Assessing the Mental Health of Emerging Adults Through a Mental Health App: Protocol for a Prospective Pilot Study

Yunusova, Asal; Lai, Jocelyn; Rivera, Alexander P; Hu, Sirui; Labbaf, Sina; Rahmani, Amir M.; Dutt, Nikil; Jain, Ramesh; Borelli, Jessica L.

doi:10.2196/25775

Cited by 13 publications

(10 citation statements)

References 79 publications

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“…For our investigation, we assessed sleep quality using the Oura ring’s personalized sleep score that uses a combination of individual body metrics (ie, height, weight, age, and gender) with a validated system that detects time spent in different stages of sleep [ 60 , 61 ]. The Samsung smartwatch tracks several user activities and physiological variables 24/7 (for more details on how these devices were used for our study, see Yunusova et al [ 72 ]). We were able to use the watch to assess participants’ heart rate variability (root mean square of successive differences between normal heartbeats [RMSSD]) and beats per minute (BPM) during diurnal periods (RMSSD and day BPM), and during the entire 24-hour period (RMSSD and resting BPM).…”

Section: Methodsmentioning

confidence: 99%

Using Multimodal Assessments to Capture Personalized Contexts of College Student Well-being in 2020: Case Study

et al. 2021

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Background The year 2020 has been challenging for many, particularly for young adults who have been adversely affected by the COVID-19 pandemic. Emerging adulthood is a developmental phase with significant changes in the patterns of daily living; it is a risky phase for the onset of major mental illness. College students during the pandemic face significant risk, potentially losing several protective factors (eg, housing, routine, social support, job, and financial security) that are stabilizing for mental health and physical well-being. Individualized multiple assessments of mental health, referred to as multimodal personal chronicles, present an opportunity to examine indicators of health in an ongoing and personalized way using mobile sensing devices and wearable internet of things. Objective To assess the feasibility and provide an in-depth examination of the impact of the COVID-19 pandemic on college students through multimodal personal chronicles, we present a case study of an individual monitored using a longitudinal subjective and objective assessment approach over a 9-month period throughout 2020, spanning the prepandemic period of January through September. Methods The individual, referred to as Lee, completed psychological assessments measuring depression, anxiety, and loneliness across 4 time points in January, April, June, and September. We used the data emerging from the multimodal personal chronicles (ie, heart rate, sleep, physical activity, affect, behaviors) in relation to psychological assessments to understand patterns that help to explicate changes in the individual’s psychological well-being across the pandemic. Results Over the course of the pandemic, Lee’s depression severity was highest in April, shortly after shelter-in-place orders were mandated. His depression severity remained mildly severe throughout the rest of the months. Associations in positive and negative affect, physiology, sleep, and physical activity patterns varied across time periods. Lee’s positive affect and negative affect were positively correlated in April (r=0.53, P=.04) whereas they were negatively correlated in September (r=–0.57, P=.03). Only in the month of January was sleep negatively associated with negative affect (r=–0.58, P=.03) and diurnal beats per minute (r=–0.54, P=.04), and then positively associated with heart rate variability (resting root mean square of successive differences between normal heartbeats) (r=0.54, P=.04). When looking at his available contextual data, Lee noted certain situations as supportive coping factors and other situations as potential stressors. Conclusions We observed more pandemic concerns in April and noticed other contextual events relating to this individual’s well-being, reflecting how college students continue to experience life events during the pandemic. The rich monitoring data alongside contextual data may be beneficial for clinicians to understand client experiences and offer personalized treatment plans. We discuss benefits as well as future directions of this system, and the conclusions we can draw regarding the links between the COVID-19 pandemic and college student mental health.

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Section: Methodsmentioning

confidence: 99%

Using Multimodal Assessments to Capture Personalized Contexts of College Student Well-being in 2020: Case Study

et al. 2021

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“…Thirty-two low and highly active participants (17 females, 15 males) were recruited through advertising on university billboards, social media, and via contacts in sport clubs. While the final sample size was similar to other Oura Ring validation studies [6,8,11,16,20,23], the MEDAL project initially aimed to recruit 40 participants but had to accept a slightly smaller sample size due to a limited time-period for data collection and access to devices needed for measurement. The study protocol and selection criteria of participants were designed to recruit a sample with large variation in PA level to enable device validation across the whole intensity span in both controlled and normal environments.…”

Section: Participants and Recruitmentmentioning

confidence: 99%

Validation of Oura ring energy expenditure and steps in laboratory and free-living

