63 research outputs found

    Using Latent Growth Modeling to Understand Longitudinal Effects in MIS Theory: A Primer

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    The use of structural equation modeling (SEM) has grown dramatically in the field of management information systems (MIS) in the past twenty years, but SEM’s focus has been primarily on cross-sectional data sets. Functionally, SEM has been used to test measurement and path models, but the SEM approach has not been applied to repeated measures designs. In this article, we describe latent growth models (LGMs), an extension of SEM, which focuses on how observed and/or latent variables change over time. The purpose of this paper is to provide a primer on the use of LGMs, as well as to advocate for its use to extend MIS theory. We illustrate several flexible applications of LGMs using longitudinal data, including conditional, unconditional, and dual growth models. We discuss the advantages of using LGMs over other more traditional longitudinal approaches, and highlight areas in MIS where researchers can use this technique effectively

    Multi-modal Predictive Models of Diabetes Progression

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    With the increasing availability of wearable devices, continuous monitoring of individuals' physiological and behavioral patterns has become significantly more accessible. Access to these continuous patterns about individuals' statuses offers an unprecedented opportunity for studying complex diseases and health conditions such as type 2 diabetes (T2D). T2D is a widely common chronic disease that its roots and progression patterns are not fully understood. Predicting the progression of T2D can inform timely and more effective interventions to prevent or manage the disease. In this study, we have used a dataset related to 63 patients with T2D that includes the data from two different types of wearable devices worn by the patients: continuous glucose monitoring (CGM) devices and activity trackers (ActiGraphs). Using this dataset, we created a model for predicting the levels of four major biomarkers related to T2D after a one-year period. We developed a wide and deep neural network and used the data from the demographic information, lab tests, and wearable sensors to create the model. The deep part of our method was developed based on the long short-term memory (LSTM) structure to process the time-series dataset collected by the wearables. In predicting the patterns of the four biomarkers, we have obtained a root mean square error of 1.67% for HBA1c, 6.22 mg/dl for HDL cholesterol, 10.46 mg/dl for LDL cholesterol, and 18.38 mg/dl for Triglyceride. Compared to existing models for studying T2D, our model offers a more comprehensive tool for combining a large variety of factors that contribute to the disease

    An Electronic Daily Diary Study of Anal Intercourse in Drug-Using Women

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    Women (N = 138) with histories of illicit drug use were recruited into an electronic diary study that used Android smartphones for data collection. The diary was to be completed each day for 12 weeks using an "app" created in HTML5 and accessed over the Internet via smartphone. Data collection included information on sexual behaviors with up to 10 partners per day and contextual factors surrounding sexual behavior such as drug use before/after, type of sexual behavior (oral, vaginal, anal), and other activities such as using condoms for vaginal and anal intercourse and use of sexual lubricants. The sample was predominantly African American (58 %); 20 % Latina, 20 % White and 2 % reported as Other. Most women reported either less than a high school education (33 %) or having a high school diploma (33 %). The mean age was 39 years (SD = 11.78). Anal intercourse occurred on days when women also reported using illicit drugs, specifically methamphetamine and cocaine. Anal intercourse was not an isolated sexual activity, but took place on days when vaginal intercourse and giving and receiving oral sex also occurred along with illicit drug use. Anal intercourse also occurred on days when women reported they wanted sex. HIV prevention interventions must address the risks of anal intercourse for women, taking into account concurrent drug use and sexual pleasure that may reduce individual harm-reduction behaviors

    Change is not always linear: The study of nonlinear and discontinuous patterns of change in psychotherapy.

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    Abstract The study of discontinuities and nonlinear change has been a fruitful endeavor across the sciences, as these shifts can provide a window into the organization of complex systems and the processes that are associated with transition. A common assumption in psychotherapy research has been that change is gradual and linear. The research designs and statistics used to study change often reflect this assumption, but some recent research reveals other patterns of change. We briefly review relevant literature on dynamical systems theory and on life transition and post-traumatic growth to highlight the significance of nonlinear and discontinuous change across areas of psychology. We describe recent applications of these ideas and methods to the study of change in psychotherapy and encourage their use to complement more traditional clinical trial designs. © 2007 Elsevier Ltd. All rights reserved. Some change can be gradual and incremental, but many systems in nature show periods of turbulence and instability, with dramatic changes or growth spurts. Ilya Prigogine, a Nobel laureate known for his theory of dissipative structures in chemistry, argues that instabilities play an important role in transformation and that "most of reality, instead of being orderly, stable, and equilibrial, is seething and bubbling with change, disorder, and process" (Prigogine & Stengers, 1984, p. xv). The study of discontinuities has been a fruitful endeavor across the sciences, as these shifts can provide a window into the organization of a system and the processes that are associated with transition. A common assumption in psychotherapy research is that change is gradual and linear. The research designs and statistics used to study change often reflect this assumption. The hypothesized predictors of change are measured once or twice and then compared between groups or correlated with symptom change at the end of treatment. Most research also focuses on group averages, with much less emphasis on the rich information available in individual time course Clinical Psychology Review 27 (2007) 715 -72

