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Original Research: CRITICAL CARE MEDICINE |

Factors Associated With Illness Perception Among Critically Ill Patients and Surrogates FREE TO VIEW

Dee Ford, MD, MSc, FCCP; Jane Zapka, ScD; Mulugeta Gebregziabher, PhD; Chengwu Yang, MD; Katherine Sterba, PhD
Author and Funding Information

From the Division of Pulmonary and Critical Care Medicine (Dr Ford), and the Division of Biostatistics, Bioinformatics, and Epidemiology (Drs Zapka, Gebregziabher, Yang, and Sterba), Medical University of South Carolina, Charleston, SC.

Correspondence to: Dee W. Ford, MD, MSc, FCCP, Medical University of South Carolina, 96 Jonathan Lucas Dr, 812-CSB, Charleston, SC 29425; e-mail: fordd@musc.edu


Funding/Support: This study was funded by the Agency for Healthcare Research and Quality EXCEED [Grant PO11HS10871] and the South Carolina Resource Centers for Minority Aging Research.

For editorial comment see page 8

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestpubs.org/site/misc/reprints.xhtml).


© 2010 American College of Chest Physicians


Chest. 2010;138(1):59-67. doi:10.1378/chest.09-2124
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Background:  We investigated illness perceptions among critically ill patients or their surrogates in a university medical ICU using a prospective survey. We hypothesized that these would vary by demographic, personal, and clinical measures.

Methods:  Patients (n = 23) or their surrogates (n = 77) were recruited. The Illness Perception Questionnaire-Revised (IPQ-R) measured six domains of illness perception: timeline-acute/chronic, consequences, emotional impact, personal control, treatment efficacy, and illness comprehension. Multiple variable linear regression models were developed with IPQ-R scores as the outcomes.

Results:  African Americans tended to perceive the illness as less enduring and reported more confidence in treatment efficacy (P < .01 for each). They also tended to report the illness as less serious, having less emotional impact, and having greater personal control (P = .0002 for each). Conversely, African Americans reported lower illness comprehension (P = .002). Faith/religion was associated with positive illness perceptions, including less concern regarding consequences (P = .02), less emotional impact (P = .03), and more confidence in treatment efficacy (P < .01). Lower patient quality of life (QOL) precritical illness was associated with negative perceptions, including greater concern about illness duration and consequences as well as perception of less personal control and less confidence in treatment efficacy (P < .01 for each). These variables were independently associated with illness perceptions after controlling for race, faith/religion, and survival to hospital discharge, whereas clinical measures were not.

Conclusions:  Illness perceptions among critically ill patients and surrogates are influenced by patient/surrogate factors, including race, faith, and precritical illness QOL, rather than clinical measures. Clinicians should recognize the variability in illness perceptions and the possible implications for patient/surrogate communication.

Figures in this Article

The ICU is a setting where patients are seriously ill and often die.1 Patients and families are under significant duress in this environment but still must make decisions about goals and preferences of care.2 Because a majority of critically ill patients are unable to make their own decisions, surrogates are often relied on for medical decision making.3 Thus, communication between patients, families, and clinicians is particularly important in an ICU4 and decision making is clearly impacted by perceptions of prognosis and treatment options.5

Patients and families use their cognitive and emotional beliefs about an illness to “make sense” of it.6 This conceptualization is based on the self-regulatory model and key elements include: beliefs about the timeline and consequences of illness, emotional reaction to the illness, beliefs about personal control over the illness, beliefs about the efficacy of treatments, and the extent to which individuals perceive adequate comprehension of the illness.6,7 We speculated that learning about critically ill patients’ and families’ illness perceptions would provide information relevant to clinicians caring for the critically ill and is conceptually related to patient/family-centered communication strategies.8 To accomplish this we used the valid and reliable Illness Perception Questionnaire-Revised (IPQ-R),9 hypothesizing that illness perceptions would vary by select demographic, personal, and clinical variables.

