To orchestrate behaviors for survival, multiple psychological components have evolved. The current theories do not clearly distinguish the distinct components. In this article, we provide a unified theoretical framework. To optimize survival, there should be four components; (1) \"need\", an alarm based on a predicted deficiency. (2) \"motivation\", a direct behavior driver. (3) \"pleasure\", a teacher based on immediate outcomes. (4) \"utility\", a teacher based on final delayed outcomes. For behavior stability, need should be accumulated into motivation to drive behavior. Based on the immediate outcome of the behavior, the pleasure should teach whether to continue the current behavior. Based on the final delay outcome, the utility should teach whether to increase future behavior by reshaping the other three components. We provide several neural substrate candidates in the food context. The proposed theoretical framework, in combination with appropriate experiments, will unravel the neural components responsible for each theoretical component.

BACKGROUND: Duchenne muscular dystrophy (DMD) is a genetic disease resulting in progressive muscle weakness, loss of ambulation, and cardiorespiratory complications. Direct estimation of health-related quality of life for patients with DMD is challenging, highlighting the need for proxy measures. This study aims to catalog and compare existing published health state utility estimates for DMD and related conditions.
METHODS: Using two search strategies, relevant utilities were extracted from the Tufts Cost-Effectiveness Analysis Registry, including health states, utility estimates, and study and patient characteristics. Analysis One identified health states with comparable utility estimates to a set of published US patient population utility estimates for DMD. A minimal clinically important difference of ± 0.03 was applied to each DMD utility estimate to establish a range, and the registry was searched to identify other health states with associated utilities that fell within each range. Analysis Two used pre-defined search terms to identify health states clinically similar to DMD. Mapping was based on the degree of clinical similarity.
RESULTS: Analysis One identified 4,308 unique utilities across 2,322 cost-effectiveness publications. The health states captured a wide range of acute and chronic conditions; 34% of utility records were extrapolated for US populations (n = 1,451); 1% were related to pediatric populations (n = 61). Analysis Two identified 153 utilities with health states clinically similar to DMD. The median utility estimates varied among identified health states. Health states similar to the early non-ambulatory DMD phase exhibited the greatest difference between the median estimate of the sample (0.39) and the existing estimate from published literature (0.21).
CONCLUSIONS: When available estimates are limited, using novel search strategies to identify utilities of clinically similar conditions could be an approach for overcoming the information gap. However, it requires careful evaluation of the utility instruments, tariffs, and raters (proxy or self).

BACKGROUND: Even if robotic assisted total knee arthroplasty (RATKA) is a widely used technique, there is still a gap of knowledge about whether this technology is effective in improving the patient utility. This measure is of paramount importance for conducting cost effectiveness analysis. The aim of this study was to compare the utility measure derived from self-reported outcomes questionnaires in patients who underwent RATKA compared to patients who underwent the manual surgery.
METHODS: We compared 72 patients operated with a robotic technique with 70 operated with traditional technique. The utility data were collected with the WOMAC (Western Ontario and McMaster University Osteoarthritis index) self-administrated questionnaire that investigates pain, stiffness and functionality of the patients, an then mapped to a utility value through a validated transforming function. We performed three surveys: the first one before the intervention (t0), the second one 1 year after the surgery (t1) and the third one at the 2 year follow up (t2).
RESULTS: we observed higher utility values in both groups. In detail, the mean utility score in the RATKA group increased from 0.37 to 0.71 (t1) and 0.78 (t2), while in the conventional group it increased from 0.41 to 0.78 (t1) and 0.78 (t2). The fixed effect coefficients of t1 and t2 were found to be 0.37 and 0.363 (p < 0.001 for both). The coefficient of the robotic technique, along with its interaction with the t1 and t2 time effect was non-significant.
CONCLUSIONS: Even if at t1 the utility of patient who underwent RATKA were lower, at longer follow up (t2) we found no significant difference compared to traditional technique, leaving the superiority of robotic assisted technique yet to be proved. Our results may be useful for calculating the gained or lost Quality Adjusted Life Years (QALYs), so that the health care system (or an insurance company) could make an appropriate decision whether to fund the robotic approach or not, after a careful assessment of the incremental costs incurred.

