A Conceptual Model for Mobile Health-enabled Slow Eating Strategies.

Ingestive behaviors (IBs) (eg, bites, chews, oral processing, swallows, pauses) have meaningful roles in enhancing satiety, promoting fullness, and decreasing food consumption, and thus may be an underused strategy for obesity prevention and treatment. Limited IB monitoring research has been conducted because of a lack of accurate automated measurement capabilities outside laboratory settings. Self-report methods are used, but they have questionable validity and reliability. This paper aimed to present a conceptual model in which IB, specifically slow eating, supported by technological advancements, contributes to controlling hedonic and homeostatic processes, providing an opportunity to reduce energy intake, and improve health outcomes.

Pursuing Collective Synchrony in Teams: A Regime-Switching Dynamic Factor Model of Speed Similarity in Soccer.

Collective synchrony refers to the simultaneous occurrence of behavior, cognition, emotion, and/or physiology within teams of three or more persons. It has been suggested that collective synchrony may emanate from the copresence of team members, from their engagement in a shared task, and from coordination enacted in pursuit of a collective goal. In this paper, a regime-switching dynamic factor analytical approach is used to examine interindividual similarities in a particular behavioral measure (i.e., speed) in a collegiate soccer team. First, the analytical approach is presented didactically, including the state space modeling framework in general, followed by the regime-switching dynamic factor model in particular. Next, an empirical application of the approach is presented. Speed similarity (covariation in speed, operationalized in two ways: running cadence and distance covered) during competitive women's soccer games is examined. A key methodological aspect of the approach is that the collective is the unit of analysis, and individuals vary about collective dynamics and their evolution. Reporting on the results of this study, we show how features of substantive interest, such as the magnitude and prevalence of behavioral similarity, can be parameterized, interpreted, and aggregated. Finally, we highlight several key findings, as well as opportunities for future research, in terms of methodological and substantive aims for advancing the study of collective synchrony.

Personal digital health in Parkinson's disease: Case histories and commentary.

The use of self-tracking of bio-behavioral states along with prescription dosing information is increasingly popular in the care and study of many human diseases. Parkinson's Disease is particularly amenable to such tracking, as patients live with the progressive disease for many years, increasing motivation to pursue quality of life changes through careful monitoring of symptoms and self-guided management of their medications and lifestyle choices. Through the use of digital self-tracking technologies, patients independently or in conjunction with professional medical advice are modulating their medications and behavioral regimens based on self-tracking data. Self-trackers engage in self-experimentation with their health, and more broadly, in personal digital health. This paper briefly depicts notable, recent patient accounts of self-tracking and the uses of digital health in Parkinson's disease: those of Sara Riggare and Kevin Krejci. It also highlights important facets of a previously unreported case: Velva Walden's care as managed jointly by her caregiver son. Key aspects of self-tracking inherent to these cases are examined and potential opportunities to advance personalized medicine through the use of digital health and self-experimentation are outlined.

A mixed-effects location scale model for time-to-event data: A smoking behavior application.

In general, mixed-effects location scale models (MELS) allow assessment of within-person and between-person variability with time-to-event data for outcomes that follow a normal or ordinal distribution. In this article, we extend the mixed-effects location scale model to time-to-event data in relation to smoking data. Better understanding of the time-graded within-person variability of factors involved in nicotine dependence can be helpful to researchers in their efforts to fine-tune smoking cessation programs. We illustrate the MELS model with data on time to first cigarette measured every day for 7 days in smokers randomized to two groups: a) those asked to keep smoking, or b) those asked to stop. Our results show that some individuals remain very stable in their time to first cigarette over the week, while others show variable patterns. The stable individuals smoked every day, did not smoke immediately upon waking, and were all in the group asked to keep smoking. Conversely, the variable individuals had at least one day during which they did not smoke, other days during which they smoked within the first 5 min of waking, and they were almost all in the group asked to quit smoking. These findings suggested that MELS have the potential to provide insights on how people try to stop smoking. More importantly, this model can be applied to other clinically important outcomes such as time to relapse in a range of cessation programs.

Effects of measurement timing on subgroup identification using growth mixture modeling: An empirical application to alcohol use.

Growth mixture modeling (GMM) identifies latent classes exhibiting distinct longitudinal patterns on an outcome. Subgroups identified by GMM may be artifactually influenced by measurement timing (e.g., timing of the initial assessment, length of the interval from the first to the last assessment, and total number of assessments) as well as the theoretically posited developmental patterns of the behavior. The current study investigated this possibility using alcohol data from the 1997 National Longitudinal Survey of Youth (n = 2686; 49.44% female; 71.84% White). Three assessment configurations were examined: all 12 waves, first 6 waves, and last 7 waves. Five subgroups were identified using all 12 waves: Normative (71.33%), Low-Increasing (8.45%), Low-Steady (8.97%), High-Slowly Decreasing (7.67%), and Extreme-Sharply Decreasing (3.57%). When comparing participants' subgroup membership for all 12 waves to the first six waves, 14% of the sample was differentially classified. When comparing all 12 waves to the last seven waves, 62% of the sample was differentially classified. Alterations in the timing of the initial assessment had a substantial impact on latent class estimation, underscoring the importance of selecting the developmental window a priori based on theory and empirical knowledge. The time-bounded nature of mixture modeling solutions (i.e., a selected developmental window within the course of a phenomenon) suggests that the latent subgroups should not be interpreted as representing subgroups that are present in the population. Future directions and strategies for testing alternative interpretations are presented. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Laboratory Validation of Inertial Body Sensors to Detect Cigarette Smoking Arm Movements.

