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Quantifying the treatment goals of people recently diagnosed with schizophrenia using best-worst scaling.

ABSTRACT: Objective:This study seeks to quantify the treatment goals of people recently diagnosed with schizophrenia and explore their impact on treatment plan. Methods:People aged 18-35 years with a confirmed diagnosis of schizophrenia within the past 5 years were surveyed in the UK, Germany, and Italy. Treatment goals were assessed via a validated best-worst scaling instrument, where participants evaluated subsets of 13 possible treatment goals identified using a balanced incomplete block design. Participants identified the most and least important goals within each task. Data were also collected on current treatment and preference for daily oral versus long-acting injectable (LAI) treatment. Hierarchical Bayes was used to identify preference weights for the goals, and latent class analysis was used to identify segments of people with similar goals. The segments were compared with the current treatment and preference for oral versus LAI treatment. Results:Across 100 participants, the average age was 26 years, 75% were male and 50% were diagnosed within 2 years ago. Overall, preferences were most favorable for reduced disease symptoms, think clearly, reduced hospitalizations, reduced anxiety, and take care of self. A total of 61% preferred oral medication and 39% LAI. Two groups were identified with different treatment goals; 50% of participants emphasized clinical goals, including reduced disease symptoms (preference weight =19.7%), reduced hospitalizations (15.5%), and reduced anxiety (10.5%). The other 50% emphasized functional goals, including improved relationships with family/friends (11.4%), increased interest in work (10.6%), experiencing a fuller range of emotions (8.4%), and ability to socialize (7.5%). Those emphasizing functional goals were more likely to be on LAI (44% versus 26%; p=0.059) and preferred LAI (46% versus 32%; p=0.151). Conclusions:People with recent-onset schizophrenia may focus more on clinical goals or functional goals, a discussion of which may help facilitate patient engagement.

SUBMITTER: Bridges JF

PROVIDER: S-EPMC5757991 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundOlder people with hypertension and multiple chronic conditions (MCC) receive complex treatments and face challenging trade-offs. Patients' preferences for different health outcomes can impact multiple treatment decisions. Since evidence about outcome preferences is especially scarce among people with MCC our aim was to elicit preferences of people with MCC for outcomes related to hypertension, and to determine how these outcomes should be weighed when benefits and harms are assessed for patient-centered clinical practice guidelines and health economic assessments.MethodsWe sent a best-worst scaling preference survey to a random sample identified from a primary care network of Kaiser Permanente (Colorado, USA). The sample included individuals age 60 or greater with hypertension and at least two other chronic conditions. We assessed average ranking of patient-important outcomes using conditional logit regression (stroke, heart attack, heart failure, dialysis, cognitive impairment, chronic kidney disease, acute kidney injury, fainting, injurious falls, low blood pressure with dizziness, treatment burden) and studied variation across individuals.ResultsOf 450 invited participants, 217 (48%) completed the survey, and we excluded 10 respondents who had more than two missing choices, resulting in a final sample of 207 respondents. Participants ranked stroke as the most worrisome outcome and treatment burden as the least worrisome outcome (conditional logit parameters: 3.19 (standard error 0.09) for stroke, 0 for treatment burden). None of the outcomes were always chosen as the most or least worrisome by more than 25% of respondents, indicating that all outcomes were somewhat worrisome to respondents. Predefined subgroup analyses according to age, self-reported life-expectancy, degree of comorbidity, number of medications and antihypertensive treatment did not reveal meaningful differences.ConclusionsAlthough some outcomes were more worrisome to patients than others, our results indicate that none of the outcomes should be disregarded for clinical practice guidelines and health economic assessments.

Project description:Epilepsy is a common, serious condition. Fortunately, seizure risk decreases with increasing seizure-free time on antiseizure medications (ASMs). Eventually, patients may consider whether to stop ASMs, which requires weighing treatment benefit versus burden. We developed a questionnaire to quantify patient preferences relevant to ASM decision-making. Respondents rated how concerning they would finding relevant items (e.g., seizure risks, side effects, cost) on a Visual Analogue Scale (VAS, 0-100) and then repeatedly chose the most and least concerning item from subsets (best-worst scaling, BWS). We pretested with neurologists, then recruited adults with epilepsy who were seizure-free at least one year. Primary outcomes were recruitment rate, and qualitative and Likert-based feedback. Secondary outcomes included VAS ratings and best-minus-worst scores. Thirty-one of 60 (52%) contacted patients completed the study. Most patients felt VAS questions were clear (28; 90%), easy to use (27; 87%), and assessed preferences well (25; 83%). Corresponding results for BWS questions were 27 (87%), 29 (97%), and 23 (77%). Physicians suggested adding a 'warmup' question showing a completed example and simplifying terminology. Patients suggested ways to clarify instructions. Cost, inconvenience of taking medication, and laboratory monitoring were the least concerning items. Cognitive side effects and a 50% seizure risk in the next year were the most concerning items. Twelve (39%) of patients made at least one 'inconsistent choice' for example ranking a higher seizure risk as lower concern compared with a lower seizure risk, though 'inconsistent choices' represented only 3% of all question blocks. Our recruitment rate was favorable, most patients agreed the survey was clear, and we describe areas for improvement. 'Inconsistent' responses may lead us to collapse seizure probability items into a single 'seizure' category. Evidence regarding how patients weigh benefits and harms may inform care and guideline development.

