Journal of Pediatric Health Care
Volume 26, Issue 1 , Pages 27-36, January 2012

Factors That Influence the Likelihood of Hiring a Health Care Advocate for a Chronically Ill Child

published online 22 July 2010.

Article Outline

Abstract 

Introduction

In response to the increasing complexity of the health care system, the field of health care advocacy has emerged. However, little is known about variables that may influence a person's likelihood of hiring a health care advocate (HCA) for their chronically ill child.

Methods

Severity (high or low) and probability of mortality (high or low) of a child's chronic illness and the child's age (1, 7, or 13 years) were manipulated using vignettes. The dependent variable was a composite score of the eight items used to measure the participants' likelihood of hiring an HCA.

Results

Participants (N = 1052) were more likely to hire an HCA for a child who was 1 year old than for a child who was 13 years old. Participants were more likely to hire an HCA for a child whose chronic illness was low rather than high in severity and whose chronic illness was high rather than low in probability of mortality.

Discussion

Use of an HCA may increase patient satisfaction, decrease medical errors, and enhance pediatric health outcomes.

Key Words: Health care advocate, pediatric chronic illness, severity, age, probability of mortality, morbidity

 

According to the World Health Report (World Health Organization, 2000), quality, efficiency, and responsiveness to the expectations of the patient population are the primary goals of health delivery systems. Yet in today's health care market, it is challenging even for well-informed patients to be certain that their best interests are being met and that they receive the best care possible.

Health care advocates … generally are defined as professionals who represent the interests of the patient and work with them to reduce the complexities implicit in the treatment of chronic illness.

In response to these challenges, the field of health care advocacy has been created. Health care advocacy grew out of the patient rights movement in the 1970s (Hurst, 2008). Health care advocates (HCAs) generally are defined as professionals who represent the interests of the patient and work with them to reduce the complexities implicit in the treatment of chronic illness. Specific duties performed by HCAs may include examining service failures in hospitals (Marsh, 1984), responding to complaints (Mailick, 1982), informing patients about their choices (Welchman & Griener, 2005), connecting patients with needed resources (Cowles & Lefcowitz, 1995), providing emotional support (Cowles & Lefcowitz, 1995), and protecting and encouraging patient rights (Schwartz, 2002).

Health advocacy services increase the rates of cancer screening (Weinrich et al., 1998), improve patients' knowledge about their condition and treatment (Salminen, Isoaho, Vahlberg, Ojanlatva, & Kivela, 2005), and improve access to health care services (Shannon, Wilber, & Allen, 2006). Use of a patient navigator program developed by the National Cancer Institute to help underserved patients overcome barriers to obtaining cancer screening increased patients' rates of screening (Ell et al., 2009). Scholle et al (2000) found that women were more likely to receive information and recommendations on breast cancer screenings when an HCA was assigned to work with them than when one was not assigned. Patients with breast cancer also reported significantly better diagnoses and increased 5-year survival rates when they used a patient navigator (Freeman, 2006).

During the past 5 years, private agencies have begun to offer health advocacy services Common Dreams News Center, News, 2005). These services provide more benefit to patients than do services offered by hospitals or insurance companies because the HCA's primary allegiance is to the patient. However, very few of these agencies exist nationwide, their services are expensive, and little, if any, research has been published on the efficacy of the services offered by these agencies. Therefore, it is important to determine the extent of public interest in this type of service and to identify the patient population that may derive the greatest benefit from these services.

One area where the services of an HCA might be particularly important is pediatrics. Approximately 53,000 children die annually in the United States, half from acute causes and the other half as the result of severe chronic illnesses (Stillion & Papadatou, 2002). An HCA may be able to help a family manage the stresses associated with such conditions and attenuate some of the health care costs by facilitating improved communication and efficiency of the entire health care team. Three factors that may affect a person's likelihood of hiring an HCA for their child are the severity (morbidity) of a child's illness, the probability of mortality, and the child's age.

