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Studies of response-shift phenomena in quality-of-life (QOL) research have grown steadily in the more than two decades of research. As a field, we have been calling a lot of different approaches “response shift” over the years, but the only approach that fully embodies the foundational (Sprangers and Schwartz, Soc Sci Med 48(11):1507–1515, 1999) theoretical model is appraisal. According to the definition proposed in this model, response shift is about individual cognitive change. This paper presents the argument that all response-shift research models need to be grounded in an understanding of cognitive appraisal. We present a reasoned argument for why appraisal is fundamental to QOL response-shift research. We describe current measurement and analytic methods for working with appraisal, and how these methods can be integrated into the current response-shift statistical ‘tool box.’ We propose future research directions on theory, methods, and cross-calibration of group-and individual-level methods. There are currently three tools available in multiple languages for assessing QOL appraisal processes. They have been tested and used to assess response shift in empirical studies of ~ 7000 people with chronic illness. The study findings illustrate how appraisal theory and methods can facilitate methodological investigations of and to enhance other response-shift detection methods. Future research directions are proposed to enrich QOL theory, responseshift methods, and interpretation of QOL change over time. Appraisal theory and methods are the closest approximation to a response-shift ‘gold standard.’ They provide the foundation for understanding response shift and point to a unified theory of QOL.

Background The present study sought to investigate how comorbidity burden influences cancer survivors' quality of life (QoL) and the challenges/adaptations during the coronavirus disease 2019 (COVID) pandemic, and to examine how appraisal processes are related to this impact. Methods This cross‐sectional study, administered in spring/summer 2020, compared cancer survivors to a general‐population comparison sample. QoL was assessed with standardized tools. COVID‐specific questions included selected items compiled by the US National Institutes of Health, and cognitive appraisal processes were assessed using the QoL Appraisal Profilev2 Short‐Form. Principal components analysis reduced the number of comparisons. Multivariate analysis of covariance investigated group differences in QoL, COVID‐specific variables, and cognitive‐appraisal processes. Linear regression investigated group differences in COVID‐specific variables as a function of cognitive‐appraisal processes, QoL, demographic covariates, and their interactions. Results Cancer survivors fared substantially better than non‐cancer participants in QoL and cognitive functioning when they had no other comorbidities, but substantially worse on QoL when they had three or more comorbidities. Cancer survivors with no comorbidities were less likely to feel worried about COVID, less likely to engage in self‐protection, and prioritized engaging in problem‐focused and prosocial actions compared to non‐cancer participants. Conversely, cancer survivors confronted with multiple comorbidities exhibited more proactive self‐protection and experienced more anxiety about the pandemic. Conclusion The impact of having multiple comorbidities in the context of cancer is associated with notable differences in social determinants of health, QoL outcomes, COVID‐specific challenges/adaptations, and appraisal of QoL. These findings provide an empirical basis for implementing appraisal‐based coping interventions. This cross‐sectional study, administered in Spring/Summer 2020, compared cancer survivors (n = 520) to a general‐population comparison sample (n = 441). The impact of having multiple comorbidities in the context of cancer is associated with notable differences in social determinants of health, quality of life (QOL) outcomes, COVID‐specific challenges/adaptations, and appraisal of QOL.

Purpose This study characterized depression trajectories during the COVID pandemic and investigated how appraisal and changes in appraisal over time related to these depression trajectories. Methods This longitudinal study of the psychosocial impact of the COVID-19 pandemic included 771 people with data at three timepoints over 15.5 months. The depression index was validated using item-response-theory methods and receiver-operating-characteristic curve analysis. The Quality of Life (QOL) Appraisal Profile v2 Short-Form assessed cognitive-appraisal processes. Sequence analysis characterized depression-trajectory groups, and random effects models examined appraisal main effects, appraisal-by-group, and appraisal-by-group-by-time interactions. Results Sequence analysis generated six trajectory groups: Stably Well (n = 241), Stably Depressed (n = 299), Worsening (n = 79), Improving (n = 83), Fluctuating Pattern 1 (No–Yes–No; n = 41), and Fluctuating Pattern 2 (Yes–No–Yes; n = 28). While all groups engaged in negative appraisal processes when they were depressed, the Stably Depressed group consistently focused on negative aspects of their life. Response-shift effects were revealed such that there were differences in the appraisal-depression relationship over time for standards of comparison and recent changes for the Stably Depressed, and in health goals for those Getting Better. Conclusion The present work is, to our knowledge, the first study of response-shift effects in depression. During these first 15.5 pandemic months, group differences highlighted the connection between negative appraisals and depression, and response-shift effects in these relationships over time. Egregious life circumstances may play a lesser role for the Stably Depressed but a greater role for people who have transient periods of depression as well as for those with improving trajectories (i.e., endogenous vs. reactive depression). How one thinks about QOL is intrinsically linked to mental health, with clear clinical implications.

