Pamela Briggs

Trust and mistrust of online health sites

Do different design and information content factors influence trust and mistrust of online health sites? Fifteen women faced with a risky health decision were observed while searching the Internet for information and advice over four consecutive weeks. In some sessions their searches were unstructured, whilst in other sessions they were directed to review specific sites, chosen for their trust design elements. Content analysis of concurrent verbalisations and group discussion protocols provided support for a staged model wherein design appeal predicted rejection (mistrust) and credibility of information and personalisation of content predicted selection (trust) of advice sites.

A framework for understanding trust factors in web-based health advice

Trust is a key factor in consumer decisions about website engagement. Consumers will engage with sites they deem trustworthy and turn away from those they mistrust. In this paper, we present a framework for understanding trust factors in web-based health advice. The framework is derived from a staged model of trust and allows predictions to be made concerning user engagement with different health websites. The framework is then validated via a series of qualitative, longitudinal studies. In each study, genuine consumers searched online for information and advice concerning their specific health issue. They engaged in free searching and were directed towards sites previously reviewed using the framework. Thematic analysis of the group discussions provided support for the framework and for the staged model of trust wherein design appeal predicted rejection (mistrust) and credibility of information and personalization of content predicted selection (trust) of advice sites. The results are discussed in terms of the merits of the framework, its limitations and directions for future work.

Trust in online advice

Many people are now influenced by the information and advice they find on the Internet, much of it of dubious quality. This article describes two studies concerned with those factors capable of influencing peoples response to online advice. The first study is a qualitative account of a group of house-hunters attempting to find worthwhile information online. The second study describes a survey of more than 2,500 people who had actively sought advice over the Internet. A framework for understanding trust in online advice is proposed in which first impressions are distinguished from more detailed evaluations. Good web design can influence the first process, but three key factors--source credibility, personalization, and predictability--are shown to predict whether people actually follow the advice given.

Personalisation and trust: a reciprocal relationship?

Trust and personalisation are related constructs. Trust is generally accepted as a prerequisite for good personalisation practice. Customers are not likely to reveal confidential information about themselves to an untrustworthy party, and they may be suspicious of data harvesting practices if they feel the information may be misused in some way. But the converse relationship might also hold: good personalisation practice may be a pre-requisite for trust building online. At present, relatively few studies of trust suggest an important role for personalisation in the formation of trust, but we argue below that personalisation may play a larger role than that suggested by the current trust literature. Following a critical review of online trust studies, we suggest that personalisation is important for the development of trust in long-term relationships between consumer and online vendor, but argue that its role in short-term interactions is unclear. We then present a study that explores the extent to which people may be influenced by the promise of a personalised transaction, in order to clarify the influence of personalised practices on initial trust judgments. Most researchers agree that trust is a vital construct for e-commerce. It has been argued that in order to develop a successful e-commerce business:

Health Websites that people can trust - the case of hypertension

Traditionally health advice has been anchored in face-to-face settings but increasingly patients are using the Internet for their health advice needs. This means that patients are now offered inconsistent advice from a range of sources and must determine which sites to trust and which to reject. To understand how consumers make these choices, 13 participants diagnosed with hypertension took part in a longitudinal study in which they searched for information and advice relevant to their condition. A content analysis of the group discussions revealed support for a staged model of trust in which mistrust or rejection of Websites is based on design factors and trust or selection of Websites is based on content factors such as source credibility and personalization. Based on this model, a set of guidelines for developing trust in health Websites is proposed and key differences between face-to-face communication and web-based systems are discussed.

Examining Trust, Forgiveness and Regret as Computational Concepts

The study of trust has advanced tremendously in recent years, to the extent that the goal of a more unified formalisation of the concept is becoming feasible. To that end, we have begun to examine the closely related concepts of regret and forgiveness and their relationship to trust and its siblings. The resultant formalisation allows computational tractability in, for instance, artificial agents. Moreover, regret and forgiveness, when allied to trust, are very powerful tools in the Ambient Intelligence (AmI) security area, especially where Human Computer Interaction and concrete human understanding are key. This paper introduces the concepts of regret and forgiveness, exploring them from social psychological as well as a computational viewpoint, and presents an extension to Marsh’s original trust formalisation that takes them into account. It discusses and explores work in the AmI environment, and further potential applications.

Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

Background How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ2 5 = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Conclusions Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice.

Image Retrieval Interfaces: A User Perspective

Surprisingly little is known about how different users conduct image searches. As a result, even the most sophisticated systems available have limited appeal to the end-user. This paper describes a study eliciting user requirements for future image databases through an online questionnaire. 125 experienced image searchers were questioned about the functions and modes of interaction that they currently use, and those they would like to see in future systems. The results of this survey, and their implications for retrieval systems design, are discussed in some detail.

A Taxonomy of the Image: On the Classification of Content for Image Retrieval

Image database (IDB) systems are at present often designed to test technology and the efficacy of retrieval algorithms, rather than being oriented towards delivering functionality to users. Research is necessary to design interfaces geared towards human usage of images. The starting point of this research needs to be consideration at a fundamental, user-centred level of how people perceive and interpret images. This article considers literature from many disciplines to describe a taxonomy of image content, from direct sensory elements to high-level abstractions. The nine categories derived will later be validated and used to direct the design of visual query interfaces for IDB systems.

Please advise : using the Internet for health and financial advice

The Internet is a popular source of information and advice especially within the fields of health and finance. Previous research has raised the issue of quality with respect to online information and has suggested differences between the way consumers and experts search for and appraise online information. However, many studies have asked students to act as ‘consumers’ or have relied upon artificial search tasks. This paper reports on research using ‘genuine’ consumers. The first study examines the trust markers held by genuine consumers in both the health and finance domains. The second study explores the perceptions of people who have actually used sources of online advice. The results indicate similarities between the trust markers of genuine consumers and experts. Trust markers differed between the two domains of health and finance and this was revealed in terms of the features of the sites visited. Genuine consumers may have different requirements and may be under different pressures compared to expert evaluators.