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Severity of the Child's Chronic Illness 

Historically the child's health status has been the strongest predictor of the use of pediatric primary care because it accounts for roughly one sixth of the total variance in the child's use of health care (Janicke & Finney, 2004). The presence of a chronic illness often is used to quantify health status (Kelleher and Starfield, 1990, Janicke et al., 1999, Newacheck and Halfon, 1986, Starfield et al., 1979, Tessler and Mechanic, 1978, Wolfe, 1980). A study by Hankin et al. (1984) showed that the presence of a chronic illness in a child was positively correlated with a greater frequency of health care use. Further, a child's chronic illness appears to be a great burden on the parental dyad. Studies by Meyer, Snelling, and Myren-Manbeck (1998) and Meyer, Burns, Griffith, and Truog (2002) demonstrated that the anxiety levels of parents whose child was diagnosed with a chronic illness can escalate to crisis levels over time. Tomlinson et al. (2007) observed more psychological distress among mothers of chronically ill children than among mothers of children with a time-limited illness. These findings suggest that pediatric chronic illness creates a great psychological strain on the child's family.

Severe pediatric chronic illness is a large financial burden on the health care system. Silber, Gleeson, & Zhao (1999) showed that children with severe chronic illnesses are more expensive to care for than children with acute, or time-limited, illnesses. Another study showed that medical care for children with chronic health conditions is up to 20 times more expensive than care for children with acute illnesses (Ireys, Anderson, Shaffer, & Neff, 1997). An HCA may be able to help a family manage the stresses associated with such conditions and to attenuate some of the health care costs by facilitating improved communication and efficiency among the health care team.

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Probability of Mortality of the Child with a Chronic Illness 

Current literature suggests that the presence of an acute illness with a high probability of mortality is a reliable predictor of consistently high use of child primary care services (Janicke & Finney, 2004). However, pediatric mortality rates have decreased significantly in the past decade because of advances in medical technology, the conquest of acute diseases via inoculation, and improved access to medical care during the past decade (Stillion & Papadatou, 2002). While it is generally agreed that a decline in pediatric mortality rates has been accompanied by a decrease in the use of the health care system, little is known about the effects of psychosocial variables on the use of the health care system. Specifically, to understand the patterns of child health care use, it is necessary to have a better grasp of the mechanisms involved in parents' decision-making processes (Janicke & Finney, 2004). For example, studies suggest that parental perceptions of poor child health (Newacheck and Halfon, 1986, Riley et al., 1993, Woodward et al., 1988) are related to greater frequency of medical care use. Therefore it is likely that parental perceptions of the child's vulnerability, that is, the odds of how likely a child is to die from an illness, may be significant factors related to parents' likelihood of hiring an HCA for their chronically ill child.

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Child's Age 

Little consensus exists about whether the age of a child predicts health service use. Rates of death from cancer, heart disease, chronic lower respiratory disease, and human immunodeficiency virus (HIV) disease rise with age, and thus older children are more likely to have a chronic illness. However, younger children appear to use child health services more frequently (Hankin et al., 1984, Newacheck and Halfon, 1986, Starfield et al., 1979, Tessler and Mechanic, 1978, Ward and Pratt, 1996). The aforementioned statements are controversial because no study has conclusively defined the effects of age on pediatric medical care use.

One possible explanation for this uncertainty is that the value placed on a child's life is based partially on subjective criteria. Janvier, Leblanc, and Barrington (2008) assigned participants to hypothetical scenarios that described patients of varying ages who were critically ill and in need of emergency resuscitation. Respondents were asked to decide whether resuscitation was in the best interest of the patient based on the patient's age, prognosis for survival, potential disability, and chance of a poor neurological outcome. The scenarios included three infants with identical prognoses who differed only in their ages (a preterm infant, a term newborn, and a 2-month-old infant), as well as older children and adults, all of whom had prognoses that were worse than those of the three infants. The results demonstrated that the percentage of respondents who believed resuscitation to be in the best interest of the three infants was directly proportional to the infant's age (∼70% for preterm infant, ∼85% for the term infant, and ∼95% for the 2-month-old infant), despite their having an identical expected prognosis. Furthermore, more than 90% of respondents believed that resuscitation was in the best interest of the 7-year-old child compared with about 70% for the premature infant, despite the fact that the premature infant was given a better prognosis. This study, combined with other disparate reports on the effect of a child's age on health care use, underlines the fact that it is necessary to further investigate the effect of this variable on pediatric medical care use.

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Hypotheses 

The four main hypotheses are: (a) participants are more likely to hire an HCA when the child has a high probability of mortality than when the probability of mortality is low; (b) participants are more likely to hire an HCA when the child's illness is more severe rather than less severe; (c) participants are more likely to hire an HCA for a child who is younger (1 year old) than for a child who is older (13 years old); and (d) participants who read vignettes that describe a child with a chronic illness who has a high probability of mortality and whose illness is high in severity are more likely to hire an HCA than those who read vignettes that describe a child with a chronic illness who has a low probability of mortality and whose illness is low in severity.

