All supplementary materials, including recruitment posters, consent forms, demographic questionnaires, and analysis workflows, are available in a public repository (Figshare: 10.6084/m9.figshare.29925167).
3.1 Mixed-Method Design and Knowledge Paradigms
This project was conceived as a transformative mixed-method design that brought together Indigenous, interpretivist, and critical realist approaches. Each paradigm caries distinct assumptions about the nature of truth (ontology), what counts as knowledge (epistemology), how knowledge can best be acquired (methodology), and the criteria for good research (quality). Our intent was not to collapse these perspectives into one, but to honour them in their integrity and allow each to contribute to the whole.
Indigenous knowledge and ceremony were at the centre. Wîwîp’son is not simply a swing but a healing practice that involves prayer, song, and spiritual guidance. This ontological grounding guided the study, with Dr. Darlene Auger leading as healing practitioner and knowledge carrier. Interpretivist methods, particularly semi-structured interviews, enabled participants to share subjective accounts of their experiences. Empirical methods, including wearable biometric sensors, offered complementary insights into physiological correlates of the swing (wîwîp’son) experience.
The research team reflected these paradigms. Some members were grounded in empirical science, with commitments to controlling confounds and cautious inference. Others contributed expertise in interpretive qualitative research and Indigenous methodologies that emphasize story, ceremony, and relational accountability. This plurality shaped the project as a collaboration respectful of one another’s knowledge systems.
We found resonance in Secwepemc leader George Manuel’s imagery: “We will steer our own canoe, but we will invite others to help with the paddling” (Contassel, 2013, p. 50). The direction of the canoe was set by Indigenous priorities, with other team members contributing skills to help propel the journey forward. For example, while early study designs proposed comparing swinging versus stationary conditions, Darlene explained that ceremony, not motion, should be the focus. The final design thus compared swing sessions with and without ceremony, ensuring that Indigenous healing practice remained central to the research process.
By adopting a concurrent transformative mixed-methods design (Creswell, 2003), we engaged multiple methods simultaneously and wove them together in the analysis to address a shared, complex question. The result was a living collaboration that evolved over time, honouring Indigenous ways of knowing while drawing on interpretivist and critical realist tools to enrich the inquiry.
3.2 Ethics
The study was approved by the University of Alberta Health Research Ethics Board (Study ID: Pro00109848) which included Indigenous ethics for conducting research on humans adopted from University nuhelot’įne thaiyots’į nistameyimâkanak Blue Quills, a First Nations owned and operated university, the first of its kind in Canada. All participants provided written informed consent prior to participation. In line with Indigenous healing protocols, the research team offered tobacco and gifts to Darlene on behalf of all participants at the outset of the project. This gesture acknowledged the cultural context of wîwîp’son and demonstrated respect for the spirit, the healer and the practice. In this way, the project attended to both university and nehiyâw ethical protocols.
Dr. Darlene Auger, healing practitioner and author, conducted all the wîwîp’son sessions. Because of this role, she could not be blinded to condition assignment. For Cohort 1 participants, the study design included a control and ceremony session, which required partial disclosure. Participants were informed that they would attend two wîwîp’son sessions, but they were not told the true purpose, or difference between sessions, until completing both. Participants were debriefed and given the opportunity to ask questions and withdraw their data if they wished; no participants elected to withdraw.
3.3 Setting
Study visits took place in two settings chosen for their cultural appropriateness and ecological validity. The first was the Indigenous Gathering Space at the University of Alberta’s downtown Enterprise Square campus (Fig. 1). This dedicated space was designed in consultation with Elders and community partners to host ceremony, dialogue, and cultural practices, including smudging, which was essential for the wîwîp’son healing sessions. The Gathering Space offered a neutral, non-laboratory environment that minimized distractions from clinical equipment while supporting relational ethics and spiritual practice.
[Figure 1 near here]
The second setting was Dr. Darlene Auger’s home, where she traditionally offers wîwîp’son (Swing Therapy) to clients. This environment provided continuity with the ceremonial context in which participants typically seek healing, and it supported Indigenous clients already familiar with the practice.
Both settings were experienced as gifts that enabled the healing ceremony to unfold in a manner consistent with Indigenous relational protocols and spiritual practice, while still accommodating physiological measurement.
3.4 Participants
Cohort 1: Volunteer participants
The first cohort consisted of 14 volunteers recruited during July-August 2021 through a convenience sampling strategy. Recruitment relied on circulation of a study poster (Figshare: 10.6084/m9.figshare.29925167) distributed by email and word of mouth. Note: recruitment coincided with the COVID-19 pandemic. Eligible participants were required to: (i) be 18 years of age or older, (ii) self-identify as female, and (iii) have no prior knowledge of or experience with Indigenous healing practices including wîwîp’son. The restriction to female-identifying participants reflected requirements of the Women’s and Children’s Health Research Institute (WCHRI), who provided partial funding for the project, rather than being intrinsic to the study design. Participants were not required to self-identify as Indigenous; demographic information, including race/ethnicity, was collected separately using a standardized form (Figshare: 10.6084/m9.figshare.29925167).
