Quality of Life Research最新文献

Purpose: Cost-utility analyses examining the value of new vaccines for pneumococcal disease will require health state utilities as inputs. Existing utilities for pneumococcal infections in young children are limited. The purpose of this study was to estimate health state utilities associated with pneumococcal infections in young children.

Methods: Six health state vignettes depicting infections due to Streptococcus pneumoniae were drafted based on published literature and clinician interviews. To address methodological challenges in estimating utilities for temporary infections in children 0-5 years of age, several time trade-off approaches were explored in a pilot study (N = 28 participants). In the subsequent utility elicitation study conducted in the UK, health states were valued using the best performing method from the pilot (10-year time horizon, with infections repeated annually) with adult general population respondents imagining a child 2-5 years of age.

Results: A total of 208 participants completed interviews (51.9% female; mean [SD] age = 41.0 [14.9] years). Mean (SD) utilities were 0.902 (0.092) for pneumonia requiring hospitalization, 0.901 (0.087) for bacteremia, 0.894 (0.103) for recurrent acute otitis media (AOM), 0.882 (0.107) for recurrent AOM treated with pressure equalization tubes, 0.878 (0.109) for bacteremic pneumonia, and 0.809 (0.145) for meningitis.

Conclusion: Lower health state utilities were associated with health states that had longer treatment periods, required more invasive treatment, and described more severe infections. Utilities from this study can be used in models examining cost-effectiveness of pneumococcal vaccines. These results have methodological implications for future research estimating utilities associated with temporary pediatric health conditions.

Purpose: To ensure the recognition and participation of all potential respondents in health research, surveys and care, including LGBTQIA + broadly, and trans people, specifically, the use of inclusive language should be considered. This scoping review aimed to identify and describe strategies considered for gender inclusivity in development and use of health questionnaires and Patient Reported Outcomes Measures (PROMs).

Methods: A systematic search of peer reviewed publications between January 2000 and September 2022 was conducted in Scopus, ProQuest Central, Ovid Medline (PubMed and EBSCO). Two reviewers independently screened identified publications titles and abstracts, followed by full text screening and data extraction from eligible articles.

Results: The search of over 5000 publications, retained 18; most acknowledged gaps in representation and advocated for gender-inclusive language. Eight articles discussed exclusion from health care and health research for gender minority groups due to the use of gendered language. Improved reliability, validity and response rates were associated with the use of gender-neutral language in seven articles. Only one article reported finding irritation among cisgender males when non-binary gender response options were used. One paper, focussing on instruments for Rheumatoid Arthritis, discussed gaps in representation if diverse gender identities were not considered when developing PROMs.

Conclusion: This scoping review points to the importance of adopting gender-inclusive language in health questionnaires and surveys to reduce the risk of excluding gender minority groups. Despite finding very few specific examples of how others have used gender-inclusive language in health questionnaires, many strengths of gender-inclusive language usage were identified.

Background: Understanding health-related quality of life (HRQoL) dynamics is essential for assessing and improving treatment experiences; however, clinical and observational studies struggle to capture their full complexity. We use simulation modeling and the case of Chimeric Antigen Receptor T-cell therapy-a type of cancer immunotherapy that can prolong survival, but carries life-threatening risks-to study HRQoL dynamics.

Methods: We developed an exploratory system dynamics model with mathematical equations and parameter values informed by literature and expert insights. We refined its feedback structure and evaluated its dynamic behavior through iterative interviews. Model simulated HRQoL from treatment approval through six months post-infusion. Two strategies-reducing the delay to infusion and enhancing social support-were incorporated into the model. To dynamically evaluate the effect of these strategies, we developed four metrics: post-treatment HRQoL decline, recovery time to pre-treatment HRQoL, post-treatment HRQoL peak, and durability of the peak.

Results: Model captures key interactions within HRQoL, providing a nuanced analysis of its continuous temporal dynamics, particularly physical well-being, psychological well-being, tumor burden, receipt and efficacy of treatment, side effects, and their management. Model analysis shows reducing infusion delays enhanced HRQoL across all four metrics. While enhanced social support improved the first three metrics for patients who received treatment, it did not change durability of the peak.

Conclusions: Simulation modeling can help explore the effects of strategies on HRQoL while also demonstrating the dynamic interactions between its key components, offering a powerful tool to investigate aspects of HRQoL that are difficult to assess in real-world settings.

Purpose: This study aimed to identify feasible, evidence-based strategies to improve the use of Patient-reported outcome measures (PROMs) implemented in clinical oncology practice.

Methods: A mixed-method study involving observations of consultations and semi-structured interviews with patients and healthcare professionals (HCPs) was conducted to identify facilitators and barriers for using PROMs; barriers and facilitators were structured following the Theoretical Domains Framework. For each barrier, evidence-based improvement strategies were selected using the Behaviour Change Techniques Taxonomy v1. Subsequently, improvement strategies were ranked on priority and feasibility by an expert panel of HCPs, information technology professionals, and PROMs implementation specialists, creating an implementation improvement strategy.

Results: Ten consultations were observed and 14 interviews conducted. Barriers for implementation included that the electronic health record and PROMs did not align to the individual needs of end users, the HCPs' hesitance to advice patients about health-related quality-of-life issues, and a lack of consensus on which HCPs were responsible for discussing PROMs with patients. Forty-one improvement strategies were identified, of which 25 remained after ranking. These included: redesigning the PROMs dashboard by including patient management advice, enhancing patient support to complete PROMs, and clarifying HCPs' responsibilities for discussing PROMs. Strategies currently considered less feasible were: improving user-friendliness of the patient portal due to technical constraints, aligning PROMs assessment frequency with clinical courses, and using baseline PROMs for early identification of vulnerabilities and supportive care needs. These will be studied in future research.

