scholarly journals Ambulatory Smoking Habits Investigation based on Physiology and Context (ASSIST) using wearable sensors and mobile phones: protocol for an observational study

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e028284 ◽  
Author(s):  
Donghui Zhai ◽  
Giuseppina Schiavone ◽  
Ilse Van Diest ◽  
Elske Vrieze ◽  
Walter DeRaedt ◽  
...  
Keyword(s):  
Observational Study ◽  
Mobile Phones ◽  
Wearable Sensors ◽  
Well Being ◽  
Heterogeneous Data ◽  
Smoking Habits ◽  
Office Worker ◽  
Ethical Review ◽  
P Value ◽  
Data Set

IntroductionSmoking prevalence continues to be high over the world and smoking-induced diseases impose a heavy burden on the medical care system. As believed by many researchers, a promising way to promote healthcare and well-being at low cost for the large vulnerable smoking population is through eHealth solutions by providing self-help information about smoking cessation. But in the absence of first-hand knowledge about smoking habits in daily life settings, systems built on these methods often fail to deliver proactive and tailored interventions for different users and situations over time, thus resulting in low efficacy. To fill the gap, an observational study has been developed on the theme of objective and non-biased monitoring of smoking habits in a longitudinal and ambulatory mode. This paper presents the study protocol. The primary objective of the study is to reveal the contextual and physiological pattern of different smoking behaviours using wearable sensors and mobile phones. The secondary objectives are to (1) analyse cue factors and contextual situations of smoking events; (2) describe smoking types with regard to users’ characteristics and (3) compare smoking types between and within subjects.Methods and analysesThis is an observational study aimed at reaching 100 participants. Inclusion criteria are adults aged between 18 and 65 years, current smoker and office worker. The primary outcome is a collection of a diverse and inclusive data set representing the daily smoking habits of the general smoking population from similar social context. Data analysation will revolve around our primary and secondary objectives. First, linear regression and linear mixed model will be used to estimate whether a factor or pattern have consistent (p value<0.05) correlation with smoking. Furthermore, multivariate multilevel analysis will be used to examine the influence of smokers’ characteristics (sex, age, education, socioeconomic status, nicotine dependence, attitudes towards smoking, quit attempts, etc), contextual factors, and physical and emotional statuses on their smoking habits. Most recent machine learning techniques will also be explored to combine heterogeneous data for classification of smoking events and prediction of craving.Ethics and disseminationThe study was designed together by an interdisciplinary group of researchers, including psychologist, psychiatrist, engineer and user involvement coordinator. The protocol was reviewed and approved by the ethical review board of UZ Leuven on 18 April 2016, with an approval number S60078. The study will allow us to characterise the types of smokers and triggering events. These findings will be disseminated through peer-reviewed articles.

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.

Burnout Syndrome among Students of a Private Medical College at Lahore

2021 ◽  
Vol 15 (9) ◽  
pp. 2896-2899
Author(s):  
Farrukh Sarfraz ◽  
Muhammad Zahid Latif ◽  
Fahad Sarfraz ◽  
Sadia Ikram ◽  
Nasir Iqbal ◽  
...  
Keyword(s):  
Medical Education ◽  
Study Design ◽  
Human Life ◽  
Maslach Burnout Inventory ◽  
Well Being ◽  
Burnout Syndrome ◽  
Ethical Review ◽  
P Value ◽  
Undergraduate Medical Students ◽  
Medical College