Background Learning healthcare communities (LHCCs) have been proposed as a next-generation evolution of learning health systems that can advance health equity; however, a practical mechanism for enabling the active and continuous community engagement required for one has not yet been described in the literature. Recognizing that community-based participatory research (CBPR) could potentially meet this need, a team at the Montefiore Medical Center/Albert Einstein College of Medicine designed a novel evidence-based CBPR model – Bridging Research, Accurate Information and Dialogue (BRAID) – that initiates meaningful, longitudinal dialogues to foster bidirectional trust between researchers, clinicians, scientists and communities. Methods A mixed-methods cohort study of two BRAID cohorts was conducted between 2022 and 2023. Eligible participants were recruited from the Bronx, New York, United States and convened in a series of conversation circles. Multimodal data was collected from all participants, including quantitative pre- and post-series surveys and same-day conversation circle feedback forms. Surveys were administered using SurveyMonkey and descriptive statistics were completed in Excel and SPSS. Results A total of 42 participants were enrolled, most of whom were people of colour who had not participated in research before. Among them, 40 participants provided at least one response to a same-day conversation circle feedback form, which reflected consistently positive experiences with BRAID. This was consistent with evidence from the post-series survey, in which every one of the 36 respondents stated that they would either definitely (83.3%, N  = 30/36) or probably (16.7%, N  = 6/36) recommend participation in BRAID to someone like them. Of note, 91.7% ( N  = 33/36) had already disseminated health information learned through BRAID downstream and 84.4% ( N  = 27/32) indicated that BRAID strengthened their trust in science and research, highlighting unique and distinguishing features of the model. Conclusions Our quantitative evidence suggests that BRAID is effective, efficient and scalable, with experiential evidence supporting that it is reproducible. These factors suggest that BRAID implementation can facilitate rapid, bidirectional information sharing that builds trust between healthcare organizations and communities. This has laid the groundwork for an LHCC in the Bronx, with the potential to be adopted by healthcare organizations elsewhere.

Background The Rapkin and Schwartz appraisal theory and measure provided a path toward documenting response-shift effects and describing individual differences in ways of thinking about quality of life (QOL) that distinguished people in different circumstances. Recent work developed and validated the QOL Appraisal Profile version 2 (QOLAP v2 ), an 85-item measure that taps response-shift-detection domains of Frame of Reference, Standards of Comparison, Sampling of Experience, and Combinatory Algorithm. Recent theoretical work proposed that appraisal measurement constitutes a new class of measurement (idiometric), distinct from psychometric and clinimetric. To validate an idiometric measure, one would document that its items reflect different circumstances and population characteristics, and explain variance in QOL. The present work sought to develop idiometric short-forms of the QOLAP v2 item bank by examining which items were most informative, retaining the appraisal-domain structure. Methods This secondary analysis ( n  = 1481) included chronically-ill patients and their caregivers from a longitudinal web-based survey (mean follow-up 16.6 months). Data included the QOLAP v2 , the Center for Disease Control Healthy Days Core Module, the PROMIS-10 Global Health, and demographic/medical variables. Appraisal items were measured at baseline (relevant to understanding cognitive appraisal processes); and with change scores (sensitive to response-shift effects). Multivariate analysis of covariance examined what demographic and health-status change variables were reflected by each of 85 appraisal items (in five sets), as dependent variables, and other demographic/medical variables. Multiple linear regression examined how appraisal items explained variance in global physical- and mental-health change, after covariate adjustment. A tally summarized item performance across all five sets of cross-sectional and longitudinal analyses. Results The vast majority (i.e., 80%) of the QOLAP v2 items performed well across the analyses presented. Using a relatively strict criterion of explaining meaningful variance across 60% of analyses, one would retain 68 items. A more lenient criterion (40%) would retain 71. Conclusions The present study provides heuristics to support investigators’ creating ‘discretionary’ QOLAP v2 short-forms to fit their study aim and amplifying individual differences in the cognitive processes underlying QOL. This approach enables adapting the measure to the study population, as per the expectation that respondent populations differ in the predominant cognitive processes used.

