Food parenting topics in social media posts: Development of a coding system, examination of frequency of food parenting concepts, and comparison across Reddit and Facebook.

This study presents development of a coding system to examine food parenting topics presented in posts on social media, and compared topics between two social media platforms (Facebook, Reddit). Publicly available social media posts were gathered from Facebook (2 groups) and Reddit (3 subreddits) and a coding system was developed based on the concept map of food parenting proposed by Vaughn et al. (2016). Based on the developed coding system, we coded posts into overarching food parenting practice constructs (coercive control: attempts to dominate, pressure or impose parents' will on child, structure: organization of child's environment to facilitate competence, autonomy support: supporting child's ability to self-regulate through allowing food choices, conversations about food, and a positive emotional climate) and recipes. We also coded posts dichotomously as including a question or advice-seeking. Differences in frequencies of food parenting constructs presented in posts on Facebook and Reddit were considered using chi-square tests of independence. Of the 2459 posts coded, 900 were related to food parenting (37%). In the subsample of 900, posts related to structure (43%) and recipes (40%) were the most frequent. Close to half of the posts (44%) included questions about food parenting. Frequency of food parenting topics in posts was related to social media platform, with coercive control and structure more frequently discussed on Reddit and recipes more commonly posted on Facebook. Results suggest that food parenting topics discuss on social media differ by platform, which can aid researchers and practitioners in targeting social media-based outreach to the topics of most interest for users. Findings give insight into the everyday food parenting topics and questions that parents and caregivers may be exposed to on social media. TAXONOMY: Development of Feeding; Parenting; Online Information Services.

A novel adaptive mixed reality system for stroke rehabilitation: principles, proof of concept, and preliminary application in 2 patients.

This article presents the principles of an adaptive mixed reality rehabilitation (AMRR) system, as well as the training process and results from 2 stroke survivors who received AMRR therapy, to illustrate how the system can be used in the clinic. The AMRR system integrates traditional rehabilitation practices with state-of-the-art computational and motion capture technologies to create an engaging environment to train reaching movements. The system provides real-time, intuitive, and integrated audio and visual feedback (based on detailed kinematic data) representative of goal accomplishment, activity performance, and body function during a reaching task. The AMRR system also provides a quantitative kinematic evaluation that measures the deviation of the stroke survivor's movement from an idealized, unimpaired movement. The therapist, using the quantitative measure and knowledge and observations, can adapt the feedback and physical environment of the AMRR system throughout therapy to address each participant's individual impairments and progress. Individualized training plans, kinematic improvements measured over the entire therapy period, and the changes in relevant clinical scales and kinematic movement attributes before and after the month-long therapy are presented for 2 participants. The substantial improvements made by both participants after AMRR therapy demonstrate that this system has the potential to considerably enhance the recovery of stroke survivors with varying impairments for both kinematic improvements and functional ability.

Food-Focused Media Literacy for Remotely Acculturating Adolescents and Mothers: A Randomized Controlled Trial of the "JUS Media? Programme".

PURPOSE: Unhealthy eating is a major modifiable risk factor for noncommunicable diseases and obesity, and remote acculturation to U.S. culture is a recently identified cultural determinant of unhealthy eating among adolescents and families in low/middle-income countries. This small-scale randomized controlled trial evaluated the efficacy of the "JUS Media? Programme," a food-focused media literacy intervention promoting healthier eating among remotely acculturating adolescents and mothers in Jamaica. METHODS: Gender-stratified randomization of 184 eligible early adolescents and mothers in Kingston, Jamaica (i.e., 92 dyads: Madolescent.age = 12.79 years, 51% girls) determined 31 "Workshops-Only" dyads, 30 "Workshops + SMS/texting" dyads, and 31 "No-Intervention-Control" dyads. Nutrition knowledge (food group knowledge), nutrition attitudes (stage of nutritional change), and nutrition behavior (24-hour recall) were primary outcomes assessed at four time points (T1/baseline, T2, T3, T4) across 5 months using repeated measures analysis of covariances. RESULTS: Compared to control, families in one or both intervention groups demonstrated significantly higher nutrition knowledge (T3 adolescents, T4 mothers: mean differences .79-1.08 on a 0-6 scale, 95% confidence interval [CI] .12-1.95, Cohen's ds = .438-.630); were more prepared to eat fruit daily (T3 adolescents and mothers: .36-.41 on a 1-5 scale, 95% CI .02-.77, ds = .431-.493); and were eating more cooked vegetables (T4 adolescents and T2 and T4 mothers: .20-.26 on a 0-1 scale, 95% CI -.03-.50, ds = .406-.607). Postintervention focus groups (6-month-delay) revealed major positive impacts on participants' health and lives more broadly. CONCLUSIONS: A food-focused media literacy intervention for remotely acculturating adolescents and mothers can improve nutrition. Replication in Jamaica and extension to the Jamaican diaspora would be useful.