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Methods 

Sample 

The participants were 1052 adults who were randomly selected from the community. The mean age of the participants was 41.5 (SD = 17.1). Forty-two percent were male and 67% were White. Eighty-two percent of the sample had medical insurance. Reported annual family incomes and educational levels, along with other demographic characteristics, are provided in Table 1.

Table 1. Demographic characteristics of the study sample
ItemValid %
Gender of respondent
Male42.1
Female57.9
Ethnicity
White68.6
Other31.4
Education
High school or less22.7
Some college/college graduate/professional degree53.8
Advanced degree23.5
Family income
< $59,99945.4
$60,000-$119,99934.9
≥ $120,00019.7
Have health insurance?
Yes82.3
No17.7

Procedure 

Participants were randomly selected and approached by research assistants in Balboa Park, located in San Diego, California. Balboa Park is the nation's largest urban cultural park. Situated on 1200 acres, it is home to 15 major museums, several performance art venues such as public gardens, and the San Diego Zoo. It receives more than 500,000 visitors each year from all over the world, including large numbers of culturally diverse visitors. It was selected as a data collection site primarily because its wealth of visitors provides a more representative population for sampling than would a purely local population.

Research assistants approached potential participants and asked them whether they would be willing to participate in a study about health care. Participants were required to understand and read English to complete the study. They were told that their participation would take 5 to 10 minutes and that they would be given $5 as a token of appreciation. Interested participants were asked whether they would be able to read two short paragraphs and complete a brief survey. Participants who met the criteria were given a cover letter explaining the purpose of the study, the scenarios, and a brief questionnaire to complete. The questionnaires were anonymous and completed individually.

Vignettes 

Two possible methods were considered: conducting qualitative interviews with clinically relevant samples of participants, or distributing vignettes to a randomly selected sample of participants. The vignette approach was chosen because it avoids problems often associated with standardized interviews by providing a concrete, detailed stimulus and greater control over the survey design, thus increasing internal validity (Alexander & Becker, 1978). The use of vignettes also allowed us to manipulate the levels of each of the variables of interest more reliably. Because our hypotheses were drawn from data based on sampling of the general population, we decided that we should confirm them in a similar population before applying them to specialized populations. Finally, the vignette approach is preferable when participants worry about confidentiality.

Participants were randomly assigned to read one of 12 vignettes that described two levels of illness severity (low or high), two levels of the probability of mortality (low or high) and three levels of the child's age (1, 7, or 13 years). The scenarios described a married couple, Ben and Julia Barnes, who had a child named Jack who was diagnosed with a chronic illness 3 months ago. Ben and Julia were described as full-time working professionals with excellent health insurance. Finally, a description of Jack's illness was included.

The Barneses were said to have watched a television program recently that described a professional known as a health care advocate. The following description of the HCA was provided in each of the scenarios. “A health care advocate is a professional who has a thorough understanding of the medical culture, as well as of the physiological component of illnesses. The major responsibilities of a health care advocate are to make sure that the needs of the patient and family are well represented and that the treatment team really listens to and responds to the family's concerns.” It was said that the services of an HCA typically were not covered by health insurance.

Vignette Manipulations 

Probability of mortality and severity variables were manipulated by describing their levels as high or low.

High severity, low probability of mortality illness condition 

In this vignette it was said that Jack Barnes was recently diagnosed with asthma, a disease in which the airways in the lungs constrict and become inflamed. It was also said that, although death from asthma has become a rare event, there still is no cure for the disease. Children with asthma often are treated with a variety of medicines, are seen frequently in the offices of multiple different medical specialists, and are regularly admitted to the hospital with conditions related to their illness.

High severity, high probability of mortality illness condition 

In this vignette it was said that Jack Barnes was recently diagnosed with idiopathic pulmonary artery hypertension (IPAH), a rare illness that leads to progressive heart failure. It also was said that IPAH diagnosed during childhood is a chronic illness and that 85% of children will die from complications of the illness within 5 to 10 years of being diagnosed. Children with IPAH are treated with a variety of medicines, are seen frequently by many different medical specialists, and are regularly admitted to the hospital with conditions related to their illness.