Project description:Background and objectiveBest-worst scaling is a theory-driven method that can be used to prioritize objects in health. We sought to characterize all studies of best-worst scaling to prioritize objects in health, to assess trends of using best-worst scaling in prioritization over time, and to assess the relationship between a legacy measure of quality (PREFS) and a novel assessment of subjective quality and policy relevance.MethodsA systematic review identified studies published through to the end of 2021 that applied best-worst scaling to study priorities in health (PROSPERO CRD42020209745), updating a prior review published in 2016. The PubMed, EBSCOhost, Embase, Scopus, APA PsychInfo, Web of Science, and Google Scholar databases were used and were supplemented by a hand search. Data describing the application, development, design, administration/analysis, quality, and policy relevance were summarized and we tested for trends by comparing articles before and after 1 January, 2017. Multivariate statistics were then used to assess the relationships between PREFS, subjective quality, policy relevance, and other possible indicators.ResultsFrom a total of 2826 unique papers identified, 165 best-worst scaling studies were included in this review. Applications of best-worst scaling to study priorities in health have continued to grow (p < 0.01) and are now used in all regions of the world, most often to study the priorities of patients/consumers (67%). Several key trends can be observed over time: increased use of pretesting (p < 0.05); increased use of online administration (p < 0.01), and decreased use of paper self-administered surveys (p = 0.02); increased use of heterogeneity analysis (p = 0.02); an increase in having a clearly stated purpose (p < 0.01); and a decrease in comparing respondents to non-respondents (p = 0.01). The average sample size has more than doubled, from 228 to 472 respondents, but formal sample size justifications remain low (5.3%) and unchanged over time (p = 0.68). While the average PREFS score remained unchanged at 3.1/5, both subjective quality and policy relevance trended up, but changes were not statistically significant (p = 0.06 and p = 0.13). Most of the variation in subjective quality was driven by PREFS (R2 = 0.42), but it was also positively assosciated with policy relevance, heterogeneity analysis, and using a balanced incomplete block design, and was negatively associated with not using developmental methods and an increasing sample size.ConclusionsUsing best-worst scaling to prioritize objects is now commonly used around the world to assess the priorities of patients and other stakeholders in health. Best practices are clearly emerging for best-worst scaling. Although legacy measures (PREFS) to measure study quality are reasonable, there may need to be new tools to assess both study quality and policy relevance.

Project description:Food safety is a global public health issue, which often arises from asymmetric information between consumers and suppliers. With the development of information technology in human life, building a food traceability information sharing platform is viewed as one of the best ways to overcome the trust crisis and resolve the problem of information asymmetry in China. However, among the myriad information available from the food supply chain, there is a lack of knowledge on consumer preference. Based on the best-worst scaling approach, this paper investigated consumer preferences for vegetable, pork, and dairy product traceability information. Specifically, this paper measured the relative importance that consumers place on the traceable information. The results indicate that consumers have varying priorities for information in different cases. "Pesticide/veterinary use," "picking/slaughtering date," and "fertilizer/feed use" are the most preferred traceable information for Chinese consumers in the case of vegetables, while "picking/slaughtering date" and "history of illness and taking protective measures" are the most preferred information in the case of pork. In the case of dairy products, consumers prefer "processing information," "environmental information of the origin," and "traceable tag certification information" most. The results of this study call for the direct involvement of the Chinese government in the food safety information sharing system as following. First, given consumers' diverse preferences, different types of traceable information should be recorded into the information sharing platform depending on food types. Second, the government could promote the step-by-step construction of such a platform based on the priority of consumers' preferences. Third, new technology should be applied to guarantee the reliability of traceable information. Finally, local preferences in terms of the way consumers receive and understand information should be taken into consideration.

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Quantifying the treatment goals of people recently diagnosed with schizophrenia using best-worst scaling.

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