Making Space a better Place: Just In Time Adaptive Interventions for Healthy Lifestyles

Just In Time Adaptive Interventions (JITAI) are a class of applications that provide tailored support at the right time and place to help people to maintain a healthy lifestyle. This paper presents the initial version of a JITAI application that helps users to make healthy food choices when walking in an urban environment. The app provides interventions based on location, time, and user characteristics. It adapts its interventions based on the type and goal of a user. The JITAI consist of an app for a mobile phone and a backend server. Using the backend, decision points and interventions can be managed as well as users. Moreover, it stores tracks and intervention data. A two-phased experiment will be set-up. The first phase will test the robustness and functionality of the application with a limited number of users. Based on this, the app will be adapted. The second phase will test the effectiveness of the different type of interventions by involving a large user group

Multi-Domain Screening:Identification of Patient’s Risk Profile Prior to Head-and-Neck Cancer Treatment

Background: Head-and-neck cancer (HNC) can give rise to oropharyngeal dysphagia (OD), malnutrition, sarcopenia, and frailty. Early identification of these phenomena in newly diagnosed HNC patients is important to reduce the risk of complications and to improve treatment outcomes. The aim of this study was (1) to determine the prevalence of the risk of OD, malnutrition, sarcopenia, and frailty; and (2) to investigate the relation between these phenomena and patients’ age, performance status, and cancer group staging. Methods: Patients (N = 128) underwent multi-domain screening consisting of the Eating Assessment Tool-10 for OD, Short Nutritional Assessment Questionnaire and BMI for malnutrition, Short Physical Performance Battery and Hand Grip Strength for sarcopenia, and Distress Thermometer and Maastricht Frailty Screening Tool for frailty. Results: 26.2%, 31.0%, 73.0%, and 46.4% of the patients were at risk for OD, malnutrition, sarcopenia, or frailty, respectively. Patients with an advanced cancer stage had a significantly higher risk of OD and high levels of distress prior to cancer treatment. Conclusions: This study identified the risk profile of newly diagnosed HNC patients using a standardized ‘quick and easy’ multi-domain screening prior to cancer treatment.</p

Mindful Eating Behavior Scale (MEBS)

The Mindful Eating Behavior Scale (MEBS) (Winkens et al., J Acad Nutr Diet 118(7):1277–1290, 2018) is a 17-item self-report scale to assess the attention element of mindful eating. The MEBS was developed to make it possible to measure mindful eating in common situations and independent from emotional or external eating. The MEBS consists of four domains: Focused Eating (5 items), Eating in response to Hunger and Satiety Cues (5 items), Eating with Awareness (3 items), and Eating Without Distraction (4 items). The MEBS was validated in a representative sample of 1,227 Dutch adults aged 55 years and older. The final confirmatory factor analysis model showed good fit (comparative fit index = 0.97, Tucker–Lewis index = 0.96, and root mean square error of approximation = 0.04). Measurement invariance was found for sex, age, and body mass index. Cronbach’s α values were medium to high (0.70–0.89). Most correlations were in the expected directions, which indicated good preliminary convergent validity. It is recommended to calculate scores on the separate domains rather than a total score combining the four domains due to low inter-factor correlations between these domains. In contrast to previous mindful eating scales, the MEBS makes it possible to disentangle mindful eating from other eating behaviors. This offers the possibility to advance the research into mindful eating, as it then becomes possible to study mechanisms. This is also useful for applied settings as it makes it possible to better match the treatment to the needs of the individual

Dysfunctional Timing in Traumatic Brain Injury Patients:Co-occurrence of Cognitive, Motor, and Perceptual Deficits

Timing is an essential part of human cognition and of everyday life activities, such as walking or holding a conversation. Previous studies showed that traumatic brain injury (TBI) often affects cognitive functions such as processing speed and time-sensitive abilities, causing long-term sequelae as well as daily impairments. However, the existing evidence on timing capacities in TBI is mostly limited to perception and the processing of isolated intervals. It is therefore open whether the observed deficits extend to motor timing and to continuous dynamic tasks that more closely match daily life activities. The current study set out to answer these questions by assessing audio motor timing abilities and their relationship with cognitive functioning in a group of TBI patients (n = 15) and healthy matched controls. We employed a comprehensive set of tasks aiming at testing timing abilities across perception and production and from single intervals to continuous auditory sequences. In line with previous research, we report functional impairments in TBI patients concerning cognitive processing speed and perceptual timing. Critically, these deficits extended to motor timing: The ability to adjust to tempo changes in an auditory pacing sequence was impaired in TBI patients, and this motor timing deficit covaried with measures of processing speed. These findings confirm previous evidence on perceptual and cognitive timing deficits resulting from TBI and provide first evidence for comparable deficits in motor behavior. This suggests basic co-occurring perceptual and motor timing impairments that may factor into a wide range of daily activities. Our results thus place TBI into the wider range of pathologies with well-documented timing deficits (such as Parkinson’s disease) and encourage the search for novel timing-based therapeutic interventions (e.g., employing dynamic and/or musical stimuli) with high transfer potential to everyday life activities

Relative Validity of the HELIUS Food Frequency Questionnaire for Measuring Dietary Intake in Older Adult Participants of the Longitudinal Aging Study Amsterdam