Study Design and Subjects

This prospective, descriptive study was conducted in a university tertiary care medical ICU (MICU). All MICU admissions were recorded in a study log and the patients’ progress tracked prospectively. When the MICU length of stay (LOS) reached 3 days, all potential subjects were approached. Subjects were either the MICU patient or their surrogate decisionmaker. If the patient lacked capacity a surrogate was invited to participate. Because the aim of this study was to examine illness perceptions from the decision maker’s perspective, patient and surrogate responses were combined. Respondent inclusion criteria were English speaking and a length of MICU stay ≥ 3 days (median MICU LOS prior to interview = 4.5 days, interquartile range [IQR] = 3-8 days). This LOS criteria was chosen to allow time for patients/surrogates to develop perceptions of the illness. We excluded incapacitated patients who did not have an identifiable surrogate. This study was approved by our institutional review board and was granted a waiver of signed consent.

Data Sources and Measures

Data sources included electronic and paper medical records, a study tracking and recruitment log, and the patient- or surrogate-completed surveys. Data abstractors were trained in and used a standardized protocol. To assess the reliability of data abstraction we had all abstractors collect the same measures on 10% of our total sample and found the agreement between abstractors to exceed 95%. Two parallel versions of the survey were designed, one for patient respondents and one for surrogates. All eligible respondents were given a $5 gift card incentive.

Measures obtained from hospital records included the patient’s age, sex, and insurance status. Age was defined as an ordinal variable with groups based on adult developmental stages as: young adult (18-39 years), middle adult (40-64 years), late adult (65-80 years), and late late adult (> 80 years). Information collected via respondent self-report included: race, education level, marital status, and disability status. Three items related to religious affiliation and religiosity were asked.10-12

Clinical and health status measures included survival to hospital discharge and medical estimates of illness severity using Acute Physiology and Chronic Health Evaluation (APACHE) II scores.13 Additional clinical measures included primary organ failure leading to MICU admission; hospital LOS prior to MICU admission categorized as immediate, short (3-6 days), and long (≥ 7 days) hospitalizations prior to MICU admission; and total hospital LOS. Precritical illness quality of life (QOL) was measured by one survey item with five possible responses condensed into excellent/very good, good/fair, and poor.14

The primary end point was respondents’ illness perceptions as measured by the IPQ-R, which quantitatively assesses respondents’ perception of illness.9 It is a valid and reliable instrument9,15 and has been widely used in different diseases,16-21 including serious acute conditions,19 and adapted for administration to families.22-24 Questions reflect the respondent’s perceptions of the illness and questions are phrased accordingly when a surrogate as opposed to patient is the respondent. We measured six domains, including: timeline—acute/chronic (six items), consequences (six items), emotional impact (six items), personal control (six items), treatment efficacy (five items), and illness comprehension (five items). Detailed explanation of this instrument, including items, scoring, and psychometric properties, is provided in the Appendix.

Statistical Analysis

Summary statistics were calculated for all variables. Fisher exact test and Wilcoxon Rank Sum test were used to compare differences between groups. The primary analyses were based on the six IPQ-R domain scores (see Appendix). Cronbach α was calculated to assess the internal reliability of each of the six domain scores using observations with complete data (n = 84). All scores had acceptable reliability, with Cronbach α ranging from 0.75 to 0.88. Analysis of variance or Kruskal-Wallis tests were used to study the relationship between IPQ-R domain scores and the demographic, personal, clinical, and health status measures. The respondent’s (patient or surrogate) demographic and personal measures were used. The patient’s clinical measures and pre-critical illness QOL were used.

Finally, six multiple variable linear regression models were developed using stepwise selection technique with the six IPQ-R domain scores as the dependent outcome measures. Variables significant in univariate analyses were considered in each model and accepted or rejected based on statistical significance. Based on univariate significance in multiple IPQ-R domains, each regression model included race and faith/religion. Survival to hospital discharge was included in each final model because of its clinical significance. Other clinical measures, including APACHE II score, primary organ failure, and LOS measures, lacked statistical relationship with the IPQ-R outcome measures and thus were not included. Because of concern about collinearity between certain factors, the variance inflation factor was determined, with variance inflation factor < 5 as the entrance criterion. Goodness of fit of the final models and the influence of individual observations were assessed using residual analysis. Statistical significance was defined as P < .05.

Figure 1 reports participant accrual. During the study period, 126 MICU admissions were study eligible and 79% (n = 100) completed the survey. Respondents were compared with eligible nonrespondents. There were no significant differences with respect to age, sex, race, insurance, APACHE II score, primary organ failure, and LOS (data not shown).

