GOAL-SETTING CHARACTERISTICS OF NUTRITION-RELATED MHEALTH SYSTEMS: A MORPHOLOGICAL ANALYSIS

Setting and pursuing goals plays a major role in health behavior change. As an elementary component of interventions and mHealth apps, goals can support people in pursuing and attaining a desired outcome or behavior. Despite its widespread use and indicated effects on behavioral performance, there is no guidance on how to design and implement goal setting, planning and evaluation for mHealth nutrition promotion. We investigate goal setting and related components in the context of mHealth and health behavior change in a structured literature review. By utilizing morphological analysis, we develop a design framework for goal setting and pursuit. We validate and refine the framework by application on popular commercial nutrition apps. As a result, we identify the coverage of goal-setting and -pursuit characteristics as well as current gaps in the implementation of commercial mHealth nutrition apps, which offer the potential for future effective development of goal setting in mHealth nutrition promotion

Theory-driven Visual Design to Support Reflective Dietary Practice via mHealth: A Design Science Approach

Design for reflection in human-computer interaction (HCI) has evolved from focusing on an abstract and outcome-driven design subject towards exposing procedural or structural reflection characteristics. Although HCI research has recognized that an individual\u27s reflection is a long-lasting, multi-layered process that can be supported by meaningful design, researchers have made few efforts to derive insights from a theoretical perspective about appropriate translation into end-user visual means. Therefore, we synthesize theoretical knowledge from reflective practice and learning and argue for a differentiation between time contexts of reflection that design needs to address differently. In an interdisciplinary design-science-research project in the mHealth nutrition promotion context, we developed theory-driven guidelines for “reflection-in-action” and “reflection-on-action”. Our final design guidelines emerged from prior demonstrations and a final utility evaluation with mockup artifacts in a laboratory experiment with 64 users. Our iterative design and the resulting design guidelines offer assistance for addressing reflection design by answering reflective practice’s respective contextual requirements. Based on our user study, we show that reflection in terms of “reflection- in-action” benefits from offering actionable choice criteria in an instant timeframe, while “reflection-on-action” profits from the structured classification of behavior-related criteria from a longer, still memorable timeframe

Effects and challenges of using a nutrition assistance system: results of a long-term mixed-method study

Healthy nutrition contributes to preventing non-communicable and diet-related diseases. Recommender systems, as an integral part of mHealth technologies, address this task by supporting users with healthy food recommendations. However, knowledge about the effects of the long-term provision of health-aware recommendations in real-life situations is limited. This study investigates the impact of a mobile, personalized recommender system named Nutrilize. Our system offers automated personalized visual feedback and recommendations based on individual dietary behaviour, phenotype, and preferences. By using quantitative and qualitative measures of 34 participants during a study of 2–3 months, we provide a deeper understanding of how our nutrition application affects the users’ physique, nutrition behaviour, system interactions and system perception. Our results show that Nutrilize positively affects nutritional behaviour (conditional R2=. 342) measured by the optimal intake of each nutrient. The analysis of different application features shows that reflective visual feedback has a more substantial impact on healthy behaviour than the recommender (conditional R2=. 354). We further identify system limitations influencing this result, such as a lack of diversity, mistrust in healthiness and personalization, real-life contexts, and personal user characteristics with a qualitative analysis of semi-structured in-depth interviews. Finally, we discuss general knowledge acquired on the design of personalized mobile nutrition recommendations by identifying important factors, such as the users’ acceptance of the recommender’s taste, health, and personalization

Infants and Newborns with Atypical Teratoid Rhabdoid Tumors (ATRT) and Extracranial Malignant Rhabdoid Tumors (eMRT) in the EU-RHAB Registry: A Unique and Challenging Population

