Objectives:
1. Analyze a specified data set.
2. Describe how data influences epidemiological practices.
3. Evaluate data analyzed from research articles using different types of variables.
Assignment 1:
Describe how epidemiological data influences changes in health practices. Provide an example and explain what data would be necessary to make a change in practice.
Assignment 2:
Discuss ways your organization uses technology to gather patient and health care information, and how this information and data are used to direct patient care and outcomes.
Assignment 3:
Article Analysis and Evaluation of Research Ethics
Search the GCU Library and find one new health care article that uses quantitative research. Do not use an article from a previous assignment, or that appears in the topic Resources or textbook.
Complete an article analysis and ethics evaluation of the research using the “Article Analysis and Evaluation of Research Ethics” template. See Chapter 5 of your textbook as needed, for assistance.
While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
Assignment 4:
There is often the requirement to evaluate descriptive statistics for data within the organization or for health care information. Every year the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals towards research, treatment options, or patient education.
Using the data on the “National Cancer Institute Data” Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the topic Resources, as needed, for assistance in with creating Excel formulas.
Provide the following descriptive statistics:
1. Measures of Central Tendency: Mean, Median, and Mode
2. Measures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range).
3. Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.
APA style is not required, but solid academic writing is expected.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
Article Analysis and Evaluation of Research Ethics
Article Citation and Permalink
(APA format)
Article 1
Point
Description
Broad Topic Area/Title
Problem Statement
(What is the problem research is addressing?)
Purpose Statement
(What is the purpose of the study?)
Research Questions
(What questions does the research seek to answer?)
Define Hypothesis
(Or state the correct hypothesis based upon variables used)
Identify Dependent and Independent Variables and Type of Data for the Variables
Population of Interest for Study
Sample
Sampling Method
Identify Data Collection
Identify how data were collected
Summarize Data Collection Approach
Discuss Data Analysis
Include what types of statistical tests were used for the variables.
Summarize Results of Study
Summary of Assumptions and Limitations
Identify the assumptions and limitations from the article.
Report other potential assumptions and limitations of your review not listed by the author.
Ethical Considerations
Evaluate the article and identify potential ethical considerations that may have occurred when sampling, collecting data, analyzing data, or publishing results. Summarize your findings below in
2
50-500 words. Provide rationale and support for your evaluation.
© 2019. Grand Canyon University. All Rights Reserved.
2
image1
| American Indian / Alaska Native (includes Hispanic) | Asian / Pacific Islander (includes Hispanic) | Black (includes Hispanic) | Hispanic (any race) | White (includes Hispanic) | National Cancer Institute (2018) Lung and bronchus cancer. Retrieved from Janary 8, 2019 from https://seer.cancer.gov/explorer/application.php?site=47&data_type=1&graph_type=2&compareBy=race&chk_sex_1=1&chk_race_5=5&chk_race_4=4&chk_race_3=3&chk_race_6=6&chk_race_2=2&chk_age_range_1=1&chk_data_type_1=1&advopt_precision=1&advopt_display=1&showDataFor=sex_1_and_age_range_1_and_data_type_1 | ||||
| Year of Diagnosis | Rate per 100,000 | ||||||||
| 2000 | 45 | 41 | 77.8 | 34 | 68 | ||||
| 2001 | 47.9 | 79 | 34.1 | 68.7 | |||||
| 2002 | 44.6 | 40.4 | 75.8 | ||||||
| 2003 | 50 | 40.9 | 77.3 | 34.5 | 67.1 | ||||
| 2004 | 51.7 | 40.5 | 75.1 | 35 | 65.8 | ||||
| 2005 | 48.7 | 40.2 | 73.7 | 33.8 | 65.9 | ||||
| 2006 | 46.4 | 39 | 73.4 | 32 | |||||
| 2007 | 43.1 | 38.8 | 71.2 | 32.7 | 65.2 | ||||
| 2008 | 38.5 | 70.8 | 32.2 | 63.9 | |||||
| 2009 | 40.1 | 71.6 | 31.8 | 63.1 | |||||
| 2010 | 42.4 | 37 | 67.8 | 30.3 | 60.4 | ||||
| 2011 | 39.6 | 36.6 | 64.1 | 29.4 | 58.5 | ||||
| 2012 | 36.7 | 64.3 | 28.2 | 57.5 | |||||
| 2013 | 39.9 | 60.5 | 28.8 | 56.3 | |||||
| 2014 | 61.3 | 26 | 55.4 | ||||||
| 2015 | 38.7 | 34.4 | 57.4 | 53.2 |
Application of AnalysisBy Elissa Torres
Essential Questions
· What are the essential elements in evaluating prior research?
· How does the analysis of quantitative versus qualitative studies differ?
· How are results communicated from data collection and analysis?
Introduction
The use of statistics and statistical analysis is part of the clinical practitioner’s role
.
This may appear in different ways from reviewing existing clinical research to participating in a study. There are some critical questions when understanding statistics and the role of clinician in health care:
· Why is it important to keep up-to-date on clinical research?
· Why is it important for health care facilities to conduct ongoing studies?
· What type of studies are important?
Previous chapters focused on understanding the elements of statistics and research, including how to select and conduct hypothesis testing based upon the type of data collected. This chapter focuses on the application of prior information to understand information written in prior research studies and set up statistical tests and interpret results both statistically and clinically.
Academic Research Study Extraction
In the evaluation of research articles, it is important that key areas can be identified for interpretation and understanding. In the review of both qualitative and quantitative research, it can be daunting to extract the relevant information to determine the primary goals and outcomes of the study. For clinical studies, this also means addressing the epidemiology.
The simplest way to extract relevant information is to first start with those key areas.
1. Topic: What is the broad topic research area/title?
2
. Problem statement: What is the problem that the research is attempting to address? In many studies, authors identify a lack of research in a specific area or population.
3. Purpose statement: Why did the author complete the study? In some studies, this often appears in a sentence containing the phrase, “the focus of this study … ”
4
. Research questions: What specific questions does the author need to address? In many articles, this is not explicitly written but can be derived.
5
.
Hypothesis
, variables, or phenomena: What are the
variables
the author has identified to address the research goal (quantitative)? How is the phenomena described that the author seeks to better understand (qualitative)?
6
.
Sample
and location: What was the sample used, and where did the study take place?
7
.
Methodology
: Was the research quantitative or qualitative? Did the author provide any more details, such as quantitative correlational or qualitative case study?
8
. Data collection: How did the author approach data collection? For example, did the author use surveys, interviews, or clinical studies?
9
. Data analysis: What approach did the author use to analyze the data? Did the author mention statistical tests? What type of statistical data was provided? What type of information is provided with qualitative studies?
10
. Results: What were the results of the study? Did the author find anything significant? Did the study address epidemiology?
These 10 questions for article evaluation are useful to perform a quick review of the study’s key elements; however, it is important to start the process by first reading the full article. The format in which information is displayed in Table 5.1 can be used as a template to organize information found for each of these article elements. In some studies, information can be easily located in the abstract and in clearly organized sections; however, this is not always the case.