Figure Jump LinkFigure 1. Respondent accrual. MICU = medical ICU.Grahic Jump Location

Table 1 includes all patients’ demographic and personal measures and demonstrates the heterogeneity in our patient population. These parameters did not differ when a surrogate as opposed to a patient was the respondent (data not shown).

Table Graphic Jump Location
Table 1 —Patient Demographic and Personal Measures

Values given as No. (%).

Because most of our patients lacked capacity, the majority of respondents were surrogates (77%). Table 2 reports surrogate respondents’ own demographic and personal measures. The surrogate respondents had close familial ties with the patient and had known the patient on average for 34 years.

Table Graphic Jump Location
Table 2 —Surrogate Respondents’ Demographic and Personal Measures

Values given as No. (%) unless otherwise noted. Totals may be < 77 due to nonresponse.

As shown in Table 3, our patients’ clinical measures did differ by respondent type. When a surrogate was the study respondent, the patient tended to be more seriously ill with higher APACHE II scores (P = .06), longer hospital LOS prior to MICU admission (P = .003), and a longer overall hospital LOS (P = .01).

Table Graphic Jump Location
Table 3 —Patient Clinical Measures by Respondent Type: Patient or Surrogate

Values given as No. (%) unless otherwise noted. APACHE = Acute Physiology and Chronic Health Evaluation; LOS = length of stay.

Table 4 highlights illness perceptions and pre-critical illness QOL reports by whether a patient or surrogate was the survey respondent. Only the emotional impact domain of the IPQ-R was different between the two groups (P = .01) with surrogate respondents reporting greater emotional impact as compared with patient respondents. Surrogate respondents also perceived lower precritical illness QOL than patient respondents (P = .03).

Table Graphic Jump Location
Table 4 —Illness Perceptions and Precritical Illness Quality of Life Reports Among Critically Ill Patients or Surrogates

QOL = quality of life.

a 

Higher scores represent beliefs that the illness is enduring, has serious consequences, and has a greater emotional impact.

b 

Higher scores represent positive beliefs about treatment efficacy, personal control over the illness, and belief that the illness is understood by the respondent.

Table 5 summarizes the significant univariate associations between IPQ-R domain scores and other measures. There were no differences for any domain by age, sex, insurance, education, marital status, disability status, APACHE II, or LOS.

Table Graphic Jump Location
Table 5 —Comparison of Illness Perception Questionnaire-Revised Domain Scores for Select Measures

N = 100. DK = do not know. See Table 4 for expansion of other abbreviation.

a 

Higher scores represent stronger beliefs that the illness is chronic, has negative consequences, and has a greater emotional impact.

b 

Higher scores represent positive beliefs about treatment efficacy, personal control over the illness, and belief that the illness is understood by the respondent.

Table 6 provides results of our adjusted multiple variable regression analyses. African American race was significant for five of six domains, with African Americans generally reporting more positive views of the critical illness. African Americans perceived the illness to be less enduring (P = .02) and less serious (P < .01), with lower emotional impact (P = .02), and the perception that they had greater personal control over its outcome (P = .03). Conversely, African American respondents reported lower comprehension of the illness (P = .04). Faith/religion was associated with more confidence in treatment efficacy (P = 03). Surrogate respondents reported lower comprehension of the illness (P = .03) and greater emotional impact (P < .01). Respondents reporting poor patient precritical illness QOL had more pessimistic views of the illness perceiving it to be more chronic (P < .01) and having less confidence in treatment efficacy (P = .01). Respondents for patients who died did perceive the illness to have more serious consequences (P = .05).

Table Graphic Jump Location
Table 6 —Multivariable Models for Association With Variations in Illness Perceptions

See Table 4 for expansion of abbreviation.

a 

Each model included race, faith, and survival to hospital discharge. APACHE II scores did not affect the models and were, therefore, not included.

b 

β = regression coefficient/effect size.

c 

Reference category = African American.

d 

Reference category = poor.

e 

Reference category = alive.

f 

Reference category = surrogate.

g 

Reference category = strongly disagree/disagree.

