Gamifying collective intelligence for the common good

The rise of the mobile internet enables the creation of applications that provide new and easier ways for people to organise themselves, raise issues, take action and interact with their city. At the same time, society faces new problems that can only be solved when citizens work together. Nevertheless, a lack of motivation or knowledge often prevents many citizens from regularly contributing to the common good. In this position paper, we present DoGood – a mobile app – as a socio-technological system that aims at supporting the collective intelligence of citizens in their pursuit of civic engagement and civic collaboratories. Our study asks to what extent gamification can motivate users to “do good” deeds. The DoGood app uses gamified elements to encourage citizens to submit and promote their civic activities as well as to join the activities of others. Gamification is sometimes criticised for simply adding a limited number of game elements, such as leaderboards, on top of an existing experience with the hope of increasing motivation. However, in the case of the DoGood app, the process of game design was an integral part of the development, and the gamified elements target the user’s intrinsic motivations instead of providing them with an external reward. In this paper, we present design elements of the app and discuss their potential to support collective intelligence for the common good.

Smart Cities, Social Capital, and Citizens at Play: A Critique and a Way Forward

Digital transformations are not contained within the digital domain but are increasingly spilling over into the physical world. In this chapter, we analyse some of the transformations undergoing in cities today towards becoming smart cities. We offer a critique of smart cities and a way forward, divided into three parts: First, we explore the concept of Smart Citizens in terms of both localities, the move towards a hyperlocal network and also the citizen’s role in the creation and use of data. We use the ‘Smart London’ plan drawn up by the Mayor of London, as a way to illustrate our discussion. Second, we turn to the civic innovations enabled by digital transformations and their potential impact on citizens and citizenship. Specifically, we are interested in the notion of social capital as an alternative form of in-kind currency and its function as an indicator of value, in order to ask, can digital transformations give rise to ‘civic capital,’ and how can such a concept help, for instance, a local government invite more representative residents and community champions to participate in community engagement for better urban planning. Third, we introduce a hybrid, location-based game under development by design agency Preliminal Games in London, UK. This illustrative case critiques and highlights the current challenges to establishing a new economic model that bridges the digital / physical divide. The game provides a vehicle for us to explore how established principles and strategies in game design such as immersive storytelling and goal setting, can be employed to encourage players to think of the interconnections of their hybrid digital / physical environments in new ways.

Effective clinical decision-making from practice-based evidence

This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decision-making processes. Effective and timely clinical decision-making can lead to positive improvements in patient’s health outcome...

Information encountering on social media and tacit knowledge sharing

The purpose of this paper is to investigate how social media may support information encountering (i.e., where individuals encounter useful and interesting information while seeking or browsing for some other information) and how this may lead to facilitation of tacit knowledge creation and sharing. The study employed a qualitative survey design that interviewed twenty-four physicians who were active users of social media to better understand the phenomenon of information encountering on social media. The data was analysed using the thematic analysis approach. The study found six main ways through which social media supports information encountering. Furthermore, drawing upon knowledge creation theories, the study concluded that information encountering on social media facilitates tacit knowledge creation and sharing among individuals. The study provides new directions for further empirical investigations to examine whether information encountering on social media actually leads to tacit knowledge creation and sharing. The findings of the study may also provide opportunities for users to adopt social media effectively or gain greater value from social media use.

Active learning: A step towards automating medical concept extraction

Objective This paper presents an automatic active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort, and (2) the robustness of incremental active learning framework across different selection criteria and datasets is determined. Materials and methods The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional Random Fields as the supervised method, and least confidence and information density as two selection criteria for active learning framework were used. The effect of incremental learning vs. standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. Two clinical datasets were used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Results The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared to the Random sampling baseline, the saving is at least doubled. Discussion Incremental active learning guarantees robustness across all selection criteria and datasets. The reduction of annotation effort is always above random sampling and longest sequence baselines. Conclusion Incremental active learning is a promising approach for building effective and robust medical concept extraction models, while significantly reducing the burden of manual annotation.

