scholarly journals Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (Preprint)

2017 ◽  
Author(s):  
Akane Sano ◽  
Sara Taylor ◽  
Andrew W McHill ◽  
Andrew JK Phillips ◽  
Laura K Barger ◽  
...  
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Wearable Sensors ◽  
High Stress ◽  
Well Being ◽  
Poor Mental Health ◽  
Wearable Sensor ◽  
Multimodal Data

BACKGROUND Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. OBJECTIVE We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. METHODS We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. RESULTS We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. CONCLUSIONS New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping.

scholarly journals Promotion of mental health in young adults via mobile phone app: study protocol of the ECoWeB (emotional competence for well-being in Young adults) cohort multiple randomised trials

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
A. Newbold ◽  
F. C. Warren ◽  
R. S. Taylor ◽  
C. Hulme ◽  
S. Burnett ◽  
...  
Keyword(s):  
Mental Health ◽  
Young Adults ◽  
Young People ◽  
Mobile Phone ◽  
Primary Endpoint ◽  
Emotional Competence ◽  
Well Being ◽  
Poor Mental Health ◽  
Link Type ◽  
Self Help

Abstract Background Promoting well-being and preventing poor mental health in young people is a major global priority. Building emotional competence (EC) skills via a mobile app may be an effective, scalable and acceptable way to do this. However, few large-scale controlled trials have examined the efficacy of mobile apps in promoting mental health in young people; none have tailored the app to individual profiles. Method/design The Emotional Competence for Well-Being in Young Adults cohort multiple randomised controlled trial (cmRCT) involves a longitudinal prospective cohort to examine well-being, mental health and EC in 16–22 year olds across 12 months. Within the cohort, eligible participants are entered to either the PREVENT trial (if selected EC scores at baseline within worst-performing quartile) or to the PROMOTE trial (if selected EC scores not within worst-performing quartile). In both trials, participants are randomised (i) to continue with usual practice, repeated assessments and a self-monitoring app; (ii) to additionally receive generic cognitive-behavioural therapy self-help in app; (iii) to additionally receive personalised EC self-help in app. In total, 2142 participants aged 16 to 22 years, with no current or past history of major depression, bipolar disorder or psychosis will be recruited across UK, Germany, Spain, and Belgium. Assessments take place at baseline (pre-randomisation), 1, 3 and 12 months post-randomisation. Primary endpoint and outcome for PREVENT is level of depression symptoms on the Patient Health Questionnaire-9 at 3 months; primary endpoint and outcome for PROMOTE is emotional well-being assessed on the Warwick-Edinburgh Mental Wellbeing Scale at 3 months. Depressive symptoms, anxiety, well-being, health-related quality of life, functioning and cost-effectiveness are secondary outcomes. Compliance, adverse events and potentially mediating variables will be carefully monitored. Conclusions The trial aims to provide a better understanding of the causal role of learning EC skills using interventions delivered via mobile phone apps with respect to promoting well-being and preventing poor mental health in young people. This knowledge will be used to develop and disseminate innovative evidence-based, feasible, and effective Mobile-health public health strategies for preventing poor mental health and promoting well-being. Trial registration ClinicalTrials.gov (www.clinicaltrials.org). Number of identification: NCT04148508 November 2019.

scholarly journals Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study (Preprint)

2021 ◽  
Author(s):  
Christine Cislo ◽  
Caroline Clingan ◽  
Kristen Gilley ◽  
Michelle Rozwadowski ◽  
Izzy Gainsburg ◽  
...  
Keyword(s):  
Mental Health ◽  
At Risk ◽  
Mobile Health ◽  
Wearable Sensors ◽  
Well Being ◽  
Student Health ◽  
Wearable Sensor ◽  
Students At Risk ◽  
College Student Population ◽  
Health And Well Being

BACKGROUND The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student’s mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being. OBJECTIVE Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19. METHODS We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. RESULTS This study enrolled 2158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing. CONCLUSIONS This study examined student health and well-being during the COVID-19 pandemic. While data collection and analyses are ongoing, the study will assess the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19. CLINICALTRIAL ClinicalTrials.gov NCT04766788

scholarly journals Military spouses with deployed partners are at greater risk of poor perinatal mental health: a scoping review

2019 ◽  
Vol 165 (5) ◽  
pp. 363-370 ◽  
Author(s):  
Lauren Rose Godier-McBard ◽  
L Ibbitson ◽  
C Hooks ◽  
M Fossey
Keyword(s):  
Mental Health ◽  
Social Support ◽  
Scoping Review ◽  
Healthcare Providers ◽  
Well Being ◽  
Perinatal Period ◽  
Poor Mental Health ◽  
Adverse Outcomes ◽  
Military Spouses ◽  
Perinatal Mental Health

