self-esteem.
Material and Methods Participants We planned to include 192 adult male inmates in one prison in Beijing, China (see the full protocol for this study; Chen, Hannibal, Xu, & Gold, 2013). Inclusion criteria
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were as follows: (a) anxiety score ≥ 49 on the State and Trait Anxiety Inventory (STAI: STAI-State or STAI-Trait [Chinese version]; that is, 1 SD above the population mean, representing mild anxiety; Spielberger, Gorsuch, & Lushene, 1970; Wang, Wang, & Ma, 1999; Zheng, Shu, Zhang, & Huang, 1993); or (b) depression score ≥ 14 on the Beck Depression Inventory (BDI [Chinese version]; that is, mild depression; Wang et al., 1999), see section “Outcome Measures” for more details on these instruments; and (c) a remaining prison term ≥ 6 months from the date of recruitment. Exclusion criteria were as follows: (a) a diagnosed severe physical disease or a psychotic disorder, (b) an intelligence quotient ≤ 69 (mild intellectual disability), or (c) unable to understand the questionnaires (as reported by the participant). A psychological counsellor gave the study recruitment information to prisoners using posters and announcements from the prison’s psychological education and counselling department. The psychological counsellor conducted measurements for all participants. More details of the flow of participants are provided in Figure 1. The Human Research Ethics Board of Aalborg University approved this study on March 20, 2012. In the absence of research ethics committee in the Chinese correctional system, there was no access to an ethical assessment from this prison. However, this study received an official administrative approval from the psychological education and counselling department in this prison after the evaluation of their expert committee. All participants signed an informed consent form to participate in the study. They were informed that they would be randomly allocated to take part in music therapy; people who were not chosen into music therapy group would receive group psychotherapy or music therapy after the study was completed. There were no incentives provided for participants and no consequences for not participating. The trial was registered (NCT01633125). A power calculation was conducted to determine test power. Assuming a medium effect size, we calculated that the planned sample size of 192 participants (24 groups with 8 participants each, up to 1 dropout per group) would have 87% power in a twotailed t test, or slightly less if some clustering occurred (Chen et al., 2013).
Randomization All eligible participants were individually randomized to two groups of equal size. One researcher (C.G.) who had no direct contact with the participants conducted a computer-generated randomization and kept this list concealed until a decision was made about inclusion.
Assessment The assessments were conducted before randomization (pre-test), after 10 sessions (mid-test), and after 20 sessions (post-test; see Figure. 1). The pre-test assessment score was also used to screen for eligibility. All assessments were self-reports. Participants delivered them to a psychological counsellor with extensive experience with prisoners, who was masked to the
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Assessed for eligibility (N = 263) Excluded (n = 63) Not meeting inclusion criteria (n = 63) Randomized (n = 200)
Allocated to group music therapy (n = 100) Received 10 sessions (n = 97) Received 6-8 sessions (n = 3)
Allocated to standard care only (n = 100)
Drop out Transferred to another prison (n = 3)
Drop out Transferred to another prison (n = 2) Illness (n = 1)
Mid-test (after 10 sessions)
Continue music therapy (n = 97) Received 20 sessions (n = 72) Received 15-19 sessions (n = 21)
Continue standard care (n = 97)
Drop out Transferred to another prison (n = 2) Reduced sentences (n = 2)
Drop out Transferred to another prison (n = 4) Lack of motivation (n = 1) Illness (n = 1)
Post-test (after 20 sessions)
Included in final analysis (n = 93)
Included in final analysis (n = 91)
Figure 1. Participants flowchart.
assignment of the participants and had to report if any instance of broken masking occurred. Participants in both groups were tested in the same room on the same day.
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Outcome Measures Anxiety was measured by the STAI. This measure consists of two similar subscales: STAI-State and STAI-Trait. Each scale encompasses 20 items measuring state anxiety or trait anxiety, respectively. Respondents are asked to rate themselves on each item on the basis of a 4-point Likert-type scale (1 = not at all, 4 = very much so [STAI-State]; 1 = almost never, 4 = almost always [STAI-Trait]). The STAI does not have a predefined cutoff. A higher score indicates a higher level of anxiety. Cronbach’s alpha was computed to examine the internal consistency of the STAI. It showed a high level of internal consistency with alpha coefficients of .849 and .848 for the two subscales separately. Depression was measured by the BDI and self-esteem was measured by the Rosenberg Self-Esteem Inventory (RSI [Chinese version]; Wang et al., 1999) and Texas Social Behavior Inventory (TSBI [Chinese version]; Wang et al., 1999). The BDI consists of a 21-question multiple-choice self-report scale. A higher score implies a higher level of depression. The cutoffs are as follows: 0 to 13: minimal depression; 14 to 19: mild depression; 20 to 28: moderate depression; and 29 to 63: severe depression (Beck, Steer, & Brown, 1996). Cronbach’s alpha coefficient for the BDI was .893. The RSI is a 10-item Likert-type scale used to assess global self-esteem. The answers are on 4-point scales (0 = strongly disagree, 3 = strongly agree). A higher score indicates a higher level of self-esteem. Scores below 15 suggest low self-esteem. The TSBI consists of a 5-point Likert-type scale with 32 items measuring social selfesteem in terms of perceived competence and confidence in social situations (1 = not at all true of me, 5 = very true of me). A higher score indicates a higher level of selfesteem. Cronbach’s alpha coefficients were .609 and .794 for the RSI and TSBI respectively. Coefficient alpha is influenced by the number of items, item correlations, and dimensionality (Cortina, 1993). Given the various characteristics of four measures and their corresponding standards, all measures showed an acceptable to high level of internal consistency. All scales in the Chinese version have been validated with Chinese people (Wang et al., 1999).
