Displaying publications 21 - 40 of 321 in total

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  1. 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*
  2. Marzuki AA, Vaghi MM, Conway-Morris A, Kaser M, Sule A, Apergis-Schoute A, et al.
    J Child Psychol Psychiatry, 2022 Dec;63(12):1591-1601.
    PMID: 35537441 DOI: 10.1111/jcpp.13628
    BACKGROUND: Computational research had determined that adults with obsessive-compulsive disorder (OCD) display heightened action updating in response to noise in the environment and neglect metacognitive information (such as confidence) when making decisions. These features are proposed to underlie patients' compulsions despite the knowledge they are irrational. Nonetheless, it is unclear whether this extends to adolescents with OCD as research in this population is lacking. Thus, this study aimed to investigate the interplay between action and confidence in adolescents with OCD.

    METHODS: Twenty-seven adolescents with OCD and 46 controls completed a predictive-inference task, designed to probe how subjects' actions and confidence ratings fluctuate in response to unexpected outcomes. We investigated how subjects update actions in response to prediction errors (indexing mismatches between expectations and outcomes) and used parameters from a Bayesian model to predict how confidence and action evolve over time. Confidence-action association strength was assessed using a regression model. We also investigated the effects of serotonergic medication.

    RESULTS: Adolescents with OCD showed significantly increased learning rates, particularly following small prediction errors. Results were driven primarily by unmedicated patients. Confidence ratings appeared equivalent between groups, although model-based analysis revealed that patients' confidence was less affected by prediction errors compared to controls. Patients and controls did not differ in the extent to which they updated actions and confidence in tandem.

    CONCLUSIONS: Adolescents with OCD showed enhanced action adjustments, especially in the face of small prediction errors, consistent with previous research establishing 'just-right' compulsions, enhanced error-related negativity, and greater decision uncertainty in paediatric-OCD. These tendencies were ameliorated in patients receiving serotonergic medication, emphasising the importance of early intervention in preventing disorder-related cognitive deficits. Confidence ratings were equivalent between young patients and controls, mirroring findings in adult OCD research.