Low severity, high probability of mortality illness condition 

In this vignette it was said that Jack Barnes was recently diagnosed with myocarditis, a rare illness that leads to progressive heart failure and produces a high probability of death in the near future. It also was said that the only cure for myocarditis is a heart transplant. However, in Jack's case, no suitable donor was said to be available. Jack's doctors have informed Jack's parents that, even with a transplant, the chances of his dying from this condition in the next 1 to 2 months are very high.

Low severity, low probability of mortality illness condition 

In this vignette it was said that Jack Barnes was recently diagnosed with an atrial septal defect (ASD), a very small hole in one of the walls separating the chambers of the heart that rarely causes death. It was said that an ASD is a very common condition and does not require any therapy. This defect is almost always present from birth and does not get larger as the heart grows. It is not associated with any complications. In Jack's case, no further treatment or surgery is required.

Child's age 

The child's age level was manipulated by describing Jack's age as 1, 7, or 13 years. These ages were chosen for several reasons: first, they are representative of three major stages of childhood (toddler, school age, and adolescent); second, they were plausible in the context of the medical scenarios presented in the vignettes; and third, they spanned the spectrum of childhood (1 to 13 years).

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Measures 

After reading the scenario, the respondents were asked to assume that they were Jack's parent and to indicate, using a 10-point Likert-type scale ranging from 1 (extremely unlikely) to 10 (extremely likely), how likely they would be to hire an HCA. The likelihood to hire an HCA was assessed using eight questions that asked how likely they would be to hire a HCA to stay with Jack while he is in the hospital, accompany you and Jack to his medical appointments, deal with insurance issues, maintain a file that contains all of Jack's medical records, inform each member of Jack's treatment team of the most recent treatment plan, research treatment options for Jack, assist with Jack's daily symptom management, and coordinate Jack's medical appointments.

A scale formed from the eight items used to measure the likelihood of hiring an HCA demonstrated excellent internal consistency (α = .919), and an exploratory factor analysis using principal axis extraction and varimax rotation indicated that a 1-factor solution best explained the data (the variance explained by the solution was 63.9%). Therefore, responses to the eight items were averaged to form a composite value and used as a dependent variable.

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Analysis 

The following results were based on a 2 (severity of the child's illness) × 2 (probability of mortality of child's illness) × 3 (child's age) between-subjects analysis of covariance (ANCOVA) using polynomial contrasts for the effect of age. Significantly correlated demographic variables, ethnicity, level of education, income, health insurance status, and the participants' understanding of the concept of an HCA were entered as covariates in the analysis.∗

On average, individuals assigned to the low severity of chronic illness condition reported that they would be more likely to hire an HCA than would individuals assigned to the high severity of chronic illness condition (Mhigh = 5.35 vs. Mlow =5.69, F (1, 1035) = 6.400, p = .012, partial η2 = .006). Furthermore, on average, individuals assigned to the high probability of mortality condition reported that they would be more likely to hire a health care advocate than would individuals assigned to the low probability of mortality condition (Mhigh = 6.10 vs. Mlow =4.94, F (1, 1035) = 76.123, p < .001, partial η2 = .069).

The results also revealed a significant effect for the linear age planned contrast (M1-year-old = 5.63 vs. M13-year-old = 5.30, F (1, 1035) = 4.054, p = .044, partial η2 = .004). Participants reported that they would be more likely to hire a health care advocate for a child who was 1 year old than for a child who was 13 years old. The quadratic effect of age was not statistically significant (F (1, 1035) = 1.609, p = .205). Also, neither of the interactions between severity and age (AgeLinear × Severity: F (1, 1035) = 1.053, p = .205, AgeQuadratic × Severity: F (1, 1035) = 2.193, p = .139) nor between probability of mortality and age (AgeLinear × Mortality: F (1, 1035) = .626, p = .429, AgeQuadratic × Mortality: F (1, 1035) = .001, p = .973) was significant.

However, the interaction between the severity and probability of mortality of chronic illness was significant (F (1, 1035) = 4.137, p = .042, partial η2 = .004). To explore this interaction, we probed the simple effects of severity within probability of mortality. The results indicated that when probability of mortality was high, participants reported that they would be more likely to hire an HCA for a child whose illness low in severity than for a child whose illness was high in severity (Mseverityhigh = 5.80 vs. Mseveritylow = 6.41, F (1, 1035) = 20.75, p < .05). However, the results indicated that there was no significant difference between severity levels when probability of mortality was low (Mseverityhigh = 4.91 vs. Mseveritylow = 4.97, F (1, 1035) = 3.39, p > .05).

