Age: 21–50
polydrug, heroine
Studies examining the effects of music/ musical production, not including sessions of music therapy held by therapists or other conducting persons. Effect sizes are only listed when reported in the articles. Amp = amphetamines; BP = blood pressure; CC = Control condition; CG = Control group; EG = experimental group; fm = females; JC = Jymmin’ condition; HR = heart rate; HRVm = heart rate volume; m = males; MIP = mood induction procedure; pd = prescription drugs; SUD = substance use disorders
a Frequency counts
* p < .05.
** p < .01.
*** p < .001
Study | Outcome | EG | CG | Type of intervention | Frequency/ duration | Measurement tools | Population | Results |
---|---|---|---|---|---|---|---|---|
Baker et al.[ ] Dingle et al.[ ] | Perceived enjoyment Engagement Motivation Mood-related experiences | = 24 48.5% m Age: 17–52 ( = 34.4) 54% alcohol 30% polydrug/ injecting 13% cannabis | - | MT CBMT (lyric analysis, songwriting, parody, improvisation, singing, listening) | 1 session for analysis, 90 min, 7 sessions per week | 5-point Likert scale yes-no questions open-ended questions | In- and outpatient rehabilitation unit (detoxification and day patients) Australia | • 75% attendance • 70.8% were at least often motivated to take part in the session • 87.5% mood regulation • 65% positive mood change • 20% music allowed contact with feelings, relaxing • 10% feelings of sadness, depression • 83.5% found sessions (extremely) enjoyable • 83% would take part in another session • 5.7 ± 2.8 emotions per session; positive: happy, vibrant, comfortable, relieved, inspired, proud; negative: sad, upset, self-conscious, confused • Correlation between “use of music to regulate mood” and “help me do something enjoyable without using substances”, = .509 . • No differences between people with alcohol and drug use disorders for engagement, enjoyment, motivation • No differences between people up to/ over the age of 25 for engagement, enjoyment, motivation |
Gardstrom et al.[ ] | Anxiety Sadness Anger | = 49 Age: early 20s to late 60s Dually diagnosed with MI and SUD | - | MT composition, listening, improvisation, performance | 1 session for analysis 20 sessions, 45min | 7-point visual analogue scale | Inpatient dual diagnosis treatment unit USA | • 51% decrease in anxiety, 38.8% no change, 10.2% increase • 42.9% decrease in anger, 55.1% no change, 2% increase • 65.2% decrease in sadness, 28.6% no change, 6.1% increase • 32.7% decrease in all three scales, 20.4% no change in all scales, 0.2% increase in all scales |
Gardstrom & Diestelkamp[ ] | Anxiety | = 53 fm = 39 with pre-session anxiety included Alcohol or other drugs, many polydrugs | - | MT composition, listening, improvisation, performance | 1 session for analysis 18 sessions, 45min, twice a week, 9 weeks | 7-point Likert scale | Females Inpatient gender-specific residential program USA | • 26.4% of the initial sample showed no pre-test anxiety (excluded) • 84.6% decrease of anxiety from pre- to posttest • 5.1% increase of anxiety • 10.3% no change • Decrease of anxiety from pre- to posttest |
Jones[ ] | Mood (11 areas) Importance of MT | = 26 (88.5% m) Age: 21–69 ( = 39.9) 85% alcohol 58% cocaine 19% cannabis 19% other drugs | Comparison between two MT groups | MT lyric analysis or songwriting | 4 days per week | Visual analogue mood scale (100mm) with combined emotions | Inpatient non-medical detoxification facility USA | • Increased feelings of acceptance, joy/happiness/enjoyment • Decreased feelings of guilty/regretful/blame, fearful/ distrustful • No significant reduction in anxiety/ nervousness/ anticipation, shame/ humiliation/ embarrassment/ disgrace, sadness/ depression, sorrowful/ suffering • No differences between methods • 75% rated MT as significant tool in their recovery (increasing significance with increasing session number). |
Silverman[ ] | Motivation (Treatment Eagerness) Working alliance Enjoyment | = 29 Whole sample: = 66 (43.9% m) Age: = 40.8 58% alcohol 12% polydrug 12% pd | Group verbal therapy = 37 | MT lyric analysis | 1 session 45 min, once a week | SOCRATES (short version) Revised Helping Alliance Questionnaire for therapist and client (HAQ) 7-point Likert scale | Inpatient detoxification unit USA | • No differences in motivation, client-rated working alliance, and perceived enjoyment between EG and CG • Higher therapist-rated working alliance for EG vs. CG • All participants noted they would attend another session. |
Silverman[ ] | Withdrawal Locus of control | = 64 Whole sample: = 118 (48.3% m) Age: = 40.2 | Group verbal therapy = 54 | MT lyric analysis | 1 session 45 min, once a week | Adjective Rating Scale for Withdrawal (ARSW) Drinking-Related Internal-External Locus of Control Scale (DRIE) | Inpatient detoxification unit USA | • No differences for withdrawal and locus of control between EG and CG • All participants except one noted they would attend another session |
Silverman[ ] | Change readiness Depression Enjoyment Helpfulness Comfort Content Being clean | = 69 Whole sample: = 140 (50% m) Age: = 43.2 | Group verbal therapy = 71 | MT songwriting | 1 session 45 min, once a week | University of Rhode Island Change Assessment (URICA) BDI-II 7-point Likert scales and follow-up interview after 1 month Lyric analysis | Inpatient detoxification unit USA | • No differences in change readiness ( = .02) and depression for CG vs. EG • More perceived helpfulness ( = .10), enjoyment ( = .13), and comfort ( = .03) for EG vs. CG • No differences in follow-up measures(enjoyment, helpfulness, depression, being clean) between EG and CG ( = .10) • EG more comments regarding enjoyment, thanks, continuation, positive cognitive changes than CG • Lyrics concerning consequences of using drugs, insight/change |
Silverman[ ] | Readiness to change Craving Helpfulness Enjoyment Motivation | = 42 (EG1; Rockumentary MT) = 43 (EG2; Recreational MT) Whole sample: = 141 (58.2% m) Age: = 38.4 55% alcohol 23% heroine 9% pd | Group verbal therapy = 56 | MT lyric analysis (EG1) or music bingo (EG2) | 1 session 45 min, once a week | Readiness to Change Questionnaire Treatment Version (RTCQ-TV) Brief substance craving scale (BSCS) 7-point Likert scales | Inpatient detoxification unit USA | • RTCQ-TV: Higher scores for Contemplation ( = .122) and Action ( = .052) for EG vs. CG • No differences in craving, helpfulness, enjoyment, and motivation between EG and CG • Correlations between motivation, enjoyment, and helpfulness across all participants • No differences between EG1 and EG2 |
Silverman[ ] | Motivation and readiness for treatment Content | Posttest = 48 Whole sample: = 99 (48.5% m) Age: = 43.9 64% alcohol 17% heroin 14% pd 3% cocaine | Pretest (wait-list CG) = 51 | MT songwriting | 1 session 45 min, once a week | Circumstances, Motivation, and Readiness Scales for Substance Abuse Treatment (CMR) Lyric Analysis | Inpatient detoxification unit USA | • Higher scores for motivation ( = .068) and readiness for treatment ( = .128) for EG vs. CG • Contents: “action”( = 44), “emotions and feelings”( = 28), “change“ ( = 26), “reflection”( = 21), “admission”( = 20), “responsibility” ( = 7) |
Silverman[ ] | Drug avoidance self-efficacy Motivation for sobriety Treatment eagerness | Posttest = 43 Whole sample: = 131 (53.4% m) Age: = 38.6 57% alcohol 24% pd 17% heroin 2% cocaine | Active CG: group verbal therapy = 41 Wait-list CG: Pretest (with group music bingo) = 47 | MT lyric analysis | 1 session 45 min, once a week | Drug Avoidance Self-Efficacy Scale (DASES) 7-point Likert scales | Inpatient detoxification unit USA | • No differences for motivation ( = .001), treatment eagerness ( = .019), or drug avoidance self-efficacy ( = .034) between EG and CGs |
Silverman[ ] | Motivation | Posttest = 49 (EG1 and EG2 with different songs) Whole sample: = 104 (54.8% m) Age: = 41.6 62% alcohol 21% pd 14% heroin 1% cocaine 1% cannabis | Pretest (wait-list CG) = 53 | MT lyric analysis | 1 session 45 min, once a week | Texas Christian University Treatment Motivation Scale- Client Evaluation of Self at Intake (CESI) | Inpatient detoxification unit USA | • Higher means for problem recognition ( = .053), desire for help ( = .0.044, treatment readiness ( = .089), and total motivation ( = .074) for EG vs. CG • No differences between EG1 and EG2 |
Silverman[ ] | Motivation to reach and maintain sobriety Treatment eagerness Knowledge of triggers and coping skills | = 21 Whole sample: = 69 (58% m) Age: = 38.5 58% alcohol 21% heroin 21% pd 1% cocaine | Education without music = 21 Recreational MT (music bingo) = 25 | MT educational MT (songwriting) | 1 session, 45 min, once a week | 7-point Likert scales lists of triggers and coping skills | Inpatient detoxification unit USA | EG with higher motivation than CG1 and CG2 ( = .177) • No between-group differences after adjustment for multiple comparisons regarding treatment eagerness, knowledge of triggers and coping skills |
Silverman[ ] | Withdrawal Current craving | = 60 Whole sample: = 144 (54% m) Age: = 36.8 81% alcohol 42% heroine 10% pd 1% cocaine 1% other | Pretest (wait-list CG) = 84 | MT lyric analysis | 1 session, 45 min, once a week | Adjective Rating Scale for Withdrawal (ARSW) Brief Substance Craving Scale (BSCS) | Inpatient detoxification unit USA | No differences between the groups regarding withdrawal ( = .026) or craving ( = .022). • No relationship between familiarity and withdrawal or craving. |
All studies included one session only for data analysis. Effect sizes are only listed when reported in the articles. amp = amphetamines; CBMT = cognitive behavioral music therapy; CG = control group; DARTNA = Drum-Assisted Recovery Therapy for Native Americans; EG = experimental group; fm = females; GIM = Guided Imagery and Music therapy; m = males; MBI = music based intervention; MI = mental illness; MT = music therapy; pd = prescription drugs; SOCRATES = The Stages of Change Readiness and Treatment Eagerness Scale; SUD = substance use disorders
b N = 121 completed all measures
c N = 100 completed all measures
*p < .05.
