scholarly journals The Impact of Self-Affirmation on Health-Related Cognition and Health Behaviour: Issues and Prospects

2010 ◽  
Vol 4 (7) ◽  
pp. 439-454 ◽  
Author(s):  
Peter R. Harris ◽  
Tracy Epton
Keyword(s):  
Health Behaviour ◽  
Health Related ◽  
The Impact

Sociospatial inequalities in health-related behaviours

2011 ◽  
Vol 36 (1) ◽  
pp. 3-24 ◽  
Author(s):  
Jamie Pearce ◽  
Ross Barnett ◽  
Graham Moon
Keyword(s):  
Social Environment ◽  
Health Behaviour ◽  
Scale Effects ◽  
Group Differences ◽  
Social Composition ◽  
The Social ◽  
Health Related ◽  
Nuanced Understanding ◽  
The Impact ◽  
Key Pathways

There has been a resurgence of interest in how the social, built and cultural environments contribute to shaping health outcomes. The pathways relating place to health behaviour have received less attention. We develop a nuanced understanding of the pathways linking individuals, places and smoking. Two key pathways operate: place-based ‘practices’ and place-based ‘regulation’. Future geographical research should pay attention to the different scale effects, encompass a wider set of influences which affect the liveability and social composition of neighbourhoods, and specify group differences in the impact of the local economic and social environment upon smoking.

ACCESSIBLE HOUSING AND HEALTH-RELATED QUALITY OF LIFE: MEASUREMENTS OF WELLBEING OUTCOMES FOLLOWING HOME MODIFICATIONS

2016 ◽  
Vol 10 (2) ◽  
pp. 38 ◽  
Author(s):  
Phillippa Carnemolla ◽  
Catherine Bridge
Keyword(s):  
Quality Of Life ◽  
Mixed Method ◽  
Exploratory Research ◽  
Health Related Quality ◽  
Care Giving ◽  
Home Modifications ◽  
Related Quality ◽  
Health Related ◽  
The Impact

The multi-dimensional relationship between housing and population health is now well recognised internationally, across both developing and developed nations. This paper examines a dimension within the housing and health relationship – accessibility – that to date has been considered difficult to measure. This paper reports on the mixed method results of larger mixed-method, exploratory study designed to measure the impact of home modifications on Health-Related Quality of Life, supported by qualitative data of recipients’ experiences of home modifications. Data was gathered from 157 Australian HACC clients, who had received home modifications. Measurements were taken for both before and after home modifications and reveal that home modifications were associated with an average 40% increase in Health-Related Quality of Life levels. The qualitative results revealed that participants positively associated home modifications across six effect themes: increased safety and confidence, improved mobility at home, increased independence, supported care-giving role, increased social participation, and ability to return home from hospital. This exploratory research gives an insight into the potential for accessible architecture to impact improvements in community health and wellbeing.

scholarly journals The impact of lymphedema on health-related quality of life up to 10 years after breast cancer treatment

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mads G. Jørgensen ◽  
Navid M. Toyserkani ◽  
Frederik G. Hansen ◽  
Anette Bygum ◽  
Jens A. Sørensen
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Cancer Treatment ◽  
Breast Cancer Treatment ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related ◽  
The Impact

