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Record W6977045155 · doi:10.6084/m9.figshare.21176957

Effects of music therapy on mood, pain, and satisfaction in the neurologic inpatient setting

2022· article· en· W6977045155 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of CalgaryAlberta Health ServicesPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMoodMusic therapyRehabilitationPatient satisfactionHealth careFocus groupPerspective (graphical)Emotional health

Abstract

fetched live from OpenAlex

Music therapy (MT) has been used in health care settings for a wide variety of treatment goals. Many inpatients with neurologic impairments struggle with low mood and pain for which MT may be a novel adjunct treatment. The aims of this study were to: (1) evaluate change in mood and pain following a single MT session; (2) explore the impact of an MT program on mood, pain and satisfaction from the perspective of the patient, family and staff. A mixed-methods study was conducted. Forty participants completed pre/post MT surveys evaluating mood, pain and satisfaction. Individual semi-structured interviews and focus groups were conducted with 14 MT program participants (inpatients), 5 family members of participants and 16 staff. There was significant improvement in mood (p < 0.001) and decrease in pain (p < 0.05) from pre-to-post MT with 74% reporting being “very satisfied” with the session. “Benefits of MT” was the overarching theme of the qualitative data. Subthemes were emotional regulation, pain management, effects on self-concept, enjoyment, and social connectedness. Improvements in mood and pain were reported from pre-to-post MT session and in interviews. Further evaluation of MT effectiveness against standard of care rehabilitation and cost implications is required.Implications for RehabilitationMusic therapy (MT) is delivered by accredited music therapists (MTAs) in health care settings, including rehabilitation units, as an individual, group or co-treatment therapy.MT can be used for a range of health outcomes, including the treatment of mood and pain, in addition to improving inpatient satisfaction.Early evidence using pre/post MT surveys suggests an improvement in mood and pain following a single therapy session.Qualitative data suggest overall benefit of offering MT services in addition to standard neurorehabilitation therapy, including improvements to emotional regulation, pain management, self-concept, enjoyment, and social connectedness. Music therapy (MT) is delivered by accredited music therapists (MTAs) in health care settings, including rehabilitation units, as an individual, group or co-treatment therapy. MT can be used for a range of health outcomes, including the treatment of mood and pain, in addition to improving inpatient satisfaction. Early evidence using pre/post MT surveys suggests an improvement in mood and pain following a single therapy session. Qualitative data suggest overall benefit of offering MT services in addition to standard neurorehabilitation therapy, including improvements to emotional regulation, pain management, self-concept, enjoyment, and social connectedness.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.299
Teacher spread0.253 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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