Study | Outcome | EG | CG | Type of intervention | Frequency/ duration | Measurement tools | Population | Results |
---|---|---|---|---|---|---|---|---|
Albornoz[ ] | Depression (self-rating/ therapist rating) | = 12 Whole sample: = 24 m Age: 16–60 Addiction and depression problem | = 12 | MT improvisation (independent therapy) | 12 sessions, 2h per week, 3 months | BDI Hamilton Rating Scale for Depression | Males Inpatient treatment for substance abuse Venezuela | • Lower post- than pre-test scores for self-rated depression for EG and CG , = 0.51 across both groups (Power for comparison: 34%) • Lower post- than pre-test scores for therapist-rated depression for EG and CG , = 0.90 across both groups (Power for comparison: 78%) • Lower post-test scores for therapist-rated depression for EG compared to CG , but not for self-rated depression |
Cevasco et al.[ ] | Anxiety Anger Depression Stress | = 20 fm Age: 19–42 | - | MT competitive games, dancing or rhythm activities | 12 sessions, 1h, twice a week each therapy 4 sessions | State-Trait Anxiety Inventory (STAI) Novaco Anger Inventory Short Form (NAI) 10-point Likert scales | Females Outpatient substance abuse program USA | • No overall effects of MT methods, individual effects of MT methods • Average daily percentage of decrease : Indicated progress for several individuals on decreased levels of depression, stress, anxiety, and anger • Mortality rate: 50%; remaining clients with lower anxiety and anger values |
Dickerson et al.[ ] | Treatment retention and completion Substance use Problem severity Comfort and strength derived from spirituality Well-being Cognitive functioning Cultural identity Adoption of principles Physical and psychiatric symptoms | = 10 (50% m) Age: 19–71 ( = 52.5) | - | MBI (drumming teacher and counselor) Drum-assisted recovery therapy for Native Americans (DARTNA) (independent therapy) | 24 sessions, 3h, twice a week | Substance Use Report Addiction Severity Index, Native American Version (ASI-NAV) Functional Assessment of Chronic Illness Therapy (FACIT): Spiritual Questions Only Expanded, Fatigue (FACIT-F) Functional Assessment of Cancer Therapy–Cognitive Functions (FACT-Cog) American Indian/ Alaska Native Cultural Identity Scale General Alcoholics Anonymous Tools of Recovery (GAATOR 2.1) BSI | Outpatient setting Native Americans USA | • 50% treatment completion (80% until week 6) • Improved psychiatry status after 6 weeks, improved medical status after 12 weeks (ASI-NAV) • Spirituality: Improved meaning/peace and total score after 12 weeks (FACIT) • Improved physical and functional well-being after 12 weeks (FACIT-F) • No improvements in adoption of principles, physical and psychiatric symptoms or cognitive functions (GAATOR 2.1, BSI, FACT-Cog) |
Dougherty[ ] | Attendance | Age: adolescent-geriatric 100% alcohol | - | MT music listening (structured sessions) sing along (group) | structured sessions: 3–4 weeks, once a week sing along: 30 min, biweekly | Percent of attendance at any given time | Inpatient rehabilitation/ Therapeutic community for alcohol dependency USA | • 80–90% attendance |
Gallagher & Steele[ ] | Mood Participation On-task behavior | = 188 Age: 20–59 ( = 36) Dually diagnosed with SUD and MI | MT music listening, group participatory music, playing instruments, relaxing, lyric analysis, drumming, songwriting, music and muscle tone/pulse rate | 45min, once a week | Roger's (1981) Happy/ Sad Faces Assessment Tool Therapist rating | Outpatient counseling (9 month stay) USA | • 91% active participation • 82% expression of thoughts and feelings • 68% positive mood changes • 64% no mood changes during the session • 53% not sociable • 46% participation in processing the session • 60% constricted or blunted affect after the session | |
Gallant et al.[ ] | Client attitudes Psychosocial functioning | = 6 couples Age: 31–51 ( = 43) Various drug addictions | - | MBI (social worker) music listening, lyric analysis, relaxation | 4 sessions, 2h, over 2 weeks | 20-Item Hudson Psychosocial Screening Instrument Content analysis | Outpatient recovery Canada | • 5/6 patients rated MT as “very helpful“ • On average clients were less anxious, less depressed, and had fewer relationship problems. • Average Hudson Score decreased from pre to post. Cohen’s U3 = 88%. • Content: Problem definition (55.8%), problem solving (44.2%), motivation-activation (38%), problem definition (36.6%), assessment (13.1%), goal setting (8.8%), action plan development (3.5%), cognition (68%), affective or emotive expression (32%) ○ “feeling” associated with music (55%) and “thinking” associated with lyrics (78%) more often. |
Howard[ ] | Depressiogenic thought frequency State immediate goals | Sample A: = 8 fm Age: = 34.9 Sample B: = 12 adolescents Age: 15–17 Chemical addictions | Within subjects comparison (PT vs. MT) or between samples comparison | MT lyric analysis (PT also including lyric analysis) | 6 sessions (alternating music and poetry), 45min, 6 weeks | Automatic Thoughts Questionnaire (ATQ) Goal attainment form (GAF) | 2 inpatient substance abuse treatment facilities (rehab-ilitation center) USA | • No differences in depressiogenic thought frequency and state immediate goals between groups or type of therapy for ATQ, GAF, or off-task behavior • High percentage of on-task behavior |
Hwang & Oh[ ] | Depression Anxiety Anger Stress | = 42 m Age: 31–73 ( = 50.2) 100% alcohol | Between methods comparison | MT singing, listening, playing instruments (therapist- or patient-selected activities) | 12 sessions (4 sessions each therapy) 0.5h, twice a week | 10-point Likert Scales | Males Inpatient alcohol treatment program South Korea | • High pretest scores of anxiety, anger, depression, and stress for singing • Decreased depression , anxiety , anger , and stress in posttest • No differences between methods • No differences between patient- and therapist-selected activities at all • Significant reduction in stress and depression for therapist-chosen activities during singing |
James[ ] Study 1 | Locus of control | Whole sample: = 20 adolescents (50% m) Age: = 15.8 Chemical addictions | Occupational therapy craft group (waitlist) N = 10 | MT music listening lyric analysis | 4 sessions, 1h, one week | Abbreviated Internal External Locus of Control Scale | Adolescents Inpatient rehabilitation service for chemical dependency USA | • Greater pre-post increase in internal locus of control for EG than CG |
James[ ] Study 2 | Locus of control | = 10 Posttest only Whole sample: = 20 adolescents (55% m) Age: = 16.4 Chemical addictions | Occupational therapy craft group (waitlist) Pretest only = 10 | MT music listening lyric analysis | 4 sessions, 1h, one week | Abbreviated Internal External Locus of Control Scale | Adolescents Inpatient rehabilitation service for chemical dependency USA | • Greater internal locus of control for EG than CG |
K. M. Murphy[ ] | Motivation Depression Coping Skills | GIM + standard program = 9 Whole sample: = 16 (56.3% m) Age: 19–55 = 37.2 56.3% polydrug 37.5% alcohol 6.3% cannabis | Standard program = 7 | MT GIM (relaxation, imagery focus, music imaging, drawing or journaling) | 8 sessions, 50-60min, 21 days | Importance, Confidence, Readiness Ruler (ICR) Beck Depression Inventory (BDI) Sense of Coherence Scale (SOC) | Inpatient residential substance abuse treatment USA | • No differences in coping skills, depression, and motivation between EG and CG in pre- and posttest • Depression : CG 46% decrease, EG 75% decrease • Retention rate : CG 50%, EG 75% |
Oklan & Henderson[ ] | Depression Psychiatric symptoms Coping skills | Case study = 1 m Age: 14 | - | MBI (unclear) Recorded Music Expressive Arts (RMEA) therapy with songwriting and production (independent therapy) | 16 sessions, 75min, 16 weeks | BDI-II Symptom Checklist 90-R (SC-90-R) Adolescent Coping Orientation to Problems Experienced (A-COPE) | Adolescent Outpatient psychological treatment, inhalant abuse, case study USA | • Depression: Reduced SC-90-R Depression score, no reduction in BDI-II after 10 weeks (normal range) • Reduction in obsessive-compulsive, depressive, psychotic, anxiety, and overall symptoms • Increased seeking spiritual support, positive imagery, self-reliance • Decreased physical diversion, humor |
Ross et al.[ ] | Problem Severity General functioning Motivation Physical and psychiatric symptoms Medication adherence Attitudes towards MT and therapist MT characteristics | = 80 (80% m) Age: 20–57 ( = 39.7) Dually diagnosed with MI and SUD 50% alcohol 37% cocaine 20% cannabis 19% polydrug 14% opiates | - | MBI (unclear) music and imagery (listening), drumming, improvisation | 1h, one to more than 6 sessions | Addiction Severity Index Clinical Global Impression Severity Scale (CGI), Global Assessment of Function Scale (GAF) SOCRATES BSI MT Questionnaire Number of sessions | Inpatient dual diagnosis unit USA | • Pretest variables unrelated to MT characteristics and MT Questionnaire • 100% medication adherence • 71% appeared at outpatient aftercare treatment • Number of sessions positively associated with aftercare appointment Pre- vs. posttest: • Relationship between MT appreciation and changes in CGI • Relationship between therapist appreciation and changes in CGI , GAF , and Taking Steps • Relationship between MT appreciation and attitudes towards the therapist Cross-sectional analyses at discharge • Relationship between MT appreciation and Taking Steps Relationship between therapist appreciation and Ambivalence , Taking Steps |
Silverman[ ] | Perceived effectiveness and enjoyment Intervention assessment compared to other groups | = 8 fm Age: 19–65 100% chemical dependency | - | MT music games, relaxation training, lyric analysis, songwriting | 8 sessions, once a week | 25-point analogue scales | Females Inpatient chemically dependency treatment USA | • No differences between the interventions regarding enjoyment and effectiveness • Mean scores for enjoyment/ effectiveness nearly at maximum • 50% reported MT as more effective and enjoyable than other groups |
Yun & Gallant[ ] | Forgiveness and grief Depression | = 21 fm Age: 28–64 ( = 48) SUD due to forgiveness/grief issues | MBI (counselor) listening, lyric analysis Individual setting | 12 sessions per client, 1h, biweekly, 6 month | Forgiveness Grief Perspectives Scale (FGPS) BDI | Females Outpatient rehabilitation center, Canada | • Decrease in forgiveness and grief from pre- to posttest ( = 1.95) • Decrease in depression from pre- to posttest ( = 2.42) • Positive correlation between forgiveness/grief and depression in pretest ( = .54) , and posttest ( = .58) |
Effect sizes are only listed when reported in the articles. For music-based intervention (MBI) studies, conducting persons are listed in brackets. BDI = Beck Depression Inventory; BSI = Brief Symptom Inventory; CG = control group; EG = experimental group; fm = female; m = male; MBI = music-based intervention; MI = Mental illness; MT = music therapy; pd = prescription drugs; SUD = substance use disorders
a Frequency counts.
b Results based on a criterion of clinical significance, i.e., changes by at least one standard deviation of the mean.
c Results based on scores from 36 participants.
