A Wearable-Based Program to Optimise Stress Regulation, Resilience, and Wellbeing in Emergency Care Settings: A Proof-of-Concept Study Protocol
Abstract
1. Introduction
Study Objectives
- (1)
- Feasibility (practicality of study methods): Assessing the practicality of recruitment and data collection, adherence/engagement to the program, fidelity of program delivery and use, and program safety.
- (2)
- Acceptability and usability: Exploring user experience with the program and devices, including perceived benefits, challenges, and suggestions for improvement.
- (3)
- Preliminary clinical effectiveness: Evaluating changes in psychological health and wellbeing using self-reported outcomes (e.g., stress, mood, and anxiety) and physiological markers (e.g., HRV, sleep quality, and circadian rhythm).
- (4)
- Preliminary economic impact: Estimating the potential cost benefits/savings of WeCare as an early intervention for vulnerable ED populations.
2. Materials and Methods
2.1. Participants and Setting
- Sample 1: Patients presenting to the ED with mild-to-moderate injuries (Injury Severity Score, ISS < 15).
- Sample 2: Patients presenting to the ED with severe injuries (ISS ≥ 15).
- Sample 3: Patients presenting to the ED with acute non-traumatic, minor-to-moderate medical complaints (Australasian Triage Scale, ATS category 3–5 = less urgent).
- Sample 4: Emergency healthcare workers exposed to workplace stress.
2.2. Design Overview
2.2.1. Experimental Component
- Sample 2: More severely injured participants (ISS ≥ 15).
- Sample 3: Non-injured patients with acute stress from medical events.
- Sample 4: Health workers from the ED exposed to workplace stress.
2.2.2. Co-Design Component
2.2.3. Cost Analysis Component
2.3. Eligibility Criteria
2.4. Recruitment, Enrolment, and Randomisation
2.5. Intervention: WeCare Program
2.5.1. Wearable Integration and Personalised Data-Driven Feedback
2.5.2. Program Framework: The “Learn–Track–Act” Paradigm
- Learn: Participants engage with digital psychoeducational content on stress, wellbeing, and self-regulation strategies via factsheets, videos, and real-life stories.
- Track: Participants monitor their daily physiological data, observe trends over time, and see how their activities influence key biometrics and how they feel, using the wearable-based app.
- Act: Participants receive personalised feedback via the app and expert guidance based on their data and engage in evidence-based self-regulation practices (e.g., lifestyle adjustments, paced breathing, and mindfulness) to support stress management and recovery.
2.5.3. Program Structure
- (1)
- Making sense of stress and wellbeing (Week 1)
- (2)
- Knowledge is power: digging into the data (Weeks 2–3)
- (3)
- In the driver’s seat: taking charge of my health (Weeks 4–6, and beyond)
2.5.4. Weekly Insights and Daily Practice Guidance
- Weekly thematic insights: Each week, participants are provided with evidence-based content aligned with the program’s focus. This includes short readings, video resources, e-learning links, and lived-experience stories. Weekly modules also offer practical guidance to support daily wellbeing practices and activities such as journaling, breathwork, mindfulness, and lifestyle modifications.
- Daily reflection prompts: To encourage engagement and deepen learning, participants receive structured prompts that support reflection on personal experiences, habits, and progress. These prompts aim to foster self-awareness and active participation in the program and behaviour change.
2.5.5. Human and AI-Based Support
2.6. Outcome Measures and Data Collection
2.6.1. Feasibility Outcomes
2.6.2. Clinical Effectiveness
- (a)
- Pre-baseline measures
- (b)
- Primary outcome measures
- Clinical self-report outcomes:
- Psychological distress: Daily ratings of 24 h average distress measured with the 1-item Subjective Units of Distress Scale (SUDS), ranging from 0 (no distress) to 100 (extreme distress) [69], plus ecological momentary assessments every 2 h for 4 days only (2 during baseline and 2 during intervention).
- Sleep quality: Measured each morning using a single-item scale from 0 (worst) to 10 (best), aligned with self-reported wake times to minimise recall bias.
- Psychophysiological outcomes: Continuously recorded via a smartwatch using photoplethysmography and an accelerometer. Adherence and data completeness will be monitored via app analytics and automated tracking tools.
- Heart rate variability (HRV) metrics: Reflects autonomic nervous system (ANS) activity. Higher parasympathetic (vagal) tone indicates improved regulation, whereas low HRV is associated with mental health risk [37,38,39]. HRV Root Mean Square of Successive Differences (HRV-rMSSD) and other time-, frequency-, and nonlinear-domain and composite metrics will be extracted from beat-to-beat intervals, especially during overnight monitoring.
