scholarly journals The importance of productive patient–professional interaction for the well-being of chronically ill patients

2014 ◽  
Vol 24 (4) ◽  
pp. 897-903 ◽  
Author(s):  
Jane Murray Cramm ◽  
Anna Petra Nieboer
Keyword(s):  
Chronically Ill ◽  
Well Being ◽  
Professional Interaction ◽  
Chronically Ill Patients

Behavioral engagement with mHealth for improved well-being among chronically ill patients: the role of human-related and app-related factors (Preprint)

2021 ◽  
Author(s):  
Freek Van Baelen ◽  
Melissa De Regge ◽  
Bart Larivière ◽  
Katrien Verleye ◽  
Sam Schelfout ◽  
...  
Keyword(s):  
Chronic Condition ◽  
Chronically Ill ◽  
Well Being ◽  
Behavioral Engagement ◽  
Related Factors ◽  
Design Factor ◽  
Mobile Health Applications ◽  
Chronically Ill Patients ◽  
The Relationship ◽  
Mhealth Apps

BACKGROUND Last decade has shown a considerable increase in the amount of mobile health applications (mHealth apps) in everyday life. These mHealth apps have the potential to significantly improve well-being for chronically ill patients. However, behavioral engagement with mHealth apps remains low. OBJECTIVE The aim of this study is to provide insight into the behavioral engagement of adults with chronic conditions with mHealth apps by investigating (1) how it is affected by human-related factors (here, physician motivation) and app-related factors (here, app integration) and (2) how it affects their well-being. Supplementary, this study considers the moderating effect of preference for traditional visits to the physician (habit) and experience in app use (app experience) by the patients. METHODS A scenario based experiment among patients with a chronic condition (n= 521) was carried out. A Bayesian SEM model with mediation and moderation analysis was conducted in MPlus. RESULTS Both physician motivation for mHealth app use and mHealth app integration have a positive effect on the behavioral engagement of chronically ill patients towards mHealth apps. Higher behavioral engagement positively influences the hedonic and eudaimonic well-being of chronically ill patients. App experience positively moderates the relationship between app integration and behavioral engagement. A patients’ habit with receiving traditional care does not moderate the relationship between physician motivation and behavioral engagement. CONCLUSIONS The human and design factor play a key role in behavioral engagement and well-being among patients with a chronic condition. During and after the development of a mHealth app, app integration and physician motivation should be a point of attention.

scholarly journals Relationship between Spiritual Well-being and Quality of Life among Chronically Ill Individuals

2015 ◽  
Vol 2 (4) ◽  
Author(s):  
Kanwal Shahbaz ◽  
Dr. Kiran Shahbaz
Keyword(s):  
Quality Of Life ◽  
Economic Status ◽  
Chronically Ill ◽  
Well Being ◽  
Life Questionnaire ◽  
Spiritual Wellbeing ◽  
Socio Economic Status ◽  
Spiritual Well Being ◽  
Chronically Ill Patients

The study was aimed to find the relationship between Spiritual Wellbeing and Quality of Life among chronically ill individuals. Likewise, relationship between demographic variables with Quality of Life and Spiritual Wellbeing were also reconnoitered. Non probability purposive sampling technique was used with chronically ill patients of 15yrs to 80yrs. For measuring spiritual wellbeing Urdu version of “Spiritual Wellness Inventory” (SWI-URDU) (Hanif, 2010) was used. Alternatively, for the measurement of Quality of life WHO Quality of Life Questionnaire (WHO-QOL-BREF) was used. A sample of 200 chronically ill patients were taken from four different hospitals of Rawalpindi and Islamabad. Reliabilities of both the instruments were computed as 0.90 for SWI and 0.74 for WHO-QOL-BREF. Findings show that quality of life and Spiritual wellbeing is positively related among chronically ill individuals. Males found to score high on spiritual wellbeing than females. Individuals with less education are more spiritually inclined as compared to individuals with high education. Quality of life was scored high by individuals with higher education as compared to less education. Married individuals were having better quality of life than unmarried, separated widow and divorced. Patients with middle socio-economic status were having better quality of life than higher and lower. Quality of life was high among individuals with better monthly income than those who have low and middle monthly incomes. Spiritual well being is higher in middle adolescents (15-17) than in late (18-20) adolescents. The current research can be implemented in designing the intervention plans for the betterment of chronically ill patients. It may also help us to develop an insight that each patient with same disease but in different age group and socio-economic status has different needs and plans of treatment and care.

Tele-Health Monitoring of Patient Wellness

2016 ◽  
Vol 25 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Ross Stewart Sparks ◽  
Chris Okugami
Keyword(s):  
Machine Learning ◽  
Vital Sign ◽  
Vital Signs ◽  
Regression Tree ◽  
Chronically Ill ◽  
Well Being ◽  
Machine Learning Techniques ◽  
Care Plans ◽  
Tree Methods ◽  
Chronically Ill Patients

AbstractThe vital signs of chronically ill patients are monitored daily. The record flags when a specific vital sign is stable or when it trends into dangerous territory. Patients also self-assess their current state of well-being, i.e. whether they are feeling worse than usual, neither unwell nor very well compared to usual, or are feeling better than usual. This paper examines whether past vital sign data can be used to forecast how well a patient is going to feel the next day. Reliable forecasting of a chronically sick patient’s likely state of health would be useful in regulating the care provided by a community nurse, scheduling care when the patient needs it most. The hypothesis is that the vital signs indicate a trend before a person feels unwell and, therefore, are lead indicators of a patient going to feel unwell. Time series and classification or regression tree methods are used to simplify the process of observing multiple measurements such as body temperature, heart rate, etc., by selecting the vital sign measures, which best forecast well-being. We use machine learning techniques to automatically find the best combination of these vital sign measurements and their rules that forecast the wellness of individual patients. The machine learning models provide rules that can be used to monitor the future wellness of a patient and regulate their care plans.