Study | Type of intervention | Frequency/ duration | Population/ Setting | Measurement tools | Topics/ Themes |
---|---|---|---|---|---|
Abdollahnejad [ ] | MBI (unclear) Lyric analysis, song sharing | 25 sessions, 45 min | Therapeutic Community for drug users Iran = 20 m Age: 20–50 | • Behavior during the sessions (video tape) | • Increased talking about important issues (e.g., relationships) • Indirect expression of thoughts and feelings • Increased exchange of opinions and experiences • Close interaction between group members (learning about each other, problem solving) • Participants were highly interested • Nostalgic experiences with music related to previous drug abuse |
Baker et al.[ ] | MT Songwriting | Once a week | Inpatient substance abuse treatment = 5 (40% m) Age: early 20 to middle-aged 60% amp, 40% alcohol | • Reaction during the session • Lyric analysis | • Incidental rebellion • Lengthy process of group problem solving, personal reflection, reevaluation • Clear engagement (declined smoking break) • Safe medium for the expression of negative emotions • Humor |
Eagle[ ] | MT Listening to music (during LSD therapy) | 5 times per day, 30 min each, | Inpatient alcohol abuse treatment USA = 16 m Age: 34–59 100% alcohol | • Behavioral observations with therapist’s notes (structured case studies) | • Importance of familiar music • Important contents: Religion and love • Nonverbal communication through music between patients and therapist • “Music “guides” patients’ experiences through the LSD therapy sessions.” (p. 35) |
Liebowitz et al.[ ] | MBI (vocal performance majors) Choral music program | Once a week, 75 min Quarterly performance | Residential facility for homeless veterans with SUD Southwestern USA = 6 (66.7% m) | • Individual semi-structured interviews ○ Duration of the association with the study site ○ Duration of the participation in the choir ○ How learned about choir ○ Expectations ○ Experiences ○ Interaction with the context ○ Impact on relationships ○ What they would tell other veterans about the choir | • Personal motivations ○ Opportunities to meet other residents ○ Affinity to singing ○ Diversion their attention from other contents ○ Opportunity to learn (singing, music) ○ Personal challenge • Emotions linked to participation ○ Anxiety ○ Enjoyment ○ Elevating effect on mood, relaxing • Perceived intragroup dynamics ○ Belonging, commitment to the choir ○ Support, enhanced performance |
Rio[ ] | MT Improvisational music | Once a week, 2h 10 months data collection | Church-based shelter with Choirhouse church choir USA = 3 m consistent members Age: 26, 45, 55 ( = 42) 66% polydrug 33% cocaine | • Behavior during the sessions (video tape, session notes, personal journal, audio tapes) • Individual semi-structured interviews in the first month ○ History, interest in music ○ Feelings, thoughts ○ Relationships ○ Music ○ Substance abuse ○ Medical, mental health issues | • Consistent attendance and intense involvement of the core group members • Identified themes: ○ Emotional expression (grief and loss, joy, state of being) ○ Beauty and spirituality (aesthetic, character, faith, altered states) ○ Relationships (support, closeness, difficulty, connecting) ○ Story (history, metaphor, shared experiences) ○ Structure (boundaries, traits, music) ○ Create/Risk (making music, void) ○ Health (psychological, physical/cognitive) |
Zanker & Glatt [ ] | MBI (artists of Council for music) Music listening | Twice a week, 30 min | Inpatient mental hospital UK Alcoholics and narcotics | • Questionnaires about individual attitude towards music and mood after listening | • Diversity and subjectivity of reactions to music • Expression of emotions through music • Group cohesion dependent on personality • Reactions to music can reflect personality aspects • Congruity between mood states and intrinsic character of music linked to improvement of clinical status and long-term outcomes • Music may serve as diagnostic tool (projection of mood into music) |
For music-based intervention (MBI) studies, persons conducting the sessions are listed in brackets. MBI = music- based interventions; MT = music therapy.
For the majority of the studies, sessions were held in group settings, except a single-case study [ 40 ] and one study with individual application of the music-based program [ 41 ]. Most of the studies, i.e., three qualitative and 23 quantitative studies, were classified as “MT studies” (according to the music therapy definition provided in Introduction). With respect to MBIs, one study was conducted by vocal performance majors [ 57 ], one by different artists of the Council of Music [ 58 ], one by a cultural drumming teacher and a substance abuse counselor [ 48 ], one by a social worker [ 44 ], one by a counselor [ 41 ], and in three cases [ 15 , 40 , 55 ] the therapist’s background remained unclear.
Not considering the case study, sample size ranged from 8 participants [ 42 , 47 ] to 188 participants [ 49 ] for the quantitative studies, and from 3 participants [ 59 ] to 20 participants [ 55 ] for the qualitative studies. One quantitative [ 50 ] and one qualitative study [ 58 ] did not report sample sizes.
Six studies examined men only [ 40 , 45 , 50 , 55 , 59 , 60 ] and five women only [ 19 , 41 – 43 , 47 ].
Regarding the diagnosis, many samples included various drug addictions, i.e., polydrug abuse. Other studies only focused on chemical dependency [ 20 , 42 , 47 ], alcohol [ 45 , 50 , 60 ] or inhalant abuse [ 40 ].
With respect to the age of the participants, four studies investigated adolescents only with mean ages/ age ranges between 15 and 17 years [ 20 , 42 ] or as a single case study with a 14-year old boy [ 40 ]. For the other studies, mean age varied from 34.4 years [ 16 ] up to 52.5 years [ 48 ]. Eleven studies [ 16 , 19 , 39 , 43 , 47 , 50 , 51 , 55 , 57 , 58 , 60 ] did not report any measure of central tendency regarding age. In 16 cases [ 15 , 16 , 38 , 39 , 41 , 43 – 49 , 55 , 59 , 60 ] numeric age ranges were reported which varied from 21 years [ 44 ] (31–51 years) to 53 years [ 48 ] (19–71 years).
Sample sizes ranged from 19 participants [ 61 ] to 59 participants [ 62 ].
Two studies examined men only [ 55 , 62 ], and three investigated both men and women. One study did not report any information about gender [ 63 ].
Regarding the diagnosis, three studies focused on alcohol addiction [ 62 – 64 ], and the others included various drug addictions.
Regarding the age, mean age ranged from 31.1 years [ 61 ] to 43.1 years [ 64 ]. Two studies did not report any measures of central tendency [ 55 , 63 ] and one reported a median age of 46.4 years [ 62 ]. Age ranges (when reported) differed only slightly from 28 years [ 65 ] (20–47) to 33 years [ 64 ] (27–59).
For an overview of the efficacy of MT/ MBI per outcome (cluster) in consideration of the quality of the studies see Fig 3 . Studies were classified according to the categorization scheme presented in Fig 1 . None of the studies met the criteria of categories (3a) and (3b), i.e., studies with CG without randomization, so that these categories are not represented in Fig 3 . In the following section, we will describe the results in more detail.
Studies with effect or no effect compared to control group (CG) were classified as of high level evidence of efficacy (black and dark grey bars). Studies reporting insufficient statistical data to conduct meta-analyses and without CG were classified as of low level evidence of efficacy (light grey bars).
For the effect of MT/ MBI on variables related to this cluster (motivation, treatment eagerness, change readiness), 10 results were collected, and eight of them (80%) represent high level evidence of efficacy. For Silverman [ 32 , 34 ] who examined different motivational constructs within the same samples only motivation scores were used. All studies except one reported all statistical data and only one included pilot data without a CG [ 15 ]. In 37.5% of studies of high level evidence of efficacy (3/8), i.e. 30% of all studies (3/10), beneficial effects of MT/ MBI were found. All RCTs except one [ 38 ] were conducted by Silverman [ 29 , 31 – 36 ], and they differed widely with respect to CG designs and scales, so a meta-analysis was not conducted.
This outcome was examined in 11 studies including Howard [ 42 ] which reported on two separate samples. Five studies report insufficient statistical data and four were non-controlled studies, so that only 27% of the results (3/11) were categorized as of high level evidence of efficacy. None of the RCTs found benefits of MT/ MBI compared to CG. A meta-analysis was not conducted due to the different CG designs.
All three data sources of high level evidence of efficacy (i.e., 50% of all studies regarding this outcome) were reported by Silverman [ 29 , 31 , 32 ], so that we did not conduct a meta-analysis. Three further studies of low level evidence of efficacy [ 16 , 46 , 47 ] did not report all necessary statistical data. One out of three RCTs, i.e., 17% of all results (1/6), reported a positive effect of MT on enjoyment.
We decided to cluster these outcomes as the variables are closely linked. Patients in states of withdrawal often experience craving, and consumption of the substance may immediately and effectively reduce the symptoms [ 37 ]. Silverman [ 30 , 32 , 37 ] conducted three different RCTs examining craving and/or withdrawal in patients addicted to various drugs (e.g., alcohol, heroine, prescription drugs and cocaine). None of the studies showed beneficial effects of MT compared to different CG. A meta-analysis was not conducted because all results were reported by the same author.
Forty percent of the results (2/5) were of high level evidence of efficacy, comparing MT to group verbal therapy, and both RCTs were conducted by Silverman [ 31 , 32 ], so a meta-analysis was not appropriate. The lack of statistical details prohibited inclusion in meta-analysis for two further studies [ 44 , 47 ], and another study was a non-controlled study [ 15 ]. All in all, 50% of studies of high level evidence of efficacy, i.e., 20% of all studies (1/5) regarding helpfulness were in favor of MT/ MBI.
