Liz Rolf-The Use of Struggle Language in Chronic Illness

Running head: USE OF STRUGGLE LANGUAGE IN CHRONIC ILLNESS 1

The Use Of Struggle Language When Discussing Chronic Illness:

Assessing The Effects On Patients

Liz Rolf

University of Missouri - St. Louis

Use of Struggle Language in Chronic Illness

Introduction

Problem Statement

With the rapid advances in medical technology, the incidence of patients with chronic

illnesses is quickly rising. Chronic illnesses that used to kill patients fairly quickly, such as

diabetes, lupus, or cystic fibrosis, can now be managed. With proper care, most patients with

illnesses such as these can live long lives, possibly even a full natural life span. Of course, as the

population has risen, so has the number of individuals with terminal illnesses, such as

Amyotrophic lateral sclerosis (ALS), that medical science cannot influence the course of.

As of 2005, it is estimated that the population of Americans with chronic illnesses stood

at 133 million, and that 63 million of those individuals had more than one chronic illness

(Bodenheimer, 2009). By 2020, it is estimated that the number of individuals with chronic

conditions will rise to 157 million, of which 81 million individuals will have more than one

chronic condition (Bodenheimer, 2009). As the number of individuals affected by disease grows,

and our culture becomes more open and informed about medical conditions in general, the

discourse on disease increases. In almost all discussion about disease, regardless of the speaker

or the audience, it is discussed using struggle language or combat metaphors. “The war on

cancer”, “cancer survivor”, “a virus invades human cells”, “your immune system defends your

body”; all are examples of discussing disease in terms of war and conquest. The use of such

language gives the impression of dividing patients into groups of “winners” (patients who

triumph over their disease, typically by being cured) and “losers” (those who succumb to illness,

or whose illness is incurable).

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Study Objective

While research has been conducted on various aspects of chronic illness, including

population statistics, employment statistics on chronic illness patients, illness perception, and the

effects of specific diseases on patients’ lives, little research has been done on the effects of the

language commonly used when discussing illness, particularly the effects that might be found in

patients with chronic illnesses. Given the growing population of chronic illness patients,

determining the effects of such language on the perceptions of chronic illness and patients with

chronic illnesses seems prudent to this investigator. Awareness of the potential effects on

perception of patients, both how patients see themselves and how other see them, might

influence the language used when discussing illness, which in turn may affect patient perception.

This proposed study would seek to determine the potential impact of struggle language on

perceptions of chronic illness.

Literature Review

Much of the current research on chronic illness focuses on Health-Related Quality of Life

(HRQoL), particularly in patients with specific illnesses. A study conducted in 2014 by Steel, et

al., looked at HRQoL as a predictive factor in life spans of patients with advanced cancer. The

study sought to “investigate the prognostic value of HRQoL in patients with hepatocellular

carcinoma and cholangiocarcinoma after adjusting for sociodemographics, disease-related

factors, and treatment-related factors (Steel, et al., 2014).” The researchers administered the

Functional Assessment of Cancer Therapy-Hepatobiliary instrument to 321 patients. Using Cox

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regression, the researchers determined that overall HRQoL was significantly associated with

longer survival rates, even after controlling for the factors listed above. Since HRQoL was found

to be predictive of survival rates of patients with hepatocellular and cholangiocarcinoma, the

researchers recommended that physicians stratify patients when testing new and novel

treatments.

A study conducted in Singapore in 2014 (Venkataraman, et al., 2014) looked at HRQoL

in 3514 individuals from the general community in Singapore. Subjects were tested on their

HRQoL (using the SF-36 health survey version) and checked for three common conditions:

diabetes mellitus, hypertension, and dyslipidemia. Each participant, for each condition, was

categorized as either: having no disease, undiagnosed, diagnosed but not taking medication, or

diagnosed and taking medication. Researchers used one-way ANOVA and multiple linear

regression to determine that disease awareness was associated with lower HRQoL, while

undiagnosed disease was associated with higher HRQoL. The researchers concluded that these

results indicate a reason why these individuals do not seek regular medical care.