Background The impact of the coronavirus disease 2019 (COVID) is worse among those with fewer financial resources, in jobs not amenable to remote work, and in denser living conditions. People of color are more likely to be among these vulnerable groups. Although race itself is a social construction and not based on underlying genetic/biological differences, this study investigated race/ethnicity differences in the negative repercussions of COVID and in the benefits of psychological and social resources. Methods This cross-sectional, web-based study ( n  = 4817) was administered to a heterogeneous United States sample in Spring/Summer 2020. Information was gathered on the following COVID-specific variables: Infection Status, Coping with Lockdown, Social Support, Post-traumatic Growth, Interpersonal Conflict, Worry about Self, Financial Impact on Family, Lack of Money, Inadequate Access to Healthcare, and Housing Instability. Resilience was operationalized as the ability to maintain a sense of wellness in the face of the pandemic, using the DeltaQuest Wellness measure. Multivariate linear regression (adjusting for demographics) and propensity-matched cohort analysis (matched on demographics) evaluated the impact of COVID-specific variables on Wellness in separate models for Whites and Non-Whites. Findings Both sets of models retained the same COVID-specific variables and explained about half of the variance in wellness. Coping with Lockdown, Social Support, and Post-traumatic Growth were associated with higher levels of Wellness in both Whites and Non-Whites, while Interpersonal Conflict and Worry about Self were associated with lower levels of Wellness. While these associations are similar, Non-Whites reported worse levels of some positive resources (e.g., social support) and more challenging levels of negative stressors (e.g., interpersonal, worry, financial). Non-Whites also reported much higher levels of post-traumatic growth. Conclusion COVID was a source of worry and even conflict, but also unlocked people’s resources in use of health-enhancing behavioral strategies, social support, and renewed gratitude for sources of personal meaning and value. The similar relationships between Whites and Non-Whites on wellness and COVID-specific stressors across racial groups underscore that race is a social construction, not a biological fact. Focusing on a renewed appreciation for sources of personal meaning, and particularly faith, seemed to buffer much of the COVID-related stress for Non-Whites.

Background Two decades of research on quality-of-life (QOL) appraisal have demonstrated links between patient experience and health outcomes and have accounted for both intra-individual change and inter-individual differences in a wide range of research contexts. The present work investigates patterns across diagnostic and demographic groupings to demonstrate how population-specific circumstances drive the structure of QOL appraisal. Methods This secondary analysis ( N  = 6448) utilized data from six patient groups: spine surgery, multiple sclerosis, heterogeneous chronically ill, heterogeneous cancer, bladder cancer, and human immunodeficiency virus (HIV). We explored patterns of inter-item correlation across patient samples, using items from the Standards of Comparison and Sampling of Experience subsections of the QOL Appraisal Profile v1 and v2. Similar matrices were compared by demographic characteristics. Results Patterns of inter-item correlations for Standards of Comparison items varied sharply across disease groups and racial groups while being similar across age, gender, and education levels. Inter-item correlation matrices for Sampling of Experience items revealed marked differences among disease groups and educational and racial categories but were similar across age and gender groups. Conclusions Appraisal parameters showed evidence of shared and unique aspects across samples and circumstances, findings which make sense in light of sample differences in health status and demographic influences. Tools to assess patient experience and meaning may be best understood as idiometric instruments. We discuss their distinctions from psychometric and clinimetric tools at theoretical, statistical, and applied levels.

Introduction Cancer impinges on nearly every aspect of the lives of patients, survivors, and loved ones. This study presents progress in developing the “What Matters to Me” Worksheet (WMTM‐Worksheet), designed to elicit personal priorities across multiple life domains. WMTM‐Worksheet items were finalized based on clinician recommendations and patient feedback. Individuals at any point in cancer treatment were interviewed post‐appointment about using the WMTM‐Worksheet prior to their appointment. Methods To finalize the WMTM Worksheet, initial samples of clinicians and patients were interviewed on its content and usability. Oncology clinicians were recruited by email; 25 accepted and were surveyed about current practices of incorporating patient priorities and preferences into treatment planning, and the usability, practicality, and feasibility of the 17‐item WMTM Worksheet. Patients were English‐ or Spanish‐speaking adults diagnosed with gynecological, head and neck, or urological cancers. Patients at any point in active treatment or follow‐up were eligible. An initial sample of 15 patients was administered a cognitive interview about the WMTM Worksheet by telephone to assess its clarity, relevance, and feasibility. Next, 61 patients taking part in the user experience portion of this study were identified through the electronic medical record (EMR), contacted by telephone, and offered participation in a onetime interview regarding the WMTM Worksheet. They received the WMTM Worksheet prior to a clinic appointment. Questions regarding user experience were administered by telephone 1–3 days later. Results Of the 61 patient respondents, 57% were over age 65, 59% female, 41% Hispanic, 45% Black; 49% had an annual income below $35,000. Patient responses yielded seven principal components, reflecting domains such as symptoms, family caregiving, work, and hobbies. Most patients (62%) said the WMTM‐Worksheet helped them think about disease and treatment; 30% said it helped communication with clinicians. Eighty‐five percent were glad to share their concerns, and only 10% found it difficult to complete. Conclusion The WMTM‐Worksheet can bring patients' broader priorities into care planning. Patients may be better able to anticipate and avoid problems. Discussion of priorities validates patients' concerns and promotes trust. Implementation will require the clinical infrastructure to support shared decision‐making and incorporate the WMTM‐Worksheet into workflow. Oncologists may benefit from communications training to determine patients' concerns and present options that best address their priorities. This study evaluated the “What Matters to Me” Worksheet, a tool designed to elicit personal priorities across multiple life domains. Patients undergoing cancer treatment reported the WMTM Worksheet helped them communicate with their clinician and think about their disease and treatment.