Table 5.1
Quantitative Article Evaluation
|
Article Citation
|
Aljohani, A. H., Alrubyyi, M. A., Alharbi, A. B., Alomair, A. M., Alomair, A. A., Aldossari,
N . A., & … Tallab, O. M. (2018). The relation between diabetes type II and anemia. 12 816/0043795 | |||||||||||||||
|
Point |
Description |
|||||||||||||||
|
Broad Topic Area/Title |
The Relation Between Diabetes Type II and Anemia |
|||||||||||||||
|
Problem Statement |
“There is consequently a need for more studies on the incidence and prevalence of anemia among patients with diabetes mainly those with renal malfunction” (p. 527). |
|||||||||||||||
|
Purpose Statement |
“This study consequently purposed to determine the pervasiveness of anemia due to renal insufficiency among patients with type 2 diabetes” (p. 526, 527). |
|||||||||||||||
|
Research Questions |
Is there a relationship between patients with anemia and patients with type II diabetes? |
|||||||||||||||
|
Define Variables/ Hypotheses |
Categorical variable: Gender Continuous variables: Age, Hb, Ferritin, MCV , TIBC , FBG, Erythroietin, eGFR, Urea, Na, K, CA, and HbA1c (found on pages 528 and 529) |
|||||||||||||||
| Sample |
50 participants Case group: 25 participants with diabetes (8 male/17 female) Control group: 25 participants without diabetes (7 male/18 female (p. 528) |
|||||||||||||||
| Methodology |
Quantitative, case-control study (p. 527) |
|||||||||||||||
|
How was Data Collected? |
Medical records for the patients were examined from physical examinations (p. 528) |
|||||||||||||||
|
How was Data Analyzed? |
SPSS; descriptive statistics for categorical; summary statistics, independent t-test; and ANOVA test; Pearson correlation for Hb and HG for both male and female (p. 528) |
|||||||||||||||
|
What Were the Results? |
The study indicated the following were statistically significant (low p-values) between the case group and control group. Hb Male and Hb Female Ferritin Male and Ferritin Female MCV Of the biochemical parameters, the following were significant: FBG, Erthropoietin, eGFR, Urea, K, C1, Ca, HbA1c Creatinine was not significant In the correlation test, HB and HG (female) was significant, but HB and HG (male) was not significant. Clinical implications: The study did find a higher occurrence of anemia in patients with diabetes (87.5% males, 82.3% female). The study also concluded that the presence of anemia may increase the likelihood of poorly controlled diabetes (p. 529). |
Check for Understanding
1. Would there be any additional evaluation of the article?
2. Did the researchers appear to follow ethical guidelines?
3. What were the assumptions and limitations of the study?
Table 5.2
Qualitative Article Evaluation
|
Jangland, E., Nyberg, B., & Yngman-Uhlin, P. (2017). It’s a matter of patient safety: Understanding challenges in everyday clinical practice for achieving good care on the surgical ward – a qualitative study. 11 11/scs.12350 |
|
|
Identify the challenges and barriers linked to quality care and patient safety in the surgical ward. |
|
|
“Identify the challenges and barriers linked to quality of care and patient safety in the surgical ward” (p. 324). Study addresses gap where there were only a few studies that looked at both the nurses’ and leaders’ perspective. |
|
|
“The aim of this study was to explore, from the perspectives of care leaders, the situations and processes that support or hinder good and safe care on the surgical ward” (p. 324). |
|
|
What are the perspectives of leaders on the processes that support good quality care in the surgical ward? What are the perspectives of leaders on processes that hinder good quality care in the surgical ward? How do leaders’ experiences inform improvement in clinical practice? |
|
|
Describe Phenomena |
Categorical variable: Gender
Continuous variables: Age, Hb, Ferritin, MCV, TIBC, FBG, Erythroietin, eGFR, Urea, Na, K, CA, and HbA1c (found on pages 528 and 529) |
|
“10 leaders in surgery departments (four department leaders and six nursing managers) from 1 university hospital and 2 county hospitals in different regions in Sweden” (pp. 324-325). |
|
|
Qualitative-descriptive design |
|
|
Repeated reflective interviews using semistructured interviews |
|
|
Systematic text condensation |
|
|
Study identified four major themes (pp. 326-328): 1. Constant demands for increased efficiency and production 2. Continual nursing turnover and loss of competence 3. A traditional hierarchical culture 4. Vague goals and responsibilities in the development of nursing care Clinical implications: Based upon the study, which has limitations as it was performed in one country (Sweden), organizational changes are required to ensure higher levels of competence of staff and resources available to surgical ward nurses to ensure higher quality care (p. 3 30 ). |
The two evaluations above provide a roadmap for reviewing prior research. Much of the research completed in the clinical setting may not be as comprehensive; however, it is important to understand the process. In a clinical setting, there may be opportunities to reduce cycle time, increase quality, or participate in studies that influence health outcomes. Understanding the process, knowing how to evaluate the data, and communicating the results enables contribution to the organization.
Application of
Statistic
s to Scenario
A medical office has noticed an increase in patient dissatisfaction and as well as an increase in usage of urgent care facility services rather than seeing their primary care physicians (PCPs). To increase understanding of the patient perception, the office surveyed the patients and received 81 responses. The survey includes a total of eight questions. The first five questions capture satisfaction and urgent care utilization responses, and the last three questions capture data on education, gender, and age group.
·
Q1
: You meet with your Primary Care Physician greater than one time per year. Responses Strongly Disagree to Strongly Agree.
·
Q2
: You spend more than 10 minutes with your Primary Care Physician discussing health concerns. Responses Strongly Disagree to Strongly Agree.
·
Q3
: You are more likely to go to urgent care versus your Primary Care Physician. Responses Strongly Disagree to Strongly Agree.
·
Q4
: What is the number of times you went to urgent care in the past 12 months? Numerical response requested.
·
Q5
: Rate your overall satisfaction with the medical office. Responses Strongly Disagree to Strongly Agree.
· Q6: What is the highest level of education you completed?
· Q7: What is your gender?
· Q8: What is your age?
To review the responses from the data collected in the scenario, click on the button below.
Scenario Data
Table 5.3
Patient Dissatisfaction Application Scenario
|
Broad Topic Area/Title |
Understand the relationship between patient satisfaction and usage of services at urgent care facilities. |
|
Problem Statement |
Recent indicator identified lower patient satisfaction and higher incidence of using services at urgent care facilities. There is a need to understand the perception of patient satisfaction for the XYZ medical office and decrease usage of urgent care. |
|
Research Questions |
What is the patient perception of satisfaction with the medical office? Do patients use urgent care as an alternative to the primary care physician (PCP)? Is there a relationship between patient satisfaction and usage of urgent care facilities? |
|
Hypothesis |
H10: There is no relationship between the perception for number of visits and perception of time spent with PCP. H1A: There is a relationship between the perception for number of visits and perception of time spent with PCP. H20: There is no relationship between the perception for number of visits and the likelihood to go to urgent care. H2A: There is a relationship between the perception for number of visits and the likelihood to go to urgent care. H30: There is no relationship between the perception for number of visits and the overall satisfaction. H3A: There is a relationship between the perception for number of visits and the overall satisfaction. H40: There is no relationship between the perception time spent with PCP and likelihood to go to urgent care. H4A: There is a relationship between the perception of time spent with PCP and likelihood to go to urgent care. H50: There is no relationship between the perception of time spent with PCP and overall satisfaction. H5A: There is a relationship between the perception of time spent with PCP and overall satisfaction. H50: There is no relationship between the number of visits to urgent care in past 12 months and overall satisfaction. H5A: There is no relationship between the number of times went to urgent care in past 12 months and overall satisfaction. |
|
Describe Phenomena (qualitative) or Define Variables/ Hypotheses (quantitative) |
Nominal: education, gender, age group Ordinal: Survey Questions 1-3 and 5 Continuous: Survey Question 4: Number of visits to urgent care in last 12 months |
|
Sample |
80 patients from XYZ medical office |
|
How is Data Being Collected? |
Sent electronic survey to 300 patients, and received 80 responses. |
|
How Will Data be Analyzed |
Descriptive statistics Correlation analysis |
|
What Were the Results? |
Statistical relationships were identified. The null hypothesis would be rejected and the alternative hypothesis would be accepted in all cases. From a practical perspective, while the results indicated higher scores for the likelihood to go to urgent care versus the PCP, the actual descriptive statistics for urgent care visits do not support this. |
Communicating Results
The data can be sorted for communication based upon summary and descriptive statistics for some of the variables prior to the hypothesis tests. As an example, to describe the sample respondents by age group and gender, the data can be converted in Excel to percentages (see Table 5.4). These percentages can be written out or included in a table.
