Once BITTEN, Twice Shy: An Applied Trauma-Informed Healthcare Model

2019 ◽  
Vol 32 (4) ◽  
pp. 291-298 ◽  
Author(s):  
Chrystal L. Lewis ◽  
Jennifer Langhinrichsen-Rohling ◽  
Candice N. Selwyn ◽  
Emma C. Lathan
Keyword(s):  
Healthcare Providers ◽  
Health Indicators ◽  
Trauma Symptoms ◽  
Vulnerable Patients ◽  
Health Related ◽  
Healthcare Model ◽  
Treatment Plans ◽  
Trauma Informed ◽  
Trust In Healthcare Providers ◽  
The Impact

Nurses need a pragmatic theory to understand and respond to the impact of vulnerable patients’ previous healthcare experiences, as these are likely to influence response and adherence to treatment plans. The authors of this paper present the new BITTEN (Betrayal history by health-related institutions, Indicator for healthcare engagement, Traumas related to healthcare, Trust in healthcare providers, patient Expectations and Needs) Model of Trauma-Informed Healthcare. BITTEN identifies patients’ current healthcare expectations and needs as a function of their previous betrayal by healthcare systems, which operates in conjunction with their current health indicators to potentially trigger trauma symptoms and impact trust in healthcare providers.

scholarly journals Mediators of Racial Differences in COVID-19 Vaccine Acceptance and Uptake: A Cohort Study in Detroit, MI

Vaccines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Abram L. Wagner ◽  
Lydia Wileden ◽  
Trina R. Shanks ◽  
Susan Door Goold ◽  
Jeffrey D. Morenoff ◽  
...  
Keyword(s):  
Racial Differences ◽  
Race And Ethnicity ◽  
Healthcare Providers ◽  
Vaccine Uptake ◽  
Vaccine Hesitancy ◽  
Black Communities ◽  
Vaccination Acceptance ◽  
Black Residents ◽  
Trust In Healthcare Providers ◽  
The Impact

Despite their disparate rates of infection and mortality, many communities of color report high levels of vaccine hesitancy. This paper describes racial differences in COVID-19 vaccine uptake in Detroit, and assesses, using a mediation model, how individuals’ personal experiences with COVID-19 and trust in authorities mediate racial disparities in vaccination acceptance. The Detroit Metro Area Communities Study (DMACS) is a panel survey of a representative sample of Detroit residents. There were 1012 respondents in the October 2020 wave, of which 856 (83%) were followed up in June 2021. We model the impact of race and ethnicity on vaccination uptake using multivariable logistic regression, and report mediation through direct experiences with COVID as well as trust in government and in healthcare providers. Within Detroit, only 58% of Non-Hispanic (NH) Black residents were vaccinated, compared to 82% of Non-Hispanic white Detroiters, 50% of Hispanic Detroiters, and 52% of other racial/ethnic groups. Trust in healthcare providers and experiences with friends and family dying from COVID-19 varied significantly by race/ethnicity. The mediation analysis reveals that 23% of the differences in vaccine uptake by race could be eliminated if NH Black Detroiters were to have levels of trust in healthcare providers similar to those among NH white Detroiters. Our analyses suggest that efforts to improve relationships among healthcare providers and NH Black communities in Detroit are critical to overcoming local COVID-19 vaccine hesitancy. Increased study of and intervention in these communities is critical to building trust and managing widespread health crises.

scholarly journals Community Health Profile of Four VDCs of North-West Part of Kathmandu

2013 ◽  
Vol 12 (1) ◽  
pp. 32-36
Author(s):  
Lochana Shrestha ◽  
Shambhu Nath Pant ◽  
Sanjeev Das Rajbhandari ◽  
Sudha Sen Malla ◽  
Sabin Bahadur Zoowa
Keyword(s):  
Community Health ◽  
Nuclear Family ◽  
Health Indicators ◽  
Feasibility Studies ◽  
Health Problems ◽  
Health Profile ◽  
North West ◽  
Health Related ◽  
The Impact ◽  
Health Diagnosis