Background: Background: Medical education is a dynamic and lifelong process directly linked with human life. The profession is supposed to minimize the human sufferings, prevent diseases and promote the healthy practices at individual and community level. Burnout in undergraduate medical education can influence the academics and overall well-being of the learners in a negative way, which will ultimately affect the process of learning. Objective: The current study was conducted to assess the magnitude of Burnout syndrome among the students of a private medical college. Study Design: Descriptive, cross sectional study design. Place & Duration: The study was conducted during the period of six months from September 2019 to March 2020 at Azra Naheed Medical College Lahore. Methodology: Non probability convenient sampling technique was used and all the students of 3rd and 4th year MBBS were invited for the study. Burnout was evaluated by using the Maslach Burnout Inventory-Student Survey (MBI-SS). Approval of institutional ethical review committee and informed consent from the participants were obtained. The collected data was organized, entered in the version 21 of SPSS and analyzed by the use of statistical tools. Results: Out of total 200 participants, 43.5% were females and 56.5 % were males, 55.5% were from 3rd year and 44.5% were from 4th year of MBBS class. The prevalence of high Burnout was found to be 45(22.5%). Gender and residence-based prevalence was studied and calculated P value of (0.87) and (0.41), showed no association. However, a statistically significant association of burnout, (P value 0.003) was found between the 3rd and 4th year MBBS classes. Conclusion: The study concludes that a substantial number of undergraduate medical students suffers from the Burnout syndrome which may influence the health, well-being and academic progress of students in a negative way. Preventive measures including counselling, early diagnosis and clinical management should be opted by the medical institutes. Key Words: Burnout, Medical Education, Emotional Exhaustion, Depersonalization

scholarly journals TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Karel Mundnich ◽  
Brandon M. Booth ◽  
Michelle L’Hommedieu ◽  
Tiantian Feng ◽  
Benjamin Girault ◽  
...  
Keyword(s):  
Job Performance ◽  
Wearable Sensors ◽  
Well Being ◽  
Behavioral Data ◽  
Physiological Data ◽  
Environmental Sensors ◽  
Hospital Workers ◽  
Data Set ◽  
Multimodal Corpus ◽  
Over Time

AbstractWe present a novel longitudinal multimodal corpus of physiological and behavioral data collected from direct clinical providers in a hospital workplace. We designed the study to investigate the use of off-the-shelf wearable and environmental sensors to understand individual-specific constructs such as job performance, interpersonal interaction, and well-being of hospital workers over time in their natural day-to-day job settings. We collected behavioral and physiological data from n = 212 participants through Internet-of-Things Bluetooth data hubs, wearable sensors (including a wristband, a biometrics-tracking garment, a smartphone, and an audio-feature recorder), together with a battery of surveys to assess personality traits, behavioral states, job performance, and well-being over time. Besides the default use of the data set, we envision several novel research opportunities and potential applications, including multi-modal and multi-task behavioral modeling, authentication through biometrics, and privacy-aware and privacy-preserving machine learning.

Customer-Related Social Stressors

2015 ◽  
Vol 14 (4) ◽  
pp. 165-181 ◽  
Author(s):  
Sarah Dudenhöffer ◽  
Christian Dormann
Keyword(s):  
Service Providers ◽  
Principal Component ◽  
Well Being ◽  
Emotional Dissonance ◽  
Social Stressors ◽  
Data Set ◽  
Confirmatory Factor Analyses ◽  
Confirmatory Factor ◽  
Service Jobs ◽  
Single Data

Abstract. The purpose of this study was to replicate the dimensions of the customer-related social stressors (CSS) concept across service jobs, to investigate their consequences for service providers’ well-being, and to examine emotional dissonance as mediator. Data of 20 studies comprising of different service jobs (N = 4,199) were integrated into a single data set and meta-analyzed. Confirmatory factor analyses and explorative principal component analysis confirmed four CSS scales: disproportionate expectations, verbal aggression, ambiguous expectations, disliked customers. These CSS scales were associated with burnout and job satisfaction. Most of the effects were partially mediated by emotional dissonance. Further analyses revealed that differences among jobs exist with regard to the factor solution. However, associations between CSS and outcomes are mainly invariant across service jobs.

FAKTOR – FAKTOR YANG BERHUBUNGAN DENGAN KEJADIAN PNEUMONIA PADA BALITA DI WILAYAH KERJA PUSKESMAS WONOREJO SAMARINDA TAHUN 2017

2018 ◽  
Vol 3 (2) ◽  
pp. 76
Author(s):  
Novi Anggun Pusvitasary
Keyword(s):  
Environmental Factors ◽  
Family Member ◽  
Cause Of Death ◽  
Family Members ◽  
Smoking Behavior ◽  
Smoking Habits ◽  
P Value ◽  
Behavioral Factors ◽  
The World ◽  
Health Standards