OBJECTIVE: This study aimed to produce Sri Lankan population norms of utility values, EuroQol visual analog scale scores, and reported problems in each domain of the EQ-5D-5L, as well as a disutility catalog, based on a representative set of Sri Lankan preferences.
METHODS: Data from a nationally representative sample of 6415 adults from the Sri Lanka Health and Ageing Study in 2018 to 2019 were used. Sri Lankan preferences were applied to EQ-5D-5L scores to produce utility values. Descriptive statistics were produced for responses by EQ-5D-5L dimension, mean utility values, and EuroQol visual analog scale scores, disaggregated by demographic and disease group. Multivariable logistic regression assessed associations with problems in each dimension, and demographic and chronic diseases. Robust ordinary least squares and tobit regressions were performed to estimate the marginal disutility of demographic covariates and disease conditions.
RESULTS: The mean utility value for the overall population was 0.867. Utility values decreased with age and increased with increasing education and richer socioeconomic quintiles. Males had higher utility values than females (0.89 vs 0.84; P < .001). Utility values declined by 0.007 with each year increase in age (P < .001) and statistically significant differences (P < .05) in utility were found by ethnicity, socioeconomic quintile, and disease conditions such as stroke, diabetes, cancer, depression, and musculoskeletal conditions, using a tobit regression.
CONCLUSIONS: This study provides the first nationally representative set of population norms based on a local value set for key demographic groups and selected chronic disease conditions for Sri Lanka. It also provides a catalog that can be easily used to calculate quality-adjusted life-years for cost-utility analysis when modeling public health interventions.

Loopholes offer an opening. Rather than comply or directly refuse, people can subvert an intended request by an intentional misunderstanding. Such behaviors exploit ambiguity and under-specification in language. Using loopholes is commonplace and intuitive in everyday social interaction, both familiar and consequential. Loopholes are also of concern in the law, and increasingly in artificial intelligence. However, the computational and cognitive underpinnings of loopholes are not well understood. Here, we propose a utility-theoretic recursive social reasoning model that formalizes and accounts for loophole behavior. The model captures the decision process of a loophole-aware listener, who trades off their own utility with that of the speaker, and considers an expected social penalty for non-cooperative behavior. The social penalty is computed through the listener\'s recursive reasoning about a virtual naive observer\'s inference of a naive listener\'s social intent. Our model captures qualitative patterns in previous data, and also generates new quantitative predictions consistent with novel studies (N = 265). We consider the broader implications of our model for other aspects of social reasoning, including plausible deniability and humor.

BACKGROUND: Physical activity (PA) plays a crucial role in health care, providing benefits in the prevention and management of many noncommunicable diseases. Wearable activity trackers (WATs) provide an opportunity to monitor and promote PA in various health care settings.
OBJECTIVE: This study aimed to develop a consensus-based framework for the optimal use of WATs in health care.
METHODS: A 4-round Delphi survey was conducted, involving a panel (n=58) of health care professionals, health service managers, and researchers. Round 1 used open-response questions to identify overarching themes. Rounds 2 and 3 used 9-point Likert scales to refine participants\' opinions and establish consensus on key factors related to WAT use in health care, including metrics, device characteristics, clinical populations and settings, and software considerations. Round 3 also explored barriers and mitigating strategies to WAT use in clinical settings. Insights from Rounds 1-3 informed a draft checklist designed to guide a systematic approach to WAT adoption in health care. In Round 4, participants evaluated the draft checklist\'s clarity, utility, and appropriateness.
RESULTS: Participation rates for rounds 1 to 4 were 76% (n=44), 74% (n=43), 74% (n=43), and 66% (n=38), respectively. The study found a strong interest in using WATs across diverse clinical populations and settings. Key metrics (step count, minutes of PA, and sedentary time), device characteristics (eg, easy to charge, comfortable, waterproof, simple data access, and easy to navigate and interpret data), and software characteristics (eg, remote and wireless data access, access to multiple patients\' data) were identified. Various barriers to WAT adoption were highlighted, including device-related, patient-related, clinician-related, and system-level issues. The findings culminated in a 12-item draft checklist for using WATs in health care, with all 12 items endorsed for their utility, clarity, and appropriateness in Round 4.
CONCLUSIONS: This study underscores the potential of WATs in enhancing patient care across a broad spectrum of health care settings. While the benefits of WATs are evident, successful integration requires addressing several challenges, from technological developments to patient education and clinician training. Collaboration between WAT manufacturers, researchers, and health care professionals will be pivotal for implementing WATs in the health care sector.