Table 5.4
Converting Frequency to Percentage Example
|
Age Group |
Female |
Percent Female |
Male |
Percent Male |
Total |
Percent Total by Age Group |
||||||||||||||||||||||
|
< 20 |
9 |
18.0% |
2 |
6.7% |
11 |
13.8% |
||||||||||||||||||||||
|
20-25 |
7 |
14.0% |
4 |
13.3% |
||||||||||||||||||||||||
|
23-31 |
10 |
20.0% |
5 |
16.7% |
15 |
18.8% |
||||||||||||||||||||||
|
32-37 |
8 |
16.0% |
12 |
15.0% |
||||||||||||||||||||||||
|
38-43 |
6 |
12.0% |
12.5% |
|||||||||||||||||||||||||
|
> 44 |
36.7% |
21 |
26.3% |
|||||||||||||||||||||||||
| Total | 50 | 30 | 80 |
Even though the responses to the survey questions were ordinal as they were translated from Strongly Disagree (1) to Strongly Agree (5), with larger samples, responses can be treated as continuous. Frequently, the three most common forms of descriptive statistics are displayed in a chart. These include the mean, median, and standard deviation (see Table 5.5).
Table 5.5
Example of Descriptive Statistics
|
Question |
n |
M |
Mdn |
SD |
||
| Q1 |
1.93 |
2.00 |
1.11 |
|||
| Q2 |
2.15 |
1.29 |
||||
| Q3 |
3.31 |
4.00 |
1.41 |
|||
| Q4 |
1.00 |
1.37 |
||||
| Q5 |
3.13 |
3.00 |
1.31 |
Beyond addressing some information on descriptive statistics, the hypothesis tests need to be addressed. Prior to conducting statistical testing, the data needs to be assessed for normality. When assessing for normality, a statistical program, such as SPSS, determines if the data meets the conditions of a normal distribution. Often, when data is derived from survey data responses with ranges from strongly disagree to strongly agree, the data is not normally distributed unless the samples are very large. In this case, the sample received was only 80. Table 5.6 displays the normality tests for the variables that will be tested. Because the sample size is lower, the
Shapiro-Wilk
results should be used. The Kolmogorov-Smirnov test is most applicable for samples of more than 2,000 data points. Based upon a 0.05 level of significance, a researcher would reject the null hypothesis, which stated that the data was normally distributed.
Table 5.6
Test for Normality
|
Tests of Normality |
|||||||||||||
|
Kolmogoroz-Smirnova |
Shapiro-Wilk | ||||||||||||
| Statistic |
df |
Sig. |
|||||||||||
|
.247 |
.000 |
.771 |
|||||||||||
|
.250 |
.810 |
||||||||||||
|
.237 |
.866 |
||||||||||||
|
.256 |
.801 |
||||||||||||
|
.211 |
.895 |
||||||||||||
|
a. Lilliefors Significance Correction |
Because the test results identified that the data was not normally distributed, a nonparametric test would be used to conduct the hypothesis testing for correlation. The correlation test to use in this scenario is the Spearman Rho test. If the data was normally distributed, the commonly used Pearson Product Moment test would be used. Table 5.7 demonstrates the SPSS output for the Spearman Rho correlation test between survey Questions 1 and 2. Correlation coefficients are reviewed on a scale of -1 to +1. The relationship is stronger if the calculated coefficient is closer to either -1 or +1. In this case, there is a strong relationship between meeting with the PCP more than one time per year and spending more than 10 minutes with the PCP discussing health concerns. Another statistic to review in the output is the
p value
. If the p-value is less than the level of significance identified in the study, the null hypothesis would be rejected and the alternative hypothesis would be accepted.
Table 5.7
Test for Correlation
Q1&Q2
|
Spearman’s rho |
Correlation Coefficient |
1.000 |
.777 ** |
|||
|
Sig. (2-tailed) |
. | |||||
| N | ||||||
Correlation coefficients are reviewed on a scale of -1 to +1. The relationship is stronger if the calculated coefficient is closer to either -1 or +1. If the correlation coefficient is positive, then the two variables are moved upward in the same direction. If the statistic is negative, then one variable increases as the other variable results decrease (Levine, Krehbiel, Berenson, 2013). In this case, there is a strong relationship between meeting with PCP more than one time per year and spending more than 10 minutes with the PCP discussing health concerns. Another statistic to review in the output is the p-value. If the p-value is less than the level of significance identified in the study, the null hypothesis would be rejected and the alternative hypothesis would be accepted. Table 5.8 displays the remaining correlation coefficients depicted in the table as
r and the corresponding p-values for the test.
Table 5.8
Correlation tests from Example
|
Variable |
n |
r’s |
p-value |
|
| Q1&Q2 | .777 |
.000* |
||
|
Q1&Q3 |
.566 |
|||
|
Q1&Q5 |
-.313 |
.005* |
||
|
Q2&Q3 |
.419 |
|||
|
Q2&Q5 |
-.348 |
.002* |
||
|
Q4&Q5 |
-.212 |
.060* |
Table 5.8 demonstrates that there is a statistical correlation between all variables tested at a 0.05 level significance except Q4 (number of times visited urgent care in the last 12 months) and Q5 (overall satisfaction with the medical office). The data output requires analysis to the original hypothesis questions in the study.
Reflective Summary
This chapter reviewed the application of statistics to research, how to identify data, select the appropriate tests, and apply this to data sets. The chapter also explored how to review articles or studies for the key elements for understanding. This understanding was further applied to a practical scenario including analysis of data collected. The statistical and practical analysis of results for communication are essential in the roles of a clinician and the tools learned in this course provided the framework for increased understanding.
Key Terms
Hypothesis: A testable statement of a relationship; an epidemiologic hypothesis is the relationship is between the exposure (person, time, and/or place) and the occurrence of a disease or condition.
M: Table notation for statistical mean of data array.
Mdn: Table notation for statistical median of data array.
N: Table notation representing the sample size.
P values:
The probability that there is enough evidence to make conclusions resulting from the data collected in the study.
r: Table notation representing the coefficient of correlation.
SD: Table notation representing the standard deviation of the data array.
Variable: A data item such as characteristics, numbers, properties, or quantities that can be measured or counted. The value of the data item can vary or be manipulated from one entity to another. There are three different types of variables—dependent, independent, and extraneous.
References
Aljohani, A. H., Alrubyyi, M. A., Alharbi, A. B., Alomair, A. M., Alomair, A. A., Aldossari, N. A., & … Tallab, O. M. (2018). The relation between diabetes type II and anemia.
The Egyptian Journal of Hospital Medicine, 70(4), 526. doi:10.12816/0043795
Levine, D. M., Krehbiel, T. C., & Berenson, M. L. (2013).
Business statistics: A first course (6th ed.). Upper Saddle River, NJ: Pearson.
Jangland, E., Nyberg, B., & Yngman-Uhlin, P. (2017). It’s a matter of patient safety: Understanding challenges in everyday clinical practice for achieving good care on the surgical ward – a qualitative study.