Pneumonia disease is the leading cause of death of babies in the world. The prevalence of pneumonia in infants is 18.5 / mil. Data from Samarinda City Health Office during the last 1 year there are 91 cases of pneumonia in Karang Anyar Village and 63 cases in Teluk Lerong Ulu Village. Factors causing pneumonia are toddler factors, behavioral factors, and environmental factors. The results show there is a relationship between house humidity (p value = 0,013; OR = 0,192), house dwelling density (p value = 0,024; OR = 0,214), and family member smoking behavior (p value = 0,006; OR = 10,450) with incidence of pneumonia in toddlers in the Working Area of Puskesmas Wonorejo Samarinda. There was no correlation between house temperature (p value = 0,214; OR = 0,337), house lighting (p value = 0,095; OR = 3,188) and family disease history (p value = 0,707; OR = 0,753) with Pneumonia occurrence in infant in region Work Puskesmas Wonorejo Samarinda. It was concluded that there was a relationship between house humidity, home dwelling density, and smoking behavior of family members with the incidence of pneumonia in infants. It is recommended to be able to apply housing health requirements that meet health standards to reduce the incidence of pneumonia in infants and change smoking habits.

Configurations to Superior Environmental Innovation Strategy: A Both–And Approach

2021 ◽  
pp. 108602662110316
Author(s):  
Tiziana Russo-Spena ◽  
Nadia Di Paola ◽  
Aidan O’Driscoll
Keyword(s):  
Climate Change ◽  
Value Chain ◽  
Critical Role ◽  
Well Being ◽  
Point Of View ◽  
Future Generations ◽  
Innovation Strategy ◽  
Environmental Innovation ◽  
Data Set

An effective climate change action involves the critical role that companies must play in assuring the long-term human and social well-being of future generations. In our study, we offer a more holistic, inclusive, both–and approach to the challenge of environmental innovation (EI) that uses a novel methodology to identify relevant configurations for firms engaging in a superior EI strategy. A conceptual framework is proposed that identifies six sets of driving characteristics of EI and two sets of beneficial outcomes, all inherently tensional. Our analysis utilizes a complementary rather than an oppositional point of view. A data set of 65 companies in the ICT value chain is analyzed via fuzzy-set comparative analysis (fsQCA) and a post-QCA procedure. The results reveal that achieving a superior EI strategy is possible in several scenarios. Specifically, after close examination, two main configuration groups emerge, referred to as technological environmental innovators and organizational environmental innovators.

scholarly journals POS0441 DEVELOPMENT OF RHEUMATOID ARTHRITIS AMONG ANTI-CITRULLINATED PROTEIN ANTIBODIES POSITIVE ASYMPTOMATIC INDIVIDUALS: A PROSPECTIVE OBSERVATIONAL STUDY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 449.1-449
Author(s):  
S. Mizuki ◽  
K. Horie ◽  
K. Imabayashi ◽  
K. Mishima ◽  
K. Oryoji
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Observational Study ◽  
Rheumatoid Factor ◽  
Prospective Observational Study ◽  
Enzyme Linked Immunosorbent Assay ◽  
P Value ◽  
Healthy Population ◽  
Asymptomatic Individuals ◽  
Citrullinated Protein

Background:In the idividuals with genetic and enviromental risk factors, immune events at mucosal surfaces occur and may precede systemic autoimmunity. Anti-citrullinated protein antibodies (ACPA) are present in the serum for an average of 3-5 years prior to the onset of rheumatoid arthritis (RA) during an asymptomatic period. In ACPA-positivite individuals, the additional presence of RA-related risk factors appears to add significant power for the development of RA. To date, there have been few reports in which clinical courses of ACPA-positive asymptomatic individuals were investigated prospectively.Objectives:To observe the clinical time course of ACPA-positive healthy population for the development of RA.Methods:Healthy volunteers without joint pain or stiffness, who attended the comprehensive health screening of our hospital, were enrolled in this prospective observational study. The serum ACPA levels were quantified by Ig-G anti-cyclic citrullinated peptide enzyme-linked immunosorbent assay with levels > 4.4 U/mL considered positive. ACPA-positive subjects were followed by rheumatologists of our department clinically or a questionnaire sent by mail for screening to detect arthritis.Results:5,971 healthy individuals without joint symptons were included. Ninty-two (1.5%) were positive for ACPA. Of these, 19 (20.7%) developed RA and two were suspected as RA by mail questionnaire. Their average age were 58-years, and women were 68%. The average duration between the date of serum sampling and diagnosis was 10.7 months. ACPA-positive individuals who developed to RA had higher serum ACPA and Ig-M rheumatoid factor levels than ACPA-positive individuals who did not (P value by Mann-Whitney U test: 0.002, 0.005, respectively).Conclusion:Among ACPA-positive asymptomatic individuals, 20% developed RA. The higher titer of ACPA and Ig-M rheumatoid factor levels are risk factors for devoloping RA.Disclosure of Interests:None declared

