Humanities
Grand Canyon University Health Related Quality of Life Questions Discussions

Grand Canyon University

Question Description

Help me study for my Psychology class. I’m stuck and don’t understand.

Question 1 - Examine the difference between quality of life and health related quality of life. Why is it important for health psychologists to understand the difference between the terms? Support your answer with scholarly sources. Cite two sources/references supporting your post

https://www.liebertpub.com/doi/10.1089/pop.2015.01... - source

Question 2 - Explore the website Healthy People 2020 and Health Related Quality of Life (HRQoL). What are some of the ways that HRQoL can be measured? How are these research statistics helpful in evaluating an individual’s quality of life?

https://www.healthypeople.gov/ source

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Health-Related Quality of Life Measurement in Oncology Advances and Opportunities This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. David Cella Arthur A. Stone The concept of health-related quality of life has a long history in the field of oncology treatment and research. We present a brief history of how the concept has evolved in oncology and the sentinel events in that process. We then focus on advances in measurement science as applied to health-related quality of life measures and argue that a compelling new set of measurement tools is now available, including brief, generic measures with good psychometric qualities (exemplified by the new PROMIS measures and the possibility of a common metric spanning all diseases). The last section of the paper turns to emerging opportunities for these measures, including in clinical trials, healthcare reform, and regulatory deliberations. Our conclusion is that health-related quality of life is more important today than it has ever been, and that the time has come for an even wider adoption of the new measures. Keywords: quality of life, health-related quality of life, cancer H ealth-related quality of life (HRQL) has never been more relevant than it is today, across healthcare generally and in oncology, specifically. What began in the 1980s as a small movement of advocates for measuring symptoms, function, and well-being in clinical trials has expanded into widespread inclusion of the patient’s perspective on treatment efficacy, safety, and shared decision-making. The concept of HRQL is broad, encompassing disease symptoms, treatment side effects, functional status in physical, mental and social domains, and general perceptions of well-being and life satisfaction (Cella, 1994; 2000; Cella & Tulsky, 1993; Gandek, Sinclair, Kosinski, & Ware, 2004; McHorney, 1999; Taylor, 2000). Some (e.g., Wilson & Cleary, 1995) have proposed a more or less “linear” conceptual framework in which HRQL is a distal and rather general perception of life quality as influenced by disease symptoms, treatment side effects, and functional limitations. Others (e.g., O’Boyle, 1994) have emphasized the essential individuality of the concept, but the majority of HRQL measures in use in oncology and elsewhere frame HRQL as a multidimensional concept inclusive of common symptoms, treatment side effects, functioning, and general perceptions of health and well-being (Aaronson et al., 1993; Anderson et al., 1996; Cella, 1994; Cella et al., 1993; Patrick & Erickson, 1988). HRQL is subjective and, therefore, best assessed February–March 2015 ● American Psychologist © 2015 American Psychological Association 0003-066X/15/$12.00 Vol. 70, No. 2, 175–185 http://dx.doi.org/10.1037/a0037821 Northwestern University University of Southern California using direct query of the individual (i.e., self-report). A related term, used with increasing frequency in the past several years, is “patient-reported outcomes” or PROs. PRO is a broader term that includes reports of behaviors, experiences and activities obtained directly from patients. Most PROs measure components of HRQL (such as symptoms), but some address concepts generally considered to be outside the range of HRQL (such as treatment adherence, tobacco use, and other health behaviors). In this article, we focus on HRQL measurement. Asking patients to report on their physical health, mental health, and functional ability has become an integral part of health surveillance (e.g., Hennessey, Moriarty, Zack, Scherr, & Brackbill, 1994) and outcome science (e.g., Conn, Hafdahl, Porock, McDaniel, & Nielsen, 2006). Many HRQL instruments are considered valid measures of health service needs and intervention outcomes. For example, the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36 [a.k.a. RAND-36]; Hays, Sherbourne, & Mazel, 1993; Ware & Sherbourne, 1992) and the Functional Assessment of Chronic Illness Therapy (FACIT) measurement system (Cella, 2000) have been employed in numerous studies. Self-rated health has also demonstrated to be a more powerful predictor of mortality and morbidity than many objective measures of health (Chase et al., 2012; Dominick, Ahern, Gold, & Heller, Editor’s note. This article is one of 13 in the “Cancer and Psychology” special issue of the American Psychologist (February–March 2015). Paige Green