- Sleep parameters: Includes sleep duration, bedtime, sleep onset latency, nocturnal heart rate, wake-up time, and sleep-related temperature deviation (if available).
- (c)
- Generalisation measures
- Clinical self-report outcomes:
- Mental health:
- Sleep quality: Pittsburgh Sleep Quality Index (PSQI) [74].
- Consumer perception of change: A 15-point Global Impression of Change Scale (−7 to +7).
- Overall health status: EQ-5D visual analogue scale (0–100).
- Psychophysiological outcomes: Continuously monitored via a smartwatch, including heart rate, respiratory rate, blood oxygen saturation (SpO2), activity metrics (e.g., steps, movement, calories, and circadian rhythm), and daily health summary metrics related to stress and daytime and night-time recovery.
2.6.3. Acceptability and Usability
- Quantitative methods: Questionnaires or visual analogue rating scales aligned with TFA constructs will assess anticipated acceptability among potential deliverers and recipients.
- Qualitative methods: Semi-structured interviews or focus groups, guided by the seven TFA constructs, will explore participants’ and stakeholders’ lived experiences of the intervention. These qualitative methods will offer in-depth insights into barriers, facilitators, and contextual factors influencing engagement, adherence, and perceived value, factors often not captured through quantitative means alone.
2.6.4. Cost Benefits
2.7. Sample Size
2.8. Data Analysis and Reporting
2.9. Study Approvals
3. Discussion
Strengths and Limitations
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
| ANS | Autonomic nervous system |
| ATS | Australasian Triage Scale |
| ED | Emergency Department |
| GAD-7 | Generalised Anxiety Disorder Scale |
| HRV | Heart rate variability |
| ICU | Intensive Care Unit |
| ISS | Injury Severity Score |
| PCL-5 | PTSD Checklist for DSM-5 |
| PHQ-9 | Patient Health Questionnaire-9 |
| PSS | Perceived Stress Scale |
| PTSD | Post-traumatic stress disorder |
| PSI | Psychosocial Index |
| PSQI | Pittsburgh Sleep Quality Index |
| rMSSD | Root Mean Square of Successive Differences |
| RNSH | Royal North Shore Hospital |
| RoBiNT | Risk of Bias in N-of-1 Trials |
| SUDS | Subjective Units of Distress Scale |
| TFA | Theoretical Framework of Acceptability |
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| Phase | When It Starts | How Long | Device Used | What Happens |
|---|---|---|---|---|
| Baseline (Usual care) |
| 1–3 weeks (7, 11, 15 days by tier) | “Blinded” smartwatch (wrist device) |
|
| WeCare Program (Intervention) | After baseline phase ends | 6 weeks (staggered by tier) | “Blinded” smartwatch Smart ring |
|
| Optional Extension (Device testing) | After intervention phase ends | 2 weeks | “Blinded” smartwatch |
|
| Participant Group | Inclusion Criteria | Exclusion Criteria |
|---|---|---|
| All |
|
|
| Mild-to-moderate injury patient group (Sample 1) |
|
|
| Severe injury patient group (Sample 2) |
|
|
| Medical patient group (Sample 3) |
|
|
| ED healthcare staff (Sample 4) |
|
|
| (a) PRE-BASELINE MEASURES | OUTCOME | Data Collection | Day 0 | Daily | Ecological * | Weekly | Pre-Program | Post-Program | Follow-Ups |
| Socio-demographic | Seven multiple-choice questions | Online/Paper | ✓ | - | - | - | - | - | - |
| Clinical | Medical and mental health history | Online/Paper | ✓ | - | - | - | - | - | - |
| Treatment and medication use | Online/Paper | ✓ | - | - | - | - | - | - | |
| Lifestyle habits | Online/Paper | ✓ | - | - | - | - | - | - | |
| Psychosocial | PSI stress | Online/Paper | ✓ | - | - | - | - | - | - |
| PSI wellbeing | Online/Paper | ✓ | - | - | - | - | - | - | |
| PSI psychological distress | Online/Paper | ✓ | - | - | - | - | - | - | |
| PSI abnormal illness behaviour | Online/Paper | ✓ | - | - | - | - | - | - | |
| PSI quality of life | Online/Paper | ✓ | - | - | - | - | - | - | |
| Pain Catastrophising Scale | Online/Paper | ✓ | - | - | - | - | - | - | |
| Injustice Experience Questionnaire | Online/Paper | ✓ | - | - | - | - | - | - | |
| Composite Scale of Morningness | Online/Paper | ✓ | - | - | - | - | - | - | |