All three studies considering LOC were RCTs, and two of them [ 20 ] (i.e., 67%) found positive effects of MBI/ MT. A meta-analysis was not conducted due to different CG designs.
For this category, many different constructs regarding the quantitative assessment of patients’ engagement and participation were subsumed, so six data sources were identified: Only one study included a CG [ 29 ] and did not identify benefits of MT. Furthermore, 50% of all data sources (3/6) did not report all statistical data [ 16 , 49 , 50 ] and 33% (2/6) were non-controlled studies [ 15 , 48 ].
Only one study out of three studies (33%) for this outcome, was of low level evidence of efficacy, i.e., a case study not including a CG [ 40 ]. None of the RCTs [ 36 , 38 ] found benefits of MT for coping skills.
For five outcome clusters, namely anxiety , medical symptoms , anger , sadness , and stress , no RCTs could be identified, so conclusions about efficacy cannot be drawn.
Only one RCT assessed follow-up scores regarding depression, enjoyment, perceived effectiveness and being clean [ 31 ] and did not identify differences between group verbal therapy and MT groups one month after intervention completion.
For at least eight categories of outcomes, studies of high level evidence of efficacy, i.e., RCTs, were identified. The descriptive summaries suggest that there is evidence for benefits of MT/ MBI compared to different control groups (CGs), especially for the variable locus of control (67% positive effects compared to CG). Additionally, regarding perceived helpfulness of the intervention, half of the RCTs reported higher values for MT compared to CG. For motivation and enjoyment there were inconsistent results, and more than half of the studies of high level evidence of efficacy did not identify statistically significant improvement for MT/ MBI participants. Regarding depression, withdrawal/ craving, participation, and coping skills none of the RCTs reported benefits for MT. Studies examining anxiety, medical symptoms, anger, sadness, and stress were all of low level evidence of efficacy, so that their results can only serve as a base for further research giving hints to constructs that should be evaluated with RCTs.
We now describe effects of MP, MT and MBI considering study characteristics according to the following categories: (1) effects of music in general, (2) effects of one session of MT/ MBI, and (3) effects of more than one session of MT/ MBI. Because most of the studies were not RCTs, conclusions about MT efficacy cannot be drawn. Thus, the summaries include descriptions of clinical effectiveness, i.e. the effects in clinical practice [ 67 ].
Studies comparing MT methods (e.g., lyric analysis and songwriting [ 46 ]) did not identify significant differences between the interventions, so that the methods are not differentiated in the following. With respect to the nomenclature, we noticed that regarding mood there is still no consensus, as mood , feelings , and emotions are often used interchangeably. For instance, Jones [ 46 ] refers to the terms “feelings and emotions” (p. 100), only to eventually assess “mood” using a visual analogue mood scale. Thus, due to the heterogeneity of the nomenclature used in the studies, it was not possible to differentiate these terms properly.
Six studies examined the impact of music on patients with SUD without therapeutical involvement of an interventionist (see Table 2 ). The following effects of listening to music were reported: Short and Dingle [ 61 ] examined the impact of sad, happy, and relaxing songs on arousal in patients with SUD and a healthy control group (CG). Whereas the participants of the CG indicated different degrees of arousal and pleasantness for the three tracks, the SUD patients rated the three pieces of classical music equally arousing and pleasant. Furthermore, their degree of craving was linked to the personal relevance of songs: The patients reported increased craving after listening to a track associated with their substance use, whereas afterwards, listening to a track associated with abstinence resulted in decreased craving. These results indicate less emotional variations in SUD patients and a direct impact of music on relapse related variables. Furthermore, Fritz et al. [ 65 ] reported a strong context dependency of music effects. They conducted a musical feedback intervention with listening to a jointly self-produced music piece or a commercial track. Self-produced music showed positive effects on mood and locus of control (LOC) only when it was presented prior to the commercial music production. Jansma et al. [ 64 ] examined the effect of mood states on alcohol cue reactivity. They induced depressive mood by presentation of depressive music or distressed mood by negative feedback following a high performance task. Alcohol cue reactivity was present, but did not differ between negative or neutral mood states. Nevertheless, the patients were less irritated and more satisfied after depressive mood induction compared to distressing mood induction.
With respect to more abstract outcomes, patients with alcohol dependency perceived colors with greater intensity after listening to music compared to people (patients and staff of a therapeutic community) without exposure to music [ 63 ]. Similarly, music during LSD therapy was associated with colors, geometric designs, and past events. Between groups with and without music exposure, there was no difference in LSD experience. Nevertheless, only listening to familiar music appeared to have an effect on general music preference [ 62 ].
Additionally, there was experimental evidence for positive effects of music listening over a longer period of time. For members of a therapeutic community for drug users, music listening before falling asleep was related to increased sleep quality and mood on the following day as well as to decreased drop-out rate during a one-month-intervention [ 55 ].
MT/ MBIs typically include more methods than simply listening to music [ 68 ]. Effects of quantitative studies examining single MT sessions (mostly lyric analysis, songwriting or improvisation) are summarized in Table 3 . Most of them were conducted in detoxification centers with a short duration of stay between three and five days. Compared to a verbal therapy CG, MT participants showed similar measures of change readiness, depression, sobriety [ 31 ], client-rated working alliance [ 29 ], LOC [ 30 ], treatment eagerness, drug avoidance self-efficacy [ 34 ], craving [ 32 ], and withdrawal symptoms [ 30 ]. Silverman compared MT groups to wait-list CGs with pretest only, and found no differences regarding craving and withdrawal [ 37 ]. Positive effects of MT vs. group verbal therapy were found for therapist-rated working alliance [ 29 ], comfort [ 31 ], and motivational variables: MT participants had higher realization that aspects of change can be better than the status quo and more active changes [ 32 ]. In line with that, MT groups showed increased problem recognition, desire for help, treatment readiness, and total motivation compared to a wait-list CG with pretest only [ 33 , 35 ]. Furthermore, Silverman [ 36 ] found higher motivation to reach and maintain sobriety for participants of educational MT compared to patients receiving education without music or a music game. In the same study, treatment eagerness and knowledge of coping skills or triggers did not differ between groups. In three other studies, similar motivation scores between MT groups and verbal therapy or pretest CG were identified [ 29 , 32 , 34 ], indicating that the effects of single MT sessions on motivational aspects are not coherent. Regarding perceived enjoyment and helpfulness, the results were not consistent as well [ 29 , 31 , 32 ].
Other studies with single sessions for data analysis were conducted in an inpatient non-medical detoxification unit [ 46 ], an in- and outpatient rehabilitation unit [ 16 ], an inpatient dual diagnosis treatment unit [ 51 ] and an inpatient gender-specific residential program [ 19 ]. All these studies reported beneficial effects on mood: For instance, 65% of the participants showed a positive mood change [ 16 ]. More specifically, a great amount of the participants reported decreased anxiety [ 19 ], anger, and sadness [ 51 ], and or an increase in acceptance, enjoyment, happiness, and joy [ 46 ]. Furthermore, 87.5% of the participants used MT for mood regulation [ 16 ]. Nevertheless, one study found no differences between pre- and posttest regarding anxiety and depression [ 46 ].
Effects of studies examining more than one session are summarized in Table 4 . Awareness, expression, and change of emotions are often mentioned as important intended therapy goals [ 50 ]. Therefore, five studies in inpatient settings [ 38 , 39 , 42 , 45 , 47 ] and five studies in outpatient settings [ 40 , 41 , 43 , 44 , 49 ] examined treatment effects on mood and emotions. Generally, MT participation was associated with positive mood changes [ 49 ], and the scores for perceived enjoyment and effectiveness of MT were almost at the maximum [ 47 ]. With respect to negative emotions, MT was linked to reduced anger, depression, stress, and anxiety [ 40 , 41 , 43 – 45 ]. Two RCTs identified beneficial effects of MT regarding therapist-reported, but not self-reported depression scores [ 38 , 39 ].
MT and MBI also affected other psychological variables: Adolescents with chemical dependency completing MT showed increased internal LOC compared to a wait-list CG engaging in alternative activities [ 20 ]. Results regarding motivation and coping skills were not clear: While in one RCT similar levels for both variables after standard treatment (CG) and additional Guided Imagery and Music (GIM) therapy were reported [ 38 ], a single case study found improved coping skills and motivation [ 40 ]. This patient had also reduced psychiatric symptoms after the MT intervention. In line with this finding, a cultural-based drumming treatment was associated with improved psychiatric and medical status in Native Americans [ 48 ]. In a non-randomized pilot study conducted in an inpatient treatment for dually diagnosed people with SUD and mental illness, Ross et al. [ 15 ] examined relationships between MT variables, psychiatric symptoms, general functioning, aftercare appointment, and motivation measured by the Stages of Change, Readiness and Treatment Eagerness Scale (SOCRATES). They found positive associations between MT appreciation and global functioning during hospital stay. Therapist appreciation was positively related to changes in global functioning and the Taking Steps subscale of SOCRATES measuring active changes. Furthermore, cross-sectional analyses at discharge revealed associations between MT appreciation and Taking Steps as well as between therapist appreciation and the Ambivalence and Taking Steps subscales of SOCRATES. Although MT variables did not directly predict improvement in psychiatric symptoms, the number of attended sessions was positively related to aftercare appointment in a following outpatient program within one week after hospital discharge. With regard to long-term effects beyond the hospital treatment, MT was also associated with sobriety and reduced substance use in another study [ 48 ]. As this pilot sample consisted of a small number of Native Americans not involved in inpatient settings, it remains unclear whether the results are transferrable to other populations. Nevertheless, MT was associated with beneficial behavioral aspects like high involvement, attendance and on-task behavior in several studies [ 42 , 49 , 50 ]. These findings suggest that MT and MBI may be important tools for recovery in line with the participants’ subjective evaluations of treatment effects and perceived helpfulness.