BackgroundPoor mental health in the perinatal period is associated with a number of adverse outcomes for the individual and the wider family. The unique circumstances in which military spouses/partners live may leave them particularly vulnerable to developing perinatal mental health (PMH) problems.MethodsA scoping review was carried out to review the literature pertaining to PMH in military spouses/partners using the methodology outlined by Arksey and O’Malley (2005). Databases searched included EBSCO, Gale Cengage Academic OneFile, ProQuest and SAGE.ResultsThirteen papers fulfilled the inclusion criteria, all from the USA, which looked a PMH or well-being in military spouses. There was a strong focus on spousal deployment as a risk factor for depressive symptoms and psychological stress during the perinatal period. Other risk factors included a lack of social/emotional support and increased family-related stressors. Interventions for pregnant military spouses included those that help them develop internal coping strategies and external social support.ConclusionsUS literature suggests that military spouses are particularly at risk of PMH problems during deployment of their serving partner and highlights the protective nature of social support during this time. Further consideration needs to be made to apply the findings to UK military spouses/partners due to differences in the structure and nature of the UK and US military and healthcare models. Further UK research is needed, which would provide military and healthcare providers with an understanding of the needs of this population allowing effective planning and strategies to be commissioned and implemented.

scholarly journals Individual- and Relationship-Level Factors Related to Better Mental Health Outcomes following Child Abuse: Results from a Nationally Representative Canadian Sample

2016 ◽  
Vol 61 (12) ◽  
pp. 776-788 ◽  
Author(s):  
Tracie O. Afifi ◽  
Harriet L. MacMillan ◽  
Tamara Taillieu ◽  
Sarah Turner ◽  
Kristene Cheung ◽  
...  
Keyword(s):  
Mental Health ◽  
Child Abuse ◽  
Health Outcomes ◽  
Well Being ◽  
Canadian Community Health Survey ◽  
Poor Mental Health ◽  
Mental Health Outcomes ◽  
Abuse History ◽  
Good Mental Health ◽  
Nationally Representative

Objective: Child abuse can have devastating mental health consequences. Fortunately, not all individuals exposed to child abuse will suffer from poor mental health. Understanding what factors are related to good mental health following child abuse can provide evidence to inform prevention of impairment. Our objectives were to 1) describe the prevalence of good, moderate, and poor mental health among respondents with and without a child abuse history; 2) examine the relationships between child abuse and good, moderate, and poor mental health outcomes; 3) examine the relationships between individual- and relationship-level factors and better mental health outcomes; and 4) determine if individual- and relationship-level factors moderate the relationship between child abuse and mental health. Method: Data were from the nationally representative 2012 Canadian Community Health Survey: Mental Health ( n = 23,395; household response rate = 79.8%; 18 years and older). Good, moderate, and poor mental health was assessed using current functioning and well-being, past-year mental disorders, and past-year suicidal ideation. Results: Only 56.3% of respondents with a child abuse history report good mental health compared to 72.4% of those without a child abuse history. Individual- and relationship-level factors associated with better mental health included higher education and income, physical activity, good coping skills to handle problems and daily demands, and supportive relationships that foster attachment, guidance, reliable alliance, social integration, and reassurance of worth. Conclusions: This study identifies several individual- and relationship-level factors that could be targeted for intervention strategies aimed at improving mental health outcomes following child abuse.

scholarly journals Shame Mediates the Relationship Between Pain Invalidation and Depression

2021 ◽  
Vol 12 ◽  
Author(s):  
Brandon L. Boring ◽  
Kaitlyn T. Walsh ◽  
Namrata Nanavaty ◽  
Vani A. Mathur
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Social Withdrawal ◽  
Well Being ◽  
Poor Mental Health ◽  
Future Research ◽  
Internalized Shame ◽  
Self Worth ◽  
The Impact ◽  
The Relationship

The experience of pain is subjective, yet many people have their pain invalidated or not believed. Pain invalidation is associated with poor mental health, including depression and lower well-being. Qualitative investigations of invalidating experiences identify themes of depression, but also social withdrawal, self-criticism, and lower self-worth, all of which are core components of shame. Despite this, no studies have quantitatively assessed the interrelationship between pain invalidation, shame, and depression. To explore this relationship, participants recounted the frequency of experienced pain invalidation from family, friends, and medical professionals, as well as their feelings of internalized shame and depressive symptoms. As shame has been shown to be a precursor for depression, we further explored the role of shame as a mediator between pain invalidation and depressive symptoms. All sources of pain invalidation were positively associated with shame and depressive symptoms, and shame fully mediated the relationship between each source of pain invalidation and depression. Relative to other sources, pain invalidation from family was most closely tied to shame and depression. Overall, findings indicate that one mechanism by which pain invalidation may facilitate depression is via the experience of shame. Future research may explore shame as a potential upstream precursor to depression in the context of pain. Findings provide more insight into the harmful influence of pain invalidation on mental health and highlight the impact of interpersonal treatment on the experiences of people in pain.