    Matched MeSH terms: Decision Making/physiology
  3. Voorhoeve A, Edejer TTT, Kapiriri L, Norheim OF, Snowden J, Basenya O, et al.
    Health Hum Rights, 2016 Dec;18(2):11-22.
    PMID: 28559673
    The goal of achieving Universal Health Coverage (UHC) can generally be realized only in stages. Moreover, resource, capacity, and political constraints mean governments often face difficult trade-offs on the path to UHC. In a 2014 report, Making fair choices on the path to UHC, the WHO Consultative Group on Equity and Universal Health Coverage articulated principles for making such trade-offs in an equitable manner. We present three case studies which illustrate how these principles can guide practical decision-making. These case studies show how progressive realization of the right to health can be effectively guided by priority-setting principles, including generating the greatest total health gain, priority for those who are worse off in a number of dimensions (including health, access to health services, and social and economic status), and financial risk protection. They also demonstrate the value of a fair and accountable process of priority setting.
    Matched MeSH terms: Decision Making*
  4. Mousavi SM, Niaki ST, Bahreininejad A, Musa SN
    ScientificWorldJournal, 2014;2014:136047.
    PMID: 25093195 DOI: 10.1155/2014/136047
    A multi-item multiperiod inventory control model is developed for known-deterministic variable demands under limited available budget. Assuming the order quantity is more than the shortage quantity in each period, the shortage in combination of backorder and lost sale is considered. The orders are placed in batch sizes and the decision variables are assumed integer. Moreover, all unit discounts for a number of products and incremental quantity discount for some other items are considered. While the objectives are to minimize both the total inventory cost and the required storage space, the model is formulated into a fuzzy multicriteria decision making (FMCDM) framework and is shown to be a mixed integer nonlinear programming type. In order to solve the model, a multiobjective particle swarm optimization (MOPSO) approach is applied. A set of compromise solution including optimum and near optimum ones via MOPSO has been derived for some numerical illustration, where the results are compared with those obtained using a weighting approach. To assess the efficiency of the proposed MOPSO, the model is solved using multi-objective genetic algorithm (MOGA) as well. A large number of numerical examples are generated at the end, where graphical and statistical approaches show more efficiency of MOPSO compared with MOGA.
    Matched MeSH terms: Decision Making
  5. Kerk, Lee Chang, Rohanin Ahmad
    MATEMATIKA, 2018;34(2):381-392.
    MyJurnal
    Optimization is central to any problem involving decision making. The area
    of optimization has received enormous attention for over 30 years and it is still popular
    in research field to this day. In this paper, a global optimization method called Improved
    Homotopy with 2-Step Predictor-corrector Method will be introduced. The method in-
    troduced is able to identify all local solutions by converting non-convex optimization
    problems into piece-wise convex optimization problems. A mechanism which only consid-
    ers the convex part where minimizers existed on a function is applied. This mechanism
    allows the method to filter out concave parts and some unrelated parts automatically.
    The identified convex parts are called trusted intervals. The descent property and the
    global convergence of the method was shown in this paper. 15 test problems have been
    used to show the ability of the algorithm proposed in locating global minimizer.
    Matched MeSH terms: Decision Making
  6. Karimi, Abbas, Zarafshan, Faraneh, Adznan Jantan, Abdul Rahman Ramli, M. Iqbal b. Saripan, Al-Haddad, S.A.R.
    MyJurnal
    Plurality voter is one of the commonest voting methods for decision making in highly-reliable applications in which the reliability and safety of the system is critical. To resolve the problem associated with sequential plurality voter in dealing with large number of inputs, this paper introduces a new generation of plurality voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. The asymptotic analysis of the new proposed algorithm has demonstrated that it has a time complexity of O(log n) which is less than time complexity of sequential plurality algorithm, i.e. O (n log n).
    Matched MeSH terms: Decision Making
  7. Chee, L.P., Wan Alwi, S.R., Lim, J.S.
    MyJurnal
    Aggregate planning acts as a blueprint for all operational planning activities. Despite
    the substantial amount of research that has been done in determining methods to
    improve aggregate planning approaches, the industry is still at a loss when it comes
    to working on the tactical planning aspect, especially in aggregate production.
    Therefore, this research work aims to present a comprehensive and generalised
    framework that will formulate a realistic batch production environment using an
    interactive Production Decision Support System. This system consists of an aggregate
    planning framework that combines a simulation model and a Pinch Analysis graphical
    approach to improve the effectiveness and efficiency of the decision-making process.
    The target is to allow operational opportunities to be captured at first sight and thus,
    maximise organisational profit. The simplicity and practicality of this new Production
    Decision Support System is demonstrated through two illustrative examples where a
    total of four heuristics were identified and turned into the new strategies to avoid the
    stock-out scenarios.
    Matched MeSH terms: Decision Making
  8. González-Briones A, Chamoso P, De La Prieta F, Demazeau Y, Corchado JM
    Sensors (Basel), 2018 May 19;18(5).
    PMID: 29783768 DOI: 10.3390/s18051633
    Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.
    Matched MeSH terms: Decision Making
  9. Najmeh Malekmohammadi, Azmi Jaafar, Mansor Monsi
    Data envelopment analysis (DEA) is a mathematical programming for evaluating the relative efficiency of decision making units (DMUs). The first DEA model (CCR model) assumed for exact data, later some authors introduced the applications of DEA which the data was imprecise. In imprecise data envelopment analysis (IDEA) the data can be ordinal, interval and fuzzy. Data envelopment analysis also can be used for the future programming of organizations and the response of the different policies, which is related to the target setting and resource allocation. The existing target model that conveys performance based targets in line with the policy making scenarios was defined for exact data. In this paper we improved the model for imprecise data such as fuzzy, ordinal and interval data. To deal with imprecise data we first established an interval DEA model. We used one of the methods to convert fuzzy and ordinal data into the interval data. A numerical experiment is used to illustrate the application to our interval model.
    Matched MeSH terms: Decision Making
  10. Chamran MK, Yau KA, Noor RMD, Wong R
