College admissions and the role of information : an experimental study

We analyze two well-known matching mechanisms—the Gale-Shapley, and the Top Trading Cycles (TTC) mechanisms—in the experimental lab in three different informational settings, and study the role of information in individual decision making. Our results suggest that—in line with the theory—in the college admissions model the Gale-Shapley mechanism outperforms the TTC mechanisms in terms of efficiency and stability, and it is as successful as the TTC mechanism regarding the proportion of truthful preference revelation. In addition, we find that information has an important effect on truthful behavior and stability. Nevertheless, regarding efficiency, the Gale-Shapley mechanism is less sensitive to the amount of information participants hold

Shared decision-making about cardiovascular disease medication in older people: A qualitative study of patient experiences in general practice

Objectives To explore older people's perspectives and experiences with shared decision-making (SDM) about medication for cardiovascular disease (CVD) prevention. Design, setting and participants Semi-structured interviews with 30 general practice patients aged 75 years and older in New South Wales, Australia, who had elevated CVD risk factors (blood pressure, cholesterol) or had received CVD-related lifestyle advice. Data were analysed by multiple researchers using Framework analysis. Results Twenty eight participants out of 30 were on CVD prevention medication, half with established CVD. We outlined patient experiences using the four steps of the SDM process, identifying key barriers and challenges: Step 1. Choice awareness: taking medication for CVD prevention was generally not recognised as a decision requiring patient input; Step 2. Discuss benefits/harms options: CVD prevention poorly understood with emphasis on benefits; Step 3. Explore preferences: goals, values and preferences (eg, length of life vs quality of life, reducing disease burden vs risk reduction) varied widely but generally not discussed with the general practitioner; Step 4. Making the decision: overall preference for directive approach, but some patients wanted more active involvement. Themes were similar across primary and secondary CVD prevention, different levels of self-reported health and people on and off medication. Conclusions Results demonstrate how older participants vary widely in their health goals and preferences for treatment outcomes, suggesting that CVD prevention decisions are preference sensitive. Combined with the fact that the vast majority of participants were taking medications, and few understood the aims and potential benefits and harms of CVD prevention, it seems that older patients are not always making an informed decision. Our findings highlight potentially modifiable barriers to greater participation of older people in SDM about CVD prevention medication and prevention in general

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy of location information. For this purpose, people should know their location privacy preferences, that is, whether or not he/she can release location information at each place and time. However, it is not easy for each user to make such decisions and it is troublesome to set the privacy preference at each time. Therefore, we propose a method to recommend location privacy preferences for decision making. Comparing to existing method, our method can improve the accuracy of recommendation by using matrix factorization and preserve privacy strictly by local differential privacy, whereas the existing method does not achieve formal privacy guarantee. In addition, we found the best granularity of a location privacy preference, that is, how to express the information in location privacy protection. To evaluate and verify the utility of our method, we have integrated two existing datasets to create a rich information in term of user number. From the results of the evaluation using this dataset, we confirmed that our method can predict location privacy preferences accurately and that it provides a suitable method to define the location privacy preference

Consumer Responses to Online Decision Aids for 3 Preference-Sensitive Health Problems

Two hundred and twenty-four adults evaluated three preference-sensitive online decision aids related to their personal self-reported health status. Respondents were recruited in 2009, and user review was conducted online outside of a research or clinical setting. The majority of respondents had some college education, were white, and were middle aged. The three decision aids tested (statins [n = 70], aspirin [n = 97], and MRI [n = 57]) have been developed through a rigorous, iterative, expert medical review process; are evidence based; and are written in plain language. The results of general linear model repeated measures analyses were statistically significant for pre-post changes in user knowledge and for between-subject differences according to health issue. Post hoc comparisons for the results of one-way analysis of variance for eight dimensions of usability show that users of the MRI decision aid, compared with the other two user groups, felt that they had learned more, that the tool had helped clear up their feelings about the issue, and that they were more inclined to talk with their physician about their health issue

Assessing decision quality in patient-centred care requires a preference-sensitive measure.