Scandinavian Journal of Caring Sciences, 31(2), 323-331. doi:10.1111/scs.12350
Rubric Criteria for Article Analysis And Evaluation Data
Collapse All Rubric CriteriaCollapse All
Article (Quantitative, APA Citation and Permalink)
7 points
Criteria Description
Article (Quantitative, APA Citation and Permalink)
5. 5: Excellent
7 points
The article presented is based on quantitative research.
Article Citation and Permalink
7 points
Criteria Description
Article Citation and Permalink
5. 5: Excellent
7 points
Article citation and permalink are presented. Article citation is accurately presented in APA format. Page numbers are accurate and used in all areas when citing information.
Broad Topic Area/Title
7 points
Criteria Description
Broad Topic Area/Title
5. 5: Excellent
7 points
Broad topic area and title are fully presented and accurate.
Problem Statement
7 points
Criteria Description
Problem Statement
5. 5: Excellent
7 points
Problem statement is accurate and clearly summarized.
Purpose Statement
7 points
Criteria Description
Purpose Statement
5. 5: Excellent
7 points
Purpose statement is accurate and clearly summarized.
Research Questions
7 points
Criteria Description
Research Questions
5. 5: Excellent
7 points
Research questions are presented and accurate.
Define Hypothesis (Or state the correct hypothesis based upon variables used.)
7 points
Criteria Description
Define Hypothesis (Or state the correct hypothesis based upon variables used.)
5. 5: Excellent
7 points
Hypothesis is accurate and clearly defined
Identify Variables and Type of Data for Variables
7 points
Criteria Description
Identify Variables and Type of Data for Variables
5. 5: Excellent
7 points
Variable type and data for variable are presented and accurate.
Population of Interest for Study
7 points
Criteria Description
Population of Interest for Study
5. 5: Excellent
7 points
Population of interest for the study is presented and accurate.
Sample
7 points
Criteria Description
Sample
5. 5: Excellent
7 points
Sample is presented and accurate. Page citation for sample information is provided.
Sampling Method
7 points
Criteria Description
Sampling Method
5. 5: Excellent
7 points
Sampling method is presented and accurate.
Identify Data Collection
7 points
Criteria Description
Identify Data Collection
5. 5: Excellent
7 points
How data were collected is fully identified and accurate.
Summary of Data Collection Approach
7 points
Criteria Description
Summary of Data Collection Approach
5. 5: Excellent
7 points
The means of data collection are thoroughly summarized and accurate. Page citation for sample information is provided.
Data Analysis
7 points
Criteria Description
Data Analysis
5. 5: Excellent
7 points
Data analysis is discussed. Types of statistical tests used for the variables are all indicated and accurate.
Summary Results of Study
7 points
Criteria Description
Summary Results of Study
5. 5: Excellent
7 points
The results of study are well summarized. The summary is accurate and clearly represents the results of the study.
Summary Assumptions and Limitations
14 points
Criteria Description
Summary Assumptions and Limitations
5. 5: Excellent
14 points
Assumptions and limitations from the article are identified and accurate. Potential assumptions and limitations not listed by the author are summarized. Strong rationale is provided to support summary.
Summary of Ethical Considerations
14 points
Criteria Description
Summary of Ethical Considerations
5. 5: Excellent
14 points
Ethical considerations related to sampling, collecting data, analyzing data, and publishing results are clearly summarized. The ethical considerations summarized are reasonable. Strong rationale and support are provided.
Mechanics of Writing
7 points
Criteria Description
Mechanics of Writing (includes spelling, punctuation, grammar, and language use)
5. 5: Excellent
7 points
The writer is clearly in command of standard, written, academic English.
Collapse All Rubric CriteriaCollapse All
Measures of Central Tendency
2
5 points
Criteria Description
Measures of Central Tendency (Mean, Median and Mode)
5. 5: Excellent
25 points
Measures of central tendency are calculated.
Measures of Variation
25 points
Criteria Description
Measures of Variation (Variance, Standard Deviation and Range)
5. 5: Excellent
25 points
Measures of central variation are calculated for variance and standard deviation. Range is identified.
Analysis of Descriptive Statistics
25 points
Criteria Description
Analysis of Descriptive Statistics
5. 5: Excellent
25 points
Analysis of the descriptive statistics for differences and health outcome recommendations between the groups is extremely thorough and accurate and includes substantial explanation and supporting details.
Excel Formulas
20 points
Criteria Description
Excel Formulas
5. 5: Excellent
20 points
Excel formulas are complete and correct for all problems.
Mechanics of Writing
5 points
Criteria Description
Mechanics of Writing (includes spelling, punctuation, grammar, language use)
5. 5: Excellent
5 points
Writer is clearly in command of standard, written, academic English.
Article:
The use of health care services by homeless shelter residents
Authors:
Kateřina Glumbíková
,
Alice Gojová
,
Michal Burda
,
Radka Poláková
&
Pavel Rusnok
Pages 699-710 | Published online: 27 Feb 2019
·
Download citation
·
https://doi-org.lopes.idm.oclc.org/10.1080/13691457.2019.1583639
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CrossMark
In this article
·
ABSTRACT
·
Introduction
·
Theoretical foundation
·
Methodology of the research
·
Results
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Discussion of the research results and implications for social work
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Conclusion
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Acknowledgements
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Disclosure statement
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Additional information
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Footnotes
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References
ABSTRACT
This submitted article is based on partial data from the Health and Use of Health Care Services by Shelters Users research, taking advantage of the sequential synergy of qualitative and quantitative research strategies. The quantitative research involved 192 respondents, while the qualitative research involved 30 communication partners. The article aims at finding out the relationship between selected health characteristics of the shelter population and their impact on the use of health care services. The article presents data from the quantitative research that are further illustrated by qualitative data. The data were analysed using descriptive statistical methods, a Fisher’s exact test, a Wilcoxon test and a Proportion Matching Test. The relationship between mental health and use of health care services (especially in the case of women) has been proven. Homeless people who do not use any health care services are, on average, for a longer period in temporary housing; whereas those who rated their health as more serious used health care services more frequently. In the conclusion, the authors present the implications for social work that resulted from the survey.
ABSTRAKT
Předložený článek je založen na dílčích údajích z oblasti zdravotní péče a využívání služeb zdravotní péče obyvateli azylových domů, s využitím sekvenční synergie kvalitativních a kvantitativních výzkumných strategií. Kvantitativní výzkum zahrnoval 192 respondentů, zatímco kvalitativní výzkum zahrnoval 30 komunikačních partnerů. Cílem článku je zjistit vztah mezi vybranými zdravotními charakteristikami populace z azylových domů a jejich dopadem na využívání zdravotnických služeb. Článek představuje údaje z kvantitativního výzkumu, který je ilustrován kvalitativními údaji. Data byla analyzována pomocí popisných statistických metod, Fisherova exaktního testu, Wilcoxonova testu a testu shody proporc. Vztah mezi duševním zdravím a využíváním služeb zdravotní péče (zejména u žen) byl prokázán. Bezdomovci, kteří nevyužívají žádné zdravotnické služby, jsou v prozatímním ubytování v průměru déle; zatímco ti, kteří považovali své zdraví za důležitější, využívali služby zdravotní péče častěji. V závěru autoři prezentují možné dopady na sociální práci, které vyplynuly z výzkumu.
