Many problematic behaviors can be conceptualized as choosing a smaller, immediate outcome over a larger, delayed outcome. For example, drug abuse involves choosing between the immediate euphoric effects of the drug and the delayed health and legal consequences of drug abuse. Individuals that consistently choose the smaller outcome are said to behavior “impulsively.” The goal of this dissertation was to understand how to change impulsive choice. Chapters 2 and 3 successfully demonstrate that impulsive choice can be altered by reframing how the choice is presented. For example, framing a delayed outcome using a specific date instead of a duration of time (e.g., 1 year) reduced impulsive choice. However, these findings do not explain why impulsive choice changed. The goal of Chapter 4 was to identify the underlying processes that result in impulsive choice with the hopes that by understanding these processes, impulsive choice can be reduced. Latent factor modeling was used to understand the role if three proposed processes in impulsive choice: marginal utility, cardinal utility, and nonlinear time perception. The results of the latent factor model indicated that nonlinear time perception does relate to how delayed outcomes are valued but not marginal utility and cardinal utility.

Forskning tyder på att faktorer som exempelvis personlighetsdrag, kön, ålder, relationsstatus och erfarenhet kan påverka en individs risktolerans. Det förekommer dock tvetydigheter om hur olika faktorer påverkar risktolerans. Denna studie undersökte vilka bakgrundsvariabler och personlighets­dimensioner som relaterade till risktolerans samt vilka variabler som var mest avgörande för att kunna förklara den totala variationen av risktolerans. Studien hade tre frågeställningar. I studien deltog 133 högskolestudenter. Deltagarna fick besvara en enkät bestående av Shafers personality scale som mäter de grundläggande personlighetsdimensionerna enligt femfaktorteorin samt 13-item instrument som mäter risktolerans. Studiens frågeställningar besvarades med Pearsons produktmomentkorrelationskoefficient och en stegvis multipel linjär regressionsanalys med forward selection. Korrelationerna visade att män, ekonomistudenter och privatsparande hade högre risktolerans än kvinnor, övriga ämnesområden och icke-privatsparade. Neuroticism korrelerade negativt med risktolerans. Samma variabler var mest avgörande och kunde förklara 28% av den totala variationen i risktolerans bland högskolestudenter. Det diskuterades att intresse och kunskap möjligen inverkade på risktolerans.

It has been said that children are the nation's most valuable asset, since the future of the nation depends on their inborn possibilities and Share and the development of these possibilities. From an economic standpoint, the bringing up of a child is an investment, in fact, a very profitable investment, not so much for the immediate family as for the community as a whole.

Diabetes is one of the most common chronic medical conditions with 34.2 million people affected in the US. It costs $327 billion in medical expenses, lost work, and wages. Diabetics are at higher risk of major medical complications. 90 to 95% of 30 million Americans with diabetes are classified as type 2 (Centers for Disease Control and Prevention, 2020). Management of diabetes is within the scope of OT practice as it is part of health management and maintenance. It is described as how a person develops, manages, and maintains routines and habits for health and wellness promotion. A 2018 online survey was conducted with US-based Occupational Therapy (OT) and Occupational Therapy Assistant (OTA) program directors. Nearly half of the OT and more than half of the OTA program directors reported only 1.5–>3hrs is devoted to diabetes care and management in their curriculum. A 2019 online survey was disseminated to OT practitioners to ascertain their self-reported competence and knowledge about type 2 diabetes mellitus and its lifestyle management. OT clinicians reported minimal to somewhat skilled in educating and training clients in self-help skills related to diabetes management. OT practitioners are suggested to take training and courses that are relevant to their practice and domain for long-term retention of content and tasks (Custers, 2010). The American Occupational Therapy Association encourages OT practitioners to include health-promoting tasks in their practice as the profession’s roots and values are aligned with the health promotion (Wood, et al., 2013).