Kristiansson

Fridolfsson

Arvidsson

et al. 2023

BMC Med Res Methodol

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Background Commercial activity trackers are increasingly used in research and compared with research-based accelerometers are often less intrusive, cheaper, with improved storage and battery capacity, although typically less validated. The present study aimed to determine the validity of Oura Ring step-count and energy expenditure (EE) in both laboratory and free-living. Methods Oura Ring EE was compared against indirect calorimetry in the laboratory, followed by a 14-day free-living study with 32 participants wearing an Oura Ring and reference monitors (three accelerometers positioned at hip, thigh, and wrist, and pedometer) to evaluate Oura EE variables and step count. Results Strong correlations were shown for Oura versus indirect calorimetry in the laboratory (r = 0.93), and versus reference monitors for all variables in free-living (r ≥ 0.76). Significant (p < 0.05) mean differences for Oura versus reference methods were found for laboratory measured sitting (− 0.12 ± 0.28 MET), standing (− 0.27 ± 0.33 MET), fast walk (− 0.82 ± 1.92 MET) and very fast run (− 3.49 ± 3.94 MET), and for free-living step-count (2124 ± 4256 steps) and EE variables (MET: − 0.34-0.26; TEE: 362–494 kcal; AEE: − 487-259 kcal). In the laboratory, Oura tended to underestimate EE with increasing discrepancy as intensity increased. The combined activities and slow running in the laboratory, and all MET placements, TEE hip and wrist, and step count in free-living had acceptable measurement errors (< 10% MAPE), whereas the remaining free-living variables showed close to (≤13.2%) acceptable limits. Conclusion This is the first study investigating the validity of Oura Ring EE against gold standard methods. Oura successfully identified major changes between activities and/or intensities but was less responsive to detailed deviations within activities. In free-living, Oura step-count and EE variables tightly correlated with reference monitors, though with systemic over- or underestimations indicating somewhat low intra-individual validity of the ring versus the reference monitors. However, the correlations between the devices were high, suggesting that the Oura can detect differences at group-level for active and total energy expenditure, as well as step count.

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“…Whilst RMT data features certainly appear relevant to depression, there is less evidence for the clinical utility of this in improving depression outcomes in young people either through objective screening, symptom management, relapse-prevention, or just-in-time adaptive interventions. Of the 28 records pertaining to clinical utility only 10 were published studies, with the remaining 18 being registries and/or protocols of clinical trials yet to be completed [78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96] .…”

Section: Clinical Utilitymentioning

confidence: 99%

Remote measurement technologies for depression in young people: A realist review with meaningful lived experience involvement and recommendations for future research and practice

Walsh

Naughton

Sharpe

et al. 2022

Preprint

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BackgroundRemote measurement technologies (RMT), such as smartphones and wearables, allow data collection from an individual in real-time during their day-to-day life, from which their mood, physiology, behaviour, and environment can be inferred. As such, RMT could monitor and detect changes relevant to depression for objective screening, symptom management, relapse-prevention, and personalised interventions. Whilst RMT for depression in young people has been previously reviewed, technological capability and digital mental health literature steeply increase each year but with limited scrutiny of the realist and ethical considerations likely to impact the benefits, implementation, and overall potential of RMT in the real-world.MethodsA realist review of RMT for depression in young people aged 14 – 24 years was conducted in collaboration with two young, lived experience co-researchers from The McPin Foundation Young People’s Network (YPN) and in accordance with the Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) for quality and publication. Iterative searches across 10 electronic databases and 7 sources of grey literature, fine-tuning of selection-criteria, data extraction and evidence synthesis with insights from the wider YPN members allowed gradual refinement of an initial framework into a realist intervention theory.ResultsOf 6118 records identified, 104 were included in evidence synthesis. What does and does not work? Smartphones were most preferred, with both passive and active data collection for a holistic approach but a balance between data quality, intrusiveness, and data privacy. From the evidence currently available, depression was best detected by changes in sleep, mobility, smartphone use, social communication, and self- or- parent-reported mood. This had some uses in screening, self-monitoring, and feedback to the healthcare professional but not in relapse-prevention and personalised interventions, where significantly more research is required. How and why? The impact of RMT as an intervention itself on depression outcomes remained unclear but self-monitoring and feedback improved emotional self-awareness, therapeutic relationship, and help-seeking behaviours. For whom? With limited standardisation and investigation of the impact of depression on adherence rates, there may be an overestimation of how much young people are likely to use RMT in the real-world. However, they were most likely to benefit those interested in and motivated by the data-driven nature, who have lower depression severity, no co-morbidities where self-monitoring could cause harm, and the presence of changeable behaviours. In what contexts? RMT facilitated monitoring during transition to university, known to be associated with worsening depression in young people; however, there were significant challenges in health care and school settings. Adaptability was important, such that RMT were culturally compelling and accurate for the local context. Overall, there were many gaps in the evidence and common methodological issues across the literature.ConclusionsFrom the evidence base and lived experience insights, realist and ethical considerations were highlighted, as well as the remaining gaps in evidence and methodological issues common across the literature. For RMT to be the scalable solution for depression in young people rather than a case of overplayed potential, several important recommendations for future research and practice were made.

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Assessing the Mental Health of Emerging Adults Through a Mental Health App: Protocol for a Prospective Pilot Study

Cited by 13 publications

References 79 publications

Using Multimodal Assessments to Capture Personalized Contexts of College Student Well-being in 2020: Case Study

Using Multimodal Assessments to Capture Personalized Contexts of College Student Well-being in 2020: Case Study

Validation of Oura ring energy expenditure and steps in laboratory and free-living

Remote measurement technologies for depression in young people: A realist review with meaningful lived experience involvement and recommendations for future research and practice

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