KEYWORDS:
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Health
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health care services
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shelter users
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homelessness
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social work
KlÍČOVÁ SLOVA:
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Zdraví
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služby zdravotní péče
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obyvatelé azylových domů
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bezdomovectví
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sociální práce
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Introduction
Homelessness is an extreme form of poverty and a highly topical problem experienced worldwide. From foreign (and also Czech) studies, we know that the health status of homeless people living in shelters is very often worse both at a psychological and physical level than that of the majority population (e.g. Brem & Seeberger,
2010
; Fitzpatrick-Lewis et al.,
2011
) and health problems tend to deepen with increasing age (e.g. Barták,
2011
; Frey,
2013
). A number of studies also describe the co-morbidity of individual diseases in this target group (see, for example, Brem & Seeberger,
2010
). A number of research surveys, e.g. Baggett, O’Connell, Singer, and Rigotti (
2010
), suggest that homeless people do not often use health care services even if they experience acute health problems. This paper aims at identifying the relationship between the selected (health) characteristics of shelter residents and their impact on their use of health care services. To achieve its objective, the paper delivers: (a) the categorisation and systematisation of findings from foreign research on barriers to access to health care for homeless people; (b) verification of hypotheses based on the results of foreign research; and (c) illustration and deepening of knowledge from the quantitative research through data obtained from the qualitative research.
Theoretical foundation
The theoretical foundation of the submitted article rests on two principal axes: the health status of the homeless shelter
1
residents and the use of health care services by this population.
Health status of the homeless shelter population
Fitzpatrick-Lewis et al. (
2011
) surveyed the health status of 1,192 residents of shelters, hostels and night shelters. 85% of the persons stayed in chronically poor health conditions, and almost 50% had been diagnosed with some medical or mental condition. Beijer, Wolf, and Fazel (
2012
) focused on the incidence of tuberculosis, C-type jaundice and HIV in homeless people using night shelters and regular shelters by analysing data from 43 published surveys (59,736 homeless people). Prevalence of tuberculosis ranged from 0.2% to 7.7%, for C-type jaundice from 3.9 to 36.2% and for HIV from 0.3 to 21.1%. Folsom et al. (
2002
) note the incidence of diabetes, arthritis, and hypertension.
Folsom et al. (
2002
) talk about the high incidence of psychiatric diagnoses, namely depression and schizophrenia, in homeless people living in shelters. These two diagnoses were up to four times more prevalent amongst the shelter population compared with the majority population. The so-called SEEWOLF-Study
2
(Bäuml, Brönner, Baur, Pitschel-Walz, & Janh,
2017
) emphasises a higher risk of depression, schizophrenia or anxiety disorders in the homeless population. A total of 232 randomly selected individuals took part in the study, out of whom 80% were men and 20% were women. The results of the study showed that approximately two thirds of the surveyed individuals suffered from a mental illness, but usually from multiple illnesses at a time.
The use of health care services by shelter residents
In individual surveys, a number of barriers related to the use of health care services by homeless people were pointed out. The first range of these barriers was a poor mental state. Gelberg, Andersen, and Leake (
2000
) mention three areas of barriers to the use of health care services by homeless people, namely the long-term situation of homelessness, mental problems and substance abuse. The positive impact on use of health care services occurred when an individual had positive experience with a GP and therefore held the perception of a GP as a regular source of care and support. The authors emphasise that the availability of health care services was not as important to people in shelters as their quality. Salize et al. (
2001
) also point to the barrier of visiting a physician when one’s issue is related to a mental illness. The researchers carried out the research with 102 probands suffering from some kind of a mental illness. Most of them identified a visit of health care services as problematic and did not use it.
The second important factor influencing the use of health care services was the existence of social support. For example, the research by Hwang et al. (
2009
) (carried out on 544 respondents) demonstrates the relationship between social support and the scope of a social network with better mental and physical health; the research by McCormack and MacIntosh (
2001
), based on the experience of 11 homeless people living in shelters, established an anchored theory of strategies that the homeless people use to acquire, maintain and restore health. The model points to three paths leading to health. Such paths are socially influenced, directly by the family and its beliefs, and indirectly by values and beliefs in a particular society. Similarly, for example, Constantino, Yookyung, and Crane (
2005
) emphasise the importance of a social support network, in particular accompaniment to health care services. The women who had an accompaniment and a self-help group available to them demonstrated a reduced emotional distress and an increased use of health care services.
The third identified factor that had an impact on the use of health care services was the duration of stay in a temporary accommodation. Baggett et al. (
2010
) conducted a study of 966 homeless people who were long-term users of night shelters and shelters. 73% of the respondents pointed out that they were a subject to unmet health care needs, including the inability to receive medical or nursing care (32%), difficulty in receiving prescribed medication (36%), problematic access to mental health treatment (21%), problematic access to eyewear (41%) as well as a problematic access to dental care (41%). A long-term life away from ‘home’ was identified as a significant predictor of unmet needs; other factors included insufficient nutrition, poor sight, and the absence of health insurance.
The fourth factor influencing the use of health care services is the severity of physical problems. Compared with the above-mentioned factors, this factor has a consolidating impact on the use of health care services. For example, Gelberg et al. (
2000
) tried to find out in their study the factors predicting the use of health care services by homeless people living in shelters. They emphasise that there is a high percentage of homeless people with high blood pressure (as much as 81%) and with a positive tuberculosis test (78%) who use health care services. On the contrary, the use of health care services is relatively low in people with visual impairment (33%), skin diseases or walking difficulties (44%) (see also Hwang et al.,
2009
; Beijer et al.,
2012
).
The fifth factor having an effect on the use of health care services is the perceived quality of health care services. In relation to this topic, Martins (
2008
) carried out a study aimed at understanding the experience of homeless shelter users with medical services. The method used was qualitative research based on in-depth interviews with 15 shelter residents. Barriers to access to health care have been identified during the research, including: condemnation, ‘labelling’ and stigmatisation, lack of systematic medical care for homeless people, feeling of ‘invisibility’ in relation to healthcare providers, lack of respect when providing treatment, and ultimately the creation of ‘underground movements’ in the area of provision of resources related to medical care.
Similarly, Lyon-Callo (
2000
) presents the results of his three-year ethnographic study from a homeless shelter and describes the barriers this group had when trying to access health care services. The first barrier is the concept of homelessness presented by mass media, which is reflected in the view of homeless people in health care services. The prevailing view is that homeless people are to blame for their situation. In addition, Laberge (
2000
) points out the barrier of homeless people’s access to health care services in the form of symbolic exclusion. Homeless people, as a result of the symbolic exclusion, can be perceived as being guilty of their own medical situation, as people who are dirty, as those the doctors are squeamish about treating. These perceived attitudes of physicians trigger reluctance to seek health care services and feelings of shame in homeless people.
Methodology of the research
The paper objective has been achieved through the presentation of partial data of a research survey focused on the health of the population of homeless shelters and the use of health services, which took place in 2018. The research used the sequential synergy of qualitative and quantitative research strategies. The aim of the research was to identify the key factors that, according to different shelter user categories, affect their health and to determine the impact of these factors on the residents’ health and their use of health care services. The qualitative research was comprised of 30 semi-structured interviews with shelter residents (17 women and 13 men), which were then analysed using Grounded Theory by K. Charmaz. The quantitative research was comprised of a questionnaire used with 192 respondents.
The paper is based on outputs from the quantitative part of the research; the data from the qualitative part is used to illustrate and elaborate the interpretation of the quantitative data in more detail. The hypotheses for the quantitative research were determined on the basis of the study of professional literature (see The Theoretical Foundation section) and on the basis of a qualitative investigation, which preceded the quantitative research, and within which we examined the themes and relationships between individual variables in the respondents’ narrations that we decided to verify in the hypotheses.
