The feasibility of using pattern recognition software to measure the influence of computer use on the consultation

BACKGROUND: A key feature of a good general practice consultation is that it is patient-centred. A number of verbal and non-verbal behaviours have been identified as important to establish a good relationship with the patient. However, the use of the computer detracts the doctor's attention away from the patient, compromising these essential elements of the consultation. Current methods to assess the consultation and the influence of the computer on them are time consuming and subjective. If it were possible to measure these quantitatively, it could provide the basis for the first truly objective way of studying the influence of the computer on the consultation. The aim was to assess whether pattern recognition software could be used to measure the influence and pattern of computer use in the consultation. If this proved possible it would provide, for the first time, an objective quantitative measure of computer use and a measure of the attention and responsiveness of the general practitioner towards the patient. METHODS: A feasibility study using pattern recognition software to analyse a consultation was conducted. A web camera, linked to a data-gathering node was used to film a simulated consultation in a standard office. Members of the research team enacted the role of the doctor and the patient, using pattern recognition software to try and capture patient-centred, non-verbal behaviour. As this was a feasibility study detailed results of the analysis are not presented. RESULTS: It was revealed that pattern recognition software could be used to analyse certain aspects of a simulated consultation. For example, trigger lines enabled the number of times the clinician's hand covered the keyboard to be counted and wrapping recorded the number of times the clinician nodded his head. It was also possible to measure time sequences and whether the movement was brief or lingering. CONCLUSION: Pattern recognition software enables movements associated with patient-centredness to be recorded. Pattern recognition software has the potential to provide an objective, quantitative measure of the influence of the computer on the consultation

Nurse-patient interaction and communication: a systematic literature review

Aim: The purpose of this review is to describe the use and definitions of the concepts of nurse-patient interaction and nurse-patient communication in nursing literature. Furthermore, empirical findings of nurse-patient communication research will be presented, and applied theories will be shown. Method: An integrative literature search was executed. The total number of relevant citations found was 97. The search results were reviewed, and key points were extracted in a standardized form. Extracts were then qualitatively summarized according to relevant aspects and categories for the review. Results: The relation of interaction and communication is not clearly defined in nursing literature. Often the terms are used interchangeably or synonymously, and a clear theoretical definition is avoided or rather implicit. Symbolic interactionism and classic sender-receiver models were by far the most referred to models. Compared to the use of theories of adjacent sciences, the use of original nursing theories related to communication is rather infrequent. The articles that try to clarify the relation of both concepts see communication as a special or subtype of interaction. Conclusion: The included citations all conclude that communication skills can be learned to a certain degree. Involvement of patients and their role in communication often is neglected by authors. Considering the mutual nature of communication, patients’ share in conversation should be taken more into consideration than it has been until now. Nursing science has to integrate its own theories of nursing care with theories of communication and interaction from other scientific disciplines like sociology

Scenario Analysis as a Tool for Informing the Design of Behaviour Change Interventions

This article presents the design process behind the specification of a behaviour change intervention method to promote energy saving. The amount of energy used for food preparation is highly influenced by people’s behaviours. A user-centred design approach based on scenario analysis was applied to provide understanding of context of use and specification of user requirements. This knowledge was applied to the design of behaviour change interventions to motivate sustainable behaviours

Individual differences in face identity processing

We investigated the relationships between individual differences in different aspects of face-identity processing, using the Glasgow Face Matching Test (GFMT) as a measure of unfamiliar face perception, the Cambridge Face Memory Test (CFMT) as a measure of new face learning, and the Before They Were Famous task (BTWF) as a measure of familiar face recognition. These measures were integrated into two separate studies examining the relationship between face processing and other tasks. For Study 1 we gathered participants’ subjective ratings of their own face perception abilities. In Study 2 we used additional measures of perceptual and cognitive abilities, and personality factors to place individual differences in a broader context. Performance was significantly correlated across the three face-identity tasks in both studies, suggesting some degree of commonality of underlying mechanisms. For Study 1 the participants’ self-ratings correlated poorly with performance, reaching significance only for judgements of familiar face recognition. In Study 2 there were few associations between face tasks and other measures, with task-level influences seeming to account for the small number of associations present. In general, face tasks correlated with each other, but did not show an overall relation with other perceptual, cognitive or personality tests. Our findings are consistent with the existence of a general face-perception factor, able to account for around 25% of the variance in scores. However, other relatively task-specific influences are also clearly operating