scholarly journals Mobile Health for All: Public-Private Partnerships Can Create a New Mental Health Landscape

2016 ◽  
Vol 3 (2) ◽  
pp. e26 ◽  
Author(s):  
Dror Ben-Zeev
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Severe Mental Illness ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Mobile Technology ◽  
Low Income ◽  
Mental Health Problems ◽  
Assistance Program ◽  
The U.S

Research has already demonstrated that different mHealth approaches are feasible, acceptable, and clinically promising for people with mental health problems. With a robust evidence base just over the horizon, now is the time for policy makers, researchers, and the private sector to partner in preparation for the near future. The Lifeline Assistance Program is a useful model to draw from. Created in 1985 by the U.S. Federal Communications Commission (FCC), Lifeline is a nationwide program designed to help eligible low-income individuals obtain home phone and landline services so they can pursue employment, reach help in case of emergency, and access social services and healthcare. In 2005, recognizing the broad shift towards mobile technology and mobile-cellular infrastructure, the FCC expanded the program to include mobile phones and data plans. The FCC provides a base level of federal support, but individual states are responsible for regional implementation, including engagement of commercial mobile phone carriers. Given the high rates of disability and poverty among people with severe mental illness, many are eligible to benefit from Lifeline and research has shown that a large proportion does in fact use this program to obtain a mobile phone and data plan. In the singular area of mobile phone use, the gap between people with severe mental illness and the general population in the U.S. is vanishing. Strategic multi-partner programs will be able to grant access to mHealth for mental health programs to those who will not be able to afford them—arguably, the people who need them the most. Mobile technology manufacturing costs are dropping. Soon all mobile phones in the marketplace, including the more inexpensive devices that are made available through subsidy programs, will have “smart” capabilities (ie, internet connectivity and the capacity to host apps). Programs like Lifeline could be expanded to include mHealth resources that capitalize on “smart” functions, such as secure/encrypted clinical texting programs and mental health monitoring and illness-management apps. Mobile phone hardware and software development companies could be engaged to add mHealth programs as a standard component in the suite of tools that come installed on their mobile phones; thus, in addition to navigation apps, media players, and games, the new Android or iPhone could come with guided relaxation videos, medication reminder systems, and evidence-based self-monitoring and self-management tools. Telecommunication companies could be encouraged to offer mHealth options with their data plans. Operating system updates pushed out by the mobile carrier companies could come with optional mHealth applications for those who elect to download them. In the same manner in which the Lifeline Assistance Program has helped increase access to fundamental opportunities to so many low-income individuals, innovative multi-partner programs have the potential to put mHealth for mental health resources in the hands of millions in the years ahead.

Factors associated with mental health among high school students in Iran: Does mobile phone overuse associate with poor mental health?

2018 ◽  
Vol 31 (1) ◽  
pp. 6-13 ◽  
Author(s):  
Hassan Mahmoodi ◽  
Haidar Nadrian ◽  
Abdolreza Shaghaghi ◽  
Mohammad Asghari Jafarabadi ◽  
Asad Ahmadi ◽  
...  
Keyword(s):  
Mental Health ◽  
High School ◽  
High School Students ◽  
Mobile Phone ◽  
Poor Mental Health ◽  
School Students ◽  
Factors Associated

scholarly journals Can Machine Learning Predict Stress Reduction Based on Wearable Sensors’ Data Following Relaxation at Workplace? A Pilot Study

Processes ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 448
Author(s):  
Alessandro Tonacci ◽  
Alessandro Dellabate ◽  
Andrea Dieni ◽  
Lorenzo Bachi ◽  
Francesco Sansone ◽  
...  
Keyword(s):  
Machine Learning ◽  
Stress Reduction ◽  
Wearable Sensors ◽  
Well Being ◽  
Significant Heterogeneity ◽  
Learning Approaches ◽  
Significant Difference ◽  
Group A ◽  
Group B ◽  
Audio Video

