Reflections on changeability versus stability of health-related quality of life: distinguishing between its environmental and genetic components

The field of health-related quality of life (HRQOL) could benefit from a broadening of perspectives to include recent advancements in research on adaptation, positive psychology, and genetics. These advances shed new light on the extent to which HRQOL is changeable or fixed. The objective of this paper is to integrate these insights and to discuss their implications for HRQOL research. We describe the Hedonic Treadmill theory, which asserts that positive events only temporarily affect happiness since people quickly return to hedonic neutrality. New empirical evidence suggests important revisions of this theory, providing a more optimistic picture of the possibility for change. Advances in positive psychology show that relatively simple interventions have the power to induce a sustainable increase in levels of happiness. Finally, a small but growing number of studies have found independent genetic influences in well-being, life satisfaction, perceived health, and even HRQOL. Given the increasing empirical evidence that HRQOL can be sustainably enhanced and is in part genetically determined, it may be useful to consider HRQOL as a concept that has state (environmental) and trait (genetic) components. This distinction will allow us to explore new pathways of improving theory, methods, and clinical practice. The overarching novel questions concern the extent to which HRQOL components are environmentally or genetically determined, and which factors lead to lasting improvement. This distinction begs for new research approaches, such as time-sampling techniques and interdisciplinary research investigating the genetic variants of HRQOL. Distinguishing between those aspects that are amenable to change from those that are relatively fixed and stable will help better target specific support interventions

Responsiveness: a reinvention of the wheel?

BACKGROUND: Since the mid eighties, responsiveness is considered to be a separate property of health status questionnaires distinct from reliability and validity. The aim of the study was to assess the strength of the relationship between internal consistency reliability, referring to an instrument's sensitivity to differences in health status among subjects at one point in time, and responsiveness referring to sensitivity to health status changes over time. METHODS: We used three different datasets comprising the scores of patients on the Barthel, the SIP and the GO-QoL instruments at two points in time. The internal consistency was reduced stepwise by removing the item that contributed most to a scale's reliability. We calculated the responsiveness expressed by the Standardized Response Mean (SRM) on each set of remaining items. The strength of the relationship between the thus obtained internal consistency coefficients and SRMs was quantified by Spearman rank correlation coefficients. RESULTS: Strong to perfect correlations (0.90 – 1.00) was found between internal consistency coefficients and SRMs for all instruments indicating, that the two can be used interchangeably. CONCLUSION: The results contradict the conviction that responsiveness is a separate psychometric property. The internal consistency coefficient adequately reflects an instrument's potential sensitivity to changes over time

The Establishment of the GENEQOL Consortium to Investigate the Genetic Disposition of Patient-Reported Quality-of-Life Outcomes

To our knowledge, no comprehensive, interdisciplinary initiatives have been taken to examine the role of genetic variants on patient-reported quality-of-life outcomes. The overall objective of this paper is to describe the establishment of an international and interdisciplinary consortium, the GENEQOL Consortium, which intends to investigate the genetic disposition of patient-reported quality-of-life outcomes. We have identified five primary patient-reported quality-of-life outcomes as initial targets: negative psychological affect, positive psychological affect, self-rated physical health, pain, and fatigue. The first tangible objective of the GENEQOL Consortium is to develop a list of potential biological pathways, genes and genetic variants involved in these quality-of-life outcomes, by reviewing current genetic knowledge. The second objective is to design a research agenda to investigate and validate those genes and genetic variants of patient-reported quality-of-life outcomes, by creating large datasets. During its first meeting, the Consortium has discussed draft summary documents addressing these questions for each patient-reported quality-of-life outcome. A summary of the primary pathways and robust findings of the genetic variants involved is presented here. The research agenda outlines possible research objectives and approaches to examine these and new quality-of-life domains. Intriguing questions arising from this endeavor are discussed. Insight into the genetic versus environmental components of patient-reported quality-of-life outcomes will ultimately allow us to explore new pathways for improving patient care. If we can identify patients who are susceptible to poor quality of life, we will be able to better target specific clinical interventions to enhance their quality of life and treatment outcomes.quality of life, self-rated health, pain, fatigue, genetic disposition, Patient-Reported Quality-of-Life Outcomes

Health care providers underestimate symptom intensities of cancer patients: A multicenter European study

