Music Therapy Practice with High-Risk Youth: A Clinician Survey/Pratique De la Musicothé Rapie Avec Les Jeunes À Risque: Un Sondage Clinique
Bibliographic record
Abstract
Studies in music therapy and allied professions indicate that music-based interventions by music therapists, social workers, and other health professionals are effectively assisting youth with a diversity of needs (Baker & Jones, 2005; Currie, 2004; Dalton & Krout, 2005; Frank, 2005; Keen, 2004; Tervo, 2001). Music therapy is used in mental health, oncology, substance misuse, and bereavement programs for adolescents (Albornoz, 2011; Faulkner, 2011; McFerran, 2010; McFerran, Roberts, & O'Grady, 2010; McFerran-Skewes, 2004; Roth & Kees, 2007). Research published in Canada and the United States document that at-risk or aggressive youth and youth offenders are also benefiting from music therapy programs (Barrett & Baker, 2012; Buchanan, 2000; Camilleri, 2007; Evans, 2010; Gladfelter, 1992; Rickson & Watkins, 2003; Rio & Tenney, 2002; Snow & D'Amico, 2010; Wyatt, 2002]. Programs designed to meet the needs of youth refugees and youth involved in gangs, as well as those experiencing schizophrenia, trauma, and body image issues, are discussed in the music therapy literature as well (Baker & Jones, 2005; Fouche & Torrence, 2005; Frank, 2005; Ruutel, 2004, Smith, 2012).Authors of several of these studies used the terms at risk or high risk to describe their clientele (Buchanan, 2000; Camilleri, 2007; Nelson, 1997; Smith, 2012; Snow & D'Amico, 2010]. While these terms were used without a standard definition, they generally referred to youth who were served by programs dealing with mental health issues, substance use, and street involvement as well as youth who were in correctional programs (Keating, Tomishina, Foster, & Alessandri, 2002; Springer, Sale, Herman, Soledad, Kasim, & Nistler, 2004; Ungar & Teram, 2000). These issues often overlap, making it difficult and impractical to separate them.Therefore, the term high-risk youth may be used as a general term to describe a cohort of youth that is distinct from the general population and can be differentiated from those whose primary needs are developmental, educational, physical, or medical in nature. In this study high-risk youth were defined as those likely to experience a decline in their global functioning due to one or more issues related to mental health, substance use, or other social, economic, or cultural disadvantages. These included correctional system involvement, street involvement, or an unstable home environment.Music Therapy and High-Risk YouthAn informal review conducted by the authors in 2007 ofthe music therapy and allied health research literature revealed 37 studies reporting the use of music with youth who met this study's definition of high risk. These studies varied in their settings, subpopulations, assessment methods, and therapeutic interventions. The earliest study found was published in 1969, and a cluster of 15 articles and one dissertation were published between 2000 and 2007. The databases searched included RILM Abstracts of Music Literature, PsycINFO, PsycARTICLES, ProQuest Dissertations & Theses, ProQuest Research Library, Wilson Select Plus, CINAHL, Social Sciences Abstracts, and MEDLINE. These sources provided a foundation for understanding the specific populations with which clinicians were working as well as the clinical needs, assessment methods, treatment goals, and interventions they were using.The settings for these studies were primarily hospitals and residential treatment programs, but since 2000 there has been a decrease in studies done in hospitals and an increase in other settings, namely schools (Currie, 2004, Dalton & Krout, 2005; Jones, Baker, & Day, 2004), private practice (Hendricks & Bradley, 2005; Keen, 2004), and community-based programs (Buchanan, 2000; McFerran-Skewes, 2004; Fouche & Torrence, 2005).The specific subpopulations identified in these publications as meeting the criteria for high-risk youth included at-risk youth (Buchanan, 2000; Fouche & Torrence, 2005), offenders (Gardstrom, 1987; Gladfelter, 1992; Nelson, 1997; Rio & Tenney, 2002; Wyatt, 2002), refugees (Baker & Jones, 2005; Jones, Baker, & Day, 2004), youth with poor body image (Ruutel, 2004), youth experiencing bereavement (Dalton & Krout, 2005), youth who had experienced abuse or trauma (Clendenon-Wallen, 1991; Keen, 2004; Slotoroff, 1994), and youth with mental health issues (Frank, 2005; Frisch, 1990; Gardstrom, 2003; Haines, 1989; Hendricks & Bradley, 2005; Tervo, 2001; Zonneveldt, 1969). …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".