Participants in this cohort each completed two study visits in the Indigenous Gathering Space. One visit involved a wîwîp’son healing session with ceremony while the other involved a non-ceremony control swing session, both conducted by Dr. Darlene Auger. The order of conditions was randomized. To maintain blinding, participants were informed that the purpose of the two sessions was to ensure consistency of results, with the true distinction between ceremony and control conditions revealed only during a debrief following the second visit.
Cohort 2: Indigenous clients
The second cohort comprised eight individuals who were existing clients of Dr. Auger and familiar with wîwîp’son and wanted to come for healing. Unlike Cohort 1, all participants in this group self-identified as Indigenous (specifically, First Nations or Métis) on the demographic form. Their inclusion reflected the guidance of Elder Dr. Maggie Hodgson (Auger’s long-time mentor), who emphasized the importance of ensuring Indigenous peoples were represented in the study alongside non-Indigenous volunteers.
These participants each took part in a single wîwîp’son session held in Dr. Auger’s home, the second study setting. This location reflected the context in which they ordinarily sought healing, thereby maintaining continuity with their lived experience. Most individuals in this cohort identified as female; however, one participant selected “nonbinary” and “other” on the demographic form and specified the term ihkwew (a nehiyâw word used by some Two-Spirit or sexuality- and gender-diverse persons).
3.5 Procedures
To reduce reactivity to wearable monitoring devices, participants were provided with a Hexoskin smart shirt, Muse-S headband, and an iPod Touch preloaded with study applications at least three days before their first session. They were instructed to use the equipment daily during this acclimatization period. A printed instruction sheet and in-person orientation were provided by the research assistant (RA, author R.W.), who remained available for troubleshooting by phone or email.
On each study day, participants arrived at the designated setting (the Indigenous Gathering Space, or Dr. Auger’s home, depending on cohort). After greeting and confirming acclimatization, the RA collected demographic information and the Pittsburgh Sleep Quality Index questionnaire. Participants then donned the Hexoskin shirt and Muse-S headband, and the RA verified device connectivity via the iPod Touch. A brief calibration protocol, including a breathing exercise and a five-minute resting baseline, was conducted to ensure data quality.
For Cohort 1, session order (healing vs. control) was randomized in advance. The RA informed Dr. Auger of the condition, while participants remained blinded until debriefing at study completion. In the control condition, participants were placed in the swing, wrapped securely in blankets, and gently rocked for 45–50 minutes. In the healing condition, procedures were similar but included smudging prior to entry, and Dr. Auger incorporated connection to spirit, prayer and song during the swinging. For Cohort 2, participants experienced a single session with ceremony, reflecting usual healing practice.
At the conclusion of each session, participants completed a visual analogue scale rating alertness. The RA then conducted a semi-structured interview, guided by a standardized script, and recorded field notes. A list of support resources was available should any participant experience distress.
Four days later, the RA conducted a follow-up interview by phone or videoconference to ask about ongoing experiences. For Cohort 1, participants returned ~ 2 weeks later for their second session in the alternate condition. After the final follow-up interview, the RA read a debriefing statement explaining the purpose of the control and ceremony conditions, and answered questions.
3.6 Measures
Physiological Monitoring
Hexoskin Smart Shirt
The Hexoskin Smart Shirt (Carré Technologies Inc., Montréal, Canada) was selected for its capacity to capture high-quality electrocardiographic (ECG) and respiratory signals in an unobtrusive manner that did not interfere with the participants during a wîwîp’son session. Unlike conventional wired laboratory-based systems, the Hexoskin is a lightweight garment that can be worn under clothing, allowing continuous physiological monitoring while respecting the integrity of the healing environment. Laboratory studies have demonstrated the accuracy of Hexoskin-derived ECG and spirometry measures during rest and exercise (Smith et al., 2019). Importantly for the present study, its reliability has also been established across body positions (lying, sitting, standing, walking), with no significant differences relative to standard laboratory systems (Villar et al., 2015; Montes et al., 2018). Its use has also been extended to clinical and complementary therapy contexts for stress reduction (Birdee et al., 2023).