Malignant rhabdoid tumors (MRT) predominantly affect infants and young children. Patients below six months of age represent a particularly therapeutically challenging group. Toxicity to developing organ sites limits intensity of treatment. Information on prognostic factors, genetics, toxicity of treatment and long-term outcomes is sparse. Methods: Clinical, genetic, and treatment data of 100 patients (aged below 6 months at diagnosis) from 13 European countries were analyzed (2005–2020). Tumors and matching blood samples were examined for SMARCB1 mutations using FISH, MLPA and Sanger sequencing. DNA methylation subgroups (ATRT-TYR, ATRT-SHH, and ATRT-MYC) were determined using 450 k / 850 k-profiling. Results: A total of 45 patients presented with ATRT, 29 with extracranial, extrarenal (eMRT) and 9 with renal rhabdoid tumors (RTK). Seventeen patients demonstrated synchronous tumors (SYN). Metastases (M+) were present in 27% (26/97) at diagnosis. A germline mutation (GLM) was detected in 55% (47/86). DNA methylation subgrouping was available in 50% (31 / 62) with ATRT or SYN; for eMRT, methylation-based subgrouping was not performed. The 5-year overall (OS) and event free survival (EFS) rates were 23.5 ± 4.6% and 19 ± 4.1%, respectively. Male sex (11 ± 5% vs. 35.8 ± 7.4%), M+ stage (6.1 ± 5.4% vs. 36.2 ± 7.4%), presence of SYN (7.1 ± 6.9% vs. 26.6 ± 5.3%) and GLM (7.7 ± 4.2% vs. 45.7 ± 8.6%) were significant prognostic factors for 5-year OS. Molecular subgrouping and survival analyses confirm a previously described survival advantage for ATRT-TYR. In an adjusted multivariate model, clinical factors that favorably influence the prognosis were female sex, localized stage, absence of a GLM and maintenance therapy. Conclusions: In this cohort of homogenously treated infants with MRT, significant predictors of outcome were sex, M-stage, GLM and maintenance therapy. We confirm the need to stratify which patient groups benefit from multimodal treatment, and which need novel therapeutic strategies. Biomarker-driven tailored trials may be a key option

Infants and newborns with Atypical Teratoid Rhabdoid Tumors (ATRT) and Extracranial Malignant Rhabdoid Tumors (eMRT) in the EU-RHAB registry: a unique and challenging population

SIMPLE SUMMARY: Malignant rhabdoid tumors (MRT) are deadly tumors that predominantly affect infants and young children. Even when considering the generally young age of these patients, the treatment of infants below the age of six months represents a particular challenge due to the vulnerability of this patient population. The aim of our retrospective study was to assess the available information on prognostic factors, genetics, toxicity of treatment and long-term outcomes of MRT. We confirmed that, in a cohort of homogenously treated infants with MRT, significant predictors of outcome were female sex, localized stage, absence of a GLM and maintenance therapy, and these significantly favorably influence prognosis. Stratification-based biomarker-driven tailored trials may be a key option to improve survival rates. ABSTRACT: Introduction: Malignant rhabdoid tumors (MRT) predominantly affect infants and young children. Patients below six months of age represent a particularly therapeutically challenging group. Toxicity to developing organ sites limits intensity of treatment. Information on prognostic factors, genetics, toxicity of treatment and long-term outcomes is sparse. Methods: Clinical, genetic, and treatment data of 100 patients (aged below 6 months at diagnosis) from 13 European countries were analyzed (2005–2020). Tumors and matching blood samples were examined for SMARCB1 mutations using FISH, MLPA and Sanger sequencing. DNA methylation subgroups (ATRT-TYR, ATRT-SHH, and ATRT-MYC) were determined using 450 k / 850 k-profiling. Results: A total of 45 patients presented with ATRT, 29 with extracranial, extrarenal (eMRT) and 9 with renal rhabdoid tumors (RTK). Seventeen patients demonstrated synchronous tumors (SYN). Metastases (M+) were present in 27% (26/97) at diagnosis. A germline mutation (GLM) was detected in 55% (47/86). DNA methylation subgrouping was available in 50% (31 / 62) with ATRT or SYN; for eMRT, methylation-based subgrouping was not performed. The 5-year overall (OS) and event free survival (EFS) rates were 23.5 ± 4.6% and 19 ± 4.1%, respectively. Male sex (11 ± 5% vs. 35.8 ± 7.4%), M+ stage (6.1 ± 5.4% vs. 36.2 ± 7.4%), presence of SYN (7.1 ± 6.9% vs. 26.6 ± 5.3%) and GLM (7.7 ± 4.2% vs. 45.7 ± 8.6%) were significant prognostic factors for 5-year OS. Molecular subgrouping and survival analyses confirm a previously described survival advantage for ATRT-TYR. In an adjusted multivariate model, clinical factors that favorably influence the prognosis were female sex, localized stage, absence of a GLM and maintenance therapy. Conclusions: In this cohort of homogenously treated infants with MRT, significant predictors of outcome were sex, M-stage, GLM and maintenance therapy. We confirm the need to stratify which patient groups benefit from multimodal treatment, and which need novel therapeutic strategies. Biomarker-driven tailored trials may be a key option

Genetic landscape of congenital insensitivity to pain and hereditary sensory and autonomic neuropathies