Finally, there was a significant interaction between severity of chronic illness, probability of mortality of chronic illness, and the quadratic effect of age (AgeQuadratic × Severity × Mortality: F (1, 1035) = 3.959, p = .047, partial η2 = .004). To explore this interaction, we probed the simple effects of severity within probability of mortality for the 7-year-old versus the average of the 1-year-old and 13-year-old conditions. The results indicated that there was a significant difference in participants' likelihood to hire an HCA between severity levels when probability of mortality was high for children who were 7 years old (Mseverityhigh7-year-old = 5.87 vs. Mseveritylow7-year-old = 6.58, F (1, 1035) = 4.85, p < .05) but that there was no significant difference in participants' likelihood to hire an HCA between severity levels when probability of mortality was either high or low for children who were 1 or 13 years old (Figure 1). This result is consistent with the 2-way probability of mortality × severity interaction, with participants reporting that they would be more likely to hire a health care advocate for a child whose illness was high in probability of mortality and low in severity than for a child whose illness was high in probability of mortality and high in severity.

  • View full-size image.
  • Figure 1 

    Likelihood of hiring an HCA based on age, severity of illness, and likelihood of mortality. HCA, Health care advocate; Hi, high; Lo, low; Sev, severity. ∗Significantly different (p < .05). This figure can be viewed in color online at www.jpedhc.org.

Correlated demographic variables 

Several demographic variables, including ethnicity, level of education, annual income, health insurance status, and the participants' understanding of the concept of an HCA, were significantly associated with the outcome and thus were entered as covariates in the ANCOVA analysis (see Table 2 for correlations). It is also worth noting that ethnicity, level of education, annual income, and the participants' understanding of the concept of an HCA remained significant, over and above the condition effects entered in the ANCOVA. Next, we examine differences in the likelihood of hiring a health care advocate as a function of each of these variables.

Table 2. Bivariate correlation values between covariates and dependent variable
EthnicityLevel of educationIncomeHealth insurance statusComprehension of the term HCA
Likelihood of hiring an HCA (scale score).216∗–.189∗–.178∗–.117∗.098∗

HCA, Health care advocate.

∗Correlation is significant at the 0.01 level.

Ethnicity and the likelihood of hiring an HCA 

Ethnicity (two levels: White or ethnic minority) was significantly associated with the likelihood of hiring a health care advocate (F (1, 1035) = 45.934, p < .001, partial η2 = .042, MWhite = 5.20 vs. MEthnicMinority = 6.45). Non-White participants reported being more likely to hire an HCA than did White participants.

Education and the likelihood of hiring an HCA 

Education (three levels: high school or less, associates'/bachelors' degree, or advanced degree) was significantly associated with the likelihood of hiring an HCA (F (1, 1035) = 20.923, p < .001, partial η2 = .020, Mhighschoolorless = 6.56 vs. Massociates/bachelors = 5.56 vs. Madvanced degree = 5.26). Participants with less education reported being more likely to hire an HCA than did participants with more education.

Annual income and the likelihood of hiring an HCA 

Annual income (three levels: < $59,999, $60,000-$119,999, and ≥ $120,000) was significantly associated with the likelihood of hiring an HCA (F (1, 1035) = 13.368, p < .001, partial η2 = .013, M < $59,999 = 6.07 vs. M$60,000-$119,999 = 5.69 vs. M ≥ 120,000 = 5.59). Participants with lower annual incomes reported being more likely to hire an HCA than did participants with greater annual incomes.

Health insurance status and the likelihood of hiring an HCA 

Health insurance status (two levels: yes or no) was not significantly associated with the likelihood of hiring an HCA (F (1, 1035) = 1.782, P =.182, partial η2 = .002).

Comprehension of the term and the likelihood of hiring an HCA 

The participants' comprehension of the term “health care advocate” (1-10) was significantly associated with the likelihood of hiring an HCA (F (1, 1035) = 15.944, P <.001, partial η2 = .015, β = .116). Participants who reported a greater understanding of the term “health care advocate” were more likely to hire an HCA than were participants who reported a lower understanding of the term.