BACKGROUND: Malaria impacts nearly 250 million individuals annually. Specifically, Uganda has one of the highest burdens, with 13 million cases and nearly 20,000 deaths. Controlling the spread of malaria relies on vector surveillance, a system where collected mosquitos are analyzed for vector species\' density in rural areas to plan interventions accordingly. However, this relies on trained entomologists known as vector control officers (VCOs) who identify species via microscopy. The global shortage of entomologists and this time-intensive process cause significant reporting delays. VectorCam is a low-cost artificial intelligence-based tool that identifies a mosquito\'s species, sex, and abdomen status with a picture and sends these results electronically from surveillance sites to decision makers, thereby deskilling the process to village health teams (VHTs).
OBJECTIVE: This study evaluates the usability of the VectorCam system among VHTs by assessing its efficiency, effectiveness, and satisfaction.
METHODS: The VectorCam system has imaging hardware and a phone app designed to identify mosquito species. Two users are needed: (1) an imager to capture images of mosquitos using the app and (2) a loader to load and unload mosquitos from the hardware. Critical success tasks for both roles were identified, which VCOs used to train and certify VHTs. In the first testing phase (phase 1), a VCO and a VHT were paired to assume the role of an imager or a loader. Afterward, they swapped. In phase 2, two VHTs were paired, mimicking real use. The time taken to image each mosquito, critical errors, and System Usability Scale (SUS) scores were recorded for each participant.
RESULTS: Overall, 14 male and 6 female VHT members aged 20 to 70 years were recruited, of which 12 (60%) participants had smartphone use experience. The average throughput values for phases 1 and 2 for the imager were 70 (SD 30.3) seconds and 56.1 (SD 22.9) seconds per mosquito, respectively, indicating a decrease in the length of time for imaging a tray of mosquitos. The loader\'s average throughput values for phases 1 and 2 were 50.0 and 55.7 seconds per mosquito, respectively, indicating a slight increase in time. In terms of effectiveness, the imager had 8% (6/80) critical errors and the loader had 13% (10/80) critical errors in phase 1. In phase 2, the imager (for VHT pairs) had 14% (11/80) critical errors and the loader (for VHT pairs) had 12% (19/160) critical errors. The average SUS score of the system was 70.25, indicating positive usability. A Kruskal-Wallis analysis demonstrated no significant difference in SUS (H value) scores between genders or users with and without smartphone use experience.
CONCLUSIONS: VectorCam is a usable system for deskilling the in-field identification of mosquito specimens in rural Uganda. Upcoming design updates will address the concerns of users and observers.

BACKGROUND: As population-based screening programs to identify genetic conditions in adults using genomic sequencing (GS) are increasingly available, validated patient-centered outcome measures are needed to understand participants\' experience. We aimed to develop and validate an instrument to assess the perceived utility of GS in the context of adult screening.
METHODS: Informed by a five-domain conceptual model, we used a five-step approach to instrument development and validation: (1) item writing, (2) cognitive testing, (3) pilot testing and item reduction, (4) psychometric testing, and (5) evaluation of construct validity. Adults undergoing risk-based or population-based GS who had received GS results as part of ongoing research studies participated in structured cognitive interviews and two rounds of surveys. After item pool refinement, we conducted an exploratory factor analysis and calculated Pearson correlations with related instruments.
RESULTS: We derived the 18-item Adult Diagnostic version of the GENEtic Utility (GENE-U) scale (total sum score α = .87). Mirroring the Pediatric Diagnostic version, the instrument has a two-factor structure, including an Informational Utility subscale (14 items, α =.89) and an Emotional Utility subscale (4 items, α =.75). The Informational Utility subscale was strongly associated with empowerment and personal utility of GS. Correlations of the Emotional Utility subscale with psychosocial impact and anxiety and depression were weak to moderate.
CONCLUSIONS: Initial psychometric testing of the Adult Screening GENE-U scale demonstrates its promise, and additional validation in translational genomics research is warranted.