This dissertation is centered on applying `nonlinearity' across various fields, a decision informed by the understanding that linear models frequently fail to capture the full extent of real-world complexities. This approach is driven by the distinct insights that nonlinearity offers, insights crucial for a more profound and precise understanding of diverse phenomena. In this regard, I have explored a variety of empirical methodologies and theoretical frameworks, each chosen for its effectiveness in unraveling and accurately depicting the complexity inherent in different subjects. The first paper, "Warming Temperatures and Potential Adaptation through Breeding: Evidence from U.S. Soft Winter Wheat," examines the impact of climate change on wheat production. Given wheat's role as a major staple for much of the global population, its susceptibility to rising temperatures presents significant challenges to food security. Despite its importance, comprehensive production data for wheat considering extensive U.S. regions is relatively scarce. To address this, I compiled a unique dataset on wheat production comprising 35,000 observations over 50 years from USDA-ARS hard-copy publications. Findings obtained through the mixed-effects model reveal significant variations in the influence of nonlinearly specified temperature on wheat production. This analysis identifies a decline not only in wheat yield across various U.S. farming sites but also in wheat quality, an aspect often neglected in similar studies. The issue is further compounded by simulations I conducted, which predict worrying decreases in both yield and quality due to rising temperatures. Despite these challenges, my analysis of varietal improvements indicates modest yet significant progress in countering the effects of warming, offering viable strategies for agricultural adaptation. In the second chapter, "Semiparametric Analysis of Out-farm Migration in China," I explore the nonlinear relationship between sectoral migration and the income gap within China. This work builds on my co-authored publication, "Intersectoral Labor Migration and Agriculture in the United States and Japan," published in Agricultural Economics. While the earlier study employed discrete thresholds and kink approaches to explore migration patterns in developed countries such as Japan and the United States, it did not reveal significant nonlinear relationships. This led me to investigate whether the results were influenced by the economic development status of the countries in question. Focusing on China, a developing country with distinct labor dynamics, I employ semiparametric methodologies to assess migration patterns, diverging from the linear assumptions common in existing literature. By using nationally representative data, it suggests a potential nonlinear relationship between farmers' sectoral migration and the income gap, providing new insights into labor migration in developing contexts. The last chapter, "Enhanced Salience of Nonlinear Pricing and Energy Conservation," explores the energy consumption of residents of Hanoi in Vietnam, using a large-scale randomized control trial. I study whether enhancing salience of information with respect to the nonlinear pricing can help energy conservation. The novelty of the project lies in its experimental design and the utilization of digital tools such as smart meters and mobile apps, adopting technologies with the potential to alter consumer behavior. Currently, we are in the post-intervention data collection phase. Supported by the International Growth Centre (IGC), the project aims to bridge the research gap in energy consumption behavior in developing countries, thereby contributing to policymaking in energy management and development in these regions. Through these diverse yet interconnected chapters, I attempt to use the varied applications of nonlinearity in studying economic and environmental issues. The main objective is to contribute to both academic knowledge and practical policymaking in these fields, addressing complexities that are often oversimplified. This approach aims to provide a more comprehensive understanding of the intricate dynamics in these areas. / Doctor of Philosophy / This dissertation focuses on the application of `nonlinearity' across various fields, acknowledging that linear models often fail to fully capture the complexities of real-world scenarios. This approach yields essential insights for a more precise understanding of diverse phenomena, incorporating a range of empirical methods and theoretical models, each selected for their efficacy in accurately depicting complexities in various subjects. The first part of my dissertation examines the agricultural sector, specifically the impact of weather on crop yields. Instead of traditional methods that use basic temperature data like minimum, maximum, or average values, I use a nonlinear approach that aligns with the specific growth stages of crops. In the area of labor economics, the dissertation explores migration patterns in China. It questions the traditional linear relationship between migration and income disparities, suggesting a more complex model that better represents the dynamics of a developing economy. The final chapter addresses the field of energy policy, examining consumer responses to nonlinear electricity pricing models in practice. This section explores the challenges faced by individuals in understanding such policies and assesses the impact of providing real-time information about nonlinear pricing on promoting energy conservation.

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The identification of preferred and reinforcing stimuli has long been a focus of behavior analysts in applied settings. Research has primarily focused on different methodologies for assessing whether stimuli are preferred and there has been additional research on identifying under what conditions those stimuli will function as reinforcers. Recently, research has begun to examine responses and reinforcers from a behavioral economic perspective. The present study compared responding in a situation where the price of one item was increased, but the price of alternative items remained the same, to a situation where the price of all available items increased. Multiple stimulus with replacement (MS) preference assessment methodology was used and price was altered by increasing the distance of the stimuli from the participant. During the first assessment, the item chosen most frequently in the first session was systematically moved 6 - 24 inches beyond the other items during subsequent sessions. During the second assessment, all items were systematically moved 6 - 24 inches beyond the starting point in front of the participant during subsequent sessions. Results for the first assessment indicated that for four of the five participants, consumption of the target item decreased as a function of increased price for that item. Results for the second assessment indicated that at high costs, clear preference for one item was observed for three of the five participants. Taken collectively, these results suggest that response effort is a variable that should be taken into consideration when evaluating effective treatments for individuals with disabilities. Preference and reinforcer effectiveness may shift as individuals are presented with tasks that require increased response effort in terms of reaching or moving about their environment. / Educational Psychology