Likelihood to hire an HCA for each of the eight tasks 

Although responses to the eight items were averaged to form a composite value and were used as a dependent variable, it was informative to examine the mean likelihood to hire an HCA for each of the eight tasks in order to provide a more complete representation of the sample (Figure 2).

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Discussion 

The finding that persons assigned to the low severity of chronic illness condition vignette would be more likely to hire an HCA than would individuals assigned to the high severity of chronic illness condition vignette was opposite to the direction predicted and may be an artifact of the vignette construction. Our vignettes may not have been explicit enough in their depiction of severity and thus might have allowed respondents to be misled by their pre-existing perceptions of the described illnesses. For example, participants may have underestimated the severity of the effects of asthma (high severity/low probability of mortality condition), which can have a serious impact on a child's health (Lilly, 2005). Most people may not be educated about this disease and therefore may incorrectly estimate its natural course and consequences (Coutinho-Sledge et al., 2007). In addition, images of persons with asthma depicted in the media support the public perception that this illness is not severe. In contrast, our low chronic illness severity and low probability of mortality condition was represented by an ASD, a small hole in the heart that was said not to cause any problems in the child's life. However, participants may have perceived a heart problem to be more severe than asthma, an illness that is commonly heard about in everyday life. Thus participants may have used prior knowledge of the illness when responding to survey questions. Future studies may need to describe the illnesses present in the scenarios in greater detail, or include manipulation checks of participants' perceptions of illness severity.

…our results indicate that pediatric mortality is an important factor in understanding an individual's likelihood of hiring an HCA for their chronically ill child.

Another hypothesis of the present study was that participants assigned to the high probability of mortality of a child's chronic illness condition vignette would be more likely to hire an HCA than would participants assigned to the low probability of mortality condition vignette. This hypothesis was supported. Thus our results indicate that pediatric mortality is an important factor in understanding an individual's likelihood of hiring an HCA for their chronically ill child. This finding is consistent with the literature on this topic (Levy, 1980, Newacheck and Halfon, 1986, Riley et al., 1993, Spurrier et al., 2000, Thomasgard and Metz, 1996, Woodward et al., 1988).

Participants who read the vignettes describing a child whose illness was high in the probability of mortality and low in severity reported that they would be more likely to hire an HCA than would participants who read the vignettes describing a child whose illness is high in the probability of mortality and high in severity. This interaction is consistent with our previous findings on the effects of chronic illness severity and the probability of mortality on the likelihood of hiring an HCA.

The significant effect of age lends support to previous research indicating that younger children are more likely to use child health services (Hankin et al., 1984, Newacheck and Halfon, 1986, Starfield et al., 1979, Tessler and Mechanic, 1978, Ward and Pratt, 1996). However, although we expected in general that, as the age of the child increased, the likelihood of hiring an HCA would decrease, we also examined the possibility that the effect of age on hiring an HCA might not be constant across ages, our reason for exploring the polynomial effects of age. Perhaps the likelihood of hiring an HCA decreases with age early in a child's life but disappears later. In other words, one might be more likely to hire an HCA for a 1-year-old than for a 7-year-old, but not necessarily for a 7-year-old versus a 13- year-old. In the present study the quadratic effect of age was not statistically significant; thus the effects on hiring an HCA are not the same across ages. Some research has indicated that the child's age serves as a proxy for the value placed on a child's life (Janvier et al., 2008).

Finally, our results indicated that a three-way interaction (AgeQuadratic × Severity × Mortality) was significant. Participants reported a greater likelihood of hiring an HCA for a 7-year-old child whose illness was high in severity and low in probability of mortality than for a 7-year-old child whose illness was low in severity and low in probability of mortality, and a greater likelihood of hiring an HCA for a child who was either 1 or 13 years old when the probability of mortality and severity were both low. In the low probability of mortality condition, children were characterized as having either an ASD (low severity) or asthma (high severity). Therefore it is possible that this finding is another artifact of the vignette construction; it appears that people who received the vignettes for 7-year-old children were more likely to perceive that asthma was more serious than the ASD, whereas those who received the same vignettes describing a 1-year-old or 13-year-old child did not understand or judge the severity in the intended way. Thus future researchers should better clarify the severity of the conditions within the vignettes to ensure that intended manipulations are clearly presented.