H1: There is a relationship between mental health and the use of health care services.
For operationalisation purposes, we defined mental health as health self-assessed on a four-point scale and the use of health care services as the frequency of use over a 6-month period.
H2: There is a relationship between the existence of social support, one’s health condition and the use of health care services.
For operationalisation purposes, we defined the existence of social contacts (family, roommates (or housemates), friends, shelter staff) perceived by a person from a shelter in relation to going to see doctors as being supportive. The health status was again self-assessed on a four-point scale, and the use of health care services was defined as the frequency of use over a 6-month period.
H3: There is a relationship between the duration of a person’s stay in temporary accommodation and the use of health care services.
The duration of stay in temporary accommodation was operationalised as the total duration of the stay in a shelter, hostel and on the street. The use of health care services was defined as the frequency of use over a 6-month period.
H4: There is a relationship between the severity of physical problems and the use of health care services.
The severity of physical problems was self-assessed on a four-point scale and the use of health care services was again defined as the frequency of use over a 6-month period.
H5: There is a relationship between the quality of health care services and their use.
The quality of health care services was operationalised as an assessment of perceived physicians’ attitude to homeless people on a four-point scale. The use of health care services was defined as the frequency of use over a 6-month period.
The respondents were selected on the basis of a quota sampling. The quota was set at 5% of the population of homeless people living in shelters in the Czech Republic. According to the Statistical Yearbook in the area of labour and social affairs (MoLSA,
2016
), in 2015, 3,659 clients over 18 years old used shelters. Our research survey involved 192 individuals (i.e. 5.2% of the population) from 7 different regions (that is territorial-administrative units in the Czech Republic) out of a total of 14. The regions included in the survey were drawn; the respondents involved were selected using a purposeful sampling through an institution (a particular homeless shelter). 55% (
n = 106) of the respondents were women. The average age of the respondents was 44 years and each respondent had an average of 2 children (who did not necessarily have to live in the shelter with them). 64% (
n = 123) of the respondents were not employed, 17% (n = 33) reported that they had jobs (and the rest of the respondents did not answer the question). 55% (
n = 106) of respondents said they had experienced ‘serious’ injuries or surgeries, 43% (
n = 83) of respondents said they should be on medication but only 36% (
n = 69) of them regularly took it. 33% (
n = 63) of the respondents said they had the experience of drug addiction. The average length of the respondents’ stay on the street was 8.5 months; the average length of the respondents’ stay in the hostel was 12.6 months and the average length of their stay in the shelter was 16 months. 57% (
n = 109) of the respondents were living in the homeless shelter for the first time, and 38% (
n = 73) of the respondents repeatedly stayed in such a facility.
The data were obtained using a self-designed questionnaire, which consisted of 25 mostly scale-based questions.
3
The questions in the questionnaire were thematically inspired by findings from the qualitative research. The design of the questions was peer reviewed and piloted with two homeless people who lived in a shelter at the time. The questionnaire’s limitation in relation to the research results is that it is not a standardised questionnaire, which may negatively affect its reliability as a research tool. The method of assisted administration of the questionnaire was used to fill out the questionnaire. A social worker and/or a researcher assisted with the completion of the questionnaires. If a social worker acted as an administrative assistant, he/she was trained beforehand regarding the meanings of individual questions and the data anonymization (the questionnaires were collected and put in an envelope which was immediately sealed after the data collection). The reason for these measures was to make sure that the data would be influenced as little as possible by the presence of a social worker in the research. Within the possible limits of the data obtained, it may be necessary to reflect on the fact that the data originated on the basis of the self-assessment of communication partners who could misunderstand a question, not respond to it, or try to make a better impression within a certain social desirability. Another limitation of the research is that despite the fact that we randomised the respondents by choosing regions involved in the research, the sampling of respondents was purposeful, that is, non-random, which could have negatively affected the data validity. The limitation in relation to the research results is the fact that as part of the data processing, we clustered the data that could have affected the results.
The data was analysed using descriptive statistical methods, the Fisher’s exact test (Agresti,
1990
), the Wilcoxon test (Bauer,
1972
), and the Newcombe’s Proportion Matching Test (
1998
).
The entire research has conformed to the Ethical Principles in Human Research adopted by the American Psychological Association (APA,
2010
). Each communication partner and respondent was asked to sign an informed consent in both stages of the research (that is within the qualitative and quantitative stages). The informed consent provided the research participants with all the necessary research essentials: research objectives, further data handling, data anonymization
4
, researchers’ discretion
5
, voluntary participation in research (the research participants had a possibility to withdraw from the research at any time as well as to refuse to answer any question). Taking into account the fact that the research target group can be considered a vulnerable human subject, we emphasised to keep a non-judging and respectful attitude to each of the respondents. Moreover, we also emphasised the necessity of their understanding of all information about the research, their rights (see above), and all asked questions. We also tried to create the environment of safety and trust and to provide the respondents enough time for their answers to the questions. (see Miovský,
2006
6
).
Results
The following text presents the results relating to individual hypotheses. In relation to the research results, it is necessary to mention the acquired data and its interpretation cannot be generalised to the whole population of homeless people nor to the population of homeless people living in a shelter in the Czech Republic.
H1: There is a relationship between mental health and the use of health care services.
A total of 18% (
n = 35) of the respondents reported that their mental status was ‘very good’, 59% (
n = 113) of the respondents reported that it was ‘good’, 20% (
n = 38) of the respondents perceived it as being ‘poor’, and 3% (
n = 6) of the respondents thought that their mental state was ‘very poor.’ A total of 68% (
n = 131) of the respondents reported that they went to see a doctor regularly, 28% (
n = 54) of the respondents did not go to see a doctor at all, and 4% (
n = 7) of the respondents did not answer the question.
In the evaluation of the results, the exact Fisher’s test was used, which showed existing dependence between the above variables (
p-value = 0.0250). The dependence is statistically significant in women (
p-value = 0.0233). However, the significance was not confirmed in men (
p-value = 0.5854). As part of our further data processing, we ranked ‘very good-good’ as ‘good mental health’ and ‘poor-very poor’ as ‘poor mental health’ and then we compared them with each other. The results showed that people with bad psychological health are less likely to seek the help of any physician (the proportion is 65% (
n = 89) versus 88% (
n = 36),
p-value = 0.0037). The difference between groups is even greater in the case of women only (65% (
n = 50) versus 91% (
n = 22),
p-value = 0.0138). In the case of men, the significance was not confirmed (
p-value = 0.2203). The research findings can be also illustrated using the statements of the communication partners from the qualitative part of the research. ‘When I had the depression and such, I wouldn’t go to see a doctor at all’ (CP 8). ‘Well, those anxieties … they prevented me from going to the doctor’ (CP 6). ‘I had different worries back then … I mean those in my mind’ (CP 3).
H2: There is a relationship between the existence of social support, health status and the use of health care services.
As a result, 38% (
n = 73) of the respondents reported that someone was there to help them to access and use health care services; 60% (
n = 115) of the respondents stated that nobody helped them, and 2% (
n = 4) of the respondents did not respond to the question. The respondents reported that the greatest amount of assistance was received from their family members and from the social workers of the shelter where they live (41%,
n = 79). A total of 14% (
n = 27) of the respondents thought that their overall health was ‘very good’, 65% (
n = 125) of the respondents were of the opinion that it was ‘good’, 18% (
n = 35) of the respondents thought it was ‘poor,’ and 3% (
n = 5) of the respondents believed that their overall health was ‘very poor’.