Congenital insensitivity to pain (CIP) and hereditary sensory and autonomic neuropathies (HSAN) are clinically and genetically heterogeneous disorders exclusively or predominantly affecting the sensory and autonomic neurons. Due to the rarity of the diseases and findings based mainly on single case reports or small case series, knowledge about these disorders is limited. Here, we describe the molecular workup of a large international cohort of CIP/HSAN patients including patients from normally under-represented countries. We identify 80 previously unreported pathogenic or likely pathogenic variants in a total of 73 families in the >20 known CIP/HSAN-associated genes. The data expand the spectrum of disease-relevant alterations in CIP/HSAN, including novel variants in previously rarely recognized entities such as ATL3-, FLVCR1- and NGF-associated neuropathies and previously under-recognized mutation types such as larger deletions. In silico predictions, heterologous expression studies, segregation analyses and metabolic tests helped to overcome limitations of current variant classification schemes that often fail to categorize a variant as disease-related or benign. The study sheds light on the genetic causes and disease-relevant changes within individual genes in CIP/HSAN. This is becoming increasingly important with emerging clinical trials investigating subtype or gene-specific treatment strategies

The Nachtlichter app: a citizen science tool for documenting outdoor light sources in public space

The relationship between satellite based measurements of city radiance at night and the numbers and types of physical lights installed on the ground is not well understood. Here we present the "Nachtlichter app", which was developed to enable citizen scientists to classify and count light sources along street segments over large spatial scales. The project and app were co-designed: citizen scientists played key roles in the app development, testing, and recruitment, as well as in analysis of the data. In addition to describing the app itself and the data format, we provide a general overview of the project, including training materials, data cleaning, and the result of some basic data consistency checks

Discourse analysis of environmental policy revisited: traditions, trends, perspectives : Introduction

Since the mid-1990s, discourse analysis has become an increasingly established framework in environmental policy analysis. The field has diversified in terms of conceptual approaches, methods, topics, and geographies. This special issue revisits trends and traditions regarding theoretical and methodological approaches, ‘old’ and ‘new’ discourses, and our knowledge about discursive effects. We contextualize and discuss the twelve contributions to this special issue against the broader trajectory of the field over the past 25 years. Our analysis reveals an abundance of theoretical approaches with limited cross-fertilization, a plethora of rich case studies but few attempts at meta-analysis, and subtle accounts of discursive effects on discourse, policy and practice without an overarching framework. We suggest seven directions for the field’s future evolution: a need for more comparative and multiple-case studies, theoretical cross-fertilization, pro-active integration of non-English-speaking research contexts, development of methodological capabilities to capture discursive developments across larger numbers of publics and policy arenas, a more explicit conceptualization of agency, power and materiality, a stronger collaboration with transdisciplinary approaches, and a reflexive engagement with the ‘critical’ ambition of discourse analysis

Can an Automated Personalized Nutrition Assistance System Successfully Change Nutrition Behavior? - Study Design

Despite a multitude of existing dietary guidelines, the rise of the number of people suffering from a diet-related disease occurs on a yearly basis. Studies show that the response to different diets varies individually, calling for more personalized measures available at any time in any context. Therefore, this paper proposes a research design based on a smartphone app, that delivers automated, personalized dietary recommendations, to encourage a healthier nutrition lifestyle. Founding on previous research in computer and nutritional science, we propose 6 different intervention factors: (1) type of dietary recommendations, (2) dietary assessment, (3) tracking of physical activity via smartphones or smart activity trackers, (4) feedback with visualization of personal nutritional data, (5) feedback with textual explanations behind recommendations, and (6) dietary recommendations including blood values. In an extensive 6-month field study, we plan to examine which of the factors influence a healthier behavior change and long-term app engagement most

A Conversational & Reflective Approach for Dietary Logging with the Food Pyramid: Chatbot RAINA

Mobile health (mHealth) applications have the potential to assist users in tracking and monitoring their behavior with the goal of raising awareness and finally supporting a healthier lifestyle. However, current nutrition-related applications mainly support weight loss through calorie counting rather than focusing on a balanced, healthy diet. In this work, we develop a chatbot that follows a more holistic approach to tracking and monitoring one’s diet. It incorporates the principles of a food pyramid to track a personal diet via free-text input and reflect on it via visual feedback. In a seven-day user study with 18 participants, we assess the user engagement and experience by analyzing usage data and results from a pre-/post-study questionnaire. Our results provide first promising insights into the user perceptions of this alternative approach regarding usability and usefulness, nutrition self-efficacy, reflective thinking, health consciousness, as well as intentions and recommendations for future use