Interventions Standard care. The control group received standard care but no music therapy during the study. Standard care in this prison included medical care, monthly mandatory mental health education, and psychological/psychotherapeutic care on a volunteer basis. The contents of mental health lessons contained trainings of mental health knowledge and behavioral coping skills, and each lesson lasted for 50 minutes. The psychological/psychotherapeutic care was provided by a counsellor for the participants who required an individual consultation. Beside these, the prison routine management for all prisoners included four hours of mandatory labor at every working day and mandatory education and exams. Of all the participants who received either standard care or treatment, only four participants received one to four extra sessions of individual psychological consultations during the study.
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Group music therapy. Participants randomized to music therapy received 20 sessions of group music therapy twice weekly. Each session lasted for 90 minutes. The choice of intensity and duration for the intervention were based on the therapist’s clinical experience, prison management, and the inmates’ average length of sentence, as well as previous findings on dose–effect relationship in music therapy (Gold, Solli, Krüger, & Lie, 2009). A more detailed discussion about the intervention choices is provided in the study protocol (Chen et al., 2013). The intervention took place in an activity room in the prison. The equipment for music therapy included one stereo, one electronic piano, two guitars, one set of hand glockenspiel, and percussion instruments such as African drums, cymbals, tambourines, and xylophones. During therapy, a prison guard sat in the room outside the group circle to ensure the music therapist’s safety. Three music therapy methods—music and imagery, improvisation, and song writing—were introduced to the group in the first three sessions. The following is a brief introduction of the three methods. Music and imagery is a method adapted from the Bonny Method of Guided Imagery and Music (BMGIM; Paik-Maier, 2010). It was introduced in the first session. In the prelude, the therapist gathered clients’ information and helped group members to find a common issue (i.e., emotion, self-exploration, family) through discussion or arts experience (i.e., improvisation, dance movement, painting). Then, the therapist selected one music piece that matched the clients’ current state and issue to induct their music imagery journey. After a short time (approximately 5 min) of imagery experience, the clients were asked to express their imagery through painting while listening to the same music repetitively. In the postlude, the therapists and group members explored the imagery and feelings together through discussion or arts activities. Improvisation, also referred to as clinical improvisation, is “the use of musical improvisation in an environment of trust and support established to meet the needs of clients” (Wigram, 2004, p. 37). In the second session, group musical improvisation activities including vocal and/or instrumental improvisation in solo, duet, dialogue, trio, or group were introduced. The members experienced free improvisation with no structure or thematic improvisation based on their capability and needs. Song writing is a method where the music therapist writes “songs for and with clients to address various therapeutic goals” (Baker & Wigram, 2005, p. 13). Structured and/or unstructured song writing techniques were applied in the third session, such as replacing blanked keywords with new lyrics in a pre-composed song, replacing whole lyrics for a song, creating new melody for the existing lyrics, or creating a new melody and lyrics. Each session after the first three introductory sessions started with a discussion about thoughts, feelings, personal issues, or incidents in prison. Then group members and the therapist together selected one method described above to continue the therapeutic process. The researchers developed a music therapy protocol for this study. This protocol lists several common group topics (e.g., friendship, trust, empathy, family, interpersonal conflict, emotional problems) and describes several music therapy activities
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under each topic. Each activity description includes therapeutic objectives, instruments and equipments, procedures of implementation, and possible topics for discussion. The activities are structured or unstructured, and a variety of music imagery, improvisation, and song writing techniques are utilized. The full manual is available from the authors and will be published separately. The therapist (X.J.C.) received biweekly supervision with her clinical supervisor to ensure the quality of the therapy and to reflect on relevant issues for her own safety. The group members were encouraged to keep a diary during the study. However, only one participant shared it with the therapist.
Statistical Analyses Statistical analyses were conducted with SPSS version 17.0 and R version 2.15.0. All statistical tests were two-tailed at the 5% significant level. After randomization, the data of all participants were included for analysis, regardless of whether they stopped the therapy early (intention to treat principle). Before the statistical analyses, all dependent variables were examined for normal distribution. All dependent variables were normally distributed, and therefore parametric procedures were used for data analysis. Because the level of missing data was below 5%, no strategy was used to analyze them. Descriptive analyses were conducted for demographic information, anxiety, depression, and self-esteem to assess baseline comparability of both groups. Effects of music therapy were analyzed using t tests for independent samples. This is a simple but valid approach to analysis of adequately randomized-controlled studies because groups are compared directly to each other and baseline variables are assumed to be balanced (Gold, 2015; Moher et al., 2010). We also performed repeated-measures ANOVAs as an overall test and examined interaction effects between time and group (using Wilk’s lambda). In addition, two types of sensitivity analyses were conducted: (a) linear mixed-effects (LME) models taking into account potential clustering by department and batch as a random effect, using endpoint scores as above and (b) the same LMEs but using change from baseline. Furthermore, LMEs were also calculated to identify potential predictors of change, including age, years of education, crime type, and criminal record. The models included both main effects and interaction effects with treatment group, but only the interaction effects were of interest and are reported. In contrast to the study protocol (Chen et al., 2013), concomitant psychological interventions were not controlled for in the analyses, because only very few participants applied for psychological treatments.
