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Record W49900619

Music Therapy Practice with High-Risk Youth: A Clinician Survey/Pratique De la Musicothé Rapie Avec Les Jeunes À Risque: Un Sondage Clinique

2013· article· fr· W49900619 on OpenAlexaboutno aff
David B. Clark, Edward A. Roth, Brian Wilson, Carolyn Anne Koebel

Bibliographic record

VenueCanadian journal of music therapy · 2013
Typearticle
Languagefr
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMusic therapyMental healthPsychological interventionPsychologyHumanitiesPsychotherapistPsychiatryArt
DOInot available

Abstract

fetched live from OpenAlex

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). …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0260.000

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.

Opus teacher head0.062
GPT teacher head0.330
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

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