scholarly journals Multicriteria Correlation Preference Information (MCCPI)-Based Ordinary Capacity Identification Method

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 300 ◽  
Author(s):  
Jian-Zhang Wu ◽  
Yi-Ping Zhou ◽  
Li Huang ◽  
Jun-Jie Dong
Keyword(s):  
Decision Making ◽  
Decision Aid ◽  
Higher Order ◽  
Decision Criteria ◽  
Preference Information ◽  
Decision Aiding ◽  
Identification Method ◽  
Explicit Information ◽  
Dominance Relationships ◽  
Decision Alternatives

Multicriteria correlation preference information (MCCPI) refers to a special type of 2-dimensional explicit information: the importance and interaction preferences regarding multiple dependent decision criteria. A few identification models have been established and implemented to transform the MCCPI into the most satisfactory 2-additive capacity. However, as one of the most commonly accepted particular type of capacity, 2-additive capacity only takes into account 2-order interactions and ignores the higher order interactions, which is not always reasonable in a real decision-making environment. In this paper, we generalize those identification models into ordinary capacity cases to freely represent the complicated situations of higher order interactions among multiple decision criteria. Furthermore, a MCCPI-based comprehensive decision aid algorithm is proposed to represent various kinds of dominance relationships of all decision alternatives as well as other useful decision aiding information. An illustrative example is adopted to show the proposed MCCPI-based capacity identification method and decision aid algorithm.

Multicriteria correlation preference information (MCCPI) with nonadditivity index for decision aiding

2020 ◽  
Vol 39 (3) ◽  
pp. 3441-3452
Author(s):  
Li Huang ◽  
Jian-Zhang Wu ◽  
Gleb Beliakov
Keyword(s):  
Decision Aid ◽  
Pairwise Comparison ◽  
Random Generation ◽  
Decision Criteria ◽  
Preference Information ◽  
Decision Aiding ◽  
Dominance Relationships ◽  
Decision Scheme ◽  
Internal Interaction ◽  
Decision Alternatives

MCCPI (Multiple Criteria Correlation Preference Information) is a kind of 2 dimensional decision preference information obtained by pairwise comparison on the importance and interaction of decision criteria. In this paper, we introduce the nonadditivity index to replace the Shapley simultaneous interaction index and construct an undated MCCPI based decision scheme. We firstly propose a diagram to help decision maker obtain the nonadditivity index type MCCPI, then establish transform equations to normalize them into desired capacity and finally adopt a random generation MCCPI based comprehensive decision aid algorithm to explore the dominance relationships and creditable ranking orders of all decision alternatives. An illustrative example is also given to demonstrate the feasibility and effectiveness of the proposed decision scheme. It’s shown that based on some good properties of nonadditivity index in practice, the updated MCCPI model can deal with the internal interaction among decision criteria with relatively less model construction and calculation effort.

scholarly journals Measuring Conflicts Using Cardinal Ranking: An Application to Decision Analytic Conflict Evaluations

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Tobias Fasth ◽  
Aron Larsson ◽  
Love Ekenberg ◽  
Mats Danielson
Keyword(s):  
Decision Making ◽  
Decision Aid ◽  
Real Life ◽  
Preference Elicitation ◽  
Stakeholder Groups ◽  
The Core ◽  
Executive Authority ◽  
Differences Of Opinion ◽  
Decision Alternatives ◽  
Public Decision

One of the core complexities involved in evaluating decision alternatives in the area of public decision-making is to deal with conflicts. The stakeholders affected by and involved in the decision often have conflicting preferences regarding the actions under consideration. For an executive authority, these differences of opinion can be problematic, during both implementation and communication, even though the decision is rational with respect to an attribute set perceived to represent social welfare. It is therefore important to involve the stakeholders in the process and to get an understanding of their preferences. Otherwise, the stakeholder disagreement can lead to costly conflicts. One way of approaching this problem is to provide means for comprehensive, yet effective stakeholder preference elicitation methods, where the stakeholders can state their preferences with respect to actions part of the current agenda of a government. In this paper we contribute two supporting methods: (i) an application of the cardinal ranking (CAR) method for preference elicitation for conflict evaluations and (ii) two conflict indices for measuring stakeholder conflicts. The application of the CAR method utilizes a do nothing alternative to differentiate between positive and negative actions. The elicited preferences can then be used as input to the two conflict indices indicating the level of conflict within a stakeholder group or between two stakeholder groups. The contributed methods are demonstrated in a real-life example carried out in the municipality of Upplands Väsby, Sweden. We show how a questionnaire can be used to elicit preferences with CAR and how the indices can be used to semantically describe the level of consensus and conflict regarding a certain attribute. As such, we show how the methods can provide decision aid in the clarification of controversies.