Results Baseline Characteristics Of 263 male applicants who took part in the study in four batches from April 2012 to April 2013, a total of 200 (76%) participants were found eligible after the screening (Figure 1). They were randomized to two groups of equal size. Four batches of
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participants from different units, with 43 to 62 people in each batch, were enrolled and completed the intervention sequentially. Participants from one batch had no contact with other batches. In the music therapy group, 12 therapy groups were formed with each one consisting of 8 to 10 people. Participants’ age ranged from 18 to 57 (M = 35.5, SD = 9.95). They had 8 years of education on average (SD = 2.61). In all, 116 participants (58%) had more than 6 years of education and only 8 (4%) had more than 12 years of education. Half of the sample was currently imprisoned for the first time. The great majority (80%) were convicted for acts of physical injury or theft. The average sentence length was 13.02 months (SD = 2.02). No specific risk assessment was conducted. The groups were balanced on all variables at baseline, indicating successful randomization. The baseline comparison of demographic and clinical characteristics of participants in music therapy and standard care is provided in Table 1.
Characteristics of Music Therapy Of 240 sessions, improvisation was applied in 107 sessions (44.6%), music imagery in 90 (37.5%), and song writing in 43 (17.9%). In the music therapy group, 72% participants received 20 sessions of therapy, and 97% participants had more than 10 sessions. Very few participants received other psychotherapy (n = 4). The reasons for 16 dropout participants were as follows: being transferred to another prison (n = 11), physical illness (n = 2), lack of motivation (n = 1), and reduced sentences (n = 2; Figure 1). Outcome data were not available for those who dropped out.
Effects of Music Therapy Table 2 compares outcomes in each group, based on t tests. At mid-program, anxiety (STAI) and depression (BDI) scores were significantly lower (STAI-State: p = .006, d = 0.40; STAI-Trait: p = .001, d = 0.49; BDI: p < .001, d = 0.54) and self-esteem (TSBI) score was significantly higher (p = .011, d = 0.37) in music therapy than in standard care. At post-program, anxiety (STAI) and depression (BDI) scores were significantly lower (STAI-State: p < .001, d = 0.87; STAI-Trait: p < .001, d = 1.03; BDI: p < .001, d = 0.87) in music therapy; self-esteem (TSBI and RSI) scores were significantly higher in music therapy (RSI: p < .001, d = 0.51; TSBI: p = .001, d = 0.51) than in standard care. All effect sizes were larger in the post-program than in the mid-program; most effect sizes were from medium to large. In the post-program, large effect sizes were found for anxiety (STAI) and depression (BDI) scores, and medium effect sizes were found for self-esteem (RSI and TSBI) scores (Table 2). In the repeatedmeasures ANOVAs, all Time × Group interactions were significant (BDI: p < .001; RSI: p < .01; STAI-State: p < .001; STAI-Trait: p < .001; TSBI: p < .05). This confirmed the results from between-group tests reported above suggesting significant effects of music therapy compared with standard care. Clustering by department and batch did not appear to play an important role in this study, as the results of LMEs (not shown) were similar to those in the t tests, and all significant effects remained significant. The same was the case for the LMEs based on change scores.
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Table 1. Baseline Comparison of Demographic and Clinical Characteristics of Participants in Music Therapy and Standard Care.
Characteristic Categorical variables Criminal record First offence One prior offence More than one prior offence Crime type Physical injury Gambling Theft Others (including fraud, sexual harassment, illegal transaction) Continuous variables Age (years) Years of education Months of current sentence Test scores State and Trait Anxiety Inventory–State State and Trait Anxiety Inventory–Trait Beck Depression Inventory Rosenberg Self-Esteem Inventory Texas Social Behavior Inventory
Music therapy (n = 100)
Standard care (n = 100)
n (%)
n (%)
51 (51) 22 (22) 27 (27)
49 (49) 26 (26) 25 (25)
38 (38) 17 (17) 43 (43) 2 (2)
43 (43) 15 (15) 37 (37) 5 (5)
M (SD)
M (SD)
t (df)
p
35.29 (9.83) 8.50 (2.73) 13.21 (2.23)
35.75 (10.07) 8.13 (2.49) 12.83 (2.00)
−0.327(198) 1.00 (198) 1.271 (198)
.744 .319 .205
48.52 (9.67)
48.03 (9.95)
−0.353 (198)
.724
48.70 (8.98)
48.52 (10.12)
−0.133 (198)
.894
24.72 (10.18) 25.92 (4.11)
23.90 (11.11) 26.04 (3.65)
−0.544 (198) 0.218 (198)
.587 .827
97.30 (15.34)
97.56 (15.22)
−0.120 (198)
.904
Difference Chi-square (df)
0.450 (2)
2.169 (3)
p
.798
.538
We conducted further LMEs to examine the interaction effects of covariates (characteristics of the offenders, including age, years of education, crime type, and criminal record) with the effects of music therapy. The results (Table 3) indicated that age and educational level as predictors influenced the effects. Effects of music therapy on STAI-Trait scores were smaller in participants with older age (p < .05) at mid-test, but not at post-test. Participants with lower education showed greater improvement on anxiety (STAI-State and STAI-Trait) at post-test than those with higher education (p < .003; p < .001). In addition, music therapy indicated greater effects for younger participants (p = .02) on self-esteem (RSI) at post-test.