Six qualitative studies examined and described the participants’ reactions, attitudes, and subjective associations in the context of MT and MBI. In four studies, the patients’ behavior during the session was recorded using video-tapes [ 55 , 59 ] therapist’s notes [ 60 , 66 ] and lyric analysis [ 66 ]. Some authors conducted semi-structured interviews [ 57 , 59 ] or used questionnaires that were analyzed qualitatively [ 58 ]. Four general themes were identified: Firstly, music served as a tool for expression of thoughts and feelings. Secondly, in all qualitative studies the role of music and MT/ MBI for group interaction, cohesion, and relationships to others, including the therapist [ 60 ] was emphasized. Thirdly, MT/ MBI were related to the learning of skills regarding music [ 57 ], problem solving [ 66 ], and social interaction [ 59 ]. Finally, MT/ MBIs were associated with benefits for health and quality of life [ 59 ]. In line with the quantitative data, the behavioral observations revealed high engagement and involvement of the participants [ 55 , 59 , 66 ].
In order to address the research question whether music therapy (MT) and music-based interventions (MBIs) are clinically efficient for people with substance use disorders (SUD), we obtained a systematic collection of articles resulting in 34 quantitative and six qualitative studies. Regarding MT/MBI efficacy, we used a descriptive approach to summarize the efficacy evidence of quantitative studies. Furthermore, we summarized effects of exposure to music stimuli, MT and MBIs to describe findings regarding effectiveness. In the following, we discuss these effects, focusing on motivation and on findings regarding the four main themes identified in qualitative analyses. Furthermore, we discuss the quality of the studies. Taken together, the studies do not show clear common effects. Additionally, only few studies have assessed outcomes related to substance use even though such outcomes are critical for treatment success. Thus, variables such as long-term sobriety need to be examined in future studies. Possible mechanisms that may contribute to positive effects of MT/MBI remain to be investigated and specified as well.
There is evidence for the direct impact of listening to music on emotions and craving without application of MT/ MBI [ 61 ]. In addition, frequent listening to relaxing tracks had a beneficial effect on sleep, mood, and treatment completion [ 55 ]. Neuro-imaging studies have demonstrated that music listening engages many brain structures important for cognitive, emotional, and sensorimotor processing [ 69 ], in particular the mesocorticolimbic system [ 70 , 71 ]. Positive short-term effects on variables like craving may reflect benefits for mental health even on a neurobiological level [ 72 ].
Apart from the general impact of music stimuli presentation, participation in single MT sessions may result in additional short-term effects. Those are important to examine because many patients with SUD attend detoxification treatments with a low frequency of therapy sessions [ 3 ]. Single MT sessions appear to be as effective as single verbal therapy sessions for various psychological outcomes (e.g., withdrawal, LOC, craving, client-rated working alliance, and depression), and there were higher scores for MT for comfort [ 31 ], therapist-rated working alliance [ 29 ], and some aspects of change readiness [ 32 ]. These findings support the use of MT in short-term treatments for SUD. Results regarding enjoyment, helpfulness, and motivation differed between studies [ 29 , 31 , 32 ], although these aspects may be especially important in short-time interventions. As they may be related to positive therapeutic experiences, these factors may facilitate the participation in additional interventions. Importantly, the only RCT with follow-up assessment did not find any beneficial effects of single MT sessions on depression, enjoyment, perceived effectiveness and sobriety [ 31 ] after a one-month period. Additional longitudinal analyses of single session effects are necessary.
Lack of motivation is a crucial problem in the treatment of SUD [ 73 ], and beneficial effects of MT and MBI on motivation were commonly described [ 74 , 75 ]. Music itself is motivating and empowering for many people and it has been suggested that engagement in music making may lead to enhanced internal change motivation [ 76 ]. High rates for on-task behavior and engagement reported in qualitative and quantitative studies included in this review support this assumption [ 55 ]. Ten studies quantitatively assessed motivation, and eight of them were RCTs. Most of them investigated single sessions [ 29 – 36 ], and two included longer interventions [ 15 , 38 ]. Despite the positive qualitative reports of patients, not all of these studies identified significant benefits for MT/ MBI. Silverman reported higher treatment and sobriety motivation after MT compared to a wait-list CG with pretest only [ 33 , 35 ], whereas others identified no differences compared to verbal therapy or pretest [ 32 , 34 ]. Different results may be due to different study designs, comparisons or measurement instruments. For instance, a Likert scale for the assessment of motivation revealed similar ratings across groups, whereas the use of a multidimensional scale resulted in higher scores for experimental group than CG in the same sample [ 32 ]. In line with that, most studies with Likert scales did not identify benefits for MT groups [ 32 , 34 , 36 ], whereas the use of some multidimensional instruments revealed significant treatment effects [ 32 , 33 , 35 ]. There is actually no consistent definition for motivation in the context of research on addiction [ 77 ]. Therefore, it is difficult to find an adequate outcome measure capturing all relevant aspects and fitting to the treatment setting. For instance, Silverman [ 33 ] examined treatment motivation and readiness with the Circumstances, Motivation, and Readiness Scales for Substance Abuse Treatment [ 78 ] and did not identify benefits for MT. The use of this instrument as a clinical assessment tool is not recommended [ 77 ] because it was originally developed in the context of a therapeutic community. It is, at this point, not possible to claim that issues with instrument selection are related to incongruence of findings; however, this is certainly an issue worthy of further investigation in future studies.
Prochaska and DiClemente [ 79 ] argued that behavior change always occurs as process with different stages of change, so that differentiating aspects of motivation regarding these stages might be useful. Considering this, beneficial effects of MT on problem recognition, desire for help, treatment readiness, and overall motivation were reported [ 35 ]. Furthermore, there might be a benefit of therapeutic use of music compared to solely music engagement without therapeutic context as MT participants showed higher motivation scores than patients playing a music game instead [ 36 ]. Nevertheless, there were no differences for treatment eagerness in the same study, suggesting that there is need to differentiate between the motivational variables. More RCTs that use the same outcome measures and use the same control group interventions are needed to draw further conclusions.
Examining more than one session of MT, K. M. Murphy [ 38 ] did not identify benefits in motivation for patients with an additional GIM intervention compared to those with standard program only. Because this study did not include a sufficient amount of participants ( N = 16), long-term effects on motivation should be systematically examined in larger samples in more detail.
In many studies, MT/ MBI had beneficial effects on mood and emotions, i.e., positive mood change, decreased negative emotions, e.g., anxiety, depression, and anger, and increased positive feelings, e.g., enjoyment and happiness. This is in line with the importance of MT for the expression and regulation of feelings, as identified in our qualitative analyses. MT provides opportunities for the exploration and expression of feelings without drugs and appears to be a non-threatening intervention [ 80 ]. Therapist-selected songs as well as songs written or selected by the participants themselves contain aspects related to feelings [ 33 ]. Many music therapy studies have demonstrated that songs may be used as a verbal and nonverbal tool for the exploration of feelings [ 12 , 16 , 46 , 81 , 82 ]. Jones reported that over the course of lyric analysis and songwriting interventions, emotional expression appears to increase, and suggests that positive mood changes may have a positive influence on further treatment-related variables such as therapeutic alliance [ 46 ]. Additionally, support by other group members may facilitate emotional expression [ 50 ]. Nevertheless, it should be noted that for many emotional variables (e.g., anxiety, anger, sadness) RCTs are needed to assess MT/ MBI efficacy.
Qualitative analyses suggested that MT/ MBI provide opportunities to learn in various areas. Many patients with SUD have poor psychosocial skills, which improved over the course of MT/ MBI [ 46 , 59 ]. M. Murphy [ 83 ] has suggested that music, as part of the participants’ everyday life, is adaptable to low levels of psychosocial functioning, and group interventions may be helpful in reducing social isolation. According to Ghetti [ 76 ], in group music therapy sessions, the therapist structures the active music making purposefully to enable group interaction in a non-threatening atmosphere. Successful group interactions in music making may help to develop social and problem solving skills. Furthermore, discussion of lyrics of popular songs can help enhance understanding of the individual’s dynamics regarding substance use and may lead to the development of more healthy coping strategies [ 76 ]. Only very few studies examined effects of MT/ MBI on cognitive abilities quantitatively. In contrast to the findings reported in qualitative studies, in RCTs no positive effects of MT on coping abilities could be identified [ 36 , 38 ], and also no effects of MBI on cognitive functioning were reported [ 48 ]. In contrast to that, a single case study showed enhanced coping after individual sessions [ 40 ]. However, these studies differed with respect to many variables, e.g., age, drugs, MT/ MBI methods, and duration so conclusions regarding treatment effect cannot be drawn at this time.
As internal change motivation is a critical aspect for the treatment of addictions, effects of MT/ MBI on locus of control (LOC) were examined as well. After a single session, MT participants did not differ regarding LOC compared to a verbal therapy group [ 30 ]. Furthermore, in an experimental setting examining effects of music stimuli presentation, increased internal LOC depended on the context [ 65 ], but after longer MT interventions, enhanced internal LOC was identified [ 20 ]. These results suggest that MT/ MBI may lead to increased internal LOC over time. When patients experience that their own abilities and actions determine what happens [ 84 ] during MT/ MBIs, this may be transferred to life outside the therapy setting and result in better outcomes of addictions’ therapy in the long term [ 85 ]. Typically in MT, music experiences are carefully structured and supported by the music therapist to enhance the potential for positive experiences by the patient [ 86 ]. This may lead to positive effects of MT on factors such as self-esteem [ 87 ] or self-efficacy [ 88 ]. However, it is important to acknowledge that asking patients to engage in music making may lead to some anxiety and insecurity as well for some patients, as has been reported in studies outside of the SUD population [ 89 ]. However, no studies to date have directly examined the relationship between mastery in music therapy and long-term treatment outcomes for patients with SUD. More research is necessary to explore this possible mechanism.
Positive group dynamics were identified as important motivators in all qualitative studies. Over the course of the intervention, behavioral observations revealed increased exchange and cohesion [ 57 , 59 , 66 ]. Nevertheless, in their study with offenders in a substance abuse/mental illness treatment program, Gallagher and Steele [ 49 ] reported that 53% of their participants were “not sociable” (p. 121). For planning of the sessions, clinicians need to keep in mind that many patients with SUD have poor social skills. However, none of the quantitative studies in our review systematically examined group-related variables, so future research should examine social skills or aspects like group cohesion. Summarizing studies with respect to the outcome cluster, participation reveals a lack of studies of high level evidence of efficacy regarding this topic as well.
