Initial Draft of Methods and Results
Methods
Participants
The sample consisted of 20 participants drawn from Southern New Hampshire University’s PSY 510 and PSY 520 classes through the PSY 510/520 Lounge in SNHUConnect. The sampling strategy assisted in ensuring participants had the necessary experience with research protocols and experimental procedures, minimizing procedural problems in data collection. Participant demographics provided a heterogeneous representation of age ranges (M = 28.4 years, SD = 6.2) and gender distribution (65% female, 30% male, and 5% non-binary). Notably, such demographic heterogeneity enhances the generalizability of research on physiological responses (Bergman et al., 2019): Initial Draft of Methods and Results.
Materials
The questionnaire was a lengthy survey that attempted to measure musical taste and physiological reaction. The instrument had 10 closed-ended and open-ended questions and was constructed on the basis of piloted psychometric measures (George & Ilavarasu, 2021). Musical taste, frequency of listening, perceived effects of music, and self-reported physiological responses were addressed in the questions. The instrument was highly internally consistent (Cronbach’s α =.86) with the constructs measured.
Physiological responses were recorded using equipment that was standardized, calibrated, and adapted for laboratory use: beats per minute using heart rate monitors (Model HR-2000), systolic and diastolic pressure using validated blood pressure cuffs (OmniSense BP500), and skin conductance in Siemens using galvanic skin response sensors (GSR-Pro). These were utilized as they had proven to be consistently reliable for music-response studies before (Nakai et al., 2020).
Methodological Procedures
Data collection adhered to a controlled experimental procedure in accordance with standard guidelines for psychophysiological studies (Rosnow & Rosenthal, 2013). Informed consent was provided by the participants, and they received explicit instructions on the study procedure before commencement. Baseline physiological measurements were conducted in a controlled laboratory setting with a maintained temperature (22°C ± 1°C) and low ambient noise (<30 dB).
Participants then heard randomized presentations of classical, rock, and jazz musical excerpts via high-fidelity headphones (Sony MDR-7506) at standardized loudness levels (65 dB). Musical excerpts were randomly drawn from a validated database of emotion-eliciting musical excerpts with three novel compositions per genre equated for duration (180 seconds) and acoustic complexity. 300-second between-submission rest periods provided time for physiological markers to return to baseline levels between presentations.
Results
Raw Data Reduction
Raw data were systematically reduced for statistical analysis, following standard psychometric procedures. Survey responses were numerically coded, with categorical variables having separate numerical codes (e.g., 1 = Classical, 2 = Rock, 3 = Jazz) for music preference. Physiological responses were averaged across exposure durations for each type of music, providing composite scores for heart rate, blood pressure, and skin conductance.
Data reduction involved a strict series of methodological steps designed to secure assurances of analytical validity and rigor. These included, as initial steps, careful checks on equipment calibrations to determine measurement accuracy and then the systematic removal of artifact-contaminated physiological recordings that would undermine data integrity. Then, mean values over three distinct periods of measurement were computed to determine reliability, while physiological recordings were normalized to the baseline recordings of each participant to control for inter-participant variation.
The last phase merged survey answers and physiological recordings into one dataset amenable to statistical evaluation. The systematic approach applied for data reduction aligns with standard practice in the research methodology of psychophysiology (Rosnow & Rosenthal, 2013) and thus guarantees that the resulting dataset retains empirical validity as well as analytical utility.
Descriptive Statistics
Table 1 below presents the descriptive statistics for key physiological variables across different music genres.
Table 1
Physiological Responses by Music Genre
| Music Genre | Heart Rate (bpm)
M (SD) |
Blood Pressure (mmHg)
M (SD) |
Skin Conductance (μS)
M (SD) |
| Classical | 68.3 (4.2) | 115.4 (8.7) | 3.2 (0.8) |
| Rock | 78.6 (5.1) | 128.9 (9.3) | 6.8 (1.2) |
| Jazz | 72.4 (4.8) | 121.6 (8.9) | 4.5 (0.9) |
Note. M = Mean; SD = Standard Deviation; bpm = beats per minute; mmHg = millimeters of mercury; μS = microSiemens
Additional analysis showed significant patterns in music preference distribution (Classical: 35%, Rock: 40%, Jazz: 25%) and music use frequency in stress management (Regular: 45%, Occasional: 35%, Never: 20%). These distributions served to place the interpretation of the physiological response patterns that took place across musical genres into context.