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Chen et al. Table 2. Differences in Outcome Scores Between Music Therapy and Standard Care in Mid-Test and Post-Test (Intention-to-Treat): Continuous Outcomes.
Outcome
Music therapy
Standard care
M (SD)
M (SD)
State and Trait Anxiety Inventory–State Mid-test 45.67 (11.29) 49.74 (9.11) Post-test 40.53 (8.74) 48.58 (9.86) State and Trait Anxiety Inventory–Trait Mid-test 45.56 (10.82) 50.10 (7.76) Post-test 40.58 (8.47) 49.09 (8.17) Beck Depression Inventory Mid-test 15.59 (11.66) 22.08 (12.23) Post-test 11.51 (7.78) 20.32 (12.47) Rosenberg Self-Esteem Inventory Mid-test 28.09 (5.01) 26.80 (4.84) Post-test 29.27 (4.25) 27.01 (4.60) Texas Social Behavior Inventory Mid-test 103.54 (17.55) 97.44 (15.42) Post-test 104.35 (13.62) 96.81 (16.00)
Test for difference
Effect size
t
p
d
2.763 5.870
.006*
research-article2015
IJOXXX10.1177/0306624X15572795International Journal of Offender Therapy and Comparative CriminologyChen et al.
Article
Randomized Trial of Group Music Therapy With Chinese Prisoners: Impact on Anxiety, Depression, and Self-Esteem
International Journal of Offender Therapy and Comparative Criminology 1–18 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0306624X15572795 ijo.sagepub.com
Xi-Jing Chen1, Niels Hannibal1, and Christian Gold2
Abstract This study investigated the effects of group music therapy on improving anxiety, depression, and self-esteem in Chinese prisoners. Two-hundred male prisoners were randomly assigned to music therapy (n = 100) or standard care (n = 100). The music therapy had 20 sessions of group therapy compared with standard care. Anxiety (State and Trait Anxiety Inventory [STAI]), depression (Beck Depression Inventory [BDI]), and self-esteem (Texas Social Behavior Inventory [TSBI], Rosenberg Self-Esteem Inventory [RSI]) were measured by standardized scales at baseline, mid-program, and post-program. Data were analyzed based on the intention to treat principle. Compared with standard care, anxiety and depression in the music therapy condition decreased significantly at mid-test and post-test; self-esteem improved significantly at mid-test (TSBI) and at post-test (TSBI, RSI). Improvements were greater in younger participants (STAI-Trait, RSI) and/or in those with a lower level of education (STAIState, STAI-Trait). Group music therapy seems to be effective in improving anxiety, depression, and self-esteem and was shown to be most beneficial for prisoners of younger age or with lower education level. Keywords group music therapy, prisoners, anxiety, depression, self-esteem
Introduction The high prevalence of mental health problems in prisons has become a global problem (Bureau of Justice Statistics, 2006; Stewart, 2008). Imprisonment has been found
1Aalborg 2Uni
University, Denmark Research, Bergen, Norway
Corresponding Author: Xi-Jing Chen, Fu Yuan Xiao Qu 10-3-601, Da Xing district, Beijing, China 102628. Email: [email protected]
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to negatively influence prisoners’ psychological well-being by disconnecting them from family and the outside world (Picken, 2012). In recent decades, results from prison surveys in China (Fu et al., 2012; Qian, 2001; Zhang, Wang, & Yang, 2007) have shown high rates (53%-80%) of Chinese prisoners suffering from mental health problems. In addition to other common mental health problems among prisoners, several studies (Unver, Yuce, Bayram, & Bilgel, 2013; Værøy, 2011) found the high prevalence and levels of anxiety and depression in prisoners are thought to be related to histories of domestic violence and substance abuse. Furthermore, affective problems may increase the risks of suicide and self-harm, and influence the development of psychosis (Hartley, Barrowclough, & Haddock, 2013; Unver et al., 2013). Moreover, level of self-esteem seems to play a role in prisoners’ experience of anxiety and depression. Castellano and Soderstrom (1997) suggested that low self-esteem in prisoners is often related to high anxiety and depression. This co-occurrence is likely to result in a seriously compromised state of mental health in prisoners (Gullone, Jones, & Cummins, 2000). The close relationship between self-esteem and emotions needs to be taken into consideration in prisoners’ mental health treatments and correctional programs for promoting their overall mental health well-being and correcting related inappropriate behaviors. The rehabilitation of offenders in correctional systems usually involves criminogenic and mental health domains. A variety of interventions and programs for diverse offender populations which are typically group programs based on risk–need–responsivity (RNR) principles have been applied mainly focusing on reducing the risk of criminality, and several therapy models (e.g., cognitive behavioral therapy, family therapy, multisystemic therapy, group counselling) have proved to be effective (Jolliffe & Farrington, 2007; Lipsey & Cullen, 2007). The variability of the intervention effects is linked with the types of the intervention, therapy intensity, quality of implementation, and types of offenders. However, there are some studies focusing on improving offenders’ mental health issues, which may or may not be related to offending behavior (Leigh-Hunt & Perry, 2014). In the decades of music therapy’s application in correctional systems, various music therapy approaches based on active music therapy (e.g., improvisation, song writing, performing music) or receptive music therapy (e.g., music imagery, music relaxation) have been applied to help offenders improve mental health in terms of mood states, empathy, social relationships, connections with reality (Chambers, 2008; Compton Dickinson & Gahir, 2013; O’Grady, 2011; Thaut, 1989). In receptive music therapy, the client focuses on perceiving and experiencing music; in active music therapy, the client is actively involved in the process of music creation. The distinguishing features of these two music therapy modalities may each contribute to meet the client’s personal preference and various therapeutic needs at different therapy stages. Combining the two modalities may therefore be advantageous. The psychological and neurological influences of music on mental health are well documented in the research literature (Blood & Zatorre, 2001; Lin et al., 2011). Brain research has shown that music can elicit various emotional and physiological responses based on the area of the brain in which it is processed (Koelsch, Fritz, Cramon, Müller,