<p>Abstract</p> <p>Background</p> <p>Many patients with advanced cancer depend upon health care providers for symptom assessment. The extent of agreement between patient and provider symptom assessments and the association of agreement with demographic- and disease-related factors was examined.</p> <p>Methods</p> <p>This cross-sectional study included 1933 patient-health care provider dyads, from 11 European countries. Patients reported symptoms by using the four-point scales of the European Organization of Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) version 3, and providers used corresponding four-point categorical scales. Level of agreement was addressed at the group level (Wilcoxon Signed-Rank test), by difference scores (provider score minus patient score), at the individual level (Intraclass Correlation Coefficients, ICCs) and visually by Bland-Altman plots. Absolute numbers and chi-square tests were used to investigate the relationship between agreement and demographic-, as well as disease-related factors.</p> <p>Results</p> <p>The prevalence of symptoms assessed as moderate or severe by patients and providers, respectively, were for pain (67 vs.47%), fatigue (71 vs. 54%), generalized weakness (65 vs. 47%), anorexia (47 vs. 25%), depression (31 vs. 17%), constipation (45 vs. 30%), poor sleep (32 vs. 21%), dyspnea (30 vs. 16%), nausea (27 vs. 14%), vomiting (14 vs. 6%) and diarrhea (14 vs. 6%). Symptom scores were identical or differed by only one response category in the majority of patient-provider assessment pairs (79-93%). Providers underestimated the symptom in approximately one of ten patients and overestimated in 1% of patients. Agreement at the individual level was moderate (ICC 0.38 to 0.59). Patients with low Karnofsky Performance Status, high Mini Mental State-score, hospitalized, recently diagnosed or undergoing opioid titration were at increased risk of symptom underestimation by providers (all p < 0.001). Also, the agreement was significantly associated with drug abuse (p = 0.024), provider profession (p < 0.001), cancer diagnosis (p < 0.001) and country (p < 0.001).</p> <p>Conclusions</p> <p>Considerable numbers of health care providers underestimated symptom intensities. Clinicians in cancer care should be aware of the factors characterizing patients at risk of symptom underestimation.</p

Small-cell lung cancer patients are just ‘a little bit’ tired: response shift and self-presentation in the measurement of fatigue

Background: Response shift has gained increasing attention in the measurement of health-related quality of life (QoL) as it may explain counter-intuitive findings as a result of adaptation to deteriorating health. Objective: To search for response shift type explanations to account for counter-intuitive findings in QoL measurement. Methods: Qualitative investigation of the response behaviour of small-cell lung cancer (SCLC) patients (n = 23) in the measurement of fatigue with The European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) question 'were you tired'. Interviews were conducted at four points during 1st line chemotherapy: at the start of chemotherapy, 4 weeks later, at the end of chemotherapy, and 6 weeks later. Patients were asked to 'think aloud' when filling in the questionnaire. Results: Fifteen patients showed discrepancies between their answer to the EORTC question 'were you tired' and their level of fatigue spontaneously reported during the interview. These patients chose the response options 'not at all' or 'a little' and explained their answers in various ways. In patients with and without discrepancies, we found indications of recalibration response shift (e.g. using a different comparison standard over time) and of change in perspective (e.g. change towards a more optimistic perspective). Patients in the discrepancy group reported spontaneously how they dealt with diagnosis and treatment, i.e. by adopting protective and assertive behaviour and by fighting the stigma. They distanced themselves from the image of the stereotypical cancer patient and presented themselves as not suffering and accepting fatigue as consequence of treatment. Conclusion: In addition to response shift, this study suggests that 'self-presentation' might be an important mechanism affecting QoL measurement, particularly during phases when a new equilibrium needs to be found

Listen to their answers! Response behaviour in the measurement of physical and role functioning

Background: Quality of life (QoL) is considered to be an indispensable outcome measure of curative and palliative treatment. However, QoL research often yields findings that raise questions about what QoL measurement instruments actually assess and how the scores should be interpreted. Objective: To investigate how patients interpret and respond to questions on the EORTC-QLQ-C30 over time and to find explanations to account for counterintuitive findings in QoL measurement. Methods: Qualitative investigation was made of the response behaviour of small-cell lung cancer patients (n = 23) in the measurement of QoL with the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30). Focus was on physical functioning (PF, items 1 to 5), role functioning (RF, items 6 and 7), global health and QoL rating (GH/QOL, items 29 and 30). Interviews were held at four points: at the start of the chemotherapy, 4 weeks later, at the end, and 6 weeks after the end of chemotherapy. Patients were asked to 'think aloud' when filling in the questionnaire. Results: Patients used various response strategies when answering questions about problems and limitations in functioning, which impacted the accuracy of the scale. Patients had scores suggesting they were less limited than they actually were by taking the wording of questions literally, by guessing their functioning in activities that they did not perform, and by ignoring or excluding certain activities that they could not perform. Conclusion: Terminally ill patients evaluate their functioning in terms of what they perceive to be normal under the circumstances. Their answers can be interpreted in terms of change in the appraisal process (Rapkin and Schwartz 2004; Health and Quality of Life Outcomes, 2, 14). More care should be taken in assessing the quality of a set of questions about physical and role functioning. © 2008 The Author(s)