This work offers insight into several important issues in critical care medicine and to our knowledge is the first description of illness perceptions within a population of critically ill patients and their surrogates. A pervasive and important finding that has not been previously reported is the impact African American race has on illness perceptions, with African Americans being more optimistic than whites on five of six domains of illness perception even after adjusting for faith/religion. Others have found African American race to be associated with preferences for more aggressive care and with greater reluctance to withdraw artificial life support.25-27 Reasons commonly cited for this include mistrust of the health-care system and greater faith/religiosity among African Americans,27 yet there is limited empirical literature on the topic despite compelling data that race/ethnicity significantly influences the course of medical care in the United States.28 Our findings suggest African Americans may have differences in preferences in part because they believe outcomes are more likely to be favorable. However, in conjunction with these generally positive perceptions, African Americans felt they had less understanding of the illness, raising concerns about effective communication.5,29 Of note, our findings contrast with others’ in that lower self-reported illness comprehension among African American respondents was not accompanied by greater emotional impact, which may indicate an adaptive response to health threats among our respondents.30 We do not have data on the influence of race other than African American and note there is often variability within a group. Thus, we caution readers against using these findings to generalize to individuals.

Activity in faith/church was independently associated with belief in treatment efficacy. It has been shown that patients place greater emphasis on faith/religion in health decision making than physicians, particularly at the end of life.31-34 Other recent work demonstrated that faith/religion-based coping among patients with advanced cancer was associated with increased use of life-prolonging treatments prior to death.35 One hypothesis our data supports is that faith/religion may result in more confidence in treatment efficacy and thus preferences for more aggressive care. A caveat, however, is that our respondents reported primarily evangelical Christian faith and thus our observations may not apply to individuals from other faith backgrounds.

Surrogate respondents reported higher emotional impact and lower illness comprehension as compared with patient respondents. The greater emotional impact may be because of the higher illness severity among patients when a surrogate was the survey respondent, related to the stress of serving as a patient surrogate, or other unidentified factors. The association between emotional distress and poor understanding of prognosis and treatment options has been reported elsewhere and is likewise associated with adverse psychologic outcomes among families of deceased ICU patients.5,29 Conversely, others have found that satisfaction with communication was higher among families of patients who died as opposed to survived an ICU admission,36 although we did not assess quality of communication.

It is not surprising that respondents reporting a lower patient precritical illness QOL had more negative illness perceptions. Although there are discrepancies between patient’s reports and surrogate’s reports around patient QOL,37,38 it is informative to characterize how the health decision maker—whether patient or surrogate—perceives QOL and the impact this has on overall illness perceptions as we have done.

The illness perception domains we measured reflect personal beliefs about the illness. Interestingly, clinical measures of illness severity were not generally predictive of illness perceptions. Precursors to illness perceptions include a variety of factors, such as previous illness experiences, information from multiple sources, and sociocultural and personality factors. It follows that illness beliefs may or may not be associated with clinical markers of illness. There is very little known about the illness beliefs of a critically ill population and future investigation should explore mechanisms underlying illness perceptions in this population.

We acknowledge several limitations of this study. Although the sample is heterogeneous with respect to age, sex, race, and markers of socioeconomic status, it is relatively small, and was conducted at one southeastern academic medical center and therefore may not be generalizable. We used stepwise regression analyses to identify the independent contributions of certain variables but this should be considered exploratory and future investigation should prospectively confirm these findings and identify additional factors associated with illness perception. There is also the possibility that our statistical techniques were unable to fully account for interactions between related factors. Investigation of decision making in the ICU is particularly challenging because of the role of surrogates; there was an unavoidable reliance on patient surrogates rather than direct patient reports, and we did not use a specific test for capacity among patients. This is a reality in day-to-day practice in the ICU, so a better understanding of perceptions and preferences needs further exploration and future investigation should consider pairing patients’ and surrogates’ reports of illness perceptions to ascertain whether these reports are congruent. Finally, in this relatively new area of scientific investigation, the limits of construct and content validity of instruments should be kept in mind, although we did find adequate internal consistency reliability and construct validity for the IPQ-R in our population (see Appendix).

This study has many strengths. Using a systematic approach to consecutive respondent recruitment, we were able to achieve a good response rate with participant diversity on major demographic and socioeconomic measures. Our nonrespondents were not different from respondents. To our knowledge, this study represents the first report explicitly eliciting patients’ and families’ perceptions of critical illness.