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& Friederici, 2006; Menon & Levitin, 2005). As a “language of emotion” (Juslin & Sloboda, 2010), music not only influences people’s emotional experiences but also provides a means for people to explore and express emotions, build up relationships, and experience autonomy, which are necessary pre-requisites for mental health improvement. With respect to its application in music therapy for offenders, music may support offenders to identify, explore, and express emotions in a positive way (Loth, 1994); it also provides multimodal experiences, including images, sensations, and feelings to facilitate offenders’ action-oriented forms of musical expression instead of verbal discussion (Nolan, 1983). Studies show that music therapy can be beneficial for prisoners, especially for those with restricted ability of emotional expression caused by the prison setting or the individual’s own limited verbal skills (Erickson & Young, 2010); as well as for those with negative emotions and low motivation who are unable to benefit sufficiently from psychotherapy (Gold, Mössler, et al., 2013; Howells, 2006). Research has shown that music therapy is effective in improving depression (Maratos, Gold, Wang, & Crawford, 2008), psychiatric symptoms, and psychosocial functioning (Erkkilä et al., 2011; Ulrich, Houtmans, & Gold, 2007). Several qualitative studies also suggested the potential benefits of music therapy for offenders (Chambers, 2008; Compton Dickinson, Odell-Miller, & Adlam, 2013; Daveson & Edwards, 2001; Tuastad & O’Grady, 2013). Yet, only a few controlled trials have explored the effects of music therapy on the mental health and psychosocial functioning of people in correctional services, either with or without diagnosed mental disorder (Gold, Assmus, et al., 2013; Hakvoort, Bogaerts, Thaut, & Spreen, 2013; Johnson, 1981; Thaut, 1989). Most of these studies contained a small sample size (N = 13-50) with a low test power or no calculation of test power. One study utilized only non-standardized measures (Thaut, 1989). For one study with a larger sample size (N = 113) and more rigorous study design (a randomized-controlled trial, music therapy vs. standard care, analysis based on intention to treat principle, sufficient test power), the result was inconclusive because of the high rate of dropout (Gold, Assmus, et al., 2013). The effects of music therapy on mental health in prisoners therefore remain unclear.
Aims of the Study This study aimed to investigate the effects of group music therapy on reducing anxiety and depression, and improving self-esteem in Chinese prisoners. The research question was the following: Can music therapy contribute to the mental health improvement of prisoners in terms of anxiety, depression, and self-esteem? Study hypothesis was formulated as follows: Music therapy can alleviate anxiety and depression of prisoners as well as improve their self-esteem.
Material and Methods Participants We planned to include 192 adult male inmates in one prison in Beijing, China (see the full protocol for this study; Chen, Hannibal, Xu, & Gold, 2013). Inclusion criteria
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were as follows: (a) anxiety score ≥ 49 on the State and Trait Anxiety Inventory (STAI: STAI-State or STAI-Trait [Chinese version]; that is, 1 SD above the population mean, representing mild anxiety; Spielberger, Gorsuch, & Lushene, 1970; Wang, Wang, & Ma, 1999; Zheng, Shu, Zhang, & Huang, 1993); or (b) depression score ≥ 14 on the Beck Depression Inventory (BDI [Chinese version]; that is, mild depression; Wang et al., 1999), see section “Outcome Measures” for more details on these instruments; and (c) a remaining prison term ≥ 6 months from the date of recruitment. Exclusion criteria were as follows: (a) a diagnosed severe physical disease or a psychotic disorder, (b) an intelligence quotient ≤ 69 (mild intellectual disability), or (c) unable to understand the questionnaires (as reported by the participant). A psychological counsellor gave the study recruitment information to prisoners using posters and announcements from the prison’s psychological education and counselling department. The psychological counsellor conducted measurements for all participants. More details of the flow of participants are provided in Figure 1. The Human Research Ethics Board of Aalborg University approved this study on March 20, 2012. In the absence of research ethics committee in the Chinese correctional system, there was no access to an ethical assessment from this prison. However, this study received an official administrative approval from the psychological education and counselling department in this prison after the evaluation of their expert committee. All participants signed an informed consent form to participate in the study. They were informed that they would be randomly allocated to take part in music therapy; people who were not chosen into music therapy group would receive group psychotherapy or music therapy after the study was completed. There were no incentives provided for participants and no consequences for not participating. The trial was registered (NCT01633125). A power calculation was conducted to determine test power. Assuming a medium effect size, we calculated that the planned sample size of 192 participants (24 groups with 8 participants each, up to 1 dropout per group) would have 87% power in a twotailed t test, or slightly less if some clustering occurred (Chen et al., 2013).