Nowadays, psychological stress represents a burdensome condition affecting an increasing number of subjects, in turn putting into practice several strategies to cope with this issue, including the administration of relaxation protocols, often performed in non-structured environments, like workplaces, and constrained within short times. Here, we performed a quick relaxation protocol based on a short audio and video, and analyzed physiological signals related to the autonomic nervous system (ANS) activity, including electrocardiogram (ECG) and galvanic skin response (GSR). Based on the features extracted, machine learning was applied to discriminate between subjects benefitting from the protocol and those with negative or no effects. Twenty-four healthy volunteers were enrolled for the protocol, equally and randomly divided into Group A, performing an audio-video + video-only relaxation, and Group B, performing an audio-video + audio-only protocol. From the ANS point of view, Group A subjects displayed a significant difference in the heart rate variability-related parameter SDNN across the test phases, whereas both groups displayed a different GSR response, albeit at different levels, with Group A displaying greater differences across phases with respect to Group B. Overall, the majority of the volunteers enrolled self-reported an improvement of their well-being status, according to structured questionnaires. The use of neural networks helped in discriminating those with a positive effect of the relaxation protocol from those with a negative/neutral impact based on basal autonomic features with a 79.2% accuracy. The results obtained demonstrated a significant heterogeneity in autonomic effects of the relaxation, highlighting the importance of maintaining a structured, well-defined protocol to produce significant benefits at the ANS level. Machine learning approaches can be useful to predict the outcome of such protocols, therefore providing subjects less prone to positive responses with personalized advice that could improve the effect of such protocols on self-relaxation perception.

scholarly journals Risk and resilience during COVID-19: A new study in the Zigler paradigm of developmental science

2020 ◽  
pp. 1-16
Author(s):  
Suniya S. Luthar ◽  
Ashley M. Ebbert ◽  
Nina L. Kumar
Keyword(s):  
Mental Health ◽  
High Stress ◽  
Well Being ◽  
Lessons Learned ◽  
Risk And Resilience ◽  
Community Based ◽  
Science And Policy ◽  
Mixed Methods Approach ◽  
Clinically Significant ◽  
Home And School

Abstract When children are exposed to serious life adversities, Ed Zigler believed that developmental scientists must expediently strive to illuminate the most critical directions for beneficial interventions. In this paper, we present a new study on risk and resilience on adolescents during COVID-19, bookended – in introductory and concluding discussions – by descriptions of programmatic work anchored in lessons learned from Zigler. The new study was conducted during the first two months of the pandemic, using a mixed-methods approach with a sample of over 2,000 students across five high schools. Overall, rates of clinically significant symptoms were generally lower as compared to norms documented in 2019. Multivariate regressions showed that the most robust, unique associations with teens’ distress were with feelings of stress around parents and support received from them. Open ended responses to three questions highlighted concerns about schoolwork and college, but equally, emphasized worries about families’ well-being, and positive outreach from school adults. The findings have recurred across subsequent school assessments, and strongly resonate with contemporary perspectives on resilience in science and policy. If serious distress is to be averted among youth under high stress, interventions must attend not just to the children's mental health but that of salient caregiving adults at home and school. The article concludes with some specific recommendations for community-based initiatives to address mental health through continued uncertainties of the pandemic.

Does precarious employment ruin youth health and marriage? Evidence from Egypt using longitudinal data

2020 ◽  
Vol 19 (3) ◽  
pp. 391-406
Author(s):  
Mesbah Fathy Sharaf ◽  
Ahmed Shoukry Rashad
Keyword(s):  
Mental Health ◽  
Longitudinal Data ◽  
Fixed Effects ◽  
Job Insecurity ◽  
Well Being ◽  
Poor Mental Health ◽  
Youth Workers ◽  
Fixed Effects Model ◽  
Precarious Employment ◽  
Content Type

Purpose This study aims to analyze whether precarious employment is associated with youth mental health, self-rated health and happiness in marriage and whether this association differs by sex. Design/methodology/approach This paper uses longitudinal data from the Survey of Young People in Egypt conducted in 2009 and 2014 and estimates a fixed-effects model to control for time-invariant unobserved individual heterogeneity. The analysis is segregated by sex. Findings The results indicate that precarious employment is significantly associated with poor mental health and less happiness in marriage for males and is positively associated with poor self-reported health for females. The adverse impact of precarious work is likely to be mediated through poor working conditions such as low salary, maltreatment at work, job insecurity and harassment from colleagues. Social implications Governmental policies that tackle job precariousness are expected to improve population health and marital welfare. Originality/value Egypt has witnessed a significant increase in the prevalence of precarious employment, particularly among youth, in recent decades, yet the evidence on its effect on the health and well-being of youth workers is sparse. This paper adds to the extant literature by providing new evidence on the social and health repercussions of job precariousness from an understudied region.

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