The aim of this study was to determine the relative validity of the HEalthy LIfe in an Urban Setting (HELIUS) food frequency questionnaire (FFQ) in assessing the dietary intake of energy, nutrients, and food groups of Dutch older men and women. In 2014-2015, 88 participants of the Longitudinal Aging Study Amsterdam aged 71.9 (SD 8.6) years completed the 238-item HELIUS FFQ and three 24-hour dietary recalls. The mean group-level bias in the intakes of energy, nutrients, and food groups between the two methods was assessed, as well as Pearson's correlation coefficients and level of agreement using quintile distribution. For the intakes of energy and macronutrients, the group-level bias was ≤5%, Pearson's correlation coefficients were moderate to good (ranging from 0.26 for total fat to 0.72 for alcohol), and agreement was moderate to high (classification in same or adjacent quintile ranging from 63% for energy, protein, and carbohydrate to 91% for alcohol). For most micronutrients and food groups, the relative validity was moderate (Pearson's correlation coefficients between 0.3 and 0.5), with the lowest correlations for β-carotene (0.08), vitamin B1 (0.19), fish (0.14), and grains (0.24). In conclusion, for energy and macronutrients, most micronutrients, and most food groups, the relative validity of the HELIUS FFQ to assess dietary intake in Dutch older adults was acceptable to good.</p

Associations of depressive symptoms and history with three a priori diet quality indices in middle-aged and older adults

Background: Evidence for the diet-depression link is growing but longitudinal studies on the reverse association are scarce. We investigated associations of (1) current depressive symptoms, (2) short-term changes in and (3) long-term history of depressive symptoms with three a priori diet quality indices. Methods: Data were from participants (≥ 55 years) of the Longitudinal Aging Study Amsterdam (LASA). The Mediterranean Diet Score (MDS), Alternative Healthy Eating Index (AHEI-2010) and Dietary Approaches to Stop Hypertension diet (DASH) were derived in 2014/2015. Depressive symptoms (Center for Epidemiologic Studies Depression scale; CES-D) were assessed in 2014/2015 and at five regular 3-yearly cycles from 2001–2003 to 2015/2016. Associations between three depression determinants and the diet indices were analysed by multivariable linear regression models. Results: Cross-sectionally (n = 1312), current depressive symptoms (CES-D ≥ 16) were associated with lower MDS (adjusted B = −1.21, 95%CI = −2.41, −0.023) and AHEI (B = −2.72, 95%CI = −5.24, −0.20) scores in men only. Chronic/recurrent depressive symptoms (CES-D ≥ 16 in both 2011–2013 and 2015/2016) were associated with lower MDS scores (n = 1233; B = −2.22, 95%CI = −3.40, −1.04) and a trend for lower AHEI scores (B = −2.37, 95%CI = −4.92, 0.18), compared to no depressive symptoms (twice CES-D < 16). History of depressive symptoms (ever CES-D ≥ 16 from 2001–2003 to 2011–2013; n = 687) was associated with lower MDS (B = −1.87, 95%CI = −3.47, −0.27) and AHEI (B = −4.33, 95%CI = −7.54, −1.13) scores in men only. No associations were found with the DASH score. Limitations: Single dietary data collection impeded investigation of prospective depression-diet associations. Conclusions: Our study in middle-aged and older adults suggests that current and past depressive symptoms are associated with poorer diet quality, particularly in men

Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies

Background: Globally, 81% of youth do not meet the physical activity (PA) guidelines. Youth of families with a low socioeconomic position are less likely to meet the recommended PA guidelines. Mobile health (mHealth) interventions are preferred by youth over traditional in-person approaches and are in line with their media preferences. Despite the promise of mHealth interventions in promoting PA, a common challenge is to engage users in the long term or effectively. Earlier reviews highlighted the association of different design features (eg, notifications and rewards) with engagement among adults. However, little is known about which design features are important for increasing engagement among youth.Objective: To inform the design process of future mHealth tools, it is important to investigate the design features that can yield effective user engagement. This systematic review aimed to identify which design features are associated with engagement in mHealth PA interventions among youth who were aged between 4 and 18 years.Methods: A systematic search was conducted in EBSCOhost (MEDLINE, APA PsycINFO, and Psychology & Behavioral Sciences Collection) and Scopus. Qualitative and quantitative studies were included if they documented design features associated with engagement. Design features and related behavior change techniques and engagement measures were extracted. Study quality was assessed according to the Mixed Method Assessment Tool, and one-third of all screening and data extraction were double coded by a second reviewer.Results: Studies (n=21) showed that various features were associated with engagement, such as a clear interface, rewards, multiplayer game mode, social interaction, variety of challenges with personalized difficulty level, self-monitoring, and variety of customization options among others, including self-set goals, personalized feedback, progress, and a narrative. In contrast, various features need to be carefully considered while designing mHealth PA interventions, such as sounds, competition, instructions, notifications, virtual maps, or self-monitoring, facilitated by manual input. In addition, technical functionality can be considered as a prerequisite for engagement. Research addressing youth from low socioeconomic position families is very limited with regard to engagement in mHealth apps.Conclusions: Mismatches between different design features in terms of target group, study design, and content translation from behavior change techniques to design features are highlighted and set up in a design guideline and future research agenda