Randomization All eligible participants were individually randomized to two groups of equal size. One researcher (C.G.) who had no direct contact with the participants conducted a computer-generated randomization and kept this list concealed until a decision was made about inclusion.
Assessment The assessments were conducted before randomization (pre-test), after 10 sessions (mid-test), and after 20 sessions (post-test; see Figure. 1). The pre-test assessment score was also used to screen for eligibility. All assessments were self-reports. Participants delivered them to a psychological counsellor with extensive experience with prisoners, who was masked to the
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Assessed for eligibility (N = 263) Excluded (n = 63) Not meeting inclusion criteria (n = 63) Randomized (n = 200)
Allocated to group music therapy (n = 100) Received 10 sessions (n = 97) Received 6-8 sessions (n = 3)
Allocated to standard care only (n = 100)
Drop out Transferred to another prison (n = 3)
Drop out Transferred to another prison (n = 2) Illness (n = 1)
Mid-test (after 10 sessions)
Continue music therapy (n = 97) Received 20 sessions (n = 72) Received 15-19 sessions (n = 21)
Continue standard care (n = 97)
Drop out Transferred to another prison (n = 2) Reduced sentences (n = 2)
Drop out Transferred to another prison (n = 4) Lack of motivation (n = 1) Illness (n = 1)
Post-test (after 20 sessions)
Included in final analysis (n = 93)
Included in final analysis (n = 91)
Figure 1. Participants flowchart.
assignment of the participants and had to report if any instance of broken masking occurred. Participants in both groups were tested in the same room on the same day.
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Outcome Measures Anxiety was measured by the STAI. This measure consists of two similar subscales: STAI-State and STAI-Trait. Each scale encompasses 20 items measuring state anxiety or trait anxiety, respectively. Respondents are asked to rate themselves on each item on the basis of a 4-point Likert-type scale (1 = not at all, 4 = very much so [STAI-State]; 1 = almost never, 4 = almost always [STAI-Trait]). The STAI does not have a predefined cutoff. A higher score indicates a higher level of anxiety. Cronbach’s alpha was computed to examine the internal consistency of the STAI. It showed a high level of internal consistency with alpha coefficients of .849 and .848 for the two subscales separately. Depression was measured by the BDI and self-esteem was measured by the Rosenberg Self-Esteem Inventory (RSI [Chinese version]; Wang et al., 1999) and Texas Social Behavior Inventory (TSBI [Chinese version]; Wang et al., 1999). The BDI consists of a 21-question multiple-choice self-report scale. A higher score implies a higher level of depression. The cutoffs are as follows: 0 to 13: minimal depression; 14 to 19: mild depression; 20 to 28: moderate depression; and 29 to 63: severe depression (Beck, Steer, & Brown, 1996). Cronbach’s alpha coefficient for the BDI was .893. The RSI is a 10-item Likert-type scale used to assess global self-esteem. The answers are on 4-point scales (0 = strongly disagree, 3 = strongly agree). A higher score indicates a higher level of self-esteem. Scores below 15 suggest low self-esteem. The TSBI consists of a 5-point Likert-type scale with 32 items measuring social selfesteem in terms of perceived competence and confidence in social situations (1 = not at all true of me, 5 = very true of me). A higher score indicates a higher level of selfesteem. Cronbach’s alpha coefficients were .609 and .794 for the RSI and TSBI respectively. Coefficient alpha is influenced by the number of items, item correlations, and dimensionality (Cortina, 1993). Given the various characteristics of four measures and their corresponding standards, all measures showed an acceptable to high level of internal consistency. All scales in the Chinese version have been validated with Chinese people (Wang et al., 1999).
Interventions Standard care. The control group received standard care but no music therapy during the study. Standard care in this prison included medical care, monthly mandatory mental health education, and psychological/psychotherapeutic care on a volunteer basis. The contents of mental health lessons contained trainings of mental health knowledge and behavioral coping skills, and each lesson lasted for 50 minutes. The psychological/psychotherapeutic care was provided by a counsellor for the participants who required an individual consultation. Beside these, the prison routine management for all prisoners included four hours of mandatory labor at every working day and mandatory education and exams. Of all the participants who received either standard care or treatment, only four participants received one to four extra sessions of individual psychological consultations during the study.
