Displaying publications 1 - 20 of 313 in total

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  1. Peng W, Lam SS, Sonne C
    Science, 2020 01 17;367(6475):257-258.
    PMID: 31949072 DOI: 10.1126/science.aba5642
    Matched MeSH terms: Decision Making*
  2. Mohamad, D., Hanif, H.M., Dom, R.M.
    MyJurnal
    Complexity has been discussed in decision making, computational, task complexity, activity network,
    supply chain, imaging, project management and mechanical. This paper reviews the definition of
    complexity and the preliminary-related definitions of complexity index in decision making. It proposes
    a complexity index for decision making, its properties, and implementation.
    Matched MeSH terms: Decision Making
  3. Lai NM, Ong JM, Chen KH, Chaiyakunapruk N, Ovelman C, Soll R
    Neonatology, 2020;117(1):125-126.
    PMID: 31487740 DOI: 10.1159/000502492
    Matched MeSH terms: Decision Making*
  4. Shamim A, Balakrishnan V, Tahir M, Shiraz M
    ScientificWorldJournal, 2014;2014:340583.
    PMID: 25506612 DOI: 10.1155/2014/340583
    The increasing use and ubiquity of the Internet facilitate dissemination of word-of-mouth through blogs, online forums, newsgroups, and consumer's reviews. Online consumer's reviews present tremendous opportunities and challenges for consumers and marketers. One of the challenges is to develop interactive marketing practices for making connections with target consumers that capitalize consumer-to-consumer communications for generating product adoption. Opinion mining is employed in marketing to help consumers and enterprises in the analysis of online consumers' reviews by highlighting the strengths and weaknesses of the products. This paper describes an opinion mining system based on novel review and feature ranking methods to empower consumers and enterprises for identifying critical product features from enormous consumers' reviews. Consumers and business analysts are the main target group for the proposed system who want to explore consumers' feedback for determining purchase decisions and enterprise strategies. We evaluate the proposed system on real dataset. Results show that integration of review and feature-ranking methods improves the decision making processes significantly.
    Matched MeSH terms: Decision Making*
  5. Arienti C, Kiekens C, Bettinsoli R, Engkasan JP, Frischknecht R, Gimigliano F, et al.
    Eur J Phys Rehabil Med, 2021 Apr;57(2):303-308.
    PMID: 33971699 DOI: 10.23736/S1973-9087.21.06877-5
    During its fourth year of existence, Cochrane Rehabilitation went on to promote evidence-informed health decision-making in rehabilitation. In 2020, the outbreak of the COVID-19 pandemic has made it necessary to alter priorities. In these challenging times, Cochrane Rehabilitation has firstly changed its internal organisation and established a new relevant project in line with pandemic needs: the REH-COVER (Rehabilitation - COVID-19 evidence-based response) action. The aim was to focus on the timely collection, review and dissemination of summarised and synthesised evidence relating to COVID-19 and rehabilitation. Cochrane Rehabilitation REH-COVER action has included in 2020 five main initiatives: 1) rapid living systematic reviews on rehabilitation and COVID-19; 2) interactive living evidence map on rehabilitation and COVID-19; 3) definition of the research topics on "rehabilitation and COVID-19" in collaboration with the World Health Organization (WHO) rehabilitation programme; 4) Cochrane Library special collection on Coronavirus (COVID-19) rehabilitation; and 5) collaboration with COVID-END for the topics "rehabilitation" and "disability." Furthermore, we are still carrying on five different special projects: Be4rehab; RCTRACK; definition of rehabilitation for research purposes; ebook project; and a prioritization exercise for Cochrane Reviews production. The Review Working Area continued to identify and "tag" the rehabilitation-relevant reviews published in the Cochrane library; the Publication Working Area went on to publish Cochrane Corners, working more closely with the Cochrane Review Groups (CRGs) and Cochrane Networks, particularly with Cochrane Musculoskeletal, Oral, Skin and Sensory Network; the Education Working Area, the most damaged in 2020, tried to continue performing educational activities such as workshops in different online meetings; the Methodology Working Area organized the third and fourth Cochrane Rehabilitation Methodological (CRM) meetings respectively in Milan and Orlando; the Communication Working Area spread rehabilitation evidences through different channels and translated the contents in different languages.