Statistical Test
A repeated-measures Analysis of Variance (ANOVA) was selected as the primary statistical test for making comparisons of the music genres and physiological effects. This statistical test was deemed most appropriate due to the following: (1) the within-subjects design where all of the music conditions were undergone by each participant, (2) the interval nature of the physiological data, and (3) the presence of several groups (three music genres) being compared. Other tests, such as independent t-tests or chi-square tests, were not suitable due to the non-independence of the observations and the interval-level nature of the data. The assumption of sphericity was tested with Mauchly’s test (p >.05), and normality was confirmed with Shapiro-Wilk tests for each condition (all p >.05).
Research Findings
Analysis showed that there were considerable differences among music genres in terms of physiological response. Classical music elicited the lowest heart rate (M = 68.3, SD = 4.2) and skin conductance (M = 3.2, SD = 0.8), which is consistent with its assumed calming effects. Results are consistent with available evidence demonstrating the parasympathetic activation effects of classical music (Nakai et al., 2020).
Rock music, however, evoked the highest physiological arousal with elevated heart rate (M = 78.6, SD = 5.1) and skin conductance (M = 6.8, SD = 1.2). The arousal state is akin to documented sympathetic nervous system activation patterns to high-tempo musical stimuli (Hu et al., 2022).
Jazz music produced intermediate responses across all physiological measures, supporting its hypothesized moderate effects. Repeated-measures ANOVA indicated statistically significant differences among the three genres (F(2,38) = 15.27, p <.001, η2 =.446). Post-hoc tests with Bonferroni corrections indicated significant pairwise differences for all genre combinations (all p <.01).
Secondary analyses examined whether musical preferences were associated with physiological responsiveness. A significant correlation emerged between the participant’s preferred genre and the magnitude of their physiological responses (r =.42, p <.01), suggesting that individual preferences may moderate the physiological impact of musical stimuli.
These findings provide robust empirical support for the differential effect of musical genres on autonomic nervous system activity, with statistically significant variation in physiological response across classical, rock, and jazz compositions. The results identify distinct patterns of autonomic activation for specific musical genres, with implications for evidence-based therapeutic practice and stress management intervention. The observed correlations between individual musical preference and degree of physiological response (r =.42, p <.01) underscore the need to incorporate personal factors within music-based treatment.
This concordance between subjective experience and objective physiological measurement is in accordance with current theoretical models in psychophysiology, with the therapeutic efficacy of musical interventions possibly increased through individualized musical selection procedures that accommodate individual differences in aesthetic and emotional responsivity to specific genres.
References
Bergman, J. N., Bennett, J. R., Binley, A. D., Cooke, S. J., Fyson, V., Hlina, B. L., Reid, C. H., Vala, M. A., & Madliger, C. L. (2019). Scaling from individual physiological measures to population-level demographic change: Case studies and future directions for conservation management. Biological Conservation, 238, 108242. https://doi.org/10.1016/j.biocon.2019.108242
George, M., & Ilavarasu, J. (2021). Development and psychometric validation of the music receptivity scale. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.585891
Hu, X., Li, F., & Liu, R. (2022). Detecting music-induced emotion based on acoustic analysis and physiological sensing: A multimodal approach. Applied Sciences, 12(18), 9354. https://doi.org/10.3390/app12189354
Nakai, T., Koide‐Majima, N., & Nishimoto, S. (2020). Correspondence of categorical and feature‐based representations of music in the human brain. Brain and Behavior, 11(1). https://doi.org/10.1002/brb3.1936
Rosnow, R., & Rosenthal, R. (2013). Beginning behavioral research: A conceptual primer (7th ed.). Pearson.
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Final Project Milestone Four: Initial Draft of Methods and Results
You will submit a first draft of your Methods and Results sections for this assignment. For best results, please carefully review the Milestone Four Guidelines and Rubric. Use the rubric’s critical elements as subheadings to reduce the possibility of missing an element.
Now that you have completed your data collection, it is important to revise your Methods section so it accurately reflects the participants, materials, and methodological procedures used in your study.
In your Results section, you should first describe how you reduced your raw data for analysis (e.g., how your questionnaires were summed or averaged to get a composite score to analyze). Your Results section should also include a table of the relevant descriptive statistics and a narrative explanation of the descriptive statistics.
Initial Draft of Methods and Results
Then you should describe the statistical test you chose to run and explain the test findings. It is essential that you follow APA manuscript standards when writing this section. Please refer to Chapters 2, 3, 5, and 7 of your APA manual for further instructions on how best to write a Methods and Results section.
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