Regarding working alliance between therapist and patients, beneficial effects from the therapist’s perspective were identified quantitatively [ 29 ] as well as qualitatively [ 60 ]. By contrast, patients attending MT did not perceive a better working alliance compared to a verbal therapy CG [ 29 ]. This is in line with previous studies identifying weak reliability between therapist-rated and patient-rated working alliance in drug treatment [ 90 ]. Regarding the relationship between different perspectives of working alliance and therapeutic success, results are not consistent: Some studies found stronger relationships between the counsellor’s/ therapist’s view and success [ 90 – 94 ], whereas in other studies the patient’s view was identified as a more important predictor [ 95 ] or both measures were only weakly correlated with success [ 96 ]. Furthermore, levels of working alliance had different effects on outcome for different types of therapies [ 97 ]. These inconsistent results indicate that working alliance may be more complex and depend on many aspects. As most of the studies emphasized the importance of the therapist’s view, especially ratings at early time points after starting the therapy [ 98 ] as examined by Silverman [ 29 ], working alliance should be examined in further MT studies.
In many studies, MT and MBI were associated with a great amount of perceived enjoyment and also reported to enhance quality of life and improve health [ 59 ]. In line with this, longer MBI were related to positive psychiatric and medical outcomes [ 40 , 48 ]. Nevertheless, these investigations were conducted in very specific settings, so that there is still a lack of studies examining health-related and long-term variables in common treatments for SUD. Especially, variables related to substance use are understudied. Furthermore, all studies examining medical symptoms were categorized as of low level evidence of efficacy in our descriptive summaries. Thus, high quality evidence has not been conducted.
Our descriptive summaries considered the quality of the identified studies and revealed that in the last years, since the review of Mays et al. in 2008, more RCTs were conducted. Thus, for outcomes like motivation, depression, enjoyment, withdrawal and craving, perceived helpfulness, working alliance, and locus of control studies of high level evidence of efficacy already exist. Nevertheless, we did not calculate meta-analyses due to study heterogeneity or because similar variables were only examined by the same author. Furthermore, across all studies included in our descriptive approach, still only 38% (25/65) were RCTs, and especially for mood variables and long-term abstinence, high quality research has not been conducted. Due to the low quality of most of the studies, in the end, strong key outcomes cannot be substantiated.
It is important to consider that in studies that examine the impact of group interventions, the independence of observations, a common assumption for standard statistical tests, may have been violated because of interactions between group members. This may have resulted in biased standard errors and erroneous inference [ 99 ].
In Table 6 , methodological recommendations are summarized that are aimed at helping to overcome issues in future research. Most importantly, studies should investigate long-term outcomes such as abstinence and use randomized controlled trial designs. In order to reduce problems related to the independence of observations, hierarchical analyses taking into account the group structure of the data or cluster randomization should be applied. However, designing and executing of cluster randomized trials is difficult because for example larger sample sizes are needed or recruitment bias could occur [ 100 ].
• Inclusion of long-term outcome variables such as abstinence and attendance of aftercare treatment programs |
• Hierarchical data analysis |
• Studies with randomized-controlled trial designs, and if randomization is not possible in the clinical context at least inclusion of a control group |
• For all types of studies reports about characteristics of the interventions, studies and participation with transparent information about statistical procedures |
• Reports of standardized effect sizes |
• Inclusion of outcome variables related to skills (e.g., cognitive abilities), group dynamics and relationships (e.g., group cohesion, working alliance), and life quality and health (e.g., medical symptoms, general functioning) |
• Use of standardized measurement instruments suitable for addiction and music therapy contexts |
• Inclusion of external researchers who are not interventionists |
If in the clinical context randomization is not possible, studies should at least include control groups as reference frameworks. In within subjects designs aimed at examining pre to post MT/MBI intervention improvements in functioning, one needs to consider that the statistical regression to the mean may be an explanation for the patients’ improvement. Including a control group may solve this issue. Studies of low level evidence of efficacy can be useful for generating hypotheses, getting information about subjective experiences, exploring effects on individual levels, or assessing the ecological validity of treatments [ 25 ]. Thus, we also included them in our review, but in 50% of these non-RCT studies (20/40), the results were reported without sufficient statistical information. Furthermore, across all studies, reports about characteristics of intervention, studies and participants varied widely, so that giving a transparent overview and comparing the studies regarding these aspects was difficult. In addition to that, only few studies reported standardized effect sizes [ 31 – 37 , 39 , 41 ], so the effects of MT/ MBI could hardly be interpreted and compared across studies. Therefore, we recommend the inclusion of reports that clearly describe characteristics of intervention, studies and participants, including diagnostic criteria, transparent information about statistical procedures, and all necessary statistical data (including effect sizes) according to the guidelines of the Task Force on Statistical Inference [ 101 ] in the articles. In addition to that, as described in the paragraphs above, high-quality research for outcomes related to skills, group interaction and relationships has not been conducted although these aspects are important topics mentioned in qualitative research. Thus, future studies should investigate variables such as cognitive abilities, group cohesion or medical symptoms among others. Measurement instruments for the same outcomes widely varied across studies (e.g., Likert scales vs. standardized tests) and they mostly captured different aspects, so comparisons were difficult. Therefore, in future research authors should use the same standardized measurement instruments that are suitable for the addiction and music therapy context. Furthermore, the researcher often acted also as music therapist and collected the data which may lead to procedural bias (such as Rosenthal effect [ 102 ]) or response bias in the data. It also remains unclear whether effects are due to the music therapy or the person of the music therapist. To reduce these tendencies, we recommend the inclusion of external researchers for data collection and analysis.
There is still no consensus regarding the effects of music therapy (MT) and music-based interventions (MBI) for patients with substance use disorders (SUD). Previous reviews [ 21 , 22 ] highlighted the need for more randomized controlled trials (RCTs) regarding long-term outcomes like maintenance of sobriety. The current literature includes additional RCTs, but most of them focused on short-term effects after single sessions in detoxification units. One RCT examined sobriety after a one-month period without significant differences between a single session of MT or group verbal therapy [ 31 ]. The only study examining abstinence after more than one session was conducted with one specific ethnic group without inpatient participants [ 48 ]. Therefore, future studies should include long-term investigations and follow-up measurements, in particular regarding variables related to substance use. Due to the great fluctuation in SUD treatments, planning of these studies may be a challenge. However, reduction of substance use and abstinence are critical aspects regarding the success of addictions’ treatment, so evaluations of treatment effects for these outcomes are necessary for future investigations. MT/ MBI appeared to be effective in the regulation of emotions and subjective outcomes, as also indicated by qualitative analyses. Nevertheless, the quantitative studies in our review were very diverse which was one important reason for not conducting meta-analyses. As MT/ MBI are commonly and specifically used in the treatment of groups and subgroups with SUD, e.g., women or adolescents [ 8 ], it is important to examine its efficacy and effectiveness in these specific populations as well. However, these results may not be generalizable across general SUD settings. Additionally, it is important to be aware that music can also trigger relapse (e.g. if the music is associated with substance abuse [ 61 ]), and that, therefore, music has to be used with great care in SUD patients.
Regarding limitations of the current review it must be noted that collecting the characteristics of the studies was particularly difficult because of missing information. We did not consider the patients’ additional diagnoses and treatment options, methods or specific therapy goals. These topics could be included in future reviews to provide additional insights in characteristics of effective MT/ MBI/ MP. Due to the small number of MT studies, separations regarding these aspects are currently not useful. Whereas this systematic review summarizes the available evidence in terms of treatment efficacy, it does not provide information about potential mechanisms of action of MT/ MBI for SUD. Furthermore, a methodological review of MT/ MBI/ MP and SUD studies may be warranted in the future. For example, studies could be codified regarding methodological strengths and weaknesses to make further methodological recommendations with respect to the investigation of concrete outcomes.
From a methodological point of view, future studies examining the efficacy of MT/ MBI/ MP for patients with SUD should include RCTs, so that meta-analytic calculations will be possible. Regarding content and outcome variables, future studies should consider including outcomes related to the qualitative findings as well as variables related to substance abuse so that a comprehensive picture of the efficacy of MT/ MBI/ MP can be drawn. In addition, we urgently need mechanistic studies that identify and examine the impact of potential treatment mediators and moderators. Additionally, the effects on problem solving, cognitive, and coping abilities and the role of MT/ MBI/ MP for different stages of motivation should be clarified. Furthermore, effects of the interventions on long-term medical and psychiatric outcomes, treatment retention and completion should be examined, while considering additional moderating and mediating variables like MT appreciation. Based on these findings, implications for future MT/ MBI as independent or adjunctive treatment programs for SUD can be developed. As individual preferences regarding music and MT as well as group dynamics appeared to be important for the success of MT [ 21 ], careful group composition and selection of materials are necessary. All in all, due to its high acceptance, flexibility, easy accessibility and low costs, MT/ MBI provide opportunities for SUD treatment for various groups in various settings. Nevertheless, its efficacy and effectiveness have to be evaluated more systematically and should focus on further long-term outcomes.
Funding statement.
The authors received no specific funding for this work.
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I feel unsettled when I stream music on Spotify. Maybe you feel that way, too. Even though it has all the music I’ve ever wanted, none of it feels necessarily rewarding, emotional, or personal. I pay a nominal fee for this privilege, knowing that essentially none of it will reach the artists I am listening to. I have unfettered access to an abundance of songs I genuinely love, along with an abundance of great songs I’ve never heard before, but I can’t shake the eerie feeling that the options before me are almost too perfect. I have personalized my experience enough to feel like this is my music, but I know that’s not really true—it’s simply a fabricated reality meant to replace the random contours of life outside the app.
The truth is that if you’re using Spotify, Apple Music, Tidal, or any other streaming service, you’re not paying for music so much as the opportunity to witness the potential of music. Music becomes an advertisement for the streaming service, and the more time and attention you give it, the more it benefits the tech company, not necessarily the music ecosystem. In Spotify, each song’s play count is prominently displayed, in effect gamifying the music industry so that tracks tacitly compete against one another inside the app. They even go so far as to turn the amount of time you spend in their app into a badge of honor during their annual year-end promotional campaigns. So you’re in the top percentile of Big Thief listeners? That’s not just a measure of your love for an artist’s music , but also a reflection of the time spent enriching the value of a company.