    Sensors (Basel), 2019 Dec 19;20(1).
    PMID: 31861500 DOI: 10.3390/s20010018
    This paper demonstrates the use of Universal Software Radio Peripheral (USRP), together with Raspberry Pi3 B+ (RP3) as the brain (or the decision making engine), to develop a distributed wireless network in which nodes can communicate with other nodes independently and make decision autonomously. In other words, each USRP node (i.e., sensor) is embedded with separate processing units (i.e., RP3), which has not been investigated in the literature, so that each node can make independent decisions in a distributed manner. The proposed testbed in this paper is compared with the traditional distributed testbed, which has been widely used in the literature. In the traditional distributed testbed, there is a single processing unit (i.e., a personal computer) that makes decisions in a centralized manner, and each node (i.e., USRP) is connected to the processing unit via a switch. The single processing unit exchanges control messages with nodes via the switch, while the nodes exchange data packets among themselves using a wireless medium in a distributed manner. The main disadvantage of the traditional testbed is that, despite the network being distributed in nature, decisions are made in a centralized manner. Hence, the response delay of the control message exchange is always neglected. The use of such testbed is mainly due to the limited hardware and monetary cost to acquire a separate processing unit for each node. The experiment in our testbed has shown the increase of end-to-end delay and decrease of packet delivery ratio due to software and hardware delays. The observed multihop transmission is performed using device-to-device (D2D) communication, which has been enabled in 5G. Therefore, nodes can either communicate with other nodes via: (a) a direct communication with the base station at the macrocell, which helps to improve network performance; or (b) D2D that improve spectrum efficiency, whereby traffic is offloaded from macrocell to small cells. Our testbed is the first of its kind in this scale, and it uses RP3 as the distributed decision-making engine incorporated into the USRP/GNU radio platform. This work provides an insight to the development of a 5G network.
    Matched MeSH terms: Decision Making
  11. Mohammed Shuaib, Zarita Zainuddin
    Sains Malaysiana, 2017;46:1997-2005.
    Integrating an exit choice model into a microscopic crowd dynamics model is an essential approach for obtaining more
    efficient evacuation model. We describe various aspects of decision-making capability of an existing rule-based exit
    choice model for evacuation processes. In simulations, however, the simulated evacuees clogging at exits have behaved
    non-intelligently, namely they do not give up their exits for better ones for safer egress. We refine the model to endow
    the individuals with the ability to leave their exits due to dynamic changes by modifying the model of their excitement
    resulted from the source of panic. This facilitates the approximately equal crowd size at exits for being until the end
    of the evacuation process, and thereby the model accomplishes more optimal evacuation. For further intelligence, we
    introduce the prediction factor that enables higher probability of equally distributing evacuees at exits. A simulation to
    validate the contribution is performed, and the results are analyzed and compared with the original model.
    Matched MeSH terms: Decision Making
  12. Nadeem MA, Surienty L, Haque MM
    Front Public Health, 2022;10:1004767.
    PMID: 36452948 DOI: 10.3389/fpubh.2022.1004767
    The agriculture sector is a traditional economic pillar of many emerging economies. However, it is facing greater occupational health and safety (OHS) challenges in Pakistan, and its performance is continuously decreasing. An effective OHS implementation provides better control over OHS challenges and may help to restore its former glory. Therefore, this study aims to explore different organizational decision-making styles and safety accountability to put OHS into practice in this sector. Based on institutional theory, a theoretical framework was developed. Two hundred and eighty-seven agriculture farms in Punjab, Pakistan were surveyed and analyzed using SmartPLS 3.3.7. The findings revealed that implementation styles (rational and incremental) and safety accountability positively impact OHS implementation. Similarly, the moderating role of mimetic motives was found positively significant in the relationship between rational style and OHS implementation, and negatively significant in the relationship between incremental style and OHS implementation. While no moderating effect of mimetic motive was found between safety accountability and OHS implementation. This study suggested that OHS implementation should not be viewed as a social or technical issue alone. Strategic arrangements should be made at the organizational level to gain better control over OHS challenges by considering the institutional environment in which the organization operates.
    Matched MeSH terms: Decision Making
  13. Allawi MF, Aidan IA, El-Shafie A
    Environ Sci Pollut Res Int, 2021 Feb;28(7):8281-8295.
    PMID: 33052565 DOI: 10.1007/s11356-020-11062-x
    The accuracy level for reservoir evaporation prediction is an important issue for decision making in the water resources field. The traditional methods for evaporation prediction could encounter numerous obstacles owing to the effect of several parameters on the shape of the evaporation pattern. The current research presented modern model called the Coactive Neuro-Fuzzy Inference System (CANFIS). Modification for such model has been achieved for enhancing the evaporation prediction accuracy. Genetic algorithm was utilized to select the effective input combination. The efficiency of the proposed model has been compared with popular artificial intelligence models according to several statistical indicators. Two different case studies Aswan High Dam (AHD) and Timah Tasoh Dam (TTD) have been considered to explore the performance of the proposed models. It is concluded that the modified GA-CANFIS model is better than GA-ANFIS, GA-SVR, and GA-RBFNN for evaporation prediction for both case studies. GA-CANFIS attained minimum RMSE (15.22 mm month-1 for AHD, 8.78 mm month-1 for TTD), minimum MAE (12.48 mm month-1 for AHD, 5.11 mm month-1 for TTD), and maximum determination coefficient (0.98 for AHD, 0.95 for TTD).
    Matched MeSH terms: Decision Making
  14. Ai DD, Sui BY, Duan CA, Xu Q, Zhao K
    Int J Technol Assess Health Care, 2024 Apr 05;40(1):e24.
    PMID: 38577775 DOI: 10.1017/S0266462324000151
    BACKGROUND: Traditional therapies are crucial in maintaining and improving human well-being. China's healthcare policymakers are attempting to use health technology assessment (HTA) as a decision-making supportive tool. The value assessment framework for Chinese patent medicine (CPM) has been developed and is being adopted and validated widely by research institutions. Subsequently, the healthcare decision-makers particularly hanker for the value framework of traditional non-pharmacological therapies.

