Safety at work The objective of the project Safety at Work is to increase safety at the workplace by applying and combining state of the art artefacts from personal protective equipment and ambient intelligence technology. In this state of the art document we focus on the developments with respect to how (persuasive) technology can help to influence behaviour in a natural, automatic way in order to make industrial environments safer. We focus on personal safety, safe environments and safe behaviour. Direct ways to influence safety The most obvious way to influence behaviour is to use direct, physical measures. In particular, this is known from product design. The safe use of a product is related to the characteristics of the product (e.g., sharp edges), the condition of people operating the product (e.g., stressed or tired), the man-machine interface (e.g., intuitive or complex) and the environmental conditions while operating the product (e.g., noisy or crowded). Design guidelines exist to help designers to make safe products. A risk matrix can be made with two axis: product hazards versus personal characteristics. For each combination one might imagine what can go wrong, and what potential solutions are. Except for ‘design for safety’ in the sense of no sharp edges or a redundant architecture, there is a development called ‘safety by design’ as well. Safety by design is a concept that encourages construction or product designers to ‘design out’ health and safety risks during design development. On this topic, we may learn from the area of public safety. Crime Prevention Through Environmental Design (or Designing Out Crime) is a multi-disciplinary approach to deterring criminal behaviour through environmental design. Designing Out Crime uses measures like taking steps to increase (the perception) that people can be seen, limiting the opportunity for crime by taking steps to clearly differentiate between public space and private space, and promoting social control through improved proprietary concern. Senses Neuroscience has shown that we have very little insight into our motivations and, consequently, are poor at predicting our own behaviour. It seems emotions are an important predictor of our behaviour. Input from our senses are important for our emotional state, and therefore influence our behaviour in an ‘ambient’ (invisible) way. The first sense we focus on is sight. Sight encompasses the perception of light intensity (illuminance) and colours (spectral distribution). Several researchers have studied the effects of light and colour in working environments. Results show, e.g., that elderly people can be helped with higher light levels, that cool colours like blue and green have a relaxing effect, while long-wavelength colours such as orange and red are stimulating and give more arousal, and that concentration and motivation of pupils at school can be influenced with light and colour settings. Identically, sound (hearing) has physiological effects (unexpected sounds cause extra cortisol -the fight or flight hormone- and the opposite for soothing sounds), psychological effects (sounds effect our emotions), cognitive effects (sounds effect our concentration) and behavioural effects (the natural behaviour of people is to avoid unpleasant sounds, and embrace pleasurable sounds). Smell affects 75% of daily emotions and plays an important role in memory, itis also important as a warning for danger (gas, burning smell). Research has shown that smell can influence work performance. Haptic feedback is a relative new area of research, and most studies focus on haptic feedback on handheld and automotive devices. Finally, employers have a duty to take every reasonable precaution to protect workers from heat stress disorders. Influence mechanisms: Cialdini To influence behaviour, we may learn from marketing psychology. Robert Cialdini states that if we have to think about every decision
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Malnutrition is a serious and widespread health problem in community-dwelling older adults who receive care in hospital and at home. Hospital and home care nurses and nursing assistants have a key role in the delivery of high-quality multidisciplinary nutritional care. Nursing nutritional care in current practice, however, is still suboptimal, which impacts its quality and continuity. There appear to be at least two reasons for this. First, there is a lack of evidence for nutritional care interventions to be carried out by nurses. Second, there are several factors, that influence nurses’ and nursing assistants’ current behaviour, such as lack of knowledge, moderate awareness of the importance and neutral attitudes. This results in a lack of attention towards nutritional care. Therefore, there is a need to generate more evidence and to focus on targeting the factors that influence nurses’ and nursing assistants’ current behaviour to eventually promote behaviour change. To increase the likelihood of successfully changing their behaviour, an evidence-based educational intervention is appropriate. This might lead to enhancing nutritional care and positively impact nutritional status, health and well-being of community-dwelling older adults. The general objectives of this thesis are: 1) To understand the current state of evidence regarding nutrition-related interventions and factors that influence current behaviour in nutritional care for older adults provided by hospital and home care nurses and nursing assistants to prevent and treat malnutrition. 2) To develop an educational intervention for hospital and home care nurses and nursing assistants to promote behaviour change by affecting factors that influence current behaviour in nutritional care for older adults and to describe the intervention development and feasibility.
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.
