Search results

The purpose of this paper is to discuss an online sensor-based support system which the authors believe can be useful in such scenarios. Persons with a cognitive impairment, such as those with Alzheimer’s disease, suffer from deficiencies in cognitive skills which reduce their independence; such patients can benefit from the provision of further assistance such as reminders for carrying out instrumental activities of daily living (IADLs).

The system proposed processes data from a network of sensors that have the capability of sensing user interactions and on-going IADLs in the living environment itself. A probabilistic learning model is built that computes joint probability distributions over different activities representing users’ behavioural patterns in performing activities. This probability model can underpin an intervention framework that prompts the user with the next step in the IADL when inactivity is being observed. This prompt for the next step is inferred from the conditional probability taken into consideration the IADL steps that have already been completed, in addition to contextual information relating to the time of day and the amount of time already spent on the activity. The originality of the work lies in combining partially observed sensor sequences and duration data associated with the IADLs. The prediction of the next step is then adjusted as further steps are completed and more time is spent towards the completion of the activity, thus updating the confidence that the prediction is correct. A reminder is only issued when there has been sufficient inactivity on the part of the patient and the confidence is high that the prediction is correct.

The results of this study verify that by including duration information the prediction accuracy of the model is increased and the confidence level for the next step in the IADL is also increased. As such, there is approximately a 10 per cent rise in the prediction performance in the case of single sensor activation in comparison to an alternative approach which did not consider activity durations.

Duration information to a certain extent has been widely ignored by activity recognition researchers and has received a very limited application within smart environments.

This study concludes that incorporating progressive duration information into partially observed sensor sequences of IADLs has the potential to increase performance of a reminder system for patients with a cognitive impairment, such as Alzheimer’s disease.

This paper aims to discuss an online sensor-based support system which is believed to be useful for persons with a cognitive impairment, such as those with Alzheimer’s disease, suffering from deficiencies in cognitive skills which reduce their independence. Such patients can benefit from the provision of further assistance such as reminders for carrying out instrumental activities of daily living (iADLs).

The system proposed processes data from a network of sensors that have the capability of sensing user interactions and ongoing iADLs in the living environment itself. A probabilistic learning model is built that computes joint probability distributions over different activities representing users’ behavioural patterns in performing activities. This probability model can underpin an intervention framework that prompts the user with the next step in the iADL when inactivity is being observed. This prompt for the next step is inferred from the conditional probability, taking into consideration the iADL steps that have already been completed, in addition to contextual information relating to the time of day and the amount of time already spent on the activity. The originality of the work lies in combining partially observed sensor sequences and duration data associated with the iADLs. The prediction of the next step is then adjusted as further steps are completed and more time is spent towards the completion of the activity; thus, updating the confidence that the prediction is correct. A reminder is only issued when there has been sufficient inactivity on the part of the patient and the confidence is high that the prediction is correct.

The results verify that by including duration information, the prediction accuracy of the model is increased, and the confidence level for the next step in the iADL is also increased. As such, there is approximately a 10 per cent rise in the prediction performance in the case of single-sensor activation in comparison to an alternative approach which did not consider activity durations. Thus, it is concluded that incorporating progressive duration information into partially observed sensor sequences of iADLs has the potential to increase performance of a reminder system for patients with a cognitive impairment, such as Alzheimer’s disease.

Activity duration information can be a potential feature in measuring the performance of a user and distinguishing different activities. The results verify that by including duration information, the prediction accuracy of the model is increased, and the confidence level for the next step in the activity is also increased. The use of duration information in online prediction of activities can also be associated to monitoring the deterioration in cognitive abilities and in making a decision about the level of assistance required. Such improvements have significance in building more accurate reminder systems that precisely predict activities and assist its users, thus, improving the overall support provided for living independently.

This innovative analysis aims to quantify the use of evaluation criteria in telemedicine and to identify current trends in metric adoption. The focus is to determine the frequency of actual performance metric reporting in telemedicine evaluation, in contrast to systematic reviews where assessment of study quality is the goal.

Automated literature search identified telemedicine studies reporting quantitative performance metrics. Studies were classified by telemedicine class; store‐and‐forward (SAF), real‐time consultation (RTC) and telecare (TC), and study stage. Studies were scanned for evaluation metric reporting, i.e. clinical outcomes, satisfaction, patient quality and cost measures.

Evaluation metric use was compared among telemedicine classes, and between pilot and routine use stages. Diagnostic accuracy was reported significantly more frequently in pilots for RTC and TC. Cost measures were more frequently reported in routine use for TC. Clinical effectiveness and hospital attendance were better reported in routine use for SAF. Comparison also revealed different evaluation strategies. In pilots, SAF favoured diagnostic accuracy, compared to RTC and TC. TC preferred clinical effectiveness evaluations and TC more frequently assessed patient satisfaction. Cost was only reported in less than 20 per cent of studies, but most frequently in RTC. Routine use led to increased reporting of all metrics, except diagnostic accuracy. Clinical effectiveness reporting increased significantly with routine use for RTC and SAF, but declined for TC.

Clinical outcomes and patient satisfaction were reported frequently in telemedicine studies, but reporting of other performance metrics was rare. Understanding current trends in metric reporting will facilitate better design of future telemedicine evaluations.