Translation and psychometric properties of the Chinese version of the Leeds Attitudes to Concordance II scale

Background Concordance is characterised as a negotiation-like health communication approach based on an equal and collaborative partnership between patients and health professionals. The Leeds Attitudes to Concordance II (LATCon II) scale was developed to measure the attitudes towards concordance. The purpose of this study was to translate the LATCon II into Chinese and psychometrically test the Chinese version of LATCon II (C-LATCon II). Methods The study involved three phases: i) translation and cross-cultural adaptation; ii) pilot study, and; iii) a cross-sectional survey (n = 366). Systematic random sampling was used to recruit hypertensive patients from nine communities covering around 78,000 residents in China. Tests of psychometric properties included content validity, construct validity, criteria-related validity (correlation between the C-LATCon II and the Therapeutic Adherence Scale for Hypertensive Patients (TASHP)), internal reliability, and test-retest reliability (n = 30). Results The study found that the C-LATCon II had a satisfactory content validity (item-level Content Validity Index (CVI) = 0.83-1, scale-level CVI/universal agreement = 0.89, and scale-level CVI/averaging calculation = 0.98), construct validity (four components extracted explained 56.66% of the total variance), internal reliability (Cronbach’s alpha of overall scale and four components was 0.78 and 0.66-0.84, respectively), and test-retest reliability (Pearson’s correlation coefficient = 0.82, p < 0.001; interclass correlation coefficient = 0.82, p < 0.001; linear weighted kappa3 statistic for each item = 0.40-0.65, p < 0.05). Criteria-related validity showed a weak association (Pearson’s correlation coefficient = 0.11, p < 0.05) between patients’ attitudes towards concordance during health communication and their health behaviours for hypertension management. Conclusions The C-LATCon II is a validated and reliable instrument which can be used to evaluate the attitudes to concordance in Chinese populations. Four components (health professionals’ attitudes, partnership between two parties, therapeutic decision making, and patients’ involvement) describe the attitudes towards concordance during health communication.

Similarity-based birdcall retrieval from environmental audio

Automated digital recordings are useful for large-scale temporal and spatial environmental monitoring. An important research effort has been the automated classification of calling bird species. In this paper we examine a related task, retrieval of birdcalls from a database of audio recordings, similar to a user supplied query call. Such a retrieval task can sometimes be more useful than an automated classifier. We compare three approaches to similarity-based birdcall retrieval using spectral ridge features and two kinds of gradient features, structure tensor and the histogram of oriented gradients. The retrieval accuracy of our spectral ridge method is 94% compared to 82% for the structure tensor method and 90% for the histogram of gradients method. Additionally, this approach potentially offers a more compact representation and is more computationally efficient.

Designing a quality health information system: Case study analysis of maternal and child health in Papua New Guinea

Papua New Guinea (PNG) is facing what must seem like an insurmountable challenge to deliver quality healthcare servicesfor women living in both rural and urban areas. Glo bal governing bodies and donor agencies including WHO and UN have indicated that PNG does not have an appropriate health information system. Although there are some systems in place, to date, little research has been conducted on improving or resolving the data integrity and integration issues of the existing health information systems and automating the capture of women and newborns information in PNG. This current research study concentrates on the adoption of eHealth, as an innovative tool to strengthen the health information systems in PNG to meet WHO standards. The research targets maternal and child health focussing on child birth records asan exemplar...

Quality of information for quality of life: Healthcare big data analytics

Big data analysis in healthcare sector is still in its early stages when comparing with that of other business sectors due to numerous reasons. Accommodating the volume, velocity and variety of healthcare data Identifying platforms that examine data from multiple sources, such as clinical records, genomic data, financial systems, and administrative systems Electronic Health Record (EHR) is a key information resource for big data analysis and is also composed of varied co-created values. Successful integration and crossing of different subfields of healthcare data such as biomedical informatics and health informatics could lead to huge improvement for the end users of the health care system, i.e. the patients.