In addition to co-opting corporate social media strategies to benefit from the attention economy, tech companies have inherently made songs fleeting, cheap, and sometimes intrusive , corrupting the cultural exchange between artist and listener. Music is now leased to you through a secret system that you don’t understand, by a company with which you should have no emotional connection. Instead of simply buying a physical product or even pirating music from Napster—both of which created uniquely personal libraries of songs that helped define the identities of a generation—millions of users now sit side by side at the ledge of one great big trough of recorded music for the monthly price of a Chipotle burrito.
There have been many passionate and excoriating essays written about how streaming services have short-changed artists with minuscule payouts. But as the reviews editor of this music publication, I find myself asking: What does a platform like Spotify afford the most engaged music fans and what are the lingering effects of its use? As the independent musician and writer Damon Krukowski once wrote, there are alternative and radical solutions to combat the upstreaming of profits and homogenization of sound that the streaming era has come to stand for. But as one of nearly half a billion people who pay a small fee to rent the vast majority of the history of recorded music—not to mention the 2 billion people per month who use YouTube for free—I have found that, after more than a decade under the influence, it has begun to reshape my relationship with music. I’m addicted to a relationship that I know is very bad for me.
I know I am addicted to Spotify the same way I was addicted to nicotine or Twitter. It makes me happy, aggrieved, needlessly defensive. Oh, you boycott Spotify and only buy CDs on Bandcamp? Good for you. I use Spotify every day for hours on end, when I’m working, at the gym, running, when I want to put some music on while making dinner, when I go to sleep.
I write off part of my Spotify use as a hazard of my job, but I just can’t get enough of that sweet streaming asbestos outside of work, too. Even though I buy a fair amount of records every year, Spotify is my main delivery system for music. It’s like being hooked on rolling papers or the yellowed smell of a casino—not the actual vice itself. The ease, the look, the familiarity—I’m addicted to the emotional labor it does for me when its “Radio” feature instantly creates a playlist of songs that kind of sound like, say, “Breakdown” by Tom Petty and the Heartbreakers while I’m sitting outside on a nice afternoon. It loosely organizes what I love and what I might love and, for the most part, it’s absolutely correct.
I’ve sometimes rationalized that it is not an unhealthy addiction: I use Spotify in a way that reflects who I am, I bend it to my whims. For the last 10 years, I have kept playlists of favorite songs—both old and new—I discovered each year, a living record of growth and change in taste. I listen to weekly playlists that are made by friends and colleagues and artists, silently connecting with their interests. I’m going beyond the algorithm, operating at a higher frequency, clipping between the walls that cannot contain my taste profile.
The seeds of this addiction were planted in the late 2000s, when the music industry was struggling to adapt to the new digital era, unsure of how to wrap a tourniquet around the vast hemorrhaging of money caused by such a fast-moving paradigm shift. The streaming era as we know it began in an unlikely place, with good intentions: On October 10, 2007, Radiohead released In Rainbows and allowed fans to pay what they wanted for its digital files. After 1.2 million downloads, the average price paid per album was $2.26. Case studies in setting a new market price don’t come in a tidier package than this.
But as free-market and egalitarian as it was, the experiment was meant to motivate fans to go out and buy an actual physical copy of the album. Devised by Radiohead’s managers Bryce Edge and Chris Hufford while they were “a bit stoned,” the pay-what-you-want stunt was a means to an end: “If we didn’t believe that when people hear the music, they will want to buy the CD, we wouldn’t do what we are doing,” Edge said at the time. A lot of Radiohead fans did buy the album when it came out—it sold 122,000 copies in America alone in its first week—but by then, the downloaders outnumbered them by a wide margin. So even though Thom Yorke later described Spotify as “the last desperate fart of a dying corpse,” his band all but invented the model of what would become the streaming era: turning music into an ad that you pay very little for, with no real incentive to go and buy what it is advertising.
Another important shift was happening in 2007. Seeing the writing on the wall, several high-profile artists were abandoning their longtime major labels to find other avenues of distribution: Madonna left Warner to sign with touring giant Live Nation, a bellwether of where the real money was being made in the industry. (JAY-Z would make a similar move the following year.) Nine Inch Nails left music mogul Jimmy Iovine’s label Interscope and independently put out an instrumental album, Ghosts I-IV ; by Trent Reznor’s estimation, the collection made millions more than it would have had they released it with the label.
Into this stew of major label woes—which included the lingering piracy boogeyman—came Spotify. Launched in 2008, the streaming start-up was a direct attempt to both stem piracy and circumvent anti-piracy laws in its native Sweden. In addition to offering a way for online listeners to legally play music, Spotify acquired its user base in markets around the globe because of how easy it was to use. No more paying per song on iTunes, no more navigating the murky waters of P2P servers, no more waiting for albums to download. Here, finally, was a solution: legal music, a lot of it, right now, for cheap.
After officially launching in the U.S. in 2011, Spotify quickly turned into a potential panacea for everything that was ailing the music industry. Two years later, newspapers were asking: Can Spotify Save the Music Industry? A race to market dominance ensued. By 2014, Reznor had mended fences with Iovine and became the chief creative officer of Iovine’s new streaming platform, Beats Music, which wanted to set itself apart from competitors like Spotify and Pandora. Instead of an algorithmic platform that served you what you wanted, its team of curators would provide you with a more human experience. Iovine saw that, through artist and influencer-created playlists, you could confer taste, status, and criticism—the stuff that the former record-buying public supposedly pined for. One of Iovine’s maxims at the time: Access is average; curation is everything. Seeing the promise of a more bespoke streaming experience, Apple bought Beats for $3 billion and relaunched the service as Apple Music in 2015.
That same year, JAY-Z stood on a stage with Madonna, Rihanna, Daft Punk, Kanye West, and several other A-list musicians to announce the artist-majority-owned service Tidal, with “a mission to re-establish the value of music.” Touting hi-fi streaming and better payouts for artists, Tidal seemed like a much-needed counterweight to Apple Music and Spotify. Finally, here was a platform not funded by Silicon Valley VCs but by (admittedly already wealthy) musicians who understood the art and work that goes into the process of creation. But since its launch, its growth has lagged dramatically behind its competitors. Last year, JAY-Z sold the majority of Tidal to Square, a mobile payment company owned by Twitter founder Jack Dorsey.
Each successive introduction of a new tech company into the streaming era sought to solve a problem created by the digital era: pirating, the devaluation of music, and the lack of human connections music once relied upon. At this point, music piracy has generally been on the decline for five years. Major labels have plugged the holes in their coffers by licensing the vast majority of their music to streaming services and meting out payouts to their signees. The exception has always been the independent-minded Bandcamp, which includes a Radiohead-style pay-what-you-want option at a record’s point of sale, and fosters holistic connection between musicians and listeners through hubs run by labels and artists. Earlier this year, Bandcamp was acquired by the software company Epic Games.
Much like social media, the streaming era has created a simulation of real life. Each company uses its technology to digitize and replace the analog practice of buying, listening, and connecting to music, all while capitalizing on the nostalgia of those activities. The seamlessness of the experience—the ease with which one song bleeds into the next, and the buffet of decisions laid before you on Spotify’s home screen—creates an artificial scarcity out of vast abundance. For me, it has caused a kind of nagging depersonalization, an experience so divergent from, say, holding an album in my hands, or being in a record store, that I feel like a little bit of a hack every time I open the app. But I also understand that for the majority of subscribers, this simulation of a beautiful, vibrant, limitless music industry is possibly all they could ever want.
Let’s say there are three general categories of music listeners: Passive, Auxiliary, and Intentional. Most of the world falls into the Passive category, absorbing music like inhaling oxygen: without much thought at all. For them, there is either music playing, or maybe it’s not music playing, who can be sure? There is perhaps little to no interrogation into why any sound is floating down from the speakers at the grocery store; it simply exists at the same megahertz as the shopping cart and the fluorescent lights and the cereal selection. Songs are liked and not liked, if they are thought about at all, and the whole relationship is pure and elegant.
The second is the Auxiliary listener, someone for whom music enhances a primary experience to make it more interesting. Common forms of auxiliary listening involve music accompanying a visual stimulus, like film scores or needle drops in movies, music videos or their modern-day equivalent: a song snippet looped in a TikTok. But the Auxiliary listener chiefly uses music as a utility: to relax, to work, to go to the gym, to get drunk, to do drugs, to have sex, to dance, to fall asleep. Music is not your life, but what was playing while you lived it.
The last is the Intentional listener, someone who chooses to listen to music for the pleasure of it in and of itself. This is admittedly the tiniest category of people, a subset that spends a remarkable amount of time listening to albums, mixtapes, DJ sets, and playlists without distraction. They are purposeful about what they select and why—for them, there is a pleasure to be found in the flow of listening to music and the emotional, intellectual, and biographical response that it creates untethered to anything but the chemical responses in the brain. Some of these people use drugs to enhance this connection, but not all of them. Music, for these people, is life.
It’s important to make these distinctions because I believe that, for Passive and Auxiliary listeners—again, the vast majority of people in the world —Spotify and the streaming era writ large have achieved an ideal compromise. The technology has made accessible what had previously been difficult or kept behind the gates of record stores or music criticism. For an older generation, there is a sudden and overwhelming pleasure in being able to listen to all the music from your life instantly, retracing the decades through a digital library.
The cognitive dissonance occurs when people in the Intentional group—people like me—try to tell people in the Passive and Auxiliary groups how to listen to music. I know the global financial devaluation of music is irreversible, and there are only a small percentage of total music listeners for whom the phrases “buy from brick-and-mortar stores” or “support Bandcamp Fridays” means anything. But what I fear is that the streaming era is actually writing the same listening histories for those who can’t be bothered with Intentional listening–all exclusively based on proprietary algorithms that seem like a way to discover music but, in fact, act more like a feedback loop.
A close friend, an Auxiliary listener, recently sent me a Spotify link to an album by classic rock revivalists Greta Van Fleet, noting that it would be good music for the gym. This sent me into a bit of a panic spiral for three reasons. One is that I wondered why I neglected to share my professional life with him: In 2018, my pan of their debut album drew the attention of those beyond Pitchfork’s usual purview, with Barstool Sports suggesting that the band must have “fucked my girlfriend,” and GVF fans threatening to “TP” my house via homemade signs they held up at concerts. The second is that I realized I am but a tiny little dust mite in the universe, and my own opinion on Greta Van Fleet is largely irrelevant beyond the scope of a few thousand music snobs and select GVF fans, and what’s actually important in the world is the bond close friends have despite these relationship glitches. Third is that Spotify knows me better than my close friend.