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease with chronic pain that gradually becomes incapacitating and negatively influences the health-related quality of life (HRQoL). This study estimates HRQoL in RA using the EuroQol five dimensions (EQ-5D) tool and its association with functional status and disease activity.
METHODS: RA patients (n = 320) aged above 18 years, visiting outpatient clinic at a tertiary care multispecialty hospital in south India were the study participants. Sociodemographic, clinical, and laboratory data were collected from them. EQ-5D-5L questionnaire and the EQ Global Health Visual Analogue Scale (EQ-VAS) were used to measure HRQoL. Disease activity was measured using Disease Activity Score-28 (DAS-28), and the Health Assessment Questionnaire (HAQ) was used to assess functional status. Pearson\'s correlation and multiple linear regression were used to measure association, and statistical significance was considered at p < 0.05.
RESULTS: The EQ-5D utility score was 0.54 ± 0.36, pain and anxiety were the most affected domains, and the mean EQ-VAS was 63.05 ± 18.54%. A moderate to high disease activity was present in 85% (DAS-28 > 3.2), and a severe functional disability in 32.8% (HAQ > 1.5) of study participants. The mean EQ-5D scores for RA patients were 0.78 (0.65-0.90) for no disease activity, 0.73 (0.65-0.80) for mild, 0.53 (0.32-0.74) for moderate and 0.47 (0.32-0.62) for high disease activity. In multiple linear regression analysis, HAQ and age independently predicted EQ-5D.
CONCLUSIONS: RA significantly impacts HRQoL, and interventions focussing on pain and anxiety management are essential. The study\'s EQ-5D values could help estimate Quality Adjusted Life Years (QALY) while conducting economic evaluation studies in RA within an Indian context.

UNASSIGNED: Understanding patient preferences for treatments may facilitate shared decision-making. This study assessed adult patient preferences for attention-deficit/hyperactivity disorder (ADHD) treatments in a sample of 600 patients in the United States (US).
UNASSIGNED: A web-based discrete choice experiment (DCE) survey was conducted among treated adults with ADHD. Participants were recruited from Dynata\'s US panel (06/22/2023-07/06/2023). Attributes and levels, identified based on clinical inputs and published data, included efficacy and safety. Participants\' preferences were estimated using conditional logistic regression. Willingness to trade-off and attributes\' relative importance were calculated. Overall preferences for treatment profiles approximating centanafadine, lisdexamfetamine, atomoxetine, and viloxazine were estimated using adjusted total utilities. Results were stratified by current treatment status. Sensitivity analyses including participants who passed validity tests were conducted.
UNASSIGNED: Among the 600 participants (mean age 37.9 years; 66.2% female; 50.8% treated), all attributes had a statistically significant impact on preferences for ADHD treatments (p < 0.001); the most important attribute was improvement in ADHD symptoms (36%), followed by risks of nausea (25%), insomnia (20%), anxiety (8%), dry mouth (6%), and feeling jittery (5%). Together, safety attributes accounted for >60% of relative importance in decision-making. Participants were willing to forgo 0.59, 0.57, 0.49, 0.32, and 0.17 percentage points of symptom improvement to achieve one-percentage-point reduced risk of insomnia, nausea, anxiety, feeling jittery, and dry mouth, respectively. Centanafadine profile had consistently higher adjusted total utilities than its comparators. Similar results were obtained in the subgroup and sensitivity analyses.
UNASSIGNED: Efficacy was the most important attribute for patients when making treatment decision, but taken together, AEs had greater relative importance than efficacy alone. Accordingly, a profile resembling that of centanafadine would be preferred by an average patient compared to key competitors due to its favorable safety profile. These findings may help improve treatment decision-making, enhance treatment satisfaction, and foster adherence.