Cigarette smoking remains the leading cause of preventable death in the United States. Traditional in-clinic cessation interventions may fail to intervene and interrupt the rapid progression to relapse that typically occurs following a quit attempt. The ability to detect actual smoking behavior in real-time is a measurement challenge for health behavior research and intervention. The successful detection of real-time smoking through mobile health (mHealth) methodology has substantial implications for developing highly efficacious treatment interventions. The current study was aimed at further developing and testing the ability of inertial sensors to detect cigarette smoking arm movements among smokers. The current study involved four smokers who smoked six cigarettes each in a laboratory-based assessment. Participants were outfitted with four inertial body movement sensors on the arms, which were used to detect smoking events at two levels: the puff level and the cigarette level. Two different algorithms (Support Vector Machines (SVM) and Edge-Detection based learning) were trained to detect the features of arm movement sequences transmitted by the sensors that corresponded with each level. The results showed that performance of the SVM algorithm at the cigarette level exceeded detection at the individual puff level, with low rates of false positive puff detection. The current study is the second in a line of programmatic research demonstrating the proof-of-concept for sensor-based tracking of smoking, based on movements of the arm and wrist. This study demonstrates efficacy in a real-world clinical inpatient setting and is the first to provide a detection rate against direct observation, enabling calculation of true and false positive rates. The study results indicate that the approach performs very well with some participants, whereas some challenges remain with participants who generate more frequent non-smoking movements near the face. Future work may allow for tracking smoking in real-world environments, which would facilitate developing more effective, just-in-time smoking cessation interventions.

Parents do matter: a longitudinal two-part mixed model of early college alcohol participation and intensity.

OBJECTIVE: We hypothesized that etiologically relevant parental, peer, and demographic variables would predict both the transition into alcohol use and consequences and the increase in intensity of these outcomes from prematriculation to the sophomore year of college. METHOD: College students (N = 388) at a midsized northeastern public university were assessed during the summer before matriculation and during the spring semesters of their freshman and sophomore years. A recently developed mixed model for analyzing longitudinal response patterns with predominating zeros was employed to examine categorical transitions (binary portion) and growth (intensity portion). RESULTS: As expected, there were strong effects of time reflected in both the binary and intensity portions of the models across the three outcomes (weekly alcohol use, heavy episodic drinking, and alcohol-related problems). Parental permissiveness of drinking and student intention to affiliate with fraternity/sorority organizations predicted the transition to use and consequence status for all three outcomes and for increases in alcohol use and consequences. Peer disapproval of drinking strongly predicted all alcohol use and consequence outcomes. Parental disapproval of heavy drinking, parental monitoring, and male gender were variably influential across the outcomes at low to moderate levels. CONCLUSIONS: Our findings indicate the importance of the parental context (e.g., parental permissiveness of drinking) as well as peer influences (e.g., intended fraternity/sorority involvement) in drinking behavior among college students. These findings underscore the need to examine both onset and growth of drinking outcomes. Intervention and prevention implications are explored.

Rapid HIV testing of women in labor: too long a delay.

For HIV-infected women who have not received antiretroviral treatment or transmission prophylaxis in pregnancy, starting antiretrovirals in labor or soon after birth can still decrease the risk of perinatal transmission. There is, therefore, potential benefit in conducting rapid HIV testing in labor, but hospitals are seldom prepared to conduct such testing. We compared protocols for rapid HIV testing at 2 hospitals to determine what proportion of women had results back early enough to intervene if results had been positive. Hospital A initially used HIV enzyme-linked immunosorbent assays (ELISAs) and changed to using rapid tests (eg, Single Use Diagnostic System [SUDS]); hospital B used only the SUDS. With use of the SUDS in hospital A, results were reported more quickly than with the ELISA protocol in the same hospital (P < 0.0001). Comparing use of the SUDS in the 2 hospitals, test results were available more quickly in hospital A than hospital B (P < 0.05), which resulted in hospital A having more results reported prior to delivery (64% vs. 38%, P < 0.05) and within 12 hours postdelivery (94% vs. 73%, P < 0.05). If HIV testing in labor is to have its maximum effect on decreasing the risk of perinatal HIV transmission, hospitals need to institute rapid HIV testing, but protocols must ensure that results are available as quickly as possible.