Background Total hip arthroplasty (THA) is a successful procedure that provides pain relief, restores function, and improves quality of life (QOL) for patients with advanced arthritis in their hip joint. To date, little research has examined the role of cognitive appraisal processes in THA outcomes. This study examined the role of cognitive appraisal processes in THA outcomes in the first year post-surgery. Methods This longitudinal cohort study collected data at pre-surgery, 6 weeks post-surgery, 3 months post-surgery, and 12 months post-surgery. Adults (n = 189) with a primary diagnosis of osteoarthritis were consecutively recruited from an active THA practice at a Canadian academic teaching hospital. Measures included the Hip Disability and Osteoarthritis Outcome Score (HOOS), the Mental Component Score (MCS) of the Rand-36, and the Brief Appraisal Inventory (BAI). Analysis of Variance examined the association between BAI items and the HOOS or MCS scores. Random effects models investigated appraisal main effects and appraisal-by-time interactions for selected BAI items. Results HOOS showed great improvement over the first 12 months after THA, and was mitigated by three appraisal processes in particular: focusing on problems with healthcare or living situation, and preparing one’s family for health changes. MCS was stable and low over time, and the following appraisal processes were implicated by very large effect sizes: not comparing themselves to healthier people, focusing on money problems, preparing their family for their health changes, or trying to shed responsibilities. Conclusions Appraisal processes are relevant to health outcomes after THA, with different processes coming into play at different points in the recovery trajectory.

PurposeUnderstanding people’s response to the pandemic needs to consider individual differences in priorities and concerns. The present study sought to understand how individual differences in cognitive-appraisal processes might moderate the impact of three COVID-specific factors—hardship, worry, and social support—on reported depression.MethodsThis longitudinal study of the psychosocial impact of the COVID-19 pandemic included 771 people with data at three timepoints over 15.5 months. Participants were recruited from panels of chronically ill or general population samples. Depression was measured by an item response theory validated depression index created using items from existing measures that reflected similar content to the Patient Health Questionnaire-8. COVID-specific factors of hardship, worry, and social support were assessed with items compiled by the National Institutes of Health. The Quality of Life Appraisal Profilev2 Short-Form assessed cognitive appraisal processes. A series of random effects models examined whether appraisal moderated the effects of hardship, worry, and social support on depression over time.ResultsOver time the association between low social support and depression was greater (p = 0.0181). Emphasizing the negative was associated with exacerbated depression, in particular for those with low social support (p = 0.0007). Focusing on demands and habituation was associated with exacerbated depression unless one experienced greater hardship (p = 0.0074). There was a stronger positive connection between recent changes and depression for those people with higher worry scores early in the pandemic as compared to later, but a stronger positive correlation for those with lower worry scores later in the pandemic (p = 0.0015). Increased endorsement of standards of comparison, emphasizing the negative, problem goals, and health goals was associated with worse depression scores (all p < 0.0001). People who were younger, disabled, or had greater difficulty paying bills also reported worse depression (p < 0.0001, 0.0001, and 0.002, respectively).ConclusionAt the aggregate level, COVID-specific stressors changed over the course of the pandemic, whereas depression and social-support resources seemed stable. However, deeper analysis revealed substantial individual differences. Cognitive-appraisal processes showed considerable variability across individuals and moderated the impact of COVID-specific stressors and resources over time. Future work is needed to investigate whether coaching individuals away from maladaptive cognitive-appraisal processes can reduce depression and lead to better overall well-being.