Pre-testing advertisements for effectiveness of communication

The purpose of this study was to examine a technique of Pre- Testing Advertisements for Effectiveness, and to seek to provide a Psychological basis for such Pre-Testing. The results of this study suggest a possible system for Pre-Testing the effectiveness of advertisements. The approach taken in this study was to test the effectiveness of communication of advertisements. Three advertisements were tested on a sample of a target audience, that Bample consisting of 78 people taken from three market segments; census classifications A, B, and Cl, whose ages ranged from 25 to 60. Respondents were given three tests : 1) Catalogue selection; 2) Focus of attention using an eye movement recorder test and; 3) completion of a questionnaire. Results showed significant differences between the effectiveness of the three experimental advertisements. Advertisements 1 and 2 failed to communicate the intended messages and were thus classified as ineffective. The 3rd advertisement was communicated effectively.Hence the system used, was shown to distinguish between advertisements. It is the aim of this study to establish whether the consumer decoded advertising communication in the manner intended by the sender, and to provide a scientifically based advertising/communication Pre-Test system which could prove useful for Advertising, Research, and for Psychology

People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting

In this paper we propose a technique to adapt a convolutional neural network (CNN) based object counter to additional visual domains and object types while still preserving the original counting function. Domain-specific normalisation and scaling operators are trained to allow the model to adjust to the statistical distributions of the various visual domains. The developed adaptation technique is used to produce a singular patch-based counting regressor capable of counting various object types including people, vehicles, cell nuclei and wildlife. As part of this study a challenging new cell counting dataset in the context of tissue culture and patient diagnosis is constructed. This new collection, referred to as the Dublin Cell Counting (DCC) dataset, is the first of its kind to be made available to the wider computer vision community. State-of-the-art object counting performance is achieved in both the Shanghaitech (parts A and B) and Penguins datasets while competitive performance is observed on the TRANCOS and Modified Bone Marrow (MBM) datasets, all using a shared counting model.Comment: 10 page

Exploring user behaviours when providing electronic consent on Health Social Networks: a ‘Just Tick Agree’ approach

In an online world, the distinction between public and private is becoming increasingly blurred with rising concerns about the privacy and security of personal health information. The aim of this study is to explore electronic consent (eConsent) on a Health Social Network (HSN) – PatientsLikeMe - to improve both the form and accessibility of contractual information presented to HSN users. Participants registered on this HSN and their interaction/behaviours was observed when agreeing to the site’s Terms and Conditions (T&C’s) and Privacy Policy (PP) documents. Focus group discussions were used to help us understand how and why certain events occurred. Several themes emerged from this data - ‘Just Tick Agree’ phenomenon, perceived societal benefits for the public good, data privacy concerns and emotional drivers towards eConsent. By achieving a deeper understanding of the eConsent process to an HSN, contributions are presented for both theory and practice. We argue that the complex language used for T&C’s and PP statements when simplified would increase user knowledge, awareness and understanding. Furthermore, HSN user behaviours (i.e. ‘Just Tick Agree’) must change when registering on HSNs and, developers of HSNs should enable user choice on registration by changing how users’ control their personal health-related data

Privacy by Design: informed consent and Internet of Things for smart health

Check: I accept the terms and conditions and privacy policy statements associated with this technological artefact! The informed consent process is becoming more of a challenge with the emergence of Internet of Things (IoT) as data may be collected without the digital health citizen being aware. It is argued in this paper that the first phase for universal usability of IoT within the smart health domain is to ensure that digital health citizens (i.e. user of technology) are fully aware of what they are consenting to when they register an account with such technological artefacts. This point is further reinforced by the proposed ‘Privacy by Design’ requirements associated with the forthcoming General Data Protection Regulation (GDPR). This paper proposes some practical approaches which should be considered when designing and developing IoT for data collection and data sharing within the health domain

Starting with small health data opportunities for mHealth in Africa

The need to obtain data to understand effective and available child mortality-reducing control measures in rural areas of developing countries is great. Evidence shows that this challenge can potentially be overcome with the increased availability of Information and Communication Technology (ICT) to support the data/information/ knowledge needs of healthcare delivery services in low resource settings. Recognising the benefits of ICT and the need for improvements in the Nigerian health sector, this paper outlines the plans for the technical feasibility assessment of the IMPACT (usIng Mobile Phones for Assessing, Classifying and Treating sick children) smartphone application to capture, store and analyse of child health assessment data. IMPACT is a secure, scalable, user friendly mobile health (mHealth) innovation that is being developed to support ‘small data’ capabilities within the context of healthcare in the community in Enugu State, Nigeria, Africa. Notwithstanding the heightened focus on ‘big data’ in health, this research is interested in investigating the opportunities associated with doing ‘small healthcare data’ well, with the long term view of building to the big data scenario for healthcare in the community in Enugu. This paper outlines the plan for the IMPACT project considering the implications for health data, knowledge management in healthcare and the big data opportunities to support disease surveillance, healthcare delivery and resourcing and healthcare practitioner education

A ground-up approach to mHealth in Nigeria: A study of primary healthcare workers’ attitude to mHealth adoption

Mobile Health (mHealth) has been piloted in developing countries to transform the delivery of healthcare services. Despite this heightened focus on mHealth, the number of fully operational mHealth solutions implemented in these locations remains surprisingly low. To extend mHealth projects beyond pilot stage it is imperative that the primary end user is positively predisposed to engaging with the mHealth intervention. Through exploring initial perceptions, we can inform later stages of mHealth projects or develop interventions to convert attitudes into commitment or motivation to use mHealth. This qualitative exploratory study aims to understand end users’, namely Primary Healthcare (PHC) workers, initial attitudes towards a mHealth project called IMPACT (usIng Mobile Phones for Assessing, Classifying and Treating sick children). We conducted a field study in Enugu State, Nigeria to understand end users’ perceptions of the relevance, benefits, threats and initial understanding of the technology influencing end users’ attitudes towards adoption of mHealth. The initial findings indicate that PHC workers expressed positive perceptions regarding the relevance and benefits associated with the IMPACT app. PHC workers focus on how the technology could support them to be more efficient and effective in their roles. However, they advocate the need for community wide education and training to eradicate negative perceptions or misgivings about the potential use of mHealth as part of a patient’s assessment

The status quo of IS conference publications on theorising eHealth in developing countries.

The purpose of this systematic review is to consolidate existing evidence on electronic health (eHealth) initiatives examined in developing countries to better inform future practice and research. More specifically, this paper examines the status quo of theorising eHealth in developing countries across a range of top Information Systems (IS) conference publications over a fifteen year period (2000–2015). While some work has been done on examining the application of theory within the eHealth domain, the associated context in which this work is performed is often over looked. Examining the papers from a theoretical and contextual perspective reveal that IS researchers’ primary attention is generalisable theory (in the form of explanation) with some consideration given to the interaction with the healthcare context. IS researchers should leverage the lessons learned from other IS sub domains and move beyond generalizable theories to further enrich the understanding of eHealth in developing countries

Approaches to mobile health evaluation: a comparative study

A major challenge faced by mobile health (mHealth) is identifying an evaluation technique which provides a rigorous evaluation while capturing the unique characteristics of the intervention. This study investigates traditional and emerging methods of mHealth evaluation, identifying existing gaps. This research is a useful first step toward developing an evaluation technique which will facilitate implementation and enable mHealth to reach its potential in accelerating socio-economic development, particularly in Low and Middle Income countries (LMICs)