McDonald, Jerry Suls, and Russell Glasgow provided the scholarly lead for the special issue. Authors’ note. David Cella, Department of Medical Social Sciences, Northwestern University; Arthur A. Stone, Department of Psychology, University of Southern California. David Cella is President of FACIT.org and has held research grants and consults on patient reported outcomes to multiple pharmaceutical companies, the National Committee on Quality Assurance, and the National Quality Forum. Arthur A. Stone is a senior scientist with the Gallup Organization and is a consultant with ERT, Inc., and Johnson and Johnson, Inc. Support for the writing of this paper was from National Institute of Arthritis, Musculoskeletal and Skin Diseases (NIAMS) Grants U54AR057951 (David Cella) and U01AR057948-01 (Arthur A. Stone). Correspondence concerning this article should be addressed to David Cella, Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, 633 N. St. Clair - 19th Floor, Chicago, IL 60611. E-mail: d-cella@northwestern.edu 175 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. A Brief History of Oncology HRQL Measurement: From Generic to Cancer-Specific and Back Again David Cella 2002; DeSalvo, Bloser, Reynolds, He, & Muntner, 2006; Eton et al., 2003; Gotay et al., 2008; Sloan et al., 2012). The inclusion of HRQL measures in medical studies has allowed researchers to demonstrate the impact of disease and treatment on people’s lives. We discuss the current state of HRQL research and applications in oncology on two levels: advances in measurement and methods and opportunities afforded by the current treatment, research, and reimbursement landscape. This is preceded by a brief history of HRQL assessment in oncology. In the concluding section we discuss threats to the high impact potential of HRQL assessment in oncology today. Through this exposition, we discuss the role of the National Institutes of Health (NIH) Common Fund initiative known as the PatientReported Outcomes Measurement System (PROMIS). The focus on PROMIS is not meant to minimize the significant impact that more established HRQL measures in oncology, such as the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (Aaronson et al., 1993; Anderson et al., 1996), the SF-36 (Ware & Sherbourne, 1992), the Functional Assessment of Cancer Therapy (FACT; Cella et al., 1993), and FACIT (Cella, 2000), have had upon cancer research. Rather, we suggest that these instruments can be linked to one another in areas where they are measuring highly similar concepts. For example, the widely used FACIT-Fatigue has been statistically linked to the PROMIS Fatigue item bank, enabling one to administer one and report scores on the other metric (Lai et al., 2014). In addition, PROMIS is a model for mixed qualitative and quantitative measurement principles applied to building high-performance HRQL tools for clinical research and practice evaluation (Cella et al., 2010; DeWalt et al., 2007; Reeve et al., 2007). 176 Prior to 1980, the measurement of HRQL in oncology was rare. Cure was the goal and extending survival time was a superordinate value. Treatment toxicity, often unbearable, was justified in service of the greater goal. Incremental, but somewhat limited success, with multiagent chemotherapy in the 1970s and 1980s led to an increasing demand to better appreciate quality of life alongside mere quantity of life, particularly in advanced cancer where gains were modest and toxicity was not easily tolerated. During that time, available HRQL instruments had been developed for use in mental health populations, chronic illness populations, or general medical outpatients. These early HRQL assessments were not designed specifically for people with cancer. In chronic illnesses and general medical patients, effective management of subjective constructs such as fatigue, pain, and negative affect were certainly valued, but measuring them formally was not typically regarded as useful. For example, the Sickness Impact Profile (Bergner, Bobbitt, Carter, & Gilson, 1981), measured a wide array of symptoms and functional effects of various chronic illnesses. It was comprehensive, with 136 items, but its length was also a liability in the cancer research setting, especially as it did not capture many important issues. Similarly, the Medical Outcomes Study had developed a comprehensive battery of questions regarding physical and mental health, including self-reported functioning and health. Although subsequently shortened to the now-familiar SF-36 in the early 1990s, early versions of the Medical Outcomes Study instrument were long and not specific to particular diseases in their content, as they were designed for general medical ambulatory care and population health evaluation. Although such assessments of general HRQL could be applied to cancer patients, these assessments, despite their length, lacked coverage of many of the important symptoms and concerns of people with cancer, and were, therefore, scored in ways that risked misunderstanding of the overall HRQL of the individual assessed. These early instruments were labeled as generic, and in some cases psychiatric, to indicate their non-specificity with regard to cancer (or other