A final noteworthy finding of this study is that people are not comfortable researching treatment options for their chronically ill child.

Of the demographic and descriptive characteristics assessed in this study, four were found to be significantly correlated with the likelihood of hiring an HCA. Non-White participants, participants with fewer years of education, and participants with lower annual incomes reported being more likely to hire an HCA than were White participants, those with more years of education, and those with higher incomes. These findings may indicate that people who are ethnic minorities, are less educated, and have lower incomes do not believe that they can competently navigate the health care system. This conclusion is supported by a study by the National Cancer Policy Board, which demonstrated that low-income ethnic minority patients were less likely than White, high-income patients to receive cancer care (National Cancer Policy Board, 1999). Furthermore, a considerable amount of literature indicates that barriers to care such as a lack of education interfere with timely access to diagnosis and treatment once a screening abnormality has been identified (Lannin et al., 1998, Roetzheim et al., 1999).

A notable finding of the present study is that participants who reported a greater comprehension of the concept of an HCA also reported a greater likelihood of hiring an HCA. This finding is important because, while there is an increasing interest in health care advocacy, there is no clear consensus on what a health advocate is, or what his or her duties are. Achieving such a consensus would be a significant step forward.

A final noteworthy finding of this study is that people are not comfortable researching treatment options for their chronically ill child. The mean likelihood of hiring an HCA to research treatment options was higher for this service than for any of the other services. This finding indicates that people generally do not feel skilled enough to explore treatment options on their own and believe that they could benefit from assistance. This information is important both for the field of behavioral medicine and for treatment providers because it implies a need for improved dispersal of information and enhancement of doctor-patient interactions and indicates a possible deficit in the medical system that could be corrected by HCAs.

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Limitations and Future Directions 

A retrospective look reveals some limitations of the present study. Its convenience sample may not represent the general population. The brief description of an HCA may not have provided the participants with an adequate picture of the services an HCA could provide. Furthermore, although the use of vignette methodology allowed us to manipulate severity of chronic illness and the child's age experimentally, it is possible that participants could not relate to the hypothetical situation. Therefore, the participants' responses on the questionnaire may not be true representations of the behavior they would exhibit when presented with the situation depicted (Sutton, 1998). In future studies it would be desirable to target participants with ill children and interview them to gain a better understanding of factors that affect the likelihood of hiring an HCA.

Another limitation of this study is that the effects of severity and probability of mortality may have been contaminated by the specific diseases that were chosen to represent these constructs. To control for the effect of specific illnesses on the likelihood to hire an HCA, future studies should represent each condition with two or more different illnesses and/or include manipulation checks for severity and probability of mortality within the vignettes.

In summary, the number of medical mistakes committed daily and the impact of these mistakes on patients has catalyzed the growth of the field of health care advocacy. However, very few researchers have investigated the various advocacy services being offered to patients. Future researchers should provide and evaluate services of HCAs offered to groups of patients with specific chronic illnesses to determine their effect on both health outcomes and health care costs. Health care organizations and researchers designing health advocacy services should target the patient populations with the greatest potential to benefit from health advocacy services. It is possible that health care advocacy services will become a cost-effective approach to increased quality of care, decreased medical errors, and enhanced health outcomes.

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References 

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Elaina A. Vasserman-Stokes, Research Assistant, Department of Psychology, San Diego State University, San Diego, CA.

Terry A. Cronan, Professor, Department of Psychology, San Diego State University, San Diego, CA.

Melody S. Sadler, Assistant Professor, Department of Psychology, San Diego State University, San Diego, CA.

  • ∗ One degree of freedom polynomial contrasts were used to examine effects of child's age. This approach was preferred because it allowed a definitive test for the predicted linear effect of age that could not be ascertained from an omnibus main effect of age (Rosenthal, Rosnow, & Rubin, 2000). Judd and McClelland (2009) have shown that when a full set of orthogonal, one degree of freedom contrasts is used, the analysis will replicate the results of a 3 × 2 × 2 ANCOVA for this study (Judd & McClelland, 2009). Thus the only difference between our approach and the standard ANCOVA is that we were able to test the conceptual question of interest directly.

 Conflicts of interest: None to report.

PII: S0891-5245(10)00180-X

doi:10.1016/j.pedhc.2010.06.016

Journal of Pediatric Health Care
Volume 26, Issue 1 , Pages 27-36, January 2012

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