A recent study conducted in the United Kingdom (Parker, et al., 2014) sought to study the

impact of chronic conditions and multimorbidity in the elderly, in order to determine which of 15

common chronic conditions impacted HRQoL the most, and what interventions might be

appropriate. Researchers studied a community-based population of individuals ages 65 and older.

The mean age of participants was 74.6 years, and of those subjects, 49.2% were male.

Multivariate modeling was used to determine that 13 of the 15 conditions studied significantly

impaired HRQoL. The three conditions that caused the greatest impact were osteoarthritis,

neurological disease, and depression. The researchers recommend that their results be used to aid

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in clinical decision making, particularly when setting treatment priorities for patients with

multimorbidity.

In Norway, a study was recently conducted that analyzed illness perception (IP) in

patients with chronic obstructive pulmonary disorder (COPD) (Borge, et al., 2014). Illness

perception refers to how patients evaluate how they live with a disease. The researchers sought to

determine whether breathlessness, a common symptom of COPD, was a precursor of IP, and

whether IP was in turn linked to HRQoL. The researchers conducted a cross-sectional survey

using 154 COPD patients. The researchers used multiple regression analyses to determine that

patients with a high IP score (high IP indicates that patients consider their condition to be a

significant threat) experienced more breathlessness. Researchers suggest that their findings might

have implications for patient counseling, possibly by helping patients learn to cope with their

COPD by restructuring their personal models of illness, which could reduce their breathlessness.

The other main focus area in chronic illness research is employability of individuals with

chronic illnesses. A study that sought to analyze the long-term effects of cancer and cancer

treatment on employment was conducted in 2008 by Short, Vasey, and BeLue. The researchers

had two objectives with this study: “(1) to quantify the increase in work disability attributable to

cancer in a cohort of adult survivors who were an average of 46 months post-diagnosis and (2) to

compare disability rates in cancer survivors to individuals with other chronic conditions (Short,

Vasey, & BeLue, 2008). “ The study compared data from two groups: 647 cancer survivors, aged

55-65, in a sample taken from the Penn State Cancer Survivor Study, and 5988 similarly aged

subjects sampled from the Health and Retirement Study. The researchers used multivariate

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logistic regression to develop estimated adjusted odds ratios for work disability for cancer

survivorship, heart disease, diabetes, stroke, lung disease, and arthritis. The results demonstrated

few significant differences in work disability for cancer survivors versus subjects with other

chronic conditions, and both subject groups had significantly higher work disability rates than

similarly aged individuals without any chronic medical conditions. The researchers concluded

that, given the elevated work disability rate, cancer survivorship should be considered a chronic

illness.

Researchers in the Netherlands recently studied the impact of illness duration and age at

diagnosis on labor participation chances (Rijken, et al., 2013). The researchers surveyed several

cohorts of individuals who have been diagnosed with a chronic illness since 1998, and studied

4634 subjects in total. Multi-level logistic regression analyses were used to determine that the

age at illness onset had a significant negative effect on labor participation chances, as did the

duration of illness. The duration of illness negative effect on employment had a stronger impact

on men that it did on women. The researchers suggest that further studies should be conducted to

study different diagnostic groups, and perhaps develop programs to guide young people with

chronic illnesses to help them develop suitable careers.

Research Questions and Hypotheses

Does the use of struggle language and combat metaphors in relation to disease affect

perceptions of disease or perceptions of individuals with a chronic illness? Does the frequency

with which the patient and/or others use struggle language in relation to illness have any

correlation to patients’ quality of life? Are there any demographic factors that correlate with

quality of life ratings? It is hypothesized that the use of struggle language and combat metaphors

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has a negative effect on patients’ quality of life. It is also hypothesized that awareness of struggle

language usage will be connected to how frequently it is used.

Methods

Instruments

Questionnaire: The participants completed a 14 question self-reporting questionnaire.