These findings should provide a cautionary note to providers and suggest that patient- and surrogate-specific factors—in our case race, faith, surrogate decision-maker, and perceived precritical illness QOL—more directly influence patient’s and surrogate’s perceptions of illness than do conventional clinical parameters. Whether this is due to inadequate communication, too little time for mental processing, or other unmeasured factors, we cannot address. Clinicians should inquire about patient’s and surrogate’s illness perceptions when embarking on discussions around prognosis and goals of care. Inaccurate perceptions can be addressed and other beliefs can be taken into account with respect to communication and planning. Our study lends further credence to the importance of eliciting the patient/family perspective as part of the overall clinical discourse.4,39-42

In this study we found that African American race, faith/religion, surrogate respondent, and precritical illness QOL were independent determinants of illness perception in an MICU. These data support other calls for more attention to eliciting patient and family perspectives as well as emphasizing the importance of exploring patient and family background and values in health decision making.

Appendix

The IPQ-R assesses the following nine domains of illness perceptions: Identity (the symptoms involved with having the illness), Cause (ideas about what caused the illness), Timeline—Acute/Chronic (beliefs about how long the illness will last), Timeline Cyclical (beliefs about the unpredictability of the illness symptoms or cyclic nature of illness), Consequences (the expected effects of the illness), Personal Control (the extent to which an individual has control over illness), Treatment Control (beliefs about treatment efficacy), Emotions (the emotional reactions to illness), and Illness Comprehension (extent to which an individual has a clear understanding of illness).9 In the current study, we present six of these subscales from a critical care setting. We omitted three domains, including symptoms, cause, and timeline-cyclical to reduce respondent burden.

Respondents indicated the extent to which they agreed or disagreed with each statement (1 = Strongly Disagree, 2 = Disagree, 3 = Neither Agree nor Disagree, 4 = Agree, 5 = Strongly Agree). The domain scores are calculated as the mean of the item scores within each of the domains. Certain items require reverse scoring to account for negative vs positive phrasing of item stems. High scores on the timeline, consequences, and emotional impact domain represent stronger beliefs that the illness is chronic and recurring, has negative consequences, and has a greater emotional impact. Conversely, high scores on the personal control, treatment efficacy, and illness comprehension domain represent positive beliefs about personal control and treatment efficacy over the illness and respondents’ beliefs that they understand the illness.

Items are listed below by subscale with the Cronbach α for each subscale. A preliminary exploration of construct validity is also discussed below.

Timeline Acute/Chronic (α = 0.85)

My illness will last a short time.

My illness is likely to be permanent rather than temporary.

My illness will last a long time.

This illness will pass quickly.

I expect to have this illness for the rest of my life.

My illness will improve in time.

Consequences (α = 0.80)

My illness is a serious condition.

My illness has major consequences on my life.

My illness does not have much effect on my life.

My illness strongly affects the way others see me.

My illness has serious financial consequences.

My illness causes difficulties for those who are close to me.

Personal Control (α = 0.75)

There is a lot that I can do to control my symptoms.

What I do can determine whether my illness gets better or worse.

The course of my illness depends on me.

Nothing I do will affect my illness.

I have the power to influence my illness.

My actions will have no effect on the outcome of my illness.

Treatment Control (α = 0.82)

There is very little that can be done to improve my illness.

My treatment will be effective in curing my illness.

The negative effects of my illness can be prevented (avoided) by my treatment.

My treatment can control my illness.

There is nothing that can help my condition.

Emotional Representations (α = 0.82)

I get depressed when I think about my illness.

When I think about my illness I get upset.

My illness makes me feel angry.

My illness does not worry me.

Having this illness makes me feel anxious.

My illness makes me feel afraid.

Illness Coherence (α = 0.88)

The symptoms of my condition are puzzling to me.

My illness is a mystery to me.

I don’t understand my illness.

My illness doesn’t make any sense to me.

I have a clear picture or understanding of my condition.

Internal Consistency Reliability

We calculated Cronbach α to assess the internal reliability of each of the six subscale scores using observations with complete data (n = 84). All of the scores had at least adequate internal reliability, with Cronbach α ranging from 0.75 to 0.88.

Construct Validity

We explored the construct validity of the IPQ-R in the critical care setting by examining the relationships between each IPQ-R subscale and a variety of illness variables. We also examined the intercorrelations between each of the IPQ-R subscales using Pearson correlations.

