Interactionality of trait-state music preference, individual variability, and music characteristics as a multi-axis paradigm for context-specific pain perception and management
Bibliographic record
Abstract
The purposes of this 3-phase study were 1) to identify salient individual variabilities and music characteristics associated with music therapy interventions for pain management, 2) to explore current pain management practices of music therapists, 3) to delineate any differences in general musical taste (trait) and context-specific music preference (state), as well as preferred music characteristics in healthy adults and cancer patients, 4) to investigate the contributions of individual variabilities, personality, behavioral coping styles, and pain levels in predicting changes from trait to state preferences and preferred music characteristics under various pain conditions, and 5) to investigate any differences in music preference patterns between healthy adults and cancer patients. In Phase I, 97 music therapists completed an online questionnaire to provide quantitative and qualitative data regarding the saliency of individual variabilities and music characteristics in determining the choice of music for pain management interventions, as well as their current practices with adult populations in clinical settings. In Phase II, 50 healthy adults (33 females, 17 males) ranging in age from 40 to 70 years (M = 57.04 ± 7.99) completed a battery of tests and questionnaires, including a Participant Intake Form (demographic information, music background, listening habits), an adapted Short Test of Music Preference – Revised (STOMP-R-A), a Music Characteristics Test, the Miller Behavioral Style Scale – abbreviated (MBSS-abbreviated), and the NEO Five-Factor Inventory-3 (NEO-FFI-3). The STOMP-R-A measured the participants’ trait and state preferences for 23 music genres. The Music Characteristics Test involved a music listening portion for participants to rate their preferences for various music characteristics. The MBSS-abbreviated measured behavioral coping styles and the NEO-FFI-3 measured the five dimensions of personality. In Phase III, 35 cancer patients (24 females, 11 males) ranging in age from 42 to 70 years (M = 57.71 ± 7.07) completed the same measurement tools as the ones used in Phase II, as well as the Short-Form McGill Pain Questionnaire–2 (SF-MPQ-2), which measured ratings for chronic, acute, and neuropathic pain. A one-way analysis of variance was used to test for response bias amongst the music therapists in Phase I. No response bias was found. Responses were reported as sums and converted to percentages of respondents for each selected response. Qualitative responses were analyzed using open coding and thematic development techniques. An intercoder was recruited to authenticate reliability for the qualitative findings. Music therapists identified age, ethnicity, culture, and religious preferences as important individual variabilities, and tempo, rhythmic complexity, and dynamics as salient music characteristics in their ratings. The results from Phase I informed the methodology for the next two phases of this study. Participants in Phases II and III were tested individually. The paired t-test was used to determine differences between trait and state music preferences across all 23 genres. The results indicated significant decreases from trait to state music preferences across music genres in both healthy adult and cancer patient groups. Calculations of the chi-square statistic and the McNemar’s test were used to detect differences between trait music preference and state music preference specific to each of the 23 genres. Multiple logistic regression analysis was used to examine the contributions of demographic factors, personality, behavioral coping style, and pain to changes from trait to state preferences and preferred music characteristics under four pain conditions. In Phase II, age, gender, and neuroticism predicted changes in trait-state preference for music genres; and gender and behavioral coping styles predicted changes in preferences for music characteristics under low-acute, high-acute, low-chronic, and high-chronic pain conditions. In Phase III, neuroticism predicted changes in trait-state preference for music genres; and age predicted changes in preferences for music characteristics under the four pain conditions. The independent t-test was used to determine differences between healthy adults’ and cancer patients’ ratings of the importance of music, music background, and music listening habits. No significant differences were found between the two groups. Healthy adults and cancer patients were most familiar with country music and rated oldies and rock as their most preferred music genres. Healthy adults reported familiarity with and preferences for greater number of genres compared to cancer patients. In general, both groups indicated decreased preferences for music under pain conditions. The findings from this study emphasized the importance of considerations for the interactions of trait-state music preferences, individual variabilities, and music characteristics as a paradigm for context-specific pain management in adult clinical settings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".