Basic demographic information was collected, including age, gender, race/ethnicity, educational

background, and employment status. Given that the study is about the use of struggle language

and chronic illness, subjects were also asked whether they had worked in the health care field,

whether they or someone they knew had a chronic illness, whether they were aware of the use of

struggle language in regards to chronic illness, and how often they and others around them used

struggle language in regards to chronic illness. Subjects were also asked to rate their quality of

life, their satisfaction with their career path, and the quality of life of someone they knew who

had a chronic illness, using the following scale: 1= Very Low, 2= Low, 3= Neutral, 4= High, 5=

Very High.

Sampling and Data Collection

The sample was obtained through a convenience sampling. There were 33 participants in

this survey. To maintain each participant’s confidentiality, the consent form was signed and filed

separately from the completed surveys. Data from the surveys was then entered into SPSS 22 for

analysis by the researcher.

Variables

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The independent variables of this study are awareness of struggle language, struggle

language use, and whether the participant has a chronic illness, or is close to someone who does.

The dependent variables of this study are quality of life of the participant and the participant’s

rating of the quality of life of someone they know with a chronic condition. These variables are

ranked on an ordinal scale, which is as follows: 1= Very Low, 2= Low, 3= Neutral, 4= High, 5=

Very High. These variables will help to determine whether struggle language use is related to

quality of life.

Analysis Strategy

For this study, there are many different ways that both the independent variables and the

dependent variables can be analyzed. Since most of the variables of interest are ordinal and

nominal variables, the tests used will be nonparametric. An Independent Samples Mann-Whitney

U test can be performed to present a significance value and an M place score to determine

whether there is a significant relationship between the respondent’s quality of life score and their

chronic illness status. An Independent Samples Mann-Whitney U test can also be used to

examine the relationship between the respondent’s chronic illness status and awareness of the

use of struggle language. An Independent Samples Kruskal-Wallis Test can be performed to

determine whether there is a relationship between the frequency with which the respondent uses

struggle language and what rating they give to the quality of life of someone with a chronic

illness. This will offer a significance value and an H score. A Spearman’s rho correlation test can

be performed to determine the relationship between an individuals’ awareness of the use of

struggle language and the frequency with which they use struggle language in relation to chronic

illness. This test will offer a significance value and a rho score.

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Ethical Concerns

The potential ethical concerns were minimal; regardless, participants were informed of

the concerns in the informed consent form and in the cover letter. Participants were made aware,

both verbally and in writing, that their participation was voluntary, and that they could withdraw

from the survey at any time. Furthermore, participants were made aware of the separation of

signed consent form from completed survey, so as to protect their anonymity.

Results

The demographics are given in Table 1, below this paragraph. There were 33 participants

in the study. Ages ranged from 17 to 62 years old, with a mean age of 40.24 years old and a

median age of 42 years old. Most of the participants were female (n=25), while only 24.2% were

male (n=8). Most of the participants were White/Non-Hispanic (n=31), while one participant

was African American and one participant described themselves as Other. The largest proportion

of participants had Bachelor’s Degrees (n=12), followed by some college but no diploma (n=10),

high school diploma/GED (n=5), Master’s Degrees (n=2), some high school but no diploma

(n=2), Associate’s Degree (n=1), and one participant had a professional degree. Most

participants were employed for wages (n=27), while some were self-employed (n=3), students

(n=2), or homemakers (n=1).