Conclusion: Evidence-based improvement strategies to ensure lasting adoption of PROMs in clinical practice were identified.

ISOQOL's Australia and New Zealand Special Interest Group (ISOQOL ANZ SIG) connects local researchers and clinicians in a geographically remote region of the world. Members of our ANZ SIG have been conducting a review following COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) guidance, which outlines a comprehensive process to critically evaluate the properties of outcome measurement instruments, including patient-reported outcome measures (PROMs). Our experience has highlighted challenges for undertaking this type of review, notably a lack of consistency in how COSMIN guidance is applied and reported. In this Letter to the Editor, members of the ANZ SIG leadership discuss the PRISMA-COSMIN for Outcome Measurement Instruments; a new guideline developed to support and improve reporting of systematic reviews of outcome measurement instruments. We explore the potential of this guidance to improve how systematic reviews of PROMs are conducted and reported, from the perspective of a regional SIG.

Purpose: The relationship between quality of life (QoL) and frailty has previously been investigated cross-sectionally and longitudinally as unidirectional where QoL depends upon frailty and where frailty depends on QoL. Here a bidirectional relationship is examined.

Methods: This work uses a latent curve model with structured residuals to address the bidirectional association between QoL and frailty in older English people considering within-person and group levels. The study measures frailty using a functional frailty measure and quality of life using CASP-12. The sample size is 17,529.

Results: There is a strong relationship between QoL (Quality of Life) and frailty, which is almost linear and inversely proportional over time. Although the cross-lagged coefficients from QoL to frailty and vice versa showed statistical significance, the impact was found to be minimal. The time between assessments (which are two years apart) and/or the few observations available per individual may have impacted the effect of this relationship. When accounting for gender, age, net wealth, and multimorbidity, some variations in the results were observed at the group level but not at the within-person level.

Conclusion: The study provides empirical evidence that supports a bidirectional association between QoL and frailty in older individuals who reside at home. These results offer valuable insights for healthcare providers, as participants did not exhibit an advanced need for health services. Additionally, involving participants in evaluating and assessing these services enhances their effectiveness and overall benefit.

Purpose: Preference-based summary scores are used to quantify values, differences, and changes in health-related quality of life (HRQoL) that can be used for cost-effectiveness analyses. The PROMIS-Preference (PROPr) measure is a preference-based summary score comprised of 7 PROMIS domains. The PROMIS-16 is a new PROMIS profile instrument. We evaluated the measurement properties of PROPr generated from the widely used PROMIS-29 + 2 compared with the PROMIS-16.

Methods: We performed a secondary analysis of data from an online survey of the general US population, with a longitudinal subsample who reported back pain. The survey included both the PROMIS-16 and the PROMIS-29 + 2 profiles. PROPr scores were calculated from each profile and compared by the distribution of scores, overall mean scores, product-moment correlations with pain measure scores (Oswestry Disability Index, Roland-Morris Disability Questionnaire, Pain Intensity, Interference with Enjoyment of Life, Interference with General Activity Scale, and Graded Chronic Pain Scale), and difference in mean scores in subgroups with 13 chronic health conditions (Cohen's d).

Results: Of the 4,115 participants in the baseline survey, 1,533 with any reported back pain were invited for the 6-month follow-up survey and 1,256 completed it. At baseline, the overall mean (SD) PROPr score was 0.532 (0.240) from PROMIS-16 and 0.535 (0.250) from PROMIS 29 + 2. At both time points, the correlations of PROPr scores with physical and mental health summary scores from the PROMIS-29 and 4 pain scales were within 0.01 between profiles. Using subgroups with chronic health conditions and comparing between profiles, Cohen's d estimates of the difference in effect size were small (< 0.2).

Conclusion: PROPr scores from the 16-item PROMIS profile measure are similar to PROPr scores from the longer PROMIS-29 + 2.

Purpose: We describe development of a short health-related quality of life measure, the patient-reported outcomes measurement information system® (PROMIS®)-16 Profile, which generates domain-specific scores for physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function, and fatigue.

Methods: An empirical evaluation of 50 candidate PROMIS items and item pairs was conducted using data from a sample of 5775 respondents from Amazon's Mechanical Turk (MTurk). Results and item response theory information curves for a subset of item pairs were presented and discussed in a stakeholder meeting to narrow the candidate item sets. A survey of the stakeholders and 124 MTurk adults was conducted to solicit preferences among remaining candidate items and finalize the measure.

Results: Empirical evaluation showed minimal differences in basic descriptive statistics (e.g., means, correlations) and associations with the PROMIS-29 + 2 Profile, thus item pairs were further considered primarily based on item properties and content. Stakeholders discussed and identified subsets of candidate item pairs for six domains, and final item pairs were agreed upon for two domains. Final items were selected based on stakeholder and MTurk-respondent preferences. The PROMIS-16 profile generates eight domain scores with strong psychometric properties.

Conclusion: The PROMIS-16 Profile provides an attractive brief measure of eight distinct domains of health-related quality of life, representing an ideal screening tool for clinical care, which can help clinicians quickly identify distinct areas of concern that may require further assessment and follow-up. Further research is needed to confirm and extend these findings.