The Test of Equal Proportions was used to test the hypothesis. The users of shelters who are helped by social workers in 87% (
n = 26) of cases evaluate their health as ‘good’ or ‘very good.’ On the other hand, only 73% (
n = 24) of the users of shelters, who are helped by family members when in need of a visit to a physician, evaluate their health as ‘good’ or ‘very good.’ However, the difference in proportion is not significant (
p-value = 0.2919). Despite the fact that a statistically significant relationship has not been demonstrated, the results of the qualitative research illustrate that social support is perceived as an important factor in the use of health care services. ‘When it’s needed … I mean that they accompany you to the doctors, otherwise I wouldn’t go to that doctor on my own … if you need it, they will support you’ (CP 10). ‘I needed to be accompanied because I was completely weak and didn’t feel like going anywhere, so I needed accompaniment’ (CP 6).
H3: There is a relationship between the length of stay in temporary accommodation and the use of health care services.
The average length of stay on the street was 8.5 months for respondents, the average length of stay in a hostel was 12.6 months, and the average length of stay in a shelter was 16 months (to illustrate the data, 57% (
n = 109), of the respondents stayed in a shelter for the first time, and 38% (
n = 73) of the respondents stayed in a shelter repeatedly). The Wilcoxon rank sum test was used to compare the length of stay in temporary accommodation between different groups of respondents who said they were using (or not using) health care services. Differences in the length of stay in the street (
p-value = 0.2403), hostel (
p-value = 0.7608) or in the shelter (
p-value = 0.2134) did not prove to be statistically significant. For homeless people who do not use any health care services, a median length of stay in temporary housing was a total of 38 months and those who responded that they were using health care services had a median length of stay of 18.75 months in temporary housing. Therefore, the results at the threshold of statistical significance (
p-value = 0.0714) show that the length of stay in temporary housing is higher in people who do not use health care services. The above-mentioned result of the quantitative survey is illustrated by the statement of one of the communication partners in the qualitative part of the research:
I’ve been homeless for four years now … one has poor quality food because doesn’t have money … sometimes you sleep outdoors, with mould and bed bugs in a homeless shelter but the longer you live in such environment, the more you get used to it and the harder it is for you to go to the doctor. You are ashamed too … and plus, you have other worries, you worry where to sleep … trying to secure some certainty … just that health is secondary … (CP 17).
H4: There is a relationship between the severity of physical difficulties and the use of health care services.
14% (
n = 25) of the respondents stated that their physical condition was ‘very good,’ 63% (
n = 115) of the respondents reported that their physical condition was ‘good,’ 19% (
n = 34) of the respondents thought it was ‘poor,’ and 4% (
n = 8) of the respondents called their condition ‘very poor.’
To show the statistical significance of the relationship between the severity of physical difficulties and the use of health care services, the exact Fisher’s test was used (
p-value = 0.0015). As part of our further data processing, we ranked a cluster of values ‘very good-good’ as ‘good physical health’ and ‘poor-very poor’ as ‘poor physical health’ and compared them with each other. The results show in only 63% (
n = 85) of cases that people with good physical health seek the help of a physician. People who evaluate their health as poor claim to seek medical help in 93% (
n = 39) of cases. The difference is huge and very statistically significant (
p-value = 0.0152). The results also show that men tend to seek help from physicians less frequently (the difference between the clusters of men and women is 56% (
n = 27) versus 90.9% (
n = 20)), but the difference is also significant in case of men (
p-value = 0.0058). The results of the quantitative survey are illustrated by the statements of the communication partners from the qualitative part of the research. They show that when a serious health problem arises, the doctor’s visit is necessary and sometimes is also a question of life and death: ‘When it’s serious, you just go to see a doctor. For example, I’ve had serious problems with my heart … you have no choice then … ’ (CP 22). ‘I had pneumonia … they thought I was gonna die, I had it in cold print that I was gonna die … it wasn’t about choosing anymore whether to go or not to go to see a doctor … ’ (CP 29).
H5: There is a relationship between the quality of health care services and their use.
The shelter users who have evaluated a physician’s attitude to homeless people as good or rather good visit physicians in 75% (
n = 111) of cases, compared with 52% (
n = 12) of those who have evaluated a physician’s attitude as bad or rather bad. This difference is significant (
p-value = 0.04). Similarly, if we ask directly whether a physician’s attitude affects their willingness to go and see a physician, then clients who claimed that the physician’s attitude affected them positively actually go to doctors more often (in 79% cases,
n = 27), and vice versa, clients who claimed that the physician’s attitude affected them negatively go to doctors in 63% cases (
n = 21). The difference is smaller than in the first comparison and is not statistically significant (
p-value = 0.49).
We examined the quality of health care services in each respondent group, namely the group of respondents that considered the distance to a doctor’s office to be an important factor of the doctor’s visit as well as the group of respondents that considered money the most important factor.
Given the implicit importance, that is, the connection between evaluation of health care services and attendance, the most important factor appears to be the physician’s attitude (the difference is 75% of attendance (
n = 111) vs. 52% of attendance (
n = 12)). If, on the contrary, we consider the explicit importance declared by clients, the most important factor is money (the difference is 90% of attendance (
n = 37) vs. 52% of attendance (
n = 14)).
Several communication partners in the qualitative part of the research described their negative experiences with physicians who showed an oppressive attitude toward the homeless.
Well, I’ll tell you that when I did everything, the doctors did their best to help me … now, some doctors … I’ll tell you directly when you’re at the rock bottom, collecting social benefits, some doctors behave horribly. You’re just a waste of time for them, which is terrible. I have experienced it a few times. (CP 6).
Discussion of the research results and implications for social work
The research results show, also as part of the reflection of the research limitations presented in its methodology, that there is a relationship between mental health and the use of health care services. The results show that people with a bad mental state are less likely to use health care services. The implications for social work therefore include:
The use of social work methods with regard to the comorbidity of a disease with an emphasis on mental health
In homeless shelter practice, there is a need to purposefully and specifically develop methods of social work that promote mental health and fulfil the requirement for the need for the multidimensional support of homeless people. This need, according to Hwang, Kirst, et al. (
2009
), arises due to the complexity of the needs resulting from interdependence and multiplication of the problems of this target group, including health related problems. One of the methods that can address the complexity of the needs and the comorbidity of disease is case management. According to Walsch and Holton (
2008
), case management makes it possible to provide people with complex problems with services in a timely and appropriate manner.
In this context, it may be interesting to note that 60% of the respondents answered that nobody was there for them. In this context, it should be mentioned that a number of researches considered the existence of social support in the use of health care services as crucial (see, e.g. Constantino et al.,
2005
; Hwang et al.,
2009
). The implication for social work therefore includes:
The importance of social support and accompaniment in supporting the use of healthcare
Social support has proven to be an important factor supporting the use of health care services. The level of this support intended for shelter residents is rather low and needs to be systematically developed. Wright and Tompkins (
2006
) draw attention to the importance of peer accompaniment in the area of health care for homeless people. One of the successful practices is the activity of the Groundswell organisation in London, which set up the ‘Homeless Health Peer Advocacy.’ It is a programme focused on accompanying homeless people to health care facilities. The accompanying people are volunteers who have experience with homelessness themselves. The provided assistance helps overcome personal, systemic, and practical barriers to access to health care.