A theory-based instrument for measuring the quality of decisions made using any form of decision technology, including both decision-aided and unaided clinical consultations is required to enable person- and patient-centred care and to respond positively to individual heterogeneity in the value aspects of decision making. Current instruments using the term 'decision quality' have adopted a decision- and thus condition-specific approach. We argue that patient-centred care requires decision quality to be regarded as both preference-sensitive across multiple relevant criteria and generic across all conditions and decisions. MyDecisionQuality is grounded in prescriptive multi criteria decision analysis and employs a simple expected value algorithm to calculate a score for the quality of a decision that combines, in the clinical case, the patient's individual preferences for eight quality criteria (expressed as importance weights) and their ratings of the decision just taken on each of these criteria (expressed as performance rates). It thus provides an index of decision quality that encompasses both these aspects. It also provides patients with help in prioritizing quality criteria for future decision making by calculating, for each criterion, the Incremental Value of Perfect Rating, that is, the increase in their decision quality score that would result if their performance rating on the criterion had been 100%, weightings unchanged. MyDecisionQuality, which is a web-based generic and preference-sensitive instrument, can constitute a key patient-reported measure of the quality of the decision-making process. It can provide the basis for future decision improvement, especially when the clinician (or other stakeholders) completes the equivalent instrument and the extent and nature of concordance and discordance can be established. Apart from its role in decision preparation and evaluation, it can also provide real time and relevant documentation for the patient's record

Risk Thresholds and Risk Classifications Pose Problems for Person-Centred Care.

Classification of a continuous risk score into risk levels is common. However, while the absolute risk score is essential, it is arguably unethical to label anyone at 'high, moderate or low risk' of a serious event, simply because management based on a single criterion (e.g. avoiding the target condition) has been determined to be effective or cost-effective at a population level. Legally, mono-criterial risk labeling can inhibit the obtaining of a fully-informed, preference-based consent, since multiple considerations (various benefits and harms) matter to most individuals, not only the single criterion that is the basis of the provided risk category. These ethical and legal challenges can be met by preference-sensitive multi-criteria decision support tools. In this future vision paper, we demonstrate, at a conceptual proof-of-method level, how such decision support can and should be developed without reference to risk-level classifications. The statin decision is used as illustration, without any empirical claims

Decision aids can support cancer clinical trials decisions: Results of a randomized trial

BACKGROUND. Cancer patients often do not make informed decisions regarding clinical trial participation. This study evaluated whether a web-based decision aid (DA) could support trial decisions compared with our cancer center’s website. METHODS. Adults diagnosed with cancer in the past 6 months who had not previously participated in a cancer clinical trial were eligible. Participants were randomized to view the DA or our cancer center’s website (enhanced usual care [UC]). Controlling for whether participants had heard of cancer clinical trials and educational attainment, multivariable linear regression examined group on knowledge, self-efficacy for finding trial information, decisional conflict (values clarity and uncertainty), intent to participate, decision readiness, and trial perceptions. RESULTS. Two hundred patients (86%) consented between May 2014 and April 2015. One hundred were randomized to each group. Surveys were completed by 87 in the DA group and 90 in the UC group. DA group participants reported clearer values regarding trial participation than UC group participants reported (least squares [LS] mean = 15.8 vs. 32, p < .0001) and less uncertainty (LS mean = 24.3 vs. 36.4, p = .025). The DA group had higher objective knowledge than the UC group’s (LS mean = 69.8 vs. 55.8, p < .0001). There were no differences between groups in intent to participate. CONCLUSIONS. Improvements on key decision outcomes including knowledge, self-efficacy, certainty about choice, and values clarity among participants who viewed the DA suggest web-based DAs can support informed decisions about trial participation among cancer patients facing this preference-sensitive choice. Although better informing patients before trial participation could improve retention, more work is needed to examine DA impact on enrollment and retention. IMPLICATIONS FOR PRACTICE: This paper describes evidence regarding a decision tool to support patients’ decisions about trial participation. By improving knowledge, helping patients clarify preferences for participation, and facilitating conversations about trials, decision aids could lead to decisions about participation that better match patients’ preferences, promoting patient-centered care and the ethical conduct of clinical research

The Future of Health Is Self-Production and Co-Creation Based on Apomediative Decision Support.