    Matched MeSH terms: Decision Making*
  6. Memon MA, Khan S, Alam K, Rahman MM, Yunus RM
    Surg Laparosc Endosc Percutan Tech, 2020 Dec 04;31(2):234-240.
    PMID: 33284258 DOI: 10.1097/SLE.0000000000000889
    In the era of evidence-based decision-making, systematic reviews (SRs) are being widely used in many health care policies, government programs, and academic disciplines. SRs are detailed and comprehensive literature review of a specific research topic with a view to identifying, appraising, and synthesizing the research findings from various relevant primary studies. A SR therefore extracts the relevant summary information from the selected studies without bias by strictly adhering to the review procedures and protocols. This paper presents all underlying concepts, stages, steps, and procedures in conducting and publishing SRs. Unlike the findings of narrative reviews, the synthesized results of any SRs are reproducible, not subjective and bias free. However, there are a number of issues related to SRs that directly impact on the quality of the end results. If the selected studies are of high quality, the criteria of the SRs are fully satisfied, and the results constitute the highest level of evidence. It is therefore essential that the end users of SRs are aware of the weaknesses and strengths of the underlying processes and techniques so that they could assess the results in the correct perspective within the context of the research question.
    Matched MeSH terms: Clinical Decision-Making*
  7. Nantha YS
    Korean J Fam Med, 2017 Nov;38(6):315-321.
    PMID: 29209469 DOI: 10.4082/kjfm.2017.38.6.315
    A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.
    Matched MeSH terms: Clinical Decision-Making; Decision Making
  8. Alsalem MA, Alsattar HA, Albahri AS, Mohammed RT, Albahri OS, Zaidan AA, et al.
    J Infect Public Health, 2021 Oct;14(10):1513-1559.
    PMID: 34538731 DOI: 10.1016/j.jiph.2021.08.026
    The problem complexity of multi-criteria decision-making (MCDM) has been raised in the distribution of coronavirus disease 2019 (COVID-19) vaccines, which required solid and robust MCDM methods. Compared with other MCDM methods, the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) have demonstrated their solidity in solving different MCDM challenges. However, the fuzzy sets used in these methods have neglected the refusal concept and limited the restrictions on their constants. To end this, considering the advantage of the T-spherical fuzzy sets (T-SFSs) in handling the uncertainty in the data and obtaining information with more degree of freedom, this study has extended FWZIC and FDOSM methods into the T-SFSs environment (called T-SFWZIC and T-SFDOSM) to be used in the distribution of COVID-19 vaccines. The methodology was formulated on the basis of decision matrix adoption and development phases. The first phase described the adopted decision matrix used in the COVID-19 vaccine distribution. The second phase presented the sequential formulation steps of T-SFWZIC used for weighting the distribution criteria followed by T-SFDOSM utilised for prioritising the vaccine recipients. Results revealed the following: (1) T-SFWZIC effectively weighted the vaccine distribution criteria based on several parameters including T = 2, T = 4, T = 6, T = 8, and T = 10. Amongst all parameters, the age criterion received the highest weight, whereas the geographic locations severity criterion has the lowest weight. (2) According to the T parameters, a considerable variance has occurred on the vaccine recipient orders, indicating that the existence of T values affected the vaccine distribution. (3) In the individual context of T-SFDOSM, no unique prioritisation was observed based on the obtained opinions of each expert. (4) The group context of T-SFDOSM used in the prioritisation of vaccine recipients was considered the final distribution result as it unified the differences found in an individual context. The evaluation was performed based on systematic ranking assessment and sensitivity analysis. This evaluation showed that the prioritisation results based on each T parameter were subject to a systematic ranking that is supported by high correlation results over all discussed scenarios of changing criteria weights values.
    Matched MeSH terms: Decision Making
  9. Albahri OS, Zaidan AA, Albahri AS, Alsattar HA, Mohammed R, Aickelin U, et al.
    J Adv Res, 2022 Mar;37:147-168.
    PMID: 35475277 DOI: 10.1016/j.jare.2021.08.009
    INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues.

    OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods.

    METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the 'recipients list' and 'COVID-19 distribution criteria'. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM.

    RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values.

    CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.

    Matched MeSH terms: Decision Making
  10. Khezrian M, Jahan A, Kadir WM, Ibrahim S
    PLoS One, 2014;9(6):e97831.
    PMID: 24897426 DOI: 10.1371/journal.pone.0097831
    Web services today are among the most widely used groups for Service Oriented Architecture (SOA). Service selection is one of the most significant current discussions in SOA, which evaluates discovered services and chooses the best candidate from them. Although a majority of service selection techniques apply Quality of Service (QoS), the behaviour of QoS-based service selection leads to service selection problems in Multi-Criteria Decision Making (MCDM). In the existing works, the confidence level of decision makers is neglected and does not consider their expertise in assessing Web services. In this paper, we employ the VIKOR (VIšekriterijumskoKOmpromisnoRangiranje) method, which is absent in the literature for service selection, but is well-known in other research. We propose a QoS-based approach that deals with service selection by applying VIKOR with improvement of features. This research determines the weights of criteria based on user preference and accounts for the confidence level of decision makers. The proposed approach is illustrated by an example in order to demonstrate and validate the model. The results of this research may facilitate service consumers to attain a more efficient decision when selecting the appropriate service.
    Matched MeSH terms: Decision Making*
  11. Thong Kai Shin, Seed, Hon Fei
    MyJurnal
    Decision making capacity is the basis for medical decision making. A person’s right to determine his or her own health care related decision has long been established and this forms the essence of medical treatment. This fundamental right extends to patients with mental health disorder who have the capacity to make such decisions. Where a mental disorder is evident, our experiences in the local settings suggested that clinicians are inclined to state that incapacity to decide for medical treatment is present without much assessment or exploration and explanation on the proposed treatment. Many patients with mental disorder in fact are capable at making decisions related to health care. Their rights to decide on medical treatment should be respected and not to be ignored.
    Matched MeSH terms: Clinical Decision-Making; Decision Making
  12. Teoh SL, Ngorsuraches S, Lai NM, Bangpan M, Chaiyakunapruk N
    Int J Food Sci Nutr, 2019 Jun;70(4):491-512.
    PMID: 30634867 DOI: 10.1080/09637486.2018.1538326
    There is a high and increasing global prevalence of nutraceuticals use. This study aims to systematically review and critically appraise all available evidence to identify the factors affecting consumers' decisions in taking nutraceuticals. Questionnaire, interview or focus group studies which directly reported factors affecting consumers' decisions in using nutraceuticals were included. A thematic synthesis method was employed to synthesis the findings from the included studies. Out of the 76 studies included, the key factors identified as the most important factors motivating consumers to take nutraceuticals were the perceived health benefits and safety of nutraceuticals, as well as the advice from healthcare professionals, friends and family. The identified barriers to take nutraceuticals were a lack of belief in the health benefit of nutraceuticals, the high cost of nutraceuticals and consumers' lack of knowledge about nutraceuticals. As a chief course of recommendation for the use of nutraceuticals, healthcare professionals should strive to utilise reliable information from clinical evidence to help consumers in making an informed decision in using nutraceuticals. Future studies should explore the possible ways to improve channelling clinical evidence information of nutraceuticals to the public.
    Matched MeSH terms: Decision Making*
  13. Saad R, Ahmad MZ, Abu MS, Jusoh MS
    ScientificWorldJournal, 2014;2014:865495.
    PMID: 24782670 DOI: 10.1155/2014/865495
    Multicriteria decision making (MCDM) is one of the methods that popularly has been used in solving personnel selection problem. Alternatives, criteria, and weights are some of the fundamental aspects in MCDM that need to be defined clearly in order to achieve a good result. Apart from these aspects, fuzzy data has to take into consideration that it may arise from unobtainable and incomplete information. In this paper, we propose a new approach for personnel selection problem. The proposed approach is based on Hamming distance method with subjective and objective weights (HDMSOW's). In case of vagueness situation, fuzzy set theory is then incorporated onto the HDMSOW's. To determine the objective weight for each attribute, the fuzzy Shannon's entropy is considered. While for the subjective weight, it is aggregated into a comparable scale. A numerical example is presented to illustrate the HDMSOW's.
    Matched MeSH terms: Decision Making*
  14. Hu Y, Loo CK
    ScientificWorldJournal, 2014;2014:240983.
    PMID: 24778580 DOI: 10.1155/2014/240983
    A novel decision making for intelligent agent using quantum-inspired approach is proposed. A formal, generalized solution to the problem is given. Mathematically, the proposed model is capable of modeling higher dimensional decision problems than previous researches. Four experiments are conducted, and both empirical experiments results and proposed model's experiment results are given for each experiment. Experiments showed that the results of proposed model agree with empirical results perfectly. The proposed model provides a new direction for researcher to resolve cognitive basis in designing intelligent agent.
    Matched MeSH terms: Decision Making*
  15. Ng CJ, Lee PY, Lee YK, Chew BH, Engkasan JP, Irmi ZI, et al.
    BMC Health Serv Res, 2013 Oct 11;13:408.
    PMID: 24119237 DOI: 10.1186/1472-6963-13-408
    BACKGROUND: Involving patients in decision-making is an important part of patient-centred care. Research has found a discrepancy between patients' desire to be involved and their actual involvement in healthcare decision-making. In Asia, there is a dearth of research in decision-making. Using Malaysia as an exemplar, this study aims to review the current research evidence, practices, policies, and laws with respect to patient engagement in shared decision-making (SDM) in Asia.