The results, therefore, show that homeless people who do not use health care services have spent, on average, a longer period of time in temporary accommodation (see also Baggett et al.,
2010
). The result corresponds with the results of the qualitative part of the research, where the communication partners themselves stated that after a certain period of homelessness health ceases to be a priority and is replaced by survival as the main priority. A long-term stay ‘on the street’ or in different forms of temporary housing was linked by communication partners to negative emotional distress aroused by insecurities about accommodation, fear of security and the necessity to provide basic life needs. The implication for social work therefore includes:
The need for rapid reintegration into housing
The need for housing stabilisation as a prerequisite for improving the health situation is also emphasised by research of the Housing First model, which according to Busch-Geertsema (
2013
) is based on the principle of normalisation of living conditions, individualisation of support and transition from support focused on a place to a more individualised support. The Housing First addresses what homeless people identify as their first priority, which is housing (Stefanic & Tsemberis,
2007
). According to Fitzpatrick-Lewis, the provision of permanent housing leads to a reduction in substance abuse and to the increased use of health care services (see also Larimer et al.,
2009
) as well as to improvement of the quality of mental health (Smith,
2005
). However, the data collected from the research also show that 64% of the respondents are unemployed. In this context, it seems necessary to direct the support provided under Housing First, not only on the area of health but also on the job acquisition that could subsequently be an important factor in maintaining housing after the programme’s end.
The results also show that there is a dependence between the severity of physical health problems and the use of health services (see also Beijer et al.,
2012
). Homeless people who rated their health as worse / more serious used health care services more often. In relation to the data from the qualitative research part, it would be worthwhile to discover which types of health care services are used by homeless people, given that communication partners in the qualitative research have reported that they were particularly emergency care services. Communication partners have also stated that they only used such services when their health problems became more urgent or more serious. It seems that the preventive use of health care services is rather lower in the case of shelter users (see Kushel, Perry, Bangsberg, Clark, & Moss,
2002
). The preventive use of health care services is rather absent; therefore social work with shelter residents should focus on promoting health prevention.
The research participants perceived the seeking of medical help as a significant barrier and held an oppressive view of physicians when the physicians associated these individuals with a situation of homelessness; see also Martins (
2008
), Lyon-Callo (
2000
) a Laberge (
2000
). The implication for social work therefore includes:
Changes in the medicalisation meta-narrative of homelessness through anti-oppressive social work
The need for an anti-oppressive approach is related to the prevailing medicalisation meta-narrative of homelessness based on a socially shared view of homeless people as weak, lazy, handicapped, and prone to psychological and social problems (Swick,
2005
), thus ignoring the multidimensional conditionality of homelessness.
The above stated is also related to another instrument of anti-oppressive social work, which is advocacy in the sense of defending the rights of recipients of social work. In the broader sense, it means the promotion of rights of whole disadvantaged groups when compared with the general public. In the narrower sense, it means the promotion of rights of specific people at different system levels (Dominelli,
2010
). Through this instrument, the right to housing for homeless people, the right to a provision of intelligible information from the authorities, or the right to dignified and respectable treatment in health care facilities can be defended.
Conclusion
The article aims at finding out about the relationship between the selected (health) characteristics of the shelter residents and their impact on the use of health care services. Based on these research results, we have formulated implications for the practice of social work with homeless people. The methods of social work used in working with homeless people should respect the multidimensionality of the needs of this target group of clients, develop and support social support resources beyond the context of social services, strive for rapid reintegration into permanent housing, and mitigate oppressive mechanisms to which homeless people are exposed by society.
Acknowledgements
This research was partially supported by the NPU II Project LQ1602 ‘IT4Innovations excellence in science’ provided by the MŠMT of Czech Republic.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Kateřina Glumbíková
is an assistant professor at the Faculty of Social Studies at the University of Ostrava. In her dissertation thesis she dealt with the topis of reintegration of single mothers living in shelters into permanent forms of living. Her research interest focuses on reflexivity in social work with families and relationship-based approach in social work with families.
Alice Gojová
is an associate professor at the Faculty of Social Studies at the University of Ostrava. In teaching and research she is interested in the topic of community social work and social work with families.
Michal Burda
is a junior researcher at the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic. He obtained his Ph.D. degree in computer science and applied mathematics from VSB-Technical University in Ostrava. His research interests focus on data mining, fuzzy logic in expert systems and statistics.
Pavel Rusnok
received amasters degree from the Czech Technical University (CTU) in mathematical engineering in 2008. Now he is assistant researcher at Institute for Research and Applications of Fuzzy Modeling at Ostrava University, where he is finishing his PhD in applied mathematics. His research interests include fuzzy logic, statistics, data mining and machine learning.
Radka Poláková
is an employee of the University of Ostrava. Her research is focused on algorithms for global optimisation (especially differential evolution) and started in 2008. She was also a member of Biostatistics centre on the university. She is placed on the second and third rank with an optimisation algorithm on the Black Box Optimization Competition organised as part of Genetic and Evolutionary Computation conference in 2016 and 2018, respectively. Her algorithm won a part for constrained problems of optimisation competition held on CEC2017 world congress in San Sebastian. Her h-index on Scopus equals to 8.
Additional information
Funding
This research was partially supported by the NPU II Project LQ1602 ‘IT4Innovations excellence in science’ provided by the Ministerstvo Školství, Mládeže a Tělovýchovy (MŠMT) of Czech Republic.
Notes
1 In the Czech Republic, a shelter is described in the Act No. 108/2006 on Social Services, Section 57 as follows: ‘Shelters provide temporary residential services to persons in an unfavourable social situation associated with a loss of housing.’ The law on social services for shelters lays down the following basic (mandatory) activities: ‘(a) the provision of food or assistance in catering, (b) accommodation, (c) assistance in the application of the rights, legitimate interests and in obtaining clarity in personal affairs.’ The law on social services (No. 108/
2006
) further provides that ‘the provision of social services in shelters shall be made by payment … ’ The stay in a shelter is limited, most often for a period of one year.
2 SEEWOLF-Studie (Seelische Erkrankungsrate in den Einrichtungen der Wohnungslosenhilfe im Großraum München).
3 The questions used ranged from yes/no questions, for example: Do you take medications prescribed to you by your doctor? through multiple-choice questions, for example: What are the health care facilities you visit? (select one or more options) Options: general practitioner, ophthalmologist, emergency room, dentist, gynaecologist, psychiatrist, dermatologist, pulmonary doctor, ear-nose-throat; other (please specify), to questions where the respondents were asked to choose the degree of their agreement on the scale, for example: How do you rate your physical health? Scale: Very good – Good – Bad – Very bad.
4 There was no mention of the name of the person or the shelter where the survey took place in the questionnaire. In the final research report, the data are presented only as data summarised for the target group as a whole; data related to individual respondents is not stated in any outputs. The data presented in this form does not help to identify a particular person. Recordings of the qualitative interviews have been transcribed and then deleted in a way that even the voice of the respondent has not been stored. Any data leading to identification of the communication partner, third party, or organisation has been anonymised.
5 The researchers informed the participants the acquired information would not be passed to a third party outside the research team (primarily to the shelter staff). They also stated that they have a reporting obligation in case the participant would report very serious facts, such as grievous body harm to a third person.
6 The author presents an overview of the Czech Republic norms and requirements for ethics approval.
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The Excel assignment for this last week requires you to demonstrate your knowledge of the specific required commands. Also, note that the summary descriptive statistics gives us a sample standard deviation and a sample variance. Is that what we need for this assignment? Take a careful look at the data and decide if this is data from the population or just a sample of it. You will submit this assignment as an excel document — this is so that I can see the excel commands you use to calculate your statistics [ie. =AVERAGE(B3:B10)]. You can do the write-up either at the bottom of the excel document or in addition, attach a word doc at the same time.
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