diseases). In the early 1980s, in response to the perceived inadequacies of the generic instruments (Patrick & Erickson, 1988), cancer-specific HRQL measures emerged (Ferrans & Powers, 1992; Schipper, Clinch, McMurray, & Levitt, 1984), and these were later eclipsed by the EORTC and FACT approaches (Aaronson et al., 1993; Anderson et al., 1996; Cella et al., 1993; Cella, 2000). All of these instruments, in particular the EORTC and FACT, were developed to ensure that their content was meaningful to people with cancer. In the case of the FACT questionnaires, this meant that a minimum of 15 cancer patients per disease site were interviewed regarding the most important quality of life issues relevant to their lives as they went through treatment for their particular diagnosis. This “empirical” approach—treating the patient as the primary source of February–March 2015 ● American Psychologist This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Arthur A. Stone information regarding content validity when it came to HRQL—foreshadowed subsequent “qualitative” practices of the PROMIS Cooperative Group (see www.nihpromis .org; Buysse et al., 2010; Cella et al., 2010; Cella, Yount, et al., 2007; Fries, Cella, Rose, Krishnan, & Bruce, 2009; Pilkonis et al., 2011; Revicki et al., 2009), guidance from the United States Food and Drug Administration (FDA) and, more recently, the Patient Centered Outcomes Research Institute (PCORI; Clancy & Collins, 2010). Research in the 1990s indicated the superiority of these cancer-specific measures when compared to the earlier versions of generic instruments. Several studies illustrated that cancer-specific tools were perceived by patients and cancer professionals as having more relevant content, including common cancer symptoms and side effects (e.g., Aaronson et al., 1993; Cella et al., 1993). Compared to their generic predecessors, these cancer-specific tools tended to be more responsive to change in clinical anchors such as tumor response, disease progression, and performance status. This was in part due to their more targeted coverage of content, and in part because they tended to ask more specific questions about symptoms or functional challenges facing cancer patients. As a rule, in classical evaluations of test performance, asking more questions about a particular concept will reduce error in the measure and contribute to reliability. Asking more of the right questions will contribute to better validity. Classic generic questionnaires used “as-is” did not fare well in this context. They were designed to be general in coverage, capturing important wide-ranging symptoms, function, and health perceptions across an array of people, often people with and without diseases or health problems. They were relatively brief but, therefore, coarse measures of these common health concerns. Still, recognition of the value of available February–March 2015 ● American Psychologist generic options such as the SF-36 questionnaire (Ware & Sherbourne, 1992), led some to recommend “. . . use of a core instrument . . . to assess the basic dimensions of QOL in a generic manner and a disease- or treatment-specific module dictated by the nature and objectives of the trial” (Nayfield, Ganz, Moinpour, Cella, & Hailey, 1992, p. 20). At the same time that the field was favoring cancerspecific over generic HRQL measures, a new generation of generic measures, exemplified by the NIH Common Fund’s PROMIS initiative, was emerging. This new generation would not be encumbered by the limitations of short, coarse “first-generation” generic measures. Unlike the static (a set of fixed items for all respondents) measures of common health concerns such as pain, fatigue, depression, anxiety, sleep disturbance, and physical, mental or social functioning, this new generation of dynamic (flexible item content) measures would, in theory, compete with cancerspecific measures for their relevance and accuracy (precision). This new generation of measures, developed with mixed qualitative and quantitative methods (described in the Instrument Development and Validation section), promised to reduce assessment burden while maintaining (or even sometimes improving) precision. As a consequence of its generic approach, these measures also promised to enable comparison of results across trials of different types of cancer and even across different chronic diseases, providing a comprehensive way to discuss HRQL. Advances Advances in measurement over the past 30 years have enabled us to meet the challenge of efficient measurement of generic concepts in a variety of chronic disease, including cancer. The advances include (a) the application of modern item response theory (IRT) methods, including advances in analytic sophistication behind the testing of assumptions necessary for appropriate application of IRT methods (e.g., confirmatory factor analysis; the bifactor model), instrument linking and equating, and improved IRT analysis software; and (b) the unprecedented sophistication in the application of technology to capture information from patients, including Web-based assessment, portable device (e.g., smart phone) applications that engage patients in the assessment, and methods