Adaptation of the Questionnaire of Hahn, Cella, Bode, and Hanrahan in Spanish Patients Affected by Asbestos Poisoning

2013 ◽  
Vol 16 ◽  
Author(s):  
Miguel Clemente ◽  
Adela Reig-Botella
Keyword(s):  
High Reliability ◽  
Chronically Ill ◽  
Well Being ◽  
Chronic Illnesses ◽  
Future Directions ◽  
The Social ◽  
Male Patients ◽  
Chronically Ill Patients ◽  
Social Companionship ◽  
Very High

AbstractThe purpose of this study was to assess whether or not the questionnaire developed by Hahn, Cella, Bode, and Hanharan (2010) for use with cancer patients accurately measures the social well-being of individuals suffering from chronic illnesses associated with asbestos poisoning. One hundred ten male patients with asbestos poisoning were age-matched in blocks to a comparison group of 70 “healthy” controls, all of whom were current or retired employees of the largest naval company in Spain. The results indicate very high reliability of the Hahn et al. (2010) test to assess social well-being in these chronically ill patients, and a high concurrent validity of the measured outcomes with regard to results of the SCL-90 Derogatis questionnaire, especially on the social well-being dimensions of negative emotional support, negative social companionship, and satisfaction. Limitations of the study and possible future directions are discussed.

scholarly journals Personal condition but social cure: Agentic ingroups elevate well‐being in chronically ill patients through perceptions of personal control

2021 ◽  
Author(s):  
Susanne Relke ◽  
Immo Fritsche ◽  
Torsten Masson ◽  
Anne‐Kathrin Kleine ◽  
Katharina Thien ◽  
...  
Keyword(s):  
Personal Control ◽  
Chronically Ill ◽  
Well Being ◽  
Chronically Ill Patients

Psychological Well-Being: A Study on Chronically Ill Patients

2012 ◽  
Author(s):  
Saika Farid ◽  
Shamim A. Ansari ◽  
Arshad Hussain
Keyword(s):  
Chronically Ill ◽  
Well Being ◽  
Psychological Well Being ◽  
Chronically Ill Patients

scholarly journals Meaning in life: An important factor for the psychological well-being of chronically ill patients?

2013 ◽  
Vol 58 (4) ◽  
pp. 334-341 ◽  
Author(s):  
Jessie Dezutter ◽  
Sara Casalin ◽  
Amy Wachholtz ◽  
Koen Luyckx ◽  
Jessica Hekking ◽  
...  
Keyword(s):  
Meaning In Life ◽  
Chronically Ill ◽  
Well Being ◽  
Psychological Well Being ◽  
Chronically Ill Patients

Telehealth Monitoring of Patients in the Community

2016 ◽  
Vol 25 (1) ◽  
pp. 37-53 ◽  
Author(s):  
Ross Sparks ◽  
Branko Celler ◽  
Chris Okugami ◽  
Rajiv Jayasena ◽  
Marlien Varnfield
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Vital Signs ◽  
Chronically Ill ◽  
Well Being ◽  
Health Condition ◽  
Depth Information ◽  
Statistical Background ◽  
Chronically Ill Patients

AbstractThis article outlines a decision support system that seeks to help community nurses monitor the well-being of their chronically ill patients. It is designed for nurses to stay in contact with their patients without spending unnecessary time on less productive aspects of community nursing, such as avoidable driving to and from patients’ houses and taking measurements of vital signs to assess their health condition. It therefore allows the nurse to spend more time on managing the factors that could lead to a healthier patient. The decision support system is developed for two levels of mathematical capability. Nurses with a statistical background are provided with in-depth information allowing them to detect changes in mean, mean square error (and hence variation), and correlations using a variation on dynamic principle components. Less mathematically inclined nurses are offered information about trends, change points, and a simpler multivariate view of a patient’s well-being involving parallel coordinate plots.

A Multiskill, 5-Week, Online Positive Emotions Training for Student Well-Being

2020 ◽  
pp. 105256292095320
Author(s):  
Maria Hamdani
Keyword(s):  
Positive Emotions ◽  
Clinical Intervention ◽  
Chronically Ill ◽  
Well Being ◽  
Instructional Materials ◽  
Online Course ◽  
Positive Events ◽  
New Techniques ◽  
Set Up ◽  
Chronically Ill Patients

The aim of this 5-week Positive Emotions Project (PEP) is to teach students simple emotional well-being techniques in an online course. I adapted a clinical intervention that Moskowitz et al. developed for chronically ill patients. The adapted training proved to be effective for academic purposes. In this instructional innovation article, I provide detailed instructional materials, and explain how to set up and conduct the training. Students read simple instructions at the start of every week, for 5 consecutive weeks. Each week focuses on one or two new techniques. I collected data and present evidence of effectiveness. A secondary take-away from the study is to use multiskill interventions, since not all the eight techniques taught through PEP were endorsed equally for future use; feeling gratitude, setting attainable goals, acts of kindness, savoring positive events, and self-affirmation were the most popular PEP skills, whereas mindfulness was the least popular.

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