Predictors and correlates of adherence to combination antiretroviral therapy (ART) for chronic HIV infection: a meta-analysis

Adherence to combination antiretroviral therapy (ART) is a key predictor of the success of human immunodeficiency virus (HIV) treatment, and is potentially amenable to intervention. Insight into predictors or correlates of non-adherence to ART may help guide targets for the development of adherence-enhancing interventions. Our objective was to review evidence on predictors/correlates of adherence to ART, and to aggregate findings into quantitative estimates of their impact on adherence. We searched PubMed for original English-language papers, published between 1996 and June 2014, and the reference lists of all relevant articles found. Studies reporting on predictors/correlates of adherence of adults prescribed ART for chronic HIV infection were included without restriction to adherence assessment method, study design or geographical location. Two researchers independently extracted the data from the same papers. Random effects models with inverse variance weights were used to aggregate findings into pooled effects estimates with 95% confidence intervals. The standardized mean difference (SMD) was used as the common effect size. The impact of study design features (adherence assessment method, study design, and the United Nations Human Development Index (HDI) of the country in which the study was set) was investigated using categorical mixed effects meta-regression. In total, 207 studies were included. The following predictors/correlates were most strongly associated with adherence: adherence self-efficacy (SMD = 0.603, P = 0.001), current substance use (SMD = -0.395, P = 0.001), concerns about ART (SMD = -0.388, P = 0.001), beliefs about the necessity/utility of ART (SMD = 0.357, P = 0.001), trust/satisfaction with the HIV care provider (SMD = 0.377, P = 0.001), depressive symptoms (SMD = -0.305, P = 0.001), stigma about HIV (SMD = -0.282, P = 0.001), and social support (SMD = 0.237, P = 0.001). Smaller but significant associations were observed for the following being prescribed a protease inhibitor-containing regimen (SMD = -0.196, P = 0.001), daily dosing frequency (SMD = -0.193, P = 0.001), financial constraints (SMD -0.187, P = 0.001) and pill burden (SMD = -0.124, P = 0.001). Higher trust/satisfaction with the HIV care provider, a lower daily dosing frequency, and fewer depressive symptoms were more strongly related with higher adherence in low and medium HDI countries than in high HDI countries. These findings suggest that adherence-enhancing interventions should particularly target psychological factors such as self-efficacy and concerns/beliefs about the efficacy and safety of ART. Moreover, these findings suggest that simplification of regimens might have smaller but significant effect

Developing core outcomes sets: methods for identifying and including patient-reported outcomes (PROs)

BACKGROUND: Synthesis of patient-reported outcome (PRO) data is hindered by the range of available PRO measures (PROMs) composed of multiple scales and single items with differing terminology and content. The use of core outcome sets, an agreed minimum set of outcomes to be measured and reported in all trials of a specific condition, may improve this issue but methods to select core PRO domains from the many available PROMs are lacking. This study examines existing PROMs and describes methods to identify health domains to inform the development of a core outcome set, illustrated with an example. METHODS: Systematic literature searches identified validated PROMs from studies evaluating radical treatment for oesophageal cancer. PROM scale/single item names were recorded verbatim and the frequency of similar names/scales documented. PROM contents (scale components/single items) were examined for conceptual meaning by an expert clinician and methodologist and categorised into health domains. A patient advocate independently checked this categorisation. RESULTS: Searches identified 21 generic and disease-specific PROMs containing 116 scales and 32 single items with 94 different verbatim names. Identical names for scales were repeatedly used (for example, ‘physical function’ in six different measures) and others were similar (overlapping face validity) although component items were not always comparable. Based on methodological, clinical and patient expertise, 606 individual items were categorised into 32 health domains. CONCLUSION: This study outlines a methodology for identifying candidate PRO domains from existing PROMs to inform a core outcome set to use in clinical trials