of real-time data capture such as experience sampling and ecological momentary assessment. Over the past decade, PROMIS investigators have stood on the shoulders of these and other advances in mixed methods of HRQL instrument development, validation, and application across many chronic conditions, including cancer. “Modern” Psychometrics Enabled by the application of IRT models drawn from a rich history in educational and personality assessment, HRQL measurement entered the 21st century with a new agenda, to return to generic assessment of common concepts known to be important to patients, using qualitative methods to ensure relevance, clarity, and comprehension and IRT psychometric and test administration methods to 177 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. ensure accuracy and brevity. IRT, first developed by Lord (1952, 1980), Rasch (1960), Birnbaum (1968), and others, extends and eclipses traditional psychometric theory. A foundational concept for IRT is the notion that items have various qualities that can be used to optimize the precision of an assessment. Items are characterized in terms of their unique ability to inform the concept of interest at a given severity level. Thus, some items may be excellent at discriminating amongst low levels of depressed mood, for example, such as an item like “I sometimes feel sad,” whereas others items may be able to discriminate among high levels of depressed mood such as “I often wish I were dead.” The point is that IRT methods attempt to utilize items that are tailored to the symptom (or whatever construct is in question) level of an individual, providing an extremely efficient method for generating precise, yet brief, tests. Prior to developing a computerized adaptive test (CAT) that selects appropriate items for individuals, based on responses to previous items, a well-characterized set of items with known information functions (an item bank) needs to be developed (Reeve, 2006; Reeve et al., 2007). These methods are familiar to anyone who has taken standardized, computer-administered achievement tests, where “easy” items are eschewed in favor of more difficult ones, relative to a rolling estimate of the respondent’s ability level. Instrument Development and Validation In this setting, “mixed methods” refers to the combining of qualitative and quantitative methods to develop relevant, accurate, and meaningful assessments of HRQL (Creswell, 2009). The qualitative component emphasizes patient engagement surrounding the elicitation of relevant content, achieving clarity in presentation of the question context (e.g., recall period), content wording, and choice of responses (Eremenco, Cella, & Arnold, 2005; Koller et al., 2012). This can be accomplished through the use of focus groups, individual content elicitation interviews, cognitive debriefing interviews, and patient surveys (Castel et al., 2008; Christodoulou, Junghaenel, DeWalt, Rothrock, & Stone, 2008; DeWalt et al., 2007). Iterative revisions to item wording, with concurrent input from expert clinicians regarding content, linguists regarding translatability into languages other than English, and literacy experts or programs regarding reading level, all help to create clear, simple questions about important content, such as pain, fatigue, depression, anxiety, sleep, physical function, and social function. Once developed, these measures can be administered to large samples of people to evaluate their relationship to one another and how their common relationship to an underlying dimension or “latent trait” can be exploited in subsequent tests of that latent trait in other people (Reeve et al., 2007). Measurement Efficiency Measurement efficiency refers to the number of questions needed to obtain a sufficiently reliable score estimate. When assessing individuals, very high reliability is needed (Reeve et al., 2007). Until recently, individual assessment 178 was only feasible with fixed-form tests that possessed very high reliability (e.g., those with internal consistency above 0.90). Most fixed-form (static) scales do not have this degree of reliability (Donaldson, 2008); those that do tend to be long (e.g., 10 or more questions measuring the same domain). IRT models and their applications (e.g., CA ...
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Running head: HEALTH RELATED QUALITY OF LIFE

Health related quality of life
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HEALTH RELATED QUALITY OF LIFE

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Question 1
There is a difference between quality of life and the health related quality of life. Quality
of life is the overall wellbeing of individuals and societies, outlining positive and negative
aspects of life. It observes satisfaction life comprising everything from physical wellbeing,
education, family, employment, wealth, and safety to freedom, security, religious views and the
surrounding (Cella and Stone, 2015). On the other hand, health related quality of life is a concept
that covers just those aspects that are part of a person’s health. HRQoL has a concentration on
the consequences of sicknesses and part...

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