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Group music therapy. Participants randomized to music therapy received 20 sessions of group music therapy twice weekly. Each session lasted for 90 minutes. The choice of intensity and duration for the intervention were based on the therapist’s clinical experience, prison management, and the inmates’ average length of sentence, as well as previous findings on dose–effect relationship in music therapy (Gold, Solli, Krüger, & Lie, 2009). A more detailed discussion about the intervention choices is provided in the study protocol (Chen et al., 2013). The intervention took place in an activity room in the prison. The equipment for music therapy included one stereo, one electronic piano, two guitars, one set of hand glockenspiel, and percussion instruments such as African drums, cymbals, tambourines, and xylophones. During therapy, a prison guard sat in the room outside the group circle to ensure the music therapist’s safety. Three music therapy methods—music and imagery, improvisation, and song writing—were introduced to the group in the first three sessions. The following is a brief introduction of the three methods. Music and imagery is a method adapted from the Bonny Method of Guided Imagery and Music (BMGIM; Paik-Maier, 2010). It was introduced in the first session. In the prelude, the therapist gathered clients’ information and helped group members to find a common issue (i.e., emotion, self-exploration, family) through discussion or arts experience (i.e., improvisation, dance movement, painting). Then, the therapist selected one music piece that matched the clients’ current state and issue to induct their music imagery journey. After a short time (approximately 5 min) of imagery experience, the clients were asked to express their imagery through painting while listening to the same music repetitively. In the postlude, the therapists and group members explored the imagery and feelings together through discussion or arts activities. Improvisation, also referred to as clinical improvisation, is “the use of musical improvisation in an environment of trust and support established to meet the needs of clients” (Wigram, 2004, p. 37). In the second session, group musical improvisation activities including vocal and/or instrumental improvisation in solo, duet, dialogue, trio, or group were introduced. The members experienced free improvisation with no structure or thematic improvisation based on their capability and needs. Song writing is a method where the music therapist writes “songs for and with clients to address various therapeutic goals” (Baker & Wigram, 2005, p. 13). Structured and/or unstructured song writing techniques were applied in the third session, such as replacing blanked keywords with new lyrics in a pre-composed song, replacing whole lyrics for a song, creating new melody for the existing lyrics, or creating a new melody and lyrics. Each session after the first three introductory sessions started with a discussion about thoughts, feelings, personal issues, or incidents in prison. Then group members and the therapist together selected one method described above to continue the therapeutic process. The researchers developed a music therapy protocol for this study. This protocol lists several common group topics (e.g., friendship, trust, empathy, family, interpersonal conflict, emotional problems) and describes several music therapy activities
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under each topic. Each activity description includes therapeutic objectives, instruments and equipments, procedures of implementation, and possible topics for discussion. The activities are structured or unstructured, and a variety of music imagery, improvisation, and song writing techniques are utilized. The full manual is available from the authors and will be published separately. The therapist (X.J.C.) received biweekly supervision with her clinical supervisor to ensure the quality of the therapy and to reflect on relevant issues for her own safety. The group members were encouraged to keep a diary during the study. However, only one participant shared it with the therapist.
Statistical Analyses Statistical analyses were conducted with SPSS version 17.0 and R version 2.15.0. All statistical tests were two-tailed at the 5% significant level. After randomization, the data of all participants were included for analysis, regardless of whether they stopped the therapy early (intention to treat principle). Before the statistical analyses, all dependent variables were examined for normal distribution. All dependent variables were normally distributed, and therefore parametric procedures were used for data analysis. Because the level of missing data was below 5%, no strategy was used to analyze them. Descriptive analyses were conducted for demographic information, anxiety, depression, and self-esteem to assess baseline comparability of both groups. Effects of music therapy were analyzed using t tests for independent samples. This is a simple but valid approach to analysis of adequately randomized-controlled studies because groups are compared directly to each other and baseline variables are assumed to be balanced (Gold, 2015; Moher et al., 2010). We also performed repeated-measures ANOVAs as an overall test and examined interaction effects between time and group (using Wilk’s lambda). In addition, two types of sensitivity analyses were conducted: (a) linear mixed-effects (LME) models taking into account potential clustering by department and batch as a random effect, using endpoint scores as above and (b) the same LMEs but using change from baseline. Furthermore, LMEs were also calculated to identify potential predictors of change, including age, years of education, crime type, and criminal record. The models included both main effects and interaction effects with treatment group, but only the interaction effects were of interest and are reported. In contrast to the study protocol (Chen et al., 2013), concomitant psychological interventions were not controlled for in the analyses, because only very few participants applied for psychological treatments.
Results Baseline Characteristics Of 263 male applicants who took part in the study in four batches from April 2012 to April 2013, a total of 200 (76%) participants were found eligible after the screening (Figure 1). They were randomized to two groups of equal size. Four batches of
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participants from different units, with 43 to 62 people in each batch, were enrolled and completed the intervention sequentially. Participants from one batch had no contact with other batches. In the music therapy group, 12 therapy groups were formed with each one consisting of 8 to 10 people. Participants’ age ranged from 18 to 57 (M = 35.5, SD = 9.95). They had 8 years of education on average (SD = 2.61). In all, 116 participants (58%) had more than 6 years of education and only 8 (4%) had more than 12 years of education. Half of the sample was currently imprisoned for the first time. The great majority (80%) were convicted for acts of physical injury or theft. The average sentence length was 13.02 months (SD = 2.02). No specific risk assessment was conducted. The groups were balanced on all variables at baseline, indicating successful randomization. The baseline comparison of demographic and clinical characteristics of participants in music therapy and standard care is provided in Table 1.