The more time I spend on Spotify, the more it pushes me away from the outer edges of the platform and toward the mushy middle. This is where everyone is serviced the same songs simply because that is what’s popular. Four years ago, while the app’s algorithmic autoplay feature was on, I was served the Pavement song “Harness Your Hopes,” a wordy and melodic—and by all accounts obscure—B-side from the beloved indie band. As of this writing, the song has over 72 million streams, more than twice as much as their actual college rock hit from the ’90s, “Cut Your Hair,” the one Pavement song your average Gen X’er might actually recognize. How did this happen? In 2020, Stereogum investigated the mystery but came up empty-handed from a technological perspective, though the answer seems obvious to me: Whereas many Pavement songs are oblique, rangy, and noisy, “Harness Your Hopes” is among the most pleasant and inoffensive songs in the band’s catalog. It is now, in the altered reality of Spotify, the quintessential Pavement song. When frontman Stephen Malkmus was asked about this anomaly, he sounded blithely defeated: “At this point we take what we can get, even in a debased form. Because what’s left?”
The whole “Harness Your Hopes” situation is in part a result of what’s called “cumulative advantage.” It’s the idea that if something—a song, a person, an idea—happens to be slightly more popular than something else at just the right point, it will tend to become more popular still. (On the other hand, something that does not catch on will usually recede in popularity, regardless of quality.) This is the metric of how most social recommendation algorithms work—on Facebook, the more “likes” an article has, the better odds a user will read it. But when this is applied to what songs are sent to which people, Spotify can engineer its own market of popularity as well as what song defines a band. Popular songs on Spotify are popular within the app because they are what most people are listening to. So from both a behavioral psychology and business perspective, it makes sense for Spotify to assume that you want to listen to what other people are listening to. The chances of the average listener staying on the app longer are much higher if Spotify curates songs that have had a similar effect on people whose taste matches theirs.
This is one of the main addictive chemicals of most streaming services: Recommend a handful songs—out of millions!—that feel uniquely personal but in fact are just what everyone else is hearing, too. If a Passive or Auxiliary listener lets the algorithmic Spotify Radio play songs based on Tom Petty’s “Breakdown,” the results are almost purely based on chronology, tempo, and feel. Gone are the filigrees and the autobiography of the song and how it existed in the world to you , the listener. Instead, everyone’s experience is now the same.
For instance, Spotify’s radio station for Ludacris’ “What’s Your Fantasy” doesn’t link to any OutKast songs, even though I watched Ludacris open for André 3000 and Big Boi when that song was released in 2000, and both acts are from Atlanta. Is Spotify aware that Big Boi is a huge Kate Bush fan? Does Spotify know that singer-songwriter John Darnielle of the Mountain Goats is a metal head? If you have seen Darnielle cover metal bands from Dio to Gorguts to Nightwish, or are familiar with one of his most popular songs, “The Best Ever Death Metal Band Out of Denton,” you know that he loves some sick riffs and moonward barks. But all of that intimate (and publicly available) knowledge is lost to machine learning. Tuning into Spotify’s Mountain Goats’ Radio won’t turn up any Dio at all—just literate and mostly acoustic indie rock songs that sound similar to the Mountain Goats. Left to a streaming service, these kinds of textured and unique connections are smoothed over or erased entirely.
I have committed my personal and professional life to making sense of music, of finding connections and context within songs to create a critical framework that allows me to organize everything I listen into an ornately chaotic web. If I started a Fugazi radio playlist, maybe I would throw some Red Hot Chili Peppers on there—you’ll hear it. If I started a Pavement radio playlist, how could I not include the Louisiana rapper Young Bleed’s song “How Ya Do Dat,” where he calls himself “ slanted and enchanted ”? I would argue that Prince’s “When Doves Cry” and Parquet Courts’ “Instant Disassembly” both utilize a stilted, inverted grammatical style in their lyrics and are absolutely in conversation with each other.
When music is so abundant and our attention is scarce, there’s power in adding more intention to your listening diet, more chaos, more risk. The thrill in finding music that is wired to your singular life is not that thousands of other people have found the same thing. It’s that the music becomes something confounding and unique, a true reflection of where you are and where you’ve been. The beauty of the algorithm of your mind is that it makes perfect sense to no one but yourself.
This week, we’re exploring how music and technology intersect, and what today’s trends and innovations might mean for the future. Read more here .
Students are often asked to write an essay on Addiction in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.
Let’s take a look…
Understanding addiction.
Addiction is a strong desire to do something repeatedly, even if it’s harmful. It’s like a brain disease. People can get addicted to different things like drugs, alcohol, or even activities like gambling.
People can get addicted for many reasons. Some may feel good when they do something, so they repeat it. Others may want to escape from problems or stress. Sometimes, it’s because of peer pressure or trying to fit in.
Addiction can harm a person’s health. It can lead to diseases, mental problems, and even death. It can also ruin relationships and cause problems at work or school.
Overcoming addiction is hard, but possible. It needs strong willpower and often help from doctors or therapists. Support from family and friends is also important. Remember, it’s okay to ask for help.
250 words essay on addiction, what is addiction.
Addiction is when a person can’t stop doing something, even if it’s harmful. It can be about drugs, alcohol, games, or even food. The person knows it’s bad but can’t stop. It’s like a strong pull that keeps them going back.
Addiction often starts with trying something new. This could be a friend offering a cigarette, or playing a new video game. At first, it seems fun and exciting. But over time, the person starts needing it more and more. It becomes a need, not just a want.
Addiction can hurt a person in many ways. It can make them sick, or cause problems at school or work. It can also hurt their relationships with family and friends. They may lie or steal to keep doing what they’re addicted to. This can lead to feelings of guilt and shame.
Fighting addiction is hard, but not impossible. It starts with admitting there’s a problem. Then, the person needs help from professionals like doctors or counselors. They can give advice, medicine, or therapy to help the person quit. Support from family and friends is also important.
Remember, it’s okay to ask for help. Everyone struggles with something at some point. With the right help and support, anyone can overcome addiction.
Addiction is a serious issue that affects many people around the world. It is a state where a person cannot stop using a substance or engaging in a behavior, even if it is harmful. The person becomes dependent on the substance or the activity to feel good or normal.
Addiction can be of two types: substance addiction and behavioral addiction. Substance addiction involves drugs, alcohol, nicotine, or other substances. Behavioral addiction involves activities like gambling, eating, or using the internet.
Addiction has a negative impact on a person’s health, relationships, and daily life. It can lead to physical health problems like heart disease or mental health issues like depression. Addiction can also strain relationships with family and friends and make it hard for the person to perform well at school or work.
Overcoming addiction is not easy, but it is possible with the right help and support. This can include professional treatment like therapy or medication, as well as support from loved ones. It is important for the person to learn healthy ways to cope with stress and other triggers that may lead to addictive behavior.
In conclusion, addiction is a complex issue that requires understanding, support, and prevention efforts. It is important for everyone to be aware of the signs of addiction and to seek help if they or someone they know is struggling. Remember, overcoming addiction is possible with the right help and support.
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500 words essay on addiction.
As we all know that excess of anything can be very dangerous, the same way, addiction of any kind can hamper the life quality of an individual. The phrase states that addiction is a family disease as one person uses and the whole family suffers. The above statement stands true in all its essence as the addict does not merely suffer but the people around him suffer greatly too. However, that does not mean they can’t be helped. Addiction is curable and we must not give up on the person who is addicted, rather help them out for a better life.
Addiction comes at a great cost and we need to be able to recognize its harmful consequences to not let ourselves or anyone become an addict. Firstly, addiction has major health hazards. Intake of anything is bad for our body , and it does not matter what type of addiction it is, it will always impact the mental and physical health of a person.
For instance, if you are addicted to drugs or food, you will get various diseases and illnesses. Similarly, if you are addicted to video games, your mental health will also suffer along with physical health.
Moreover, people who are addicts usually face monetary issues. As they use that thing in excess, they spend loads of money on it. People become obsessed with spending all their fortunes on that one thing to satisfy their addiction. Thus, all these addictions of drugs , alcohol , gambling, and more drain the finances of a person and they usually end up in debt or even worse.
Furthermore, the personal and professional relationships of addicts suffer the most. They end up doing things or making decisions that do not work in their favor. This constraint the relationships of people and they drift apart.
Moreover, it also hampers their studies or work life. When you are spending all your money and time on your addiction, naturally your concentration levels in other things will drop. However, all this is not impossible to beat. There are many ways through which one can beat their addiction.
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It is best to work towards beating your addiction rather than getting beat by it. One can try many ways to do so. Firstly, recognize and identify that you have an addiction problem. That is the first step to getting cured. You need to take some time and understand the symptoms in order to treat them. Motivate yourself to do better.
After that, understand that the journey will be long but worthwhile. Identify the triggers in your life and try to stay away from them as far as possible. There is no shame in asking for professional help. Always remember that professionals can always help you get better. Enroll yourself in rehabilitation programs and try to make the most out of them.
Most importantly, do not be hesitant in talking to your loved ones. Approach them and talk it out as they care most about you. They will surely help you get on the right path and help you in beating addiction for better health and life.
Q.1 What are the consequences of addiction?
A.1 Addiction has very severe consequences. Some of them are health hazards, monetary issues, relationship problems, adverse problems on studies and work of a person. It seriously hampers the quality of life of a person.
Q.2 How can one get rid of addiction?
A.2 A little help can go a long way. One can get rid of addiction by enrolling in rehabilitation programs and opening up about their struggle. Try to take professional help and talk with your close ones to become better.
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The concept of "musical addictivity" has previously been proposed, arguing that music activates the reward centers of the brain and thus can lead to behavioral addiction. Recent studies support this idea for music consumption. However, there has not been any research on whether these findings could be transferred to music practicing so far. Anecdotal evidence has shown that some musicians ...
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The seeds of this addiction were planted in the late 2000s, when the music industry was struggling to adapt to the new digital era, unsure of how to wrap a tourniquet around the vast hemorrhaging ...
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500 Words Essay on Addiction. As we all know that excess of anything can be very dangerous, the same way, addiction of any kind can hamper the life quality of an individual. The phrase states that addiction is a family disease as one person uses and the whole family suffers. The above statement stands true in all its essence as the addict does ...