No / Nonadherence to antihypertensive medicines limits their effectiveness, increases the risk of adverse health outcome, and is associated with significant health care costs. The multiple causes of nonadherence differ both within and between patients and are influenced by patients’ care settings. Objectives The objective of this article was to identify determinants of patient nonadherence to antihypertensive medicines, drawing from psychosocial and economic models of behavior. Methods Outpatients with hypertension from Austria, Belgium, England, Germany, Greece, Hungary, The Netherlands, Poland, and Wales were recruited to a cross-sectional online survey. Nonadherence to medicines was assessed using the Morisky Medication Adherence Scale (primary outcome) and the Medication Adherence Rating Scale. Associations with adherence and nonadherence were tested for demographic, clinical, and psychosocial factors. Results A total of 2595 patients completed the questionnaire. The percentage of patients classed as nonadherent ranged from 24% in The Netherlands to 70% in Hungary. Low age, low self-efficacy, and respondents’ perceptions of their illness and cost-related barriers were associated with nonadherence measured on the Morisky Medication Adherence Scale across several countries. In multilevel, multivariate analysis, low self-efficacy (odds ratio = 0.73; 95% confidence interval 0.70–0.77) and a high number of perceived barriers to taking medicines (odds ratio = 1.70; 95% confidence interval 1.38–2.09) were the main significant determinants of nonadherence. Country differences explained 11% of the variance in nonadherence. Conclusions Among the variables measured, patients’ adherence to antihypertensive medicines is influenced primarily by their self-efficacy, illness beliefs, and perceived barriers. These should be targets for interventions for improving adherence, as should an appreciation of differences among the countries in which they are being delivered.

Impaired social functioning conferred by mental illnesses has been constantly implicated in previous literatures. However, studies of social abnormalities in psychiatric conditions are often challenged by the difficulties of formalizing dynamic social exchanges and quantifying their neurocognitive underpinnings. Recently, the rapid growth of computational psychiatry as a new field along with the development of multiplayer economic paradigms provide powerful tools to parameterize complex interpersonal processes and identify quantitative indicators of social impairments. By utilizing these methodologies, the current set of studies aimed to examine social decision making during multiplayer economic games in participants diagnosed with depression (study 1) and combat-related post-traumatic stress disorder (PTSD, study 2), as well as an online population with elevated symptoms of borderline personality disorder (BPD, study 3). We then quantified and disentangled the impacts of multiple latent decision-making components, mainly social valuation and social learning, on maladaptive social behavior via explanatory modeling. Different underlying alterations were revealed across diagnoses. Atypical social exchange in depression and BPD were found attributed to altered social valuation and social learning respectively, whereas both social valuation and social learning contributed to interpersonal dysfunction in PTSD. Additionally, model-derived indices of social abnormalities positively correlated with levels of symptom severity (study 1 and 2) and exhibited a longitudinal association with symptom change (study 1). Our findings provided mechanistic insights into interpersonal difficulties in psychiatric illnesses, and highlighted the importance of a computational understanding of social function which holds potential clinical implications in differential diagnosis and precise treatment. / Doctor of Philosophy / People with psychiatric conditions often suffer from impaired social relationships due to an inability to engage in everyday social interactions. As different illnesses can sometimes produce the same symptoms, social impairment can also have different causes. For example, individuals who constantly avoid social activities may find them less interesting or attempt to avoid potential negative experiences. While those who display elevated aggression may have a strong desire for social dominance or falsely believe that others are also aggressive. However, it is hard to infer what drives these alterations by just observing the behavior. To address this question, we enrolled people with three different kinds of psychopathology to play an interactive game together with another player and mathematically modeled their latent decision-making processes. By comparing their model parameters to those of the control population, we were able to infer how people with psychopathology made the decisions and which part of the decision-making processes went wrong that led to disrupted social interactions. We found altered model parameters differed among people with major depression, post-traumatic stress disorder and borderline personality disorder, suggesting different causes underlying impaired social behavior observed in the game, the extent of which also positively correlated with their psychiatric symptom severity. Understanding the reasons behind social dysfunctions associated with psychiatric illnesses can help us better differentiate people with different diagnoses and design more effective treatments to restore interpersonal relationships.