Zoekresultaten

The identification of synthetic drug laboratories based on the detection of precursors

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Digital health interventions to improve eating behaviour of people with a lower socioeconomic position: a scoping review of behaviour change techniques

Specific approaches are needed to reach and support people with a lower socioeconomic position (SEP) to achieve healthier eating behaviours. There is a growing body of evidence suggesting that digital health tools exhibit potential to address these needs because of its specific features that enable application of various behaviour change techniques (BCTs). The aim of this scoping review is to identify the BCTs that are used in diet-related digital interventions targeted at people with a low SEP, and which of these BCTs coincide with improved eating behaviour. The systematic search was performed in 3 databases, using terms related to e/m-health, diet quality and socioeconomic position. A total of 17 full text papers were included. The average number of BCTs per intervention was 6.9 (ranged 3–15). BCTs from the cluster ‘Goals and planning’ were applied most often (25x), followed by the clusters ‘Shaping knowledge’ (18x) and ‘Natural consequences’ (18x). Other frequently applied BCT clusters were ‘Feedback and monitoring’ (15x) and ‘Comparison of behaviour’ (13x). Whereas some BCTs were frequently applied, such as goal setting, others were rarely used, such as social support. Most studies (n = 13) observed a positive effect of the intervention on eating behaviour (e.g. having breakfast) in the low SEP group, but this was not clearly associated with the number or type of applied BCTs. In conclusion, more intervention studies focused on people with a low SEP are needed to draw firm conclusions as to which BCTs are effective in improving their diet quality. Also, further research should investigate combinations of BCTs, the intervention design and context, and the use of multicomponent approaches. We encourage intervention developers and researchers to describe interventions more thoroughly, following the systematics of a behaviour change taxonomy, and to select BCTs knowingly.

A Systematic review on Commercially Available Integrated Systems for Forensic DNA Analysis

This systematic review describes and discusses three commercially available integrated systems for forensic DNA analysis, i.e., ParaDNA, RapidHIT, and ANDE. A variety of aspects, such as performance, time-to-result, ease-of-use, portability, and costs (per analysis run) of these three (modified) rapid DNA analysis systems, are considered. Despite their advantages and developmental progress, major steps still have to be made before rapid systems can be broadly applied at crime scenes for full DNA profiling. Aspects in particular that need (further) improvement are portability, performance, the possibility to analyze a (wider) variety of (complex) forensic samples, and (cartridge) costs. Moreover, steps forward regarding ease-of-use and time-to-result will benefit the broader use of commercial rapid DNA systems. In fact, it would be a profit if rapid DNA systems could be used for full DNA profile generation as well as indicative analyses that can give direction to forensic investigators which will speed up investigations.

Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity

Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing. Objective: First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field. Methods: A scoping review was conducted based on the framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given. Results: In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages. Conclusions: The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.

Towards a core-set of mobility measures in ageing research

BACKGROUND: Mobility is a key determinant and outcome of healthy ageing but its definition, conceptual framework and underlying constructs within the physical domain may need clarification for data comparison and sharing in ageing research. This study aimed to (1) review definitions and conceptual frameworks of mobility, (2) explore agreement on the definition of mobility, conceptual frameworks, constructs and measures of mobility, and (3) define, classify and identify constructs.METHODS: A three-step approach was adopted: a literature review and two rounds of expert questionnaires (n = 64, n = 31, respectively). Agreement on statements was assessed using a five-point Likert scale; the answer options 'strongly agree' or 'agree' were combined. The percentage of respondents was subsequently used to classify agreements for each statement as: strong (≥ 80%), moderate (≥ 70% and < 80%) and low (< 70%).RESULTS: A variety of definitions of mobility, conceptual frameworks and constructs were found in the literature and among respondents. Strong agreement was found on defining mobility as the ability to move, including the use of assistive devices. Multiple constructs and measures were identified, but low agreements and variability were found on definitions, classifications and identification of constructs. Strong agreements were found on defining physical capacity (what a person is maximally capable of, 'can do') and performance (what a person actually does in their daily life, 'do') as key constructs of mobility.CONCLUSION: Agreements on definitions of mobility, physical capacity and performance were found, but constructs of mobility need to be further identified, defined and classified appropriately. Clear terminology and definitions are essential to facilitate communication and interpretation in operationalising the physical domain of mobility as a prerequisite for standardisation of mobility measures.

Relaxing or exciting? Mobile emotion recording in natural settings.