Use of an Atrial Fibrillation Medication Decision Aid Improves Knowledge and Process for Decision Making (Preprint)

2018 ◽  
Author(s):  
Molly Beinfeld ◽  
Suzanne Brodney ◽  
Michael Barry ◽  
Erika Poole ◽  
Adam Kunin
Keyword(s):  
Atrial Fibrillation ◽  
Decision Making ◽  
Shared Decision Making ◽  
Anticoagulant Therapy ◽  
Decision Aid ◽  
Response Rate ◽  
Intervention Group ◽  
Shared Decision ◽  
Community Based ◽  
Baseline Group

BACKGROUND A rural community-based Cardiology practice implemented shared decision making supported by an evidence-based decision aid booklet to improve the quality of anticoagulant therapy decisions in patients with atrial fibrillation. OBJECTIVE To develop a practical workflow for implementation of an anticoagulant therapy decision aid and to assess the impact on patients’ knowledge and process for anticoagulant medication decision making. METHODS The organization surveyed all patients with atrial fibrillation being seen at Copley Hospital to establish a baseline level of knowledge, certainty about the decision and process for decision making. The intervention surveys included the same knowledge, certainty, process and demographic questions as the baseline surveys, but also included questions asking for feedback on the decision aid booklet. Stroke risk scores (CHA2DS2-VASc score) were calculated by Copley staff for both groups using EMR data. RESULTS We received 46 completed surveys in the baseline group (64% response rate) and 50 surveys in the intervention group (72% response rate). The intervention group had higher knowledge score than the baseline group (3.6 out of 4 correct answers vs 3.1, p=0.036) and Decision Process Score (2.89 out of 4 vs 2.09, p=0.0023) but similar scores on the SURE scale (3.12 out of 4 vs 3.17, p=0.79). Knowledge and Process score differences were sustained even after adjusting for co-variates in stepwise linear regression analyses. Patients with high school or lower education appeared to benefit the most from shared decision making, as demonstrated by their knowledge scores. CONCLUSIONS It is feasible and practical to implement shared decision making supported by decision aids in a community-based Cardiology practice. Shared decision making can improve knowledge and process for decision making for patients with atrial fibrillation. CLINICALTRIAL None

InformedTogether: A decision aid to support shared decision making about mechanical ventilation in severe COPD patients

2018 ◽  
Author(s):  
Meliss Basile ◽  
Johanna Andrews ◽  
Sonia Jacome ◽  
Meng Zhang ◽  
Andrzej Kozikowski ◽  
...  
Keyword(s):  
Decision Making ◽  
Mechanical Ventilation ◽  
Shared Decision Making ◽  
Decision Aid ◽  
Shared Decision ◽  
Copd Patients ◽  
Severe Copd

scholarly journals Development of a decision aid to support colorectal cancer screening: perspectives of Asians in an endemic urban community—a qualitative research study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sok Wei Julia Yuen ◽  
Tsang Yew Tay ◽  
Ning Gao ◽  
Nian Qin Tho ◽  
Ngiap Chuan Tan
Keyword(s):  
Colorectal Cancer ◽  
Decision Making ◽  
Decision Aid ◽  
Controlled Trial ◽  
Local Population ◽  
Primary Care Clinic ◽  
Screening Rate ◽  
Care Clinic ◽  
Crc Screening ◽  
Knowledge Deficits