    METHODS: In this study, we conducted a comprehensive literature review to collect information on healthcare decision-making in Malaysia. We also consulted medical education researchers, key opinion leaders, governmental organisations, and patient support groups to assess the extent to which patient involvement was incorporated into the medical curriculum, healthcare policies, and legislation.

    RESULTS: There are very few studies on patient involvement in decision-making in Malaysia. Existing studies showed that doctors were aware of informed consent, but few practised SDM. There was limited teaching of SDM in undergraduate and postgraduate curricula and a lack of accurate and accessible health information for patients. In addition, peer support groups and 'expert patient' programmes were also lacking. Professional medical bodies endorsed patient involvement in decision-making, but there was no definitive implementation plan.

    CONCLUSION: In summary, there appears to be little training or research on SDM in Malaysia. More research needs to be done in this area, including baseline information on the preferred and actual decision-making roles. The authors have provided a set of recommendations on how SDM can be effectively implemented in Malaysia.

    Matched MeSH terms: Decision Making*
  16. Almahdi EM, Zaidan AA, Zaidan BB, Alsalem MA, Albahri OS, Albahri AS
    J Med Syst, 2019 Jun 06;43(7):219.
    PMID: 31172296 DOI: 10.1007/s10916-019-1339-9
    This study presents a prioritisation framework for mobile patient monitoring systems (MPMSs) based on multicriteria analysis in architectural components. This framework selects the most appropriate system amongst available MPMSs for the telemedicine environment. Prioritisation of MPMSs is a challenging task due to (a) multiple evaluation criteria, (b) importance of criteria, (c) data variation and (d) unmeasurable values. The secondary data presented as the decision evaluation matrix include six systems (namely, Yale-National Aeronautics and Space Administration (NASA), advanced health and disaster aid network, personalised health monitoring, CMS, MobiHealth and NTU) as alternatives and 13 criteria (namely, supported number of sensors, sensor front-end (SFE) communication, SFE to mobile base unit (MBU) communications, display of biosignals on the MBU, storage of biosignals on the MBU, intra-body area network (BAN) communication problems, extra-BAN communication problems, extra-BAN communication technology, extra-BAN communication protocols, back-end system communication technology, intended geographic area of use, end-to-end security and reported trial problems) based on the architectural components of MPMSs. These criteria are adopted from the most relevant studies and are found to be applicable to this study. The prioritisation framework is developed in three stages. (1) The unmeasurable values of the MPMS evaluation criteria in the adopted decision evaluation matrix based on expert opinion are represented by using the best-worst method (BWM). (2) The importance of the evaluation criteria based on the architectural components of the MPMS is determined by using the BWM. (3) The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is utilised to rank the MPMSs according to the determined importance of the evaluation criteria and the adopted decision matrix. For validation, mean ± standard deviation is used to verify the similarity of systematic prioritisations objectively. The following results are obtained. (1) The BWM represents the unmeasurable values of the MPMS evaluation criteria. (2) The BWM is suitable for weighing the evaluation criteria based on the architectural components of the MPMS. (3) VIKOR is suitable for solving the MPMS prioritisation problem. Moreover, the internal and external VIKOR group decision making are approximately the same, with the best MPMS being 'Yale-NASA' and the worst MPMS being 'NTU'. (4) For the objective validation, remarkable differences are observed between the group scores, which indicate the similarity of internal and external prioritisation results.
    Matched MeSH terms: Decision Making*
  17. Ho, S.E., Koo, Y.L., Ismail, S., Hing, H.L., Widad, O., Chung, H.T., et al.
    Medicine & Health, 2013;8(2):73-80.
    MyJurnal
    Decision making in nursing is one of the most important skills nurses must apply and utilize in their nursing practice. The aim of this study was to determine the perception of clinical decision making ability among nursing students. A descriptive cross-sectional study was conducted in a tertiary hospital. A total of 54 nursing students were recruited using a modified version of Clinical Decision Making in Nursing Scale (CDMNS) adapted from Jenkins (1985). The findings showed good CDMNS score with mean and standard deviation of (124.24±12.713). The four sub-scales of CDMNS were: searching for alternative (33.24±4.821), canvassing (28.74±3.514), evaluation and re-evaluation (31.43±3.922), searching for information (30.83±4.765). Nineteen (35%) of the participants chose nursing as their first choice, whereas 35 participants (65%) did not. Thirthy seven (69%) participants were satisfied with their nursing competency, 17 (31%) were unsatisfied. There were significant differences between searching for alternatives, evaluation and re-evaluation, and nursing as their first choice (p=