In recent years, organisations around the world have been seriously affected by a range of economic, political and social upheavals that have gathered momentum in most parts of the globe. The viability of the conventional (pyramidal) organisational structures is being challenged in conjunction with major shifts in the roles of mid and top managers. In many countries, the pace of the above socio‐economic events and uncertainties is happening at an unprecedented pace. Some markets are showing signs of potential gigantic expansions while others (historically prosperous) are on the verge of complete collapse (Dent, 1991). In responding to the socio‐economic challenges of the nineties, organisations (across the board) have resorted to dismantling the conventional pyramidal structure and adopting so‐called “leaner” structures (see Zeffane, 1992). The most common struggle has been to maintain market share in an economic environment increasingly characterised by excess labour supply (Bamber, 1990; Green & Macdonald, 1991). As organisations shifted their strategies from “mass production” to “post‐fordism” (see, for example Kern and Schumann, 1987), there has been a significant tendency to emphasise flexibility of both capital and labour in order to cater for the niche markets which are claimed to be rapidly emerging, world‐wide. This has resulted in massive organisational restructuring world‐wide.

The purpose of this paper is to explore how young people who offend with others define delinquent and criminal groups and consider the social risk factors associated with gang membership and criminal exploitation.

The sample consisted of 15 young people who were purposively sampled from a group of 14- to 17-year-old males who had been identified as at risk of gang involvement and referred to a community-based programme. Using a social identity framework, a thematic analysis was undertaken to investigate how the participants viewed their role in offending as part of a group.

The participants identified peer groups, street gangs and the involvement of adult criminals as distinct categories of offending groups. Unlike prior models for gang involvement, some members of the sample were involved in multiple groups to perform different categories of crime. Importantly, participants displayed an awareness of exploitation and described successful exit strategies from criminal groups.

Understanding how young people who are involved in delinquent behaviour and offending define gang and group offending.

The implications for gang and group offending prevention and intervention programmes are discussed.

The literature on child criminal exploitation and UK drug markets is in its infancy. This paper offers further evidence for the processes of joining and leaving delinquent and criminal groups.

The purpose of this paper is to provide background to this special issue and consider how critically oriented research can be applied to health and social care management.

Basic principles of critical management studies are introduced briefly to frame subsequent papers in this issue.

In order to identify the wicked problems and darker sides of the care field, there is a need to study things in alternative ways through critical lenses. Giving a voice to those in less powerful positions may result in redefinition and redesign of conventional roles and agency of patients, volunteers and professionals and call into question the taken-for-granted understanding of health and social care management.

The special issue as a whole was designed to enhance critical approaches to the discussion in the field of health and social care. This editorial hopefully raises awareness of CMS and serves as an opening for further discussion on critical views in the research on management and organization in this field.

To the best of our knowledge, the studies on determining adherence to the Mediterranean dietary pattern (MDP) in Iran as a non-Mediterranean country are scarce. Thus, the aim of the study is to determine the adherence to the MDP in a sample of female adolescents who are residents of Tehran, Iran.

In this cross-sectional study, 263 female adolescents aged 15-18 years were studied. Information on socio-demographic, lifestyle and anthropometric variables were obtained using a structured questionnaire. Also, dietary intakes were determined using a validated 168-item food frequency questionnaire. Adherence to MDP was characterized using Mediterranean-style dietary pattern score (MSDPS).

Typically, the mean ± SD MSDPS was low in the present study (15.9 ± 5.6). The mean ± SD age and body mass index of the study population was 16.2 ± 0.9 years and 22.2 ± 4.1 kg/m², respectively. In this study, the maximum MSDPS was 34.3, which was only one-third of maximum possible score (100). Multiple linear regression analyses showed that higher MSDPS scores were positively associated with age (standardized β = 0.1; p = 0.006), higher energy intake (standardized β = 0.2; p < 0.001) and marginally higher physical activity (standardized β = 0.1; p = 0.079).

Understanding low adherence to MDP in Tehranian female adolescents can provide basic knowledge to launch systematic programmes for gravitation toward MDP.

The purpose of this paper was to evaluate the impact of a competition-based intervention combining high-resolution electricity feedback, incentives, information and prompts on college dormitory residents’ energy consumption and participation in demand response events. The authors also investigated changes in individual-level pro-environmental behaviors and examined psychosocial correlates of behavior change.

Residents of 39 suites in a freshman residence hall competed against one another to reduce energy consumption and win prizes as part of a three-week competition. Feedback was provided in near real-time at the suite-level via an interactive touch-screen kiosk. Participants also completed baseline and follow-up surveys.

Electricity use among all suites was approximately 6.4 per cent lower during the competition period compared to baseline, a significant reduction. Additionally, participants reported engaging in various pro-environmental behaviors significantly more frequently during the competition relative to baseline. Changes in pro-environmental behavior were associated with changes in level of group identification and perceived social norms.

In three weeks, dormitory residents saved 3,158 kWh of electricity compared to baseline – the equivalent of more than 3,470 pounds of carbon dioxide emissions. The findings provide evidence that real-time feedback, combined with incentives, information and prompts, can motivate on-campus residents to reduce energy consumption.

The authors contribute to a limited body of evidence supporting the effectiveness of dorm energy competitions in motivating college students to save energy. In addition, the authors identified individual-level behavioral and psychosocial changes made during such an intervention. University residential life planners may also use the results of this research to inform student programming.