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Table 1Demographic information and independent and dependent variables

N=33 Frequency Percent Mean Median Minimum Maximum

DemographicsGender

Female 25 75.8% ---- ---- ---- ----Male 8 24.2% ---- ---- ---- ----

Age, years ---- ---- 40.24 42.0 17 62

EthnicityAfrican American 1 3.0% ---- ---- ---- ----Other 1 3.0% ---- ---- ---- ….White/Non-Hispanic 31 31.0% ---- ---- ---- ----

Education Some High School, No Diploma 2 6.1% ---- ---- ---- ----High School Diploma/GED 5 15.2% ---- ---- ---- ----Some College, No Diploma 10 30.3% ---- ---- ---- ----Associate’s Degree 1 3.0% ---- ---- ---- ----Bachelor’s Degree 12 36.4% ---- ---- ---- ----Master’s Degree 2 6.1% ---- ---- ---- ----Professional Degree 1 3.0% ---- ---- ---- ----

Employment StatusEmployed for Wages 27 81.8% ---- ---- ---- ----Self-Employed 3 9.1% ---- ---- ---- ----Homemaker 1 3.0% ---- ---- ---- ----Student 2 6.1% ---- ---- ---- ----

Independent Variable

Current or Former Health Care WorkerYes 7 21.2% ---- ---- ---- ----No 26 78.8% ---- ---- ---- ----

Awareness of Struggle Language UseYes 17 51.5% ---- ---- ---- ----Somewhat Aware 7 21.2% ---- ---- ---- ----Not Sure 2 6.1% ---- ---- ---- ----No 7 21.2% ---- ---- ---- ----

Respondent has a Chronic IllnessYes 5 15.2% ---- ---- ---- ----No 28 84.8% ---- ---- ---- ----

Respondent Knows Someone with a Chronic IllnessYes 22 66.7% ---- ---- ---- ----No 11 33.3% ---- ---- ---- ----

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Table 1, ContinuedDemographic information and independent and dependent variables

N=33 Frequency Percent Mean Median Minimum Maximum

How Frequently does Respondent use Struggle LanguageOften 4 12.1% ---- ---- ---- ----Sometimes 9 27.3% ---- ---- ---- ----Rarely 9 27.3% ---- ---- ---- ----Never 11 33.3% ---- ---- ---- ----

How Frequently do Others Use Struggle LanguageOften 6 18.2% ---- ---- ---- ----Sometimes 15 45.5% ---- ---- ---- ----Rarely 6 18.2% ---- ---- ---- ----Never 6 18.2% ---- ---- ---- ----

Dependent Variable

Respondent’s Quality of LifeNeutral 5 15.2% ---- ---- ---- ----High 18 54.5% ---- ---- ---- ----Very High 10 30.3% ---- ---- ---- ----

Respondent’s Satisfaction With Career PathLow 3 9.1% ---- ---- ---- ----Neutral 7 21.2% ---- ---- ---- ----High 16 48.5% ---- ---- ---- ----Very High 7 21.2% ---- ---- ---- ----

Respondent’s Rating of Quality of Life of Someone with a Chronic IllnessVery Low 1 3.0% ---- ---- ---- ----Low 6 18.2% ---- ---- ---- ----Neutral 16 48.5% ---- ---- ---- ----High 8 24.2% ---- ---- ---- ----Very High 2 6.1% ---- ---- ---- ----

Independent and Dependent Variable

Independent Variable: Of the participants, 7 had previously worked or volunteered in the health

care field, while most had not (n=26). The majority of participants were aware of the use of

struggle language in relation to chronic illnesses (n=17), while some were somewhat aware

(n=7), not aware (n=7), or not sure (n=2). Only a few participants had a chronic illness (n=5),

while most did not (n=28). The majority of participants did know someone with a chronic illness

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(n=22), while the minority did not (n=11). A small majority of participants never use struggle

language in reference to chronic illness (n=11), while some participants rarely used it (n=9), or

used it sometimes (n=9); only 4 participants used struggle language often. More participants

were accustomed to hearing others use struggle language sometimes (n=15), while equal

numbers of participants heard other use struggle language often (n=6), rarely (n=6), or never

(n=6).

Dependent Variable: The majority of participants rated their quality of life as high (n=18), while

others rated their quality of life as very high (n=10), or neutral (n=5). Most participants rated

their career path satisfaction as high (n=16), while equal amounts rated their career path as either

very high (n=7) or neutral (n=7); only 3 participants rated their career path satisfaction as low.