Introduction: There are different hidden health related problems in community. These needs to be identify and adhered by effective, efficient tools to bring the better outcomes. One of the effective tools for the identification and quantification of the health problems in a community is Community Health Diagnosis. The aim of this study was to find out the common health problems in community, describe the related demographic, education, socio –economic and environmental factors and to convey health message to improve health profile of community. Methods: Four weeks Community Health Diagnosis was conducted in four selected VDCs after feasibility studies in 16 VDCs. Sample size households (HH) were calculated based on morbidity status of each VDCs. Students covered allocated number of Households in each VDCs by selecting household with convenience sampling method. Results: In all studied VDCs, nuclear family was the commonest, CBR and literacy rate were good compared to national figure. Population pyramid showed that active age group was more in these VDCs. There was lack of government tap for drinking water and latrine. Maternal parameters were found to be better than national fi gure. Conclusions: Though there is more illiteracy rate in all studied VDCs compare to national figure, maternal parameters, child health indicators and fertility rates are better which may be the impact of effective health education.  Medical Journal of Shree Birendra Hospital; January-June 2013/vol.12/Issue1/32-36DOI: http://dx.doi.org/10.3126/mjsbh.v12i1.9090     

Collaborative Healthcare: Exploring its Meaning through Content Analysis in Social Media (Preprint)

2021 ◽  
Author(s):  
Tahereh Maghsoudi ◽  
Ana Beatriz Hernández-Lara ◽  
Rosalía Cascón-Pereira
Keyword(s):  
Social Media ◽  
Meaning Making ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Health Indicators ◽  
Healthcare Delivery System ◽  
The Social ◽  
Health Related ◽  
Multi Stakeholder ◽  
Evolution Of Meaning

BACKGROUND The healthcare delivery system is a multi-stakeholder and multi-player system aiming to provide services to promote, restore, and improve health indicators in communities. This highlights the importance of collaboration in the healthcare system. Collaborative healthcare is an emerging concept that has mainly been explored in terms of the practices of healthcare professionals. In an era when social media are becoming key to the evolution of meaning-making, there is a lack of knowledge on how collaborative healthcare meanings are being constructed in the social media discourse OBJECTIVE This paper aims to explore the meanings of collaborative healthcare on social media. METHODS We utilize a dual qualitative approach of visual and textual analysis of posts extracted from Instagram to examine the meanings of collaborative healthcare as perceived by both healthcare providers and laypeople. We use the web scraping technique to extract posts from Instagram. RESULTS wellness centers and health-related professionals were the main group of users who contributed to constructing the meaning of collaborative healthcare (38% and 36%, respectively). The study reveals that Instagram users highlight four main themes within the concept of collaborative healthcare, namely knowledge sharing, events, self-care, and advertising. Interestingly, we found that advertising has the highest frequency (262 posts); the term “collaborative” is used by wellness centers as a hallmark for advertising their services. CONCLUSIONS This study has contributed to unveiling the multiple meanings of collaborative healthcare shared by social media users and accordingly in developing some theoretical reflections and practical implications to improve public health.

The Impact of Internal Work Environment on the Retention of Healthcare Providers at Turaif General Hospital

2019 ◽  
Vol 10 (12) ◽  
pp. 1183-1199
Author(s):  
Mohammed Alrouili ◽  
Keyword(s):  
Work Environment ◽  
General Hospital ◽  
Professional Growth ◽  
Healthcare Providers ◽  
Entire Study ◽  
Internal Work ◽  
Research Findings ◽  
Study Population ◽  
The Right ◽  
The Impact

This study attempted to identify the impact of internal work environment on the retention of healthcare providers at Turaif General Hospital in the Kingdom of Saudi Arabia. In particular, the study aimed to identify the dimensions of work circumstances, compensation, and relationship with colleagues, professional growth, and the level of healthcare providers’ retention. In order to achieve the study goals, the researcher used the descriptive analytical approach. The researcher used the questionnaire as the study tool. The study population comprised all the healthcare providers at Turaif General Hospital. Questionnaires were distributed to the entire study sample that consisted of 220 individuals. The number of questionnaires valid for study was 183 questionnaires. The research findings were as follows: the participants’ estimate of the work circumstances dimension was high (3.64), the participants’ estimate of the compensation dimension was moderate (3.32), the participants’ estimate of the relationship with colleagues dimension was high (3.62), the participants’ estimate of the professional growth dimension was weak (2.39), and the participants’ estimate of healthcare providers’ retention level was intermediate (2.75). Accordingly, the researcher’s major recommendations are: the need to create the right atmosphere for personnel in hospitals, the interest of the hospital to provide the appropriate conditions for the staff in terms of the physical and moral aspects for building the work adjustment in the staff, and conducting training courses and educational lectures for personnel in hospitals on how to cope with the work pressures.

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.

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