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Record W4413735947 · doi:10.33137/jrmh.v8i2.45342

Assessment of Songwriting Interventions Using BPNSS: A Study on In-Patient Recovery and Self-Determination

2025· article· en· W4413735947 on OpenAlexaff
Regina Wasalinska-Hannah, Katie DuTemple

Bibliographic record

VenueJournal of Recovery in Mental Health · 2025
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychological interventionPsychologyMedicineNursing

Abstract

fetched live from OpenAlex

This study examines the viability of songwriting as a recovery intervention for patients in a mental health hospital setting. Using the Basic Psychological Needs Satisfaction Scale (BPNSS) as a tool for measuring one’s sense of autonomy, relatedness and competence, first-time participants were asked to complete the scale before and directly following a one-hour songwriting group, with open-text questions included in the post-intervention scale. Forty-nine participants from two different in-patient units - Crisis and Critical Care (CCC) and Medical Withdrawal Services (MWS) - volunteered to take part in the study. Results indicated that participants from CCC only saw a statistically significant increase in competence scores, with open-text responses from both units supporting this finding. Common sentiments from open-text responses included growth in confidence and self belief, elevation in mood and expression of emotions through creative practice. Developing competence can be important when entering into recovery, and can lead to an increase in confidence. While the initial findings from this pilot study are promising, further research is needed to determine the efficacy of songwriting as a mental health intervention.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.477
Teacher spread0.420 · 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 teacher head, 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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