Influencing Busy People in a Social Network.

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach.

Stimulating Contributions to Public Goods through Information Feedback: Some Experimental Results.

In traditional public good experiments participants receive an endowment from the experimenter that can be invested in a public good or kept in a private account. In this paper we present an experimental environment where participants can invest time during five days to contribute to a public good. Participants can make contributions to a linear public good by logging into a web application and performing virtual actions. We compared four treatments, with different group sizes and information of (relative) performance of other groups. We find that information feedback about performance of other groups has a small positive effect if we control for various attributes of the groups. Moreover, we find a significant effect of the contributions of others in the group in the previous day on the number of points earned in the current day. Our results confirm that people participate more when participants in their group participate more, and are influenced by information about the relative performance of other groups.

A computational framework for constructing interactive feedback for assisting motor learning.

New motion capture technologies are allowing detailed, precise and complete monitoring of movement through real-time kinematic analysis. However, a clinically relevant understanding of movement impairment through kinematic analysis requires the development of computational models that integrate clinical expertise in the weighing of the kinematic parameters. The resulting kinematics based measures of movement impairment would further need to be integrated with existing clinical measures of activity disability. This is a challenging process requiring computational solutions that can extract correlations within and between three diverse data sets: human driven assessment of body function, kinematic based assessment of movement impairment and human driven assessment of activity. We propose to identify and characterize different sensorimotor control strategies used by normal individuals and by hemiparetic stroke survivors acquiring a skilled motor task. We will use novel quantitative approaches to further our understanding of how human motor function is coupled to multiple and simultaneous modes of feedback. The experiments rely on a novel interactive tasks environment developed by our team in which subjects are provided with rich auditory and visual feedback of movement variables to drive motor learning. Our proposed research will result in a computational framework for applying virtual information to assist motor learning for complex tasks that require coupling of proprioception, vision audio and haptic cues. We shall use the framework to devise a computational tool to assist with therapy of stroke survivors. This tool will utilize extracted relationships in a pre-clinical setting to generate effective and customized rehabilitation strategies.

A low cost, adaptive mixed reality system for home-based stroke rehabilitation.

This paper presents a novel, low-cost, real-time adaptive multimedia environment for home-based upper extremity rehabilitation of stroke survivors. The primary goal of this system is to provide an interactive tool with which the stroke survivor can sustain gains achieved within the clinical phase of therapy and increase the opportunity for functional recovery. This home-based mediated system has low cost sensing, off the shelf components for the auditory and visual feedback, and remote monitoring capability. The system is designed to continue active learning by reducing dependency on real-time feedback and focusing on summary feedback after a single task and sequences of tasks. To increase system effectiveness through customization, we use data from the training strategy developed by the therapist at the clinic for each stroke survivor to drive automated system adaptation at the home. The adaptation includes changing training focus, selecting proper feedback coupling both in real-time and in summary, and constructing appropriate dialogues with the stroke survivor to promote more efficient use of the system. This system also allows the therapist to review participant's progress and adjust the training strategy weekly.

Mixed reality rehabilitation for stroke survivors promotes generalized motor improvements.

This paper presents results from a clinical study of stroke survivors using an adaptive, mixed-reality rehabilitation (AMRR) system for reach and grasp therapy. The AMRR therapy provides audio and visual feedback on the therapy task, based on detailed motion capture, that places the movement in an abstract, artistic context. This type of environment promotes the generalizability of movement strategies, which is shown through kinematic improvements on an untrained reaching task and higher clinical scale scores, in addition to kinematic improvements in the trained task.

An adaptive mixed reality training system for stroke rehabilitation.

This paper presents a novel mixed reality rehabilitation system used to help improve the reaching movements of people who have hemiparesis from stroke. The system provides real-time, multimodal, customizable, and adaptive feedback generated from the movement patterns of the subject's affected arm and torso during reaching to grasp. The feedback is provided via innovative visual and musical forms that present a stimulating, enriched environment in which to train the subjects and promote multimodal sensory-motor integration. A pilot study was conducted to test the system function, adaptation protocol and its feasibility for stroke rehabilitation. Three chronic stroke survivors underwent training using our system for six 75-min sessions over two weeks. After this relatively short time, all three subjects showed significant improvements in the movement parameters that were targeted during training. Improvements included faster and smoother reaches, increased joint coordination and reduced compensatory use of the torso and shoulder. The system was accepted by the subjects and shows promise as a useful tool for physical and occupational therapists to enhance stroke rehabilitation.