Data collection and analysis
ECG data were collected in a Lead II configuration at a sampling rate of 256 Hz, along with three-axis acceleration data at 64 Hz, using the Hexoskin application running on iPod Touch devices. Custom MATLAB scripts (versions R2021b and R2022a) were used to visualize R-R intervals overlaid on ECG waveforms with automated quality control flagging. R-R intervals marked as noisy, unreliable, or both were excluded. Acceleration data were used to identify supine positioning, swing motion onset and cessation, and session boundaries. R-R time series were trimmed to include data from 5 minutes after swing motion onset to 5 minutes before cessation. Preprocessed R-R intervals were analyzed using the HRVAS toolbox (Ramshur, 2010), which included ectopic beat removal, wavelet packet detrending, and cubic spline resampling at 2 Hz. Power spectral density was estimated using Welch’s periodogram (512 points, 256 window, 128 overlap), and power was extracted from low-frequency (0.04–0.15 Hz) and high-frequency (0.15–0.40 Hz) bands in line with established HRV conventions (DeBeck et al., 2010; Shaffer & Ginsberg, 2017).
Muse-S EEG Headband
The Muse-S (InteraXon Inc., Toronto, Canada) was chosen to provide an unobtrusive, wearable option for electroencephalographic (EEG) monitoring that respected the healing context of wîwîp’son sessions. Compared to conventional cap-based EEG, the Muse-S is lightweight, comfortable, and well tolerated, allowing participants to remain immersed in the healing session. Previous studies have established the feasibility of research-grade analyses using the earlier Muse headset (Hashemi et al., 2016; Wilkinson et al., 2020), and the Muse-S represented an improved design with enhanced electrode contact and comfort.
Data collection and analysis: EEG data were collected using the Muse-S headband (4-channel configuration: TP9, AF7, AF8, TP10; reference FPz) at 256 Hz via the MindMonitor application on iPod Touch devices. Both MindMonitor and Hexoskin applications were run in parallel on the same devices. Raw data were imported into EEGLAB (Delorme & Makeig, 2004) for preprocessing, artifact rejection, and spectral analysis in line with established guidelines for frequency-domain EEG (Keil et al., 2022). Accelerometer and gyroscope channels from the Muse-S were used to mark: (i) settling into the swing (supine), (ii) onset of sustained periodic swing motion, and (iii) swing cessation/exit. EEG analysis was restricted to the stable swing epoch, trimmed to begin 5 min after swing onset and to end 5 min before cessation (like the ECG analysis pipeline). Within this window, movement-contaminated segments were excluded prior to spectral estimation.
Power spectral density was extracted for standard EEG frequency bands: delta (1–4 Hz), theta (4–8 Hz), alpha (7.5–13 Hz), beta (13–30 Hz), and gamma (30–44 Hz). A flowchart illustration of the EEG preprocessing workflow is available as supplementary material (Figshare: 10.6084/m9.figshare.29925167). EEG and physiological signals (Hexoskin) were not temporally synchronized. For each participant, relative band power (i.e. the proportional contribution of each frequency band to the total spectral power) was calculated. Relative power was chosen to normalize for session-specific differences in signal amplitude and artifact, thereby reducing the influence of absolute signal strength, and improving comparability of brain-state metrics within participants across sessions (Control vs. Healing). For the present analyses, spectral estimates were averaged across the two prefrontal electrodes (AF7 and AF8). This decision was made a priori to focus on prefrontal cortical activity, given its well-established role in top-down regulation of limbic structures such as the amygdala (Banks et al., 2007; Morawetz et al., 2017) and their downstream influence on cardiovascular autonomic centers in the brainstem (Jennings et al., 2015; Schumann et al., 2021). Temporal electrodes (TP9, TP10) were excluded to minimize mixing prefrontal and temporal sources. From the prefrontal relative power values, the Delta-Alpha Ratio (DAR) and Delta + Theta/Alpha + Beta Ratio (DTABR) were calculated as a quantitative markers of “cortical arousal” (Finnigan & Van Putten, 2013; Lendner et al., 2020).
EEG frequency band changes between sessions were visualized using paired estimation plots (“Cumming plots”), which display raw paired values alongside the mean paired difference with effect size estimates. Effect sizes were calculated using Hedges’ g for repeated measures, which corrects for small sample bias (Hedges & Olkin, 1985). Qualitative thresholds for interpreting g were: small (< 0.2), moderate (0.5), and large (> 0.8, Cohen, 1988). Confidence intervals (95% CI) were derived by bootstrap resampling and permutation p values are reported for completeness.
Self-Report Measures
Demographics
Participants completed a demographic form including age at the time of data collection, gender identity, and race/ethnicity. These data were used descriptively to contextualize the sample and to confirm representation of Indigenous participants.
Pittsburgh Sleep Quality Index (PSQI)
The PSQI (Buysse et al., 1989) was administered to assess global sleep quality as a potential covariate influencing physiological or experiential responses during wîwîp’son sessions. The PSQI yields a global score ranging from 0 to 21, with higher scores indicating poorer sleep quality. A standardized cutoff of > 5 has been shown to distinguish “poor sleepers” with high sensitivity and specificity. We anticipated that poor sleep quality could influence participants’ experiences (e.g. increased likelihood of falling asleep during swinging). In the present study, PSQI scores were compared between the two participant cohorts; the measure was not further incorporated into other analyses.