    Anxiety, Depression, and Fear of Cancer Recurrence in Head and Neck Cancer

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    Objective: Patients with head and neck cancer (HNC) report some of the highest levels of psychological distress amid managing their disease as well as debilitating and disfiguring treatment side effects. Fear of cancer recurrence (FCR) is a top unmet need and concern of patients with HNC. Prior research suggests elevated symptoms of anxiety and depression are potential antecedents to FCR, but findings have been limited in HNC populations. The aim of the present study was to examine early level and change in symptoms of anxiety and depression in relation to later change in FCR among patients with HNC. Methods: The study is a secondary analysis of data collected from 2011-2014 through the Head and Neck 5000 Study in the United Kingdom. A sample of 4891 patients completed self-report longitudinal assessments of anxiety and depression symptoms at baseline, 4, and 12 months and FCR at 4 and 12 months. Results: Utilizing multiple indicator latent change score modeling, results revealed baseline anxiety and increases in anxiety from baseline to 4 months were both positively associated with increases in FCR from 4 to 12 months. Neither baseline depression nor change in depression from baseline to 4 months were significantly associated with FCR change. Conclusions: Findings indicate that early level and increases in symptoms of anxiety were markers of increased FCR in patients with HNC. Future research may consider anxiety as a unique antecedent and maintaining factor of FCR and targeting anxiety early in the cancer trajectory may have downstream effects on FCR development. Public significance statements: This study examined change in fear of cancer recurrence (FCR) as a function of early level and change in symptoms of anxiety and depression in the year after head and neck cancer diagnosis. Results indicated that early level and increases in anxiety but not depression were associated with later increases in FCR. Identifying patients with clinically elevated anxiety and ensuring early intervention may mitigate possible downstream development of FCR.Output Status: Forthcomin

    Anxiety, Depression, and Fear of Cancer Recurrence in Head and Neck Cancer

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    Objective: Patients with head and neck cancer (HNC) report some of the highest levels of psychological distress amid managing their disease as well as debilitating and disfiguring treatment side effects. Fear of cancer recurrence (FCR) is a top unmet need and concern of patients with HNC. Prior research suggests elevated symptoms of anxiety and depression are potential antecedents to FCR, but findings have been limited in HNC populations. The aim of the present study was to examine early level and change in symptoms of anxiety and depression in relation to later change in FCR among patients with HNC. Methods: The study is a secondary analysis of data collected from 2011-2014 through the Head and Neck 5000 Study in the United Kingdom. A sample of 4891 patients completed self-report longitudinal assessments of anxiety and depression symptoms at baseline, 4, and 12 months and FCR at 4 and 12 months. Results: Utilizing multiple indicator latent change score modeling, results revealed baseline anxiety and increases in anxiety from baseline to 4 months were both positively associated with increases in FCR from 4 to 12 months. Neither baseline depression nor change in depression from baseline to 4 months were significantly associated with FCR change. Conclusions: Findings indicate that early level and increases in symptoms of anxiety were markers of increased FCR in patients with HNC. Future research may consider anxiety as a unique antecedent and maintaining factor of FCR and targeting anxiety early in the cancer trajectory may have downstream effects on FCR development. Public significance statements: This study examined change in fear of cancer recurrence (FCR) as a function of early level and change in symptoms of anxiety and depression in the year after head and neck cancer diagnosis. Results indicated that early level and increases in anxiety but not depression were associated with later increases in FCR. Identifying patients with clinically elevated anxiety and ensuring early intervention may mitigate possible downstream development of FCR

    Jean-Philippe Laurenceau - Dynamical systems analysis of dyadic coupled systems

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    Content: Self-Regulating Procresses; Equilibria and Fluctuations; Passive Self-Regulation of a Pendulum; Self-Regulation of Conpled Pendula; Conpled Trajectories; Modeling Choices; Limitation
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