Digital design interventions for creating new presentations of self in public urban places

During everyday urban life, people spend time in public urban places waiting for specific events to occur. During these times, people sometimes tend to engage with their information and communication technology (ICT) devices in a way that shuts off interactions with collocated people. These devices could also be used to better connect with the urban space and collocated people within. This chapter presents and discusses the impact of three design interventions on the urban user experience enabling collocated people to share lightweight, non-privacy-sensitive data in the urban space. We investigate and discuss the impact on the urban experience under the notions of people, place, and technology with an emphasis on how the sharing of non-privacy-sensitive data can positively transform anonymous public urban places in various ways through anonymous digital augmentations.

Design patterns for urban gardening

Urban agriculture is practiced in many forms within urban spaces, ranging from large organised community gardens to individuals with a backyard or balcony. We present the synthesis of findings from three studies exploring different types of urban agriculture: city farms, residential gardeners, and a grassroots group that supports local communities. Where the findings of individual studies are used to justify a design approach, there are often difficulties encountered because of different context of the original study. Through our understanding and synthesis of multiple studies, we propose a set of design patterns. The proposed patterns can be utilised concurrently depending on the scale and context of both the physical garden, and community. The relationships between the patterns and their concurrent use are discussed, and the resulting links provided the foundation for a pattern language. The eight initial patterns provide a foundation on which we would encourage other researchers to contribute, in order to develop a pattern language to holistically consider urban agriculture beyond the scope of our experiences in Brisbane, and to enrich the patterns with a variety of gardening practices.

Enriching architectural design education through interactive displays and local community engagement

Designers have a social responsibility to deal with the needs, issues, and problems that their clients and communities are confronted with. Students of design require opportunities to reflect on their role as social facilitators to develop an attitude towards community engagement through different phases and aspects of their careers. However, current design courses are challenged by compressed timeframes and fragmented scenarios of different academic requirements that do not actively teach community engagement. This paper outlines a participatory and technological approach that was employed to address these issues within the teaching of Architecture and Urban Design at the Queensland University of Technology, Brisbane, Australia. A multi-phase community based research project with actual stakeholders was implemented over a two-year period. Approximately 150 students in the final year of the Bachelor of Design-Architecture; 10 students in the Master of Architecture and 15 students in the Master of Design-Urban Design have informed and influenced each others’ learning through the teaching and research nexus facilitated by this project. The technical approach was implemented in form of a bespoke digital platform that supported the display and discussion of digital media on a series of interactive touch walls. The platform allowed students to easily upload their final designs onto large interactive surfaces, where visitors could explore the media and provide comments. Through the use of this technical platform and the introduction of neogeography, students have been able to broaden their level of interaction and support their learning experience through external structured and unstructured feedback from the local community. Students have not only been exposed to community representatives, but they also have been working in parallel on a specific case study providing each other, across different years and courses, material for reflection and data to structure their design activities.

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

A method for matching patients to advanced prostate cancer clinical trials

Objective: To illustrate a new method for simplifying patient recruitment for advanced prostate cancer clinical trials using natural language processing techniques. Background: The identification of eligible participants for clinical trials is a critical factor to increase patient recruitment rates and an important issue for discovery of new treatment interventions. The current practice of identifying eligible participants is highly constrained due to manual processing of disparate sources of unstructured patient data. Informatics-based approaches can simplify the complex task of evaluating patient’s eligibility for clinical trials. We show that an ontology-based approach can address the challenge of matching patients to suitable clinical trials. Methods: The free-text descriptions of clinical trial criteria as well as patient data were analysed. A set of common inclusion and exclusion criteria was identified through consultations with expert clinical trial coordinators. A research prototype was developed using Unstructured Information Management Architecture (UIMA) that identified SNOMED CT concepts in the patient data and clinical trial description. The SNOMED CT concepts model the standard clinical terminology that can be used to represent and evaluate patient’s inclusion/exclusion criteria for the clinical trial. Results: Our experimental research prototype describes a semi-automated method for filtering patient records using common clinical trial criteria. Our method simplified the patient recruitment process. The discussion with clinical trial coordinators showed that the efficiency in patient recruitment process measured in terms of information processing time could be improved by 25%. Conclusion: An UIMA-based approach can resolve complexities in patient recruitment for advanced prostate cancer clinical trials.