scholarly journals Primary Prevention of Dementia: An Ethical Review

2020 ◽  
pp. 1-10
Author(s):  
Dorothee Horstkötter ◽  
Kay Deckers ◽  
Sebastian Köhler
Keyword(s):  
Synergistic Effects ◽  
Well Being ◽  
Ethical Review ◽  
Medical Risk ◽  
Medical Risk Factors ◽  
Societal Challenges ◽  
Dementia Prevention ◽  
Health Related ◽  
Personal Level

Dementia poses important medical and societal challenges, and of all health risks people face in life, dementia is one of the most feared. Recent research indicates that up to about 40% of all cases of dementia might be preventable. A series of environmental, social, and medical risk-factors have been identified and that should be targeted from midlife onwards when people are still cognitively healthy. At first glance, this seems not merely advisable, but even imperative. However, these new developments trigger a series of new ethical questions and concerns which have hardly been addressed to date. Pro-active ethical reflection, however, is crucial to ensure that the interests and well-being of those affected, ultimately all of us, are adequately respected. This is the goal of the current contribution. Against the background of a concrete case in primary dementia prevention, it provides a systematic overview of the current ethical literature and sketches an ethical research agenda. First, possible benefits of increased well-being must be balanced with the burdens of being engaged in particularly long-term interventions for which it is unclear whether they will ever pay out on a personal level. Second, while knowledge about one’s options to maintain brain health might empower people, it might also undermine autonomy, put high social pressure on people, medicalize healthy adults, and stigmatize those who still develop dementia. Third, while synergistic effects might occur, the ideals of dementia prevention might also conflict with other health and non-health related values people hold in life.

scholarly journals Validation of the Workplace Integrated Safety and Health (WISH) assessment in a sample of nursing homes using Item Response Theory (IRT) methods

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e045656
Author(s):  
María Andrée López Gómez ◽  
Daniel A Gundersen ◽  
Leslie I Boden ◽  
Glorian Sorensen ◽  
Jeffrey N Katz ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Nursing Homes ◽  
Item Response ◽  
Well Being ◽  
P Value ◽  
Response Theory ◽  
Health Safety ◽  
Worker Health ◽  
Safety And Health ◽  
The Usa

ObjectivesTo validate and test the dimensionality of six constructs from the Workplace Integrated Safety and Health (WISH) assessment, an instrument that assesses the extent to which organisations implement integrated systems approaches for protecting and promoting worker health, safety and well-being, in a sample of nursing homes in the USA.DesignValidation of an assessment scale using data from a cross-sectional survey.SettingNursing homes certified by the Centers for Medicaid and Medicare services in three states of the USA: Ohio, California and Massachusetts.Participants569 directors of nursing from nursing homes serving adults and with more than 30 beds participated in the study.ResultsGraded response Item Response Theory (IRT) models showed that five out of six constructs were unidimensional based on balanced interpretation of model fit statistics—M2 or C2 with p value >0.05, Comparative Fit Index >0.95, lower bound of the root mean squared error of approximation 90% CI <0.06 and standardised root mean square residual <0.08. Overall measure and construct reliability ranged from acceptable to good. Category boundary location parameters indicated that items were most informative for respondents in lower range of latent scores (ie, β1, β2, β3 typically below 0). A few items were recommended to be dropped from future administrations of the instrument based on empirical and substantive interpretation.ConclusionsThe WISH instrument has utility to understand to what extent organisations integrate protection and promotion of worker health, safety and well-being; however, it is most informative in organisations that present lower scores.

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