Visual Analog Scale (VAS) for Alertness
A 10-cm visual analog scale (VAS) was used to assess subjective alertness following each session. The scale was anchored with 0 = minimally alert and 10 = maximally alert. Participants were instructed to “rate your feelings of alertness on this scale from 0–10” and to mark a point along the line accordingly. Scores were quantified as the measured distance (in cm) from the left anchor. For Cohort 1, the primary purpose of the VAS was to compare alertness ratings between the two experimental conditions; no a priori directional hypothesis was specified. The VAS also enabled descriptive comparisons of alertness between Cohort 1 and Cohort 2 participants.
Interviews
Data generation: Semi-structured interviews (Rubin & Rubin, 2012) were conducted immediately following each wîwîp’son session and again four days later. Interviews lasted 20–40 minutes and followed a standardized guide (Figshare repository: 10.6084/m9.figshare.29925167) designed to elicit participants’ experiences during and after a swing session. Prompts focused on expectations, emotions, physical and sensory perceptions, and any changes noticed following the session, including sleep and dreaming. Dr. Auger was interested in capturing data on dreams as during her years of experience in offering wîwîp’son healing sessions, many people had reported significant ‘spiritual messaging’ dreams that offered healing. Interviews were not audio-recorded; instead, detailed field notes were taken by the interviewer to ensure participant comfort and confidentiality.
Data analysis: Interview notes were imported into NVivo (QSR International) for thematic analysis (Braun & Clarke, 2014). An initial coding framework was collaboratively developed by members of the research team, based on interview questions and participant responses. Codes were refined iteratively, with additional codes incorporated in response to recurring participant expressions. Analysis proceeded inductively moving through familiarization, coding, candidate themes, and refinement. Early coding emphasized within-participant (ideographic) themes, with later stages comparing experiences across participants. The final interpretive stage was guided by Indigenous knowledge traditions, i.e. The Medicine Wheel Framework, which shaped the organization of findings into four overarching themes: Physical, Spiritual, Emotional, and Mental Healing.
To support analytic transparency, each participant’s data were organized into three documents (healing session, control session, and follow-up interview). Healing and control sessions were internally coded as “Aspen” and “Fern” visits, and follow-up interviews were coded separately (e.g., “positive emotions” vs. “follow-up—positive emotions”) to allow comparison within and across sessions. Coding distinctions were refined during analysis; for example, expressions of being happy or joyful were coded as “positive emotions,” whereas calm, peaceful, relaxing were coded under “calm/peaceful.” Additional codes such as “grounded” and “presence” were created to reflect recurring participant language. Inter-rater reliability checks were conducted by two team members (A.A. and F.F.) on a subset of participants to ensure coding consistency. An audit trail of coding decisions and revisions was maintained throughout. While both healing and control sessions were included for comparison, analysis emphasized healing experiences, as these consistently elicited richer emotional, sensory, and spiritual descriptions, affording more in-depth analysis.
3.7 Additional Analysis
For quantitative variables including age, alertness (VAS), Pittsburg Sleep Quality Index (PSQI), and swing session duration, we used estimation statistics rather than relying solely on null hypothesis significance testing (Ho et al., 2019). Within-cohort comparisons (Cohort 1: Healing vs. Control) were analyzed using paired estimation methods, and between-cohort comparisons (Cohort 1 Healing vs. Cohort 2 Healing) were analyzed using two independent group estimation. All analyses were conducted using the DABEST framework (https://www.estimationstats.com; https://github.com/ACCLAB/DABEST-Matlab), which provides effect sizes with 95% confidence intervals derived from 5,000 bootstrap samples (bias-corrected and accelerated). Permutation tests were additionally implemented (5,000 reshuffles) to generate p-values, included here to satisfy journal reporting standards. Effect sizes are reported in the format: effect size [95% CI lower bound, upper bound].
For the analysis of physiological arousal state, ECG-derived heart rate variability (HRV) metrics were complemented by blinded expert assessment. Composite images were generated for each participant in Cohort 1, consisting of R-R interval series, power spectral density plots, time-frequency spectrograms, and LF/HF ratio time-courses for both Contol and Healing sessions. Two independent clinical experts, blinded to session type, reviewed each participant’s pair of images and classified the Healing session relative to the Control as: 1) Calm (lower arousal), 2) Stress (higher arousal), or 3) No Difference. Interrater reliability was quantified using Cohen’s kappa, which demonstrated substantial agreement (κ = 0.75). Discrepancies in classification were resolved by consensus.