Abstract Background Colorectal cancer (CRC) is a common malignancy worldwide. Despite being the most common cancer in Singapore, CRC screening rate remains low due to knowledge deficits, social reasons such as inconvenience and a lack of reminder or recommendation. A decision aid (DA) may facilitate an individual’s decision-making to undertake CRC screening by addressing misconceptions and barriers. We postulate that a more person-centred and culturally adapted DA will better serve the local population. The views of the target users are thus needed to develop such a DA. A CRC screening DA prototype has been adapted from an American DA to cater to the Asian users. This study aimed to explore user perspectives on an adapted CRC screening DA-prototype in terms of the design, content and perceived utility. Methods The study used in-depth interviews (IDIs) and focus group discussions (FGDs) to gather qualitative data from English-literate multi-ethnic Asian adults aged 50 years old and above. They had yet to screen for CRC before they were recruited from a public primary care clinic in Singapore. The interviews were audio-recorded, transcribed and analysed to identify emergent themes via thematic analysis. Results This study included 27 participants involved in 5 IDI and 5 FGDs. Participants found the DA easily comprehensible and of appropriate length. They appreciated information about the options and proposed having multi-lingual DAs. The design, in terms of the layout, size and font, was well-accepted but there were suggestions to digitalize the DA. Participants felt that the visuals were useful but there were concerns about modesty due to the realism of the illustration. They would use the DA for information-sharing with their family and for discussion with their doctor for decision making. They preferred the doctor’s recommendation for CRC screening and initiating the use of the DA. Conclusions Participants generally had favourable perceptions of the DA-prototype. A revised DA will be developed based on their feedback. Further input from doctors on the revised DA will be obtained before assessing its effectiveness to increase CRC screening rate in a randomized controlled trial.

scholarly journals Patient decision aid based on multi-criteria decision analysis for disease-modifying drugs for multiple sclerosis: prototype development

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
I. E. H. Kremer ◽  
P. J. Jongen ◽  
S. M. A. A. Evers ◽  
E. L. J. Hoogervorst ◽  
W. I. M. Verhagen ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Decision Aid ◽  
Healthcare Professionals ◽  
Treatment Options ◽  
Shared Decision ◽  
Patient Decision Aid ◽  
Disease Modifying Drugs ◽  
Patient Decision ◽  
Further Development

Abstract Background Since decision making about treatment with disease-modifying drugs (DMDs) for multiple sclerosis (MS) is preference sensitive, shared decision making between patient and healthcare professional should take place. Patient decision aids could support this shared decision making process by providing information about the disease and the treatment options, to elicit the patient’s preference and to support patients and healthcare professionals in discussing these preferences and matching them with a treatment. Therefore, a prototype of a patient decision aid for MS patients in the Netherlands—based on the principles of multi-criteria decision analysis (MCDA) —was developed, following the recommendations of the International Patient Decision Aid Standards. MCDA was chosen as it might reduce cognitive burden of considering treatment options and matching patient preferences with the treatment options. Results After determining the scope to include DMDs labelled for relapsing-remitting MS and clinically isolated syndrome, users’ informational needs were assessed using focus groups (N = 19 patients) and best-worst scaling surveys with patients (N = 185), neurologists and nurses (N = 60) to determine which information about DMDs should be included in the patient decision aid. Next, an online format and computer-based delivery of the patient decision aid was chosen to enable embedding of MCDA. A literature review was conducting to collect evidence on the effectiveness and burden of use of the DMDs. A prototype was developed next, and alpha testing to evaluate its comprehensibility and usability with in total thirteen patients and four healthcare professionals identified several issues regarding content and framing, methods for weighting importance of criteria in the MCDA structure, and the presentation of the conclusions of the patient decision aid ranking the treatment options according to the patient’s preferences. Adaptations were made accordingly, but verification of the rankings provided, validation of the patient decision aid, evaluation of the feasibility of implementation and assessing its value for supporting shared decision making should be addressed in further development of the patient decision aid. Conclusion This paper aimed to provide more transparency regarding the developmental process of an MCDA-based patient decision aid for treatment decisions for MS and the challenges faced during this process. Issues identified in the prototype were resolved as much as possible, though some issues remain. Further development is needed to overcome these issues before beta pilot testing with patients and healthcare professionals at the point of clinical decision-making can take place to ultimately enable making conclusions about the value of the MCDA-based patient decision aid for MS patients, healthcare professionals and the quality of care.

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