When asked to rate the quality of life of someone they know/knew with a chronic illness, the

majority of participants rated the person’s quality of life as neutral (n=16), followed by high

(n=8), low (n=6), very high (n=2), or very low (n=1).

Statistical Tests

The statistical test results are given in Table 2, below this section. A Mann-Whitney U

test was used to examine the difference in quality of life scores between individuals who did and

did not have chronic illnesses. The significance level is 0.290 and the U-value is 91.50 with 33

degrees of freedom. These results do not appear to be significant. A Mann-Whitney U test was

used to examine the levels of awareness of struggle language use between individuals who did

and did not have chronic illnesses. The significance level is 0.045 and the U value is 110.0 with

33 degrees of freedom. This result is significant because the significance level is below 5%,

which indicates that there is a connection between struggle language awareness and chronic

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illness status. Participants who have a chronic illness were significantly more likely to be aware

of the use of struggle language (M place = 9.00) than individuals who do not have a chronic

illness (M place = 18.43). A Kruskal-Wallis test was conducted to examine the relationship

between a respondent’s quality of life rating for someone with a chronic illness and the

frequency with which the respondent uses struggle language in relation to chronic illness. No

significant relationship was found (H(3)=.742, P=.863), indicating that the there were no

significant differences. A Spearman rho correlation coefficient was calculated for the

relationship between a respondent’s awareness of struggle language and the frequency with

which they use struggle language. A strong positive correlation was found (rho(31)=.458,

P=.007), indicating a significant relationship between awareness and usage. Participants who

were more aware of the use of struggle language in regards to chronic illness were more likely to

use struggle language themselves.

Table 2Results from Statistical TestsIndependent Variable Dependent Variable Test Conducted Results

Respondent’s Chronic Illness Status Quality of Life Mann-Whitney U test U=91.50 P=0.290Respondent’s Chronic Illness Status Awareness of Struggle Lang. Mann-Whitney U test U=110.0 P=.045Respondent’s QoL Rating for Person Frequency of Struggle Kruskal-Wallis test H(3)=.742 P=.863With Chronic Illness Language UsageAwareness of Struggle Language Frequency of Struggle Spearman Correlation rho(31)=.458 P=.007

Language Usage

Limitations

There are many limitations that may have affected the results of this survey. The sample

size was small, and it was heavily female and white, which is likely partly due to the distribution

process. There was also a very small population of respondents who had chronic illnesses, which

could certainly skew the results. And because the surveys were self-reported, respondents

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falsifying their answers is always a possibility.

Conclusion

Implications

The results of this study might be useful in future practice if more work was done to

survey chronic illness patients to determine their feelings about the use of struggle language, and

if those feelings are negative, then perhaps society could work towards building a more person-

focused, less combat-focused vocabulary for chronic illness. Currently, this study is helpful in

proving that individuals, both with and without chronic illnesses, are aware of the use of struggle

language, and that awareness of such language is connected to how frequently it is used.

Conclusions

The results of this study have been inconclusive in proving my hypothesis that increased

use of struggle language would be connected to lower quality of life ratings in people with

chronic illnesses, as no such connection was found. My hypothesis that awareness of struggle

language usage and frequency of struggle language usage was not disproven, although I did

expect the opposite result (higher levels of awareness would result in less frequent usage).

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References

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Disease: Can The U.S. Health Care Workforce Do The Job? Health Affairs, 64-74.

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Borge, C. R., Moum, T., Puline Lein, M., Austegard, E. L., & Wahl, A. K. (2014). Illness

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Parker, L., Moran, G. M., Roberts, L. M., Calvert, M., & McCahon, D. (2014). The burden of

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Venkataraman, K., Khoo, C., Wee, H. L., Tan, C. S., Ma, S., Heng, D., & ... Thumboo, J. (2014).

Associations between Disease Awareness and Health-Related Quality of Life in a Multi-

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Liz Rolf-The Use of Struggle Language in Chronic Illness