AbstractThe impact of breast cancer-related lymphedema (BCRL) on long-term quality of life is unknown. The aim of this study was to investigate the impact of BCRL on health-related quality of life (HRQoL) up to 10 years after breast cancer treatment. This regional population-based study enrolled patients treated for breast cancer with axillary lymph node dissection between January 1st 2007 and December 31th 2017. Follow up and assessments of the included patients were conducted between January 2019 and May 2020. The study outcome was HRQoL, evaluated with the Lymphedema Functioning, Disability and Health Questionnaire, the Disabilities of the Arm, Shoulder and Hand Questionnaire and the Short Form (36) Health Survey Questionnaire. Multivariate linear logistic regression models adjusted for confounders provided mean score differences (MDs) with 95% confidence intervals in each HRQoL scale and item. This study enrolled 244 patients with BCRL and 823 patients without BCRL. Patients with BCRL had significantly poorer HRQoL than patients without BCRL in 16 out of 18 HRQoL subscales, for example, in physical function (MDs 27, 95%CI: 24; 30), mental health (MDs 24, 95%CI: 21; 27) and social role functioning (MDs 20, 95%CI: 17; 23). Age, BMI, BCRL severity, hand and dominant arm affection had only minor impact on HRQoL (MDs < 5), suggesting a high degree of inter-individual variation in coping with lymphedema. This study showed that BCRL is associated with long-term impairments in HRQoL, especially affecting the physical and psychosocial domains. Surprisingly, BCRL diagnosis rather than clinical severity drove the largest impairments in HRQoL.

scholarly journals Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yahya Albalawi ◽  
Jim Buckley ◽  
Nikola S. Nikolov
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Comprehensive Evaluation ◽  
Classification Problem ◽  
Data Sets ◽  
Word Embeddings ◽  
Data Set ◽  
Lower Accuracy ◽  
Health Related ◽  
The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

516 Impacts of Chronic Nausea and Vomiting on Daytime Sleepiness and Fatigue

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A203-A203
Author(s):  
Maurice Ohayon ◽  
Y J Chen ◽  
Marie-Lise Cote
Keyword(s):  
Longitudinal Study ◽  
Daytime Sleepiness ◽  
Nausea And Vomiting ◽  
Prospective Longitudinal Study ◽  
Logistic Regression Models ◽  
Related Quality ◽  
Health Related ◽  
Chronic Nausea ◽  
Prospective Longitudinal ◽  
The Impact

Abstract Introduction Chronic nausea and vomiting (CNV), common symptoms in patients with GI disorders like gastroparesis, can be a debilitating health problem with considerable impact on patients’ health-related quality of life during daytime. Yet, little is known about how CNV may impact on sleepiness and fatigue during the daytime. Our aim was to examine the impact of CNV on daytime sleepiness and fatigue based on the data from a longitudinal study. Methods Prospective longitudinal study with two waves: 12,218 subjects interviewed by phone during wave 1 (W1); 10,931 during wave 2 (W2) three years later. The sample was representative of the US general population. Analyses included subjects participating to both waves (N=10,931). CNV was defined as episodes of nausea and vomiting occurring at least twice a month for at least 1 month (outside pregnancy). Logistic regression models were employed to determine whether CNV is a predictive variable for excessive sleepiness or fatigue. Results Out of all W1 participants, 9.8% (95% CI: 9.2%-10.4%) reported nausea only while 3% (95% CI: 2.7%-3.3%) reported CNV. In W2, 7.7% (95% CI: 7.2%-8.2%) reported nausea only and 2.5% (95% CI: 2.2%-2.8%) reported having CNV. Of the subjects who participated in both W1 and W2, 25.7% of them reported CNV in W1. CNV subjects reported more frequently excessive daytime sleepiness (53.5% vs. 25.9%) and being moderately or severely fatigued (38.6% vs, 5.4%) compared with the participants without nausea or vomiting. After controlling for age, sex, BMI, health status, alcohol intake, sleep disorders and psychiatric disorders that might impact on daytime sleepiness or fatigue, it was found that subjects with CNV at both W1 and W2 had a significantly higher relative risk of reporting daytime sleepiness (RR: 2.7 (95% CI:1.9–3.9) p&lt;0.0001) and fatigue (RR: 4.9 (95% CI:3.2–7.5) p&lt;0.0001) at W2, compared with the participants without nausea or vomiting. Conclusion Many factors are likely to influence daytime sleepiness. CNV appears to be an important contributor even after controlling for several factors that can explain the sleepiness. This underlines the extent to which alertness could be disturbed and impacted by chronicity of nausea/vomiting symptoms. Support (if any) This analysis study was funded by Takeda Pharmaceutical Company

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