Cultural changes are needed in medicine if the benefits of technological advances are to benefit healthcare users. The Digital Health Manifesto of 'medical futurist' doctor Bertalan Meskó and 'e-patient' Dave deBronkart, The Patient Will See You Now by Eric Topol and The Patient as CEO by Robin Farmanfarmaian, are among the proliferating warnings of the approaching paradigm shift in medicine, resulting, above all, from technological advances that gives users independent access to exponentially increasing amounts of information about themselves. We question their messages only in suggesting they do not sufficiently shift the focus from 'patient' to 'person' and consequently fail to recognise the need for the credible, efficient, ethical and independent decision support that can ensure the 'democratisation of knowledge' is person empowering, not overpowering. Such decision support can ensure the 'democratisation of decision,' leading to higher quality decisions and fully-informed and preference-based consent to health provider actions. The coming paradigm will therefore be characterised by apomediative ('direct-to-consumer') decision support tools, engaged with by the person in the community to help them make health production decisions for themselves (including whether to consult a healthcare professional or provider), as well as intermediative ('direct-from-clinician') tools, delivered by a health professional in a 'shared decision making' or 'co-creation of health' process. This vision paper elaborates on the implementation of these preference-sensitive decision support tools through the technique of Multi-Criteria Decision Analysis

Preference-Sensitive Apomediative Decision Support Is Key to Facilitating Self-Produced Health.

In the health capital model, the main function of health services is not to produce health, but to support the person in their self-production investments. In the health context there are three types of decision support tools, depending on the role of the provider (e.g. clinician) and person. Non-mediative tools are designed to help the clinician decide what is best for the patient. Intermediative Patient Decision Aids are designed to help the clinician and patient decide together, in an encounter, what is best for the patient. Apomediative Personalised Decision Support Tools are designed to help the person decide what is best for themselves, including whether to seek a professional consultation and/or to prepare for, and engage in, an intermediative consultation. Only preference-sensitive apomediative support tools ensure that the key requirements of self-produced health are met, along with legally informed and preference-based consent to any subsequent provider action. The desirable form of apomediative support is a publicly accessible, direct-to-citizen, provider-independent, multi-criteria analysis-based decision support of the sort available in many other areas of self-production. Which (UK), Tænk (Denmark), Choice (Australia) and numerous other comparison magazines and websites provide independent multi-criterial support for decisions on, for example, which food and transport to buy to self-produce nutrition and movement. A personalised decision support tool for the statin decision is provided as illustration: Should I go to my general practitioner and ask for a statin prescription or go to discuss taking statins, in the light of the preliminary opinion of the tool

A marker of biological ageing predicts adult risk preference in European starlings, Sturnus vulgaris

Why are some individuals more prone to gamble than others? Animals often show preferences between 2 foraging options with the same mean reward but different degrees of variability in the reward, and such risk preferences vary between individuals. Previous attempts to explain variation in risk preference have focused on energy budgets, but with limited empirical support. Here, we consider whether biological ageing, which affects mortality and residual reproductive value, predicts risk preference. We studied a cohort of European starlings (Sturnus vulgaris) in which we had previously measured developmental erythrocyte telomere attrition, an established integrative biomarker of biological ageing. We measured the adult birds’ preferences when choosing between a fixed amount of food and a variable amount with an equal mean. After controlling for change in body weight during the experiment (a proxy for energy budget), we found that birds that had undergone greater developmental telomere attrition were more risk averse as adults than were those whose telomeres had shortened less as nestlings. Developmental telomere attrition was a better predictor of adult risk preference than either juvenile telomere length or early-life food supply and begging effort. Our longitudinal study thus demonstrates that biological ageing, as measured via developmental telomere attrition, is an important source of lasting differences in adult risk preferences