    Study site: Nursing students, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM)
    Matched MeSH terms: Clinical Decision-Making; Decision Making
  18. Lee YK, Ng CJ
    Z Evid Fortbild Qual Gesundhwes, 2017 Jun;123-124:66-68.
    PMID: 28527637 DOI: 10.1016/j.zefq.2017.05.019
    Shared decision making (SDM) activities in Malaysia began around 2010. Although the concept is not widespread, there are opportunities to implement SDM in both the public and private healthcare sectors. Malaysia has a multicultural society and cultural components (such as language differences, medical paternalism, strong family involvement, religious beliefs and complementary medicine) influence medical decision making. In terms of policy, the Ministry of Health has increasingly mentioned patient-centered care as a component of healthcare delivery while the Malaysian Medical Council's guidelines on doctors' duties mentioned collaborative partnerships as a goal of doctor-patient relationships. Current research on SDM comprises baseline surveys of decisional role preferences, development and implementation of locally developed patient decision aids, and conducting of SDM training workshops. Most of this research is carried out by public research universities. In summary, the current state of SDM in Malaysia is still at its infancy. However, there are increasing recognition and efforts from the academic institutions and Ministry of Health to conduct research in SDM, develop patient decision support tools and initiate national discussion on patient involvement in decision making.
    Matched MeSH terms: Decision Making*
  19. Lee DS, Abdullah KL, Subramanian P, Bachmann RT, Ong SL
    J Clin Nurs, 2017 Dec;26(23-24):4065-4079.
    PMID: 28557238 DOI: 10.1111/jocn.13901
    AIMS AND OBJECTIVES: To explore whether there is a correlation between critical thinking ability and clinical decision-making among nurses.

    BACKGROUND: Critical thinking is currently considered as an essential component of nurses' professional judgement and clinical decision-making. If confirmed, nursing curricula may be revised emphasising on critical thinking with the expectation to improve clinical decision-making and thus better health care.

    DESIGN: Integrated literature review.

    METHODS: The integrative review was carried out after a comprehensive literature search using electronic databases Ovid, EBESCO MEDLINE, EBESCO CINAHL, PROQuest and Internet search engine Google Scholar. Two hundred and 22 articles from January 1980 to end of 2015 were retrieved. All studies evaluating the relationship between critical thinking and clinical decision-making, published in English language with nurses or nursing students as the study population, were included. No qualitative studies were found investigating the relationship between critical thinking and clinical decision-making, while 10 quantitative studies met the inclusion criteria and were further evaluated using the Quality Assessment and Validity Tool. As a result, one study was excluded due to a low-quality score, with the remaining nine accepted for this review.

    RESULTS: Four of nine studies established a positive relationship between critical thinking and clinical decision-making. Another five studies did not demonstrate a significant correlation. The lack of refinement in studies' design and instrumentation were arguably the main reasons for the inconsistent results.

    CONCLUSIONS: Research studies yielded contradictory results as regard to the relationship between critical thinking and clinical decision-making; therefore, the evidence is not convincing. Future quantitative studies should have representative sample size, use critical thinking measurement tools related to the healthcare sector and evaluate the predisposition of test takers towards their willingness and ability to think. There is also a need for qualitative studies to provide a fresh approach in exploring the relationship between these variables uncovering currently unknown contributing factors.

    RELEVANCE TO CLINICAL PRACTICE: This review confirmed that evidence to support the existence of relationships between critical thinking and clinical decision-making is still unsubstantiated. Therefore, it serves as a call for nurse leaders and nursing academics to produce quality studies in order to firmly support or reject the hypothesis that there is a statistically significant correlation between critical thinking and clinical decision-making.

    Matched MeSH terms: Clinical Decision-Making*
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