The six IPQ-R domains were structurally organized as expected in this study; most optimistic and pessimistic beliefs were associated with one another, respectively. For example, stronger belief about one’s personal control over the illness was associated with believing the illness had a shorter timeline (r = −0.43, P < .0001), better treatment efficacy (r = 0.56, P < .0001), and having fewer emotions associated with the illness (r = −0.23, P = .03). In addition, having stronger emotional impact from the illness was associated with believing it was more permanent (r = 0.35, P = .0005), having less comprehension of the illness (r = −0.22, P = .03), and having lower confidence in treatment efficacy (r = −0.28, P = .006).

Author contributions:Dr Ford: contributed to designing and conducting this research and writing the manuscript.

Dr Zapka: contributed to designing and conducting this research and writing the manuscript.

Dr Gebregziabher: contributed to data management, statistical analyses, and writing the manuscript.

Dr Yang: contributed to data management, statistical analyses, and writing the manuscript.

Dr Sterba: contributed to validation reporting for the IPQ-R, design of the Appendix, and writing the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: The findings reported here are those of the authors and do not necessarily represent the views of Agency for Healthcare Research and Quality or the South Carolina Resource Centers for Minority Aging Research.

Other contributions: We thank the following individuals at the Medical University of South Carolina for their assistance: Lisa Johnson, BS, for project management; Ester Williams-Cummings and Winnie Hennessy, RN, PhD, for assistance with subject recruitment and data collection; Wenle Zhao, PhD, for data management; and Suzanne Simkovich, MA, for preparation of tables and figures.

APACHE

Acute Physiology and Chronic Health Evaluation

IPQ-R

Illness Perception Questionnaire-Revised

IQR

interquartile range

LOS

length of stay

MICU

medical ICU

QOL

quality of life

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King DE, Wells BJ. End-of-life issues and spiritual histories. South Med J. 2003;964:391-393. [CrossRef] [PubMed]
 
Steinhauser KE, Christakis NA, Clipp EC, McNeilly M, McIntyre L, Tulsky JA. Factors considered important at the end of life by patients, family, physicians, and other care providers. JAMA. 2000;28419:2476-2482. [CrossRef] [PubMed]
 
Steinhauser KE, Clipp EC, McNeilly M, Christakis NA, McIntyre LM, Tulsky JA. In search of a good death: observations of patients, families, and providers. Ann Intern Med. 2000;13210:825-832. [PubMed]
 
Phelps AC, Maciejewski PK, Nilsson M, et al. Religious coping and use of intensive life-prolonging care near death in patients with advanced cancer. JAMA. 2009;30111:1140-1147. [CrossRef] [PubMed]
 
Wall RJ, Curtis JR, Cooke CR, et al. Family satisfaction in the ICU. Differences between families of survivors and nonsurvivors. Chest. 2007;1325:1425-1433. [CrossRef] [PubMed]
 
Scales DC, Tansey CM, Matte A, Herridge MS. Difference in reported pre-morbid health-related quality of life between ARDS survivors and their substitute decision makers. Intensive Care Med. 2006;3211:1826-1831. [CrossRef] [PubMed]
 
Hofhuis J, Hautvast JL, Schrijvers AJ, Bakker J. Quality of life on admission to the intensive care: can we query the relatives? Intensive Care Med. 2003;296:974-979. [PubMed]
 
Curtis JR, Engelberg RA, Wenrich MD, Shannon SE, Treece PD, Rubenfeld GD. Missed opportunities during family conferences about end-of-life care in the intensive care unit. Am J Respir Crit Care Med. 2005;1718:844-849. [CrossRef] [PubMed]
 
McDonagh JR, Elliott TB, Engelberg RA, et al. Family satisfaction with family conferences about end-of-life care in the intensive care unit: increased proportion of family speech is associated with increased satisfaction. Crit Care Med. 2004;327:1484-1488. [CrossRef] [PubMed]
 
Stapleton RD, Engelberg RA, Wenrich MD, Goss CH, Curtis JR. Clinician statements and family satisfaction with family conferences in the intensive care unit. Crit Care Med. 2006;346:1679-1685. [CrossRef] [PubMed]
 
White DB, Braddock CH III, Bereknyei S, Curtis JR. Toward shared decision making at the end of life in intensive care units: opportunities for improvement. Arch Intern Med. 2007;1675:461-467. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1. Respondent accrual. MICU = medical ICU.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Patient Demographic and Personal Measures

Values given as No. (%).