| Brief Resilience Scale | Online/Paper | ✓ | - | - | - | - | - | - | |
| General Self-Efficacy Scale | Online/Paper | ✓ | - | - | - | - | - | - | |
| (b) PRIMARY OUTCOMES | OUTCOME | Data collection | Day 0 | Daily | Ecological * | Weekly | Pre-program | Post-program | Follow-ups |
| Mental health status | Subjective Units of Distress Scale | Online/Paper | ✓ | ✓ | ✓ | - | - | ✓ | ✓ |
| Sleep quality | Numeric Rating Scale (0 to 10) | Online/Paper | ✓ | ✓ | - | - | - | ✓ | ✓ |
| Autonomic function | HRV metrics | Wearable devices | - | ✓ ** | - | - | - | ✓ ** | ✓ ** |
| Sleep function | Sleep metrics | Wearable devices | - | ✓ ** | - | - | - | ✓ **^ | ✓ **^ |
| (c) GENERALISATION MEASURES | OUTCOME | Data collection | Day 0 | Daily | Ecological * | Weekly | Pre-program | Post-program | Follow-ups |
| ‘Proximal’ Generalisation Measures | |||||||||
| Mental health function | Perceived Stress Scale | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ |
| Patient Health Questionnaire | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ | |
| PTSD Checklist for DSM-5 | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ | |
| Generalised Anxiety Disorder Questionnaire | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ | |
| Sleep | The Pittsburgh Sleep Quality Index | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ |
| Adverse events and life stressors | Self-reported adverse events and stressors diaries | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ |
| Consumer perception | Numeric Rating Scale (−7 to +7) | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ |
| Quality of life | EQ-5D-5L—Health score (0 to 100) | Online/Paper | ✓ | - | - | ✓ | - | ✓ | ✓ |
| Physiological status | HR, RR, Sp02, activity, summary scores, temp | Wearable devices | - | ✓ ** | - | - | - | ✓ **^ | ✓ **^ |
| ‘Distal’ Generalisation Measures | |||||||||
| Mental wellbeing | The World Health Organisation-Five Well-Being Index | Online/Paper | - | - | - | - | ✓ | ✓ | ✓ |
| Cognitive functioning | Perceived Deficits Questionnaire | Online/Paper | - | - | - | - | ✓ | ✓ | ✓ |
| Pain interference | Numeric Rating Scales (0 to 10) | Online/Paper | - | - | - | - | ✓ | ✓ | ✓ |
| Fatigue | Numeric Rating Scales (0 to 10) | Online/Paper | - | - | - | - | ✓ | ✓ | ✓ |
| Social participation | WHODAS 2.0 Participation Domain | Online/Paper | - | - | - | - | ✓ | ✓ | ✓ |
| Consumer satisfaction | Was-It-Worth-It Questionnaire | Online/Paper | - | - | - | - | ✓ | ✓ | ✓ |
| Continuation of use | Three custom questions | Online/Paper | - | - | - | - | - | ✓ | ✓ |
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Share and Cite
Pozzato, I.; Parker, M.; Tate, R.; Arora, M.; Bourke, J.; Ahmadi, M.; Gillett, M.; McBain, C.; Tran, Y.; Arora, V.; et al. A Wearable-Based Program to Optimise Stress Regulation, Resilience, and Wellbeing in Emergency Care Settings: A Proof-of-Concept Study Protocol. Sensors 2026, 26, 104. https://doi.org/10.3390/s26010104
Pozzato I, Parker M, Tate R, Arora M, Bourke J, Ahmadi M, Gillett M, McBain C, Tran Y, Arora V, et al. A Wearable-Based Program to Optimise Stress Regulation, Resilience, and Wellbeing in Emergency Care Settings: A Proof-of-Concept Study Protocol. Sensors. 2026; 26(1):104. https://doi.org/10.3390/s26010104
Chicago/Turabian StylePozzato, Ilaria, Maia Parker, Robyn Tate, Mohit Arora, John Bourke, Matthew Ahmadi, Mark Gillett, Candice McBain, Yvonne Tran, Vaibhav Arora, and et al. 2026. "A Wearable-Based Program to Optimise Stress Regulation, Resilience, and Wellbeing in Emergency Care Settings: A Proof-of-Concept Study Protocol" Sensors 26, no. 1: 104. https://doi.org/10.3390/s26010104
APA StylePozzato, I., Parker, M., Tate, R., Arora, M., Bourke, J., Ahmadi, M., Gillett, M., McBain, C., Tran, Y., Arora, V., Schoffl, J., Cameron, I. D., Middleton, J. W., & Craig, A. (2026). A Wearable-Based Program to Optimise Stress Regulation, Resilience, and Wellbeing in Emergency Care Settings: A Proof-of-Concept Study Protocol. Sensors, 26(1), 104. https://doi.org/10.3390/s26010104