Characteristics of Music Therapy Of 240 sessions, improvisation was applied in 107 sessions (44.6%), music imagery in 90 (37.5%), and song writing in 43 (17.9%). In the music therapy group, 72% participants received 20 sessions of therapy, and 97% participants had more than 10 sessions. Very few participants received other psychotherapy (n = 4). The reasons for 16 dropout participants were as follows: being transferred to another prison (n = 11), physical illness (n = 2), lack of motivation (n = 1), and reduced sentences (n = 2; Figure 1). Outcome data were not available for those who dropped out.
Effects of Music Therapy Table 2 compares outcomes in each group, based on t tests. At mid-program, anxiety (STAI) and depression (BDI) scores were significantly lower (STAI-State: p = .006, d = 0.40; STAI-Trait: p = .001, d = 0.49; BDI: p < .001, d = 0.54) and self-esteem (TSBI) score was significantly higher (p = .011, d = 0.37) in music therapy than in standard care. At post-program, anxiety (STAI) and depression (BDI) scores were significantly lower (STAI-State: p < .001, d = 0.87; STAI-Trait: p < .001, d = 1.03; BDI: p < .001, d = 0.87) in music therapy; self-esteem (TSBI and RSI) scores were significantly higher in music therapy (RSI: p < .001, d = 0.51; TSBI: p = .001, d = 0.51) than in standard care. All effect sizes were larger in the post-program than in the mid-program; most effect sizes were from medium to large. In the post-program, large effect sizes were found for anxiety (STAI) and depression (BDI) scores, and medium effect sizes were found for self-esteem (RSI and TSBI) scores (Table 2). In the repeatedmeasures ANOVAs, all Time × Group interactions were significant (BDI: p < .001; RSI: p < .01; STAI-State: p < .001; STAI-Trait: p < .001; TSBI: p < .05). This confirmed the results from between-group tests reported above suggesting significant effects of music therapy compared with standard care. Clustering by department and batch did not appear to play an important role in this study, as the results of LMEs (not shown) were similar to those in the t tests, and all significant effects remained significant. The same was the case for the LMEs based on change scores.
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Table 1. Baseline Comparison of Demographic and Clinical Characteristics of Participants in Music Therapy and Standard Care.
Characteristic Categorical variables Criminal record First offence One prior offence More than one prior offence Crime type Physical injury Gambling Theft Others (including fraud, sexual harassment, illegal transaction) Continuous variables Age (years) Years of education Months of current sentence Test scores State and Trait Anxiety Inventory–State State and Trait Anxiety Inventory–Trait Beck Depression Inventory Rosenberg Self-Esteem Inventory Texas Social Behavior Inventory
Music therapy (n = 100)
Standard care (n = 100)
n (%)
n (%)
51 (51) 22 (22) 27 (27)
49 (49) 26 (26) 25 (25)
38 (38) 17 (17) 43 (43) 2 (2)
43 (43) 15 (15) 37 (37) 5 (5)
M (SD)
M (SD)
t (df)
p
35.29 (9.83) 8.50 (2.73) 13.21 (2.23)
35.75 (10.07) 8.13 (2.49) 12.83 (2.00)
−0.327(198) 1.00 (198) 1.271 (198)
.744 .319 .205
48.52 (9.67)
48.03 (9.95)
−0.353 (198)
.724
48.70 (8.98)
48.52 (10.12)
−0.133 (198)
.894
24.72 (10.18) 25.92 (4.11)
23.90 (11.11) 26.04 (3.65)
−0.544 (198) 0.218 (198)
.587 .827
97.30 (15.34)
97.56 (15.22)
−0.120 (198)
.904
Difference Chi-square (df)
0.450 (2)
2.169 (3)
p
.798
.538
We conducted further LMEs to examine the interaction effects of covariates (characteristics of the offenders, including age, years of education, crime type, and criminal record) with the effects of music therapy. The results (Table 3) indicated that age and educational level as predictors influenced the effects. Effects of music therapy on STAI-Trait scores were smaller in participants with older age (p < .05) at mid-test, but not at post-test. Participants with lower education showed greater improvement on anxiety (STAI-State and STAI-Trait) at post-test than those with higher education (p < .003; p < .001). In addition, music therapy indicated greater effects for younger participants (p = .02) on self-esteem (RSI) at post-test.
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Chen et al. Table 2. Differences in Outcome Scores Between Music Therapy and Standard Care in Mid-Test and Post-Test (Intention-to-Treat): Continuous Outcomes.
Outcome
Music therapy
Standard care
M (SD)
M (SD)
State and Trait Anxiety Inventory–State Mid-test 45.67 (11.29) 49.74 (9.11) Post-test 40.53 (8.74) 48.58 (9.86) State and Trait Anxiety Inventory–Trait Mid-test 45.56 (10.82) 50.10 (7.76) Post-test 40.58 (8.47) 49.09 (8.17) Beck Depression Inventory Mid-test 15.59 (11.66) 22.08 (12.23) Post-test 11.51 (7.78) 20.32 (12.47) Rosenberg Self-Esteem Inventory Mid-test 28.09 (5.01) 26.80 (4.84) Post-test 29.27 (4.25) 27.01 (4.60) Texas Social Behavior Inventory Mid-test 103.54 (17.55) 97.44 (15.42) Post-test 104.35 (13.62) 96.81 (16.00)
Test for difference
Effect size
t
p
d
2.763 5.870
.006*