Table Graphic Jump Location
Table 2 —Surrogate Respondents’ Demographic and Personal Measures

Values given as No. (%) unless otherwise noted. Totals may be < 77 due to nonresponse.

Table Graphic Jump Location
Table 3 —Patient Clinical Measures by Respondent Type: Patient or Surrogate

Values given as No. (%) unless otherwise noted. APACHE = Acute Physiology and Chronic Health Evaluation; LOS = length of stay.

Table Graphic Jump Location
Table 4 —Illness Perceptions and Precritical Illness Quality of Life Reports Among Critically Ill Patients or Surrogates

QOL = quality of life.

a 

Higher scores represent beliefs that the illness is enduring, has serious consequences, and has a greater emotional impact.

b 

Higher scores represent positive beliefs about treatment efficacy, personal control over the illness, and belief that the illness is understood by the respondent.

Table Graphic Jump Location
Table 5 —Comparison of Illness Perception Questionnaire-Revised Domain Scores for Select Measures

N = 100. DK = do not know. See Table 4 for expansion of other abbreviation.

a 

Higher scores represent stronger beliefs that the illness is chronic, has negative consequences, and has a greater emotional impact.

b 

Higher scores represent positive beliefs about treatment efficacy, personal control over the illness, and belief that the illness is understood by the respondent.

Table Graphic Jump Location
Table 6 —Multivariable Models for Association With Variations in Illness Perceptions

See Table 4 for expansion of abbreviation.

a 

Each model included race, faith, and survival to hospital discharge. APACHE II scores did not affect the models and were, therefore, not included.

b 

β = regression coefficient/effect size.

c 

Reference category = African American.

d 

Reference category = poor.

e 

Reference category = alive.

f 

Reference category = surrogate.

g 

Reference category = strongly disagree/disagree.

References

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King DE, Wells BJ. End-of-life issues and spiritual histories. South Med J. 2003;964:391-393. [CrossRef] [PubMed]
 
Steinhauser KE, Christakis NA, Clipp EC, McNeilly M, McIntyre L, Tulsky JA. Factors considered important at the end of life by patients, family, physicians, and other care providers. JAMA. 2000;28419:2476-2482. [CrossRef] [PubMed]
 
Steinhauser KE, Clipp EC, McNeilly M, Christakis NA, McIntyre LM, Tulsky JA. In search of a good death: observations of patients, families, and providers. Ann Intern Med. 2000;13210:825-832. [PubMed]
 
Phelps AC, Maciejewski PK, Nilsson M, et al. Religious coping and use of intensive life-prolonging care near death in patients with advanced cancer. JAMA. 2009;30111:1140-1147. [CrossRef] [PubMed]
 
Wall RJ, Curtis JR, Cooke CR, et al. Family satisfaction in the ICU. Differences between families of survivors and nonsurvivors. Chest. 2007;1325:1425-1433. [CrossRef] [PubMed]
 
Scales DC, Tansey CM, Matte A, Herridge MS. Difference in reported pre-morbid health-related quality of life between ARDS survivors and their substitute decision makers. Intensive Care Med. 2006;3211:1826-1831. [CrossRef] [PubMed]
 
Hofhuis J, Hautvast JL, Schrijvers AJ, Bakker J. Quality of life on admission to the intensive care: can we query the relatives? Intensive Care Med. 2003;296:974-979. [PubMed]
 
Curtis JR, Engelberg RA, Wenrich MD, Shannon SE, Treece PD, Rubenfeld GD. Missed opportunities during family conferences about end-of-life care in the intensive care unit. Am J Respir Crit Care Med. 2005;1718:844-849. [CrossRef] [PubMed]
 
McDonagh JR, Elliott TB, Engelberg RA, et al. Family satisfaction with family conferences about end-of-life care in the intensive care unit: increased proportion of family speech is associated with increased satisfaction. Crit Care Med. 2004;327:1484-1488. [CrossRef] [PubMed]
 
Stapleton RD, Engelberg RA, Wenrich MD, Goss CH, Curtis JR. Clinician statements and family satisfaction with family conferences in the intensive care unit. Crit Care Med. 2006;346:1679-1685. [CrossRef] [PubMed]
 
White DB, Braddock CH III, Bereknyei S, Curtis JR. Toward shared decision making at the end of life in intensive care units: opportunities for improvement. Arch Intern Med. 2007;1675:461-467. [CrossRef] [PubMed]
 
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