    METHODS: To construct a practical value framework for traditional non-pharmacological therapies, a scoping review methodology was adopted to identify the evaluation domains and obstacles. A search, screening, and analysis process was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Evidence was retrieved from scientific databases and HTA agencies' websites.

    RESULTS: The search strategy identified 5 guidelines records and 17 acupuncture HTA reports. By synthesizing the valuable reports of CPM and acupuncture evaluation in representative countries, this study found that Mainland China was promoting the comprehensive value assessment of CPM, whereas the United Kingdom, Singapore, Canada, the United States, and Malaysia had carried out the HTA evaluation of acupuncture for various conditions among which chronic pain was the most common. UK and Singapore applied the HTA results to support acupuncture reimbursement decisions. Three domains, including safety, effectiveness, and economy, were commonly adopted. The identified biggest challenge of evaluating traditional non-pharmacological therapies is the scarce high-quality clinical evidence.

    CONCLUSIONS: This study identified value domains and issues of traditional therapies, and pointed out future research implications, to promote the development value framework of traditional therapies.

    Matched MeSH terms: Decision Making
  15. Man MY, Ong MS, Mohamad MS, Deris S, Sulong G, Yunus J, et al.
    Malays J Med Sci, 2015 Dec;22(Spec Issue):9-19.
    PMID: 27006633 MyJurnal
    Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system.
    Matched MeSH terms: Decision Making
  16. Alamoodi AH, Zughoul O, David D, Garfan S, Pamucar D, Albahri OS, et al.
    J Med Syst, 2024 Aug 31;48(1):81.
    PMID: 39214943 DOI: 10.1007/s10916-024-02090-y
    Artificial intelligence (AI) has become a crucial element of modern technology, especially in the healthcare sector, which is apparent given the continuous development of large language models (LLMs), which are utilized in various domains, including medical beings. However, when it comes to using these LLMs for the medical domain, there's a need for an evaluation platform to determine their suitability and drive future development efforts. Towards that end, this study aims to address this concern by developing a comprehensive Multi-Criteria Decision Making (MCDM) approach that is specifically designed to evaluate medical LLMs. The success of AI, particularly LLMs, in the healthcare domain, depends on their efficacy, safety, and ethical compliance. Therefore, it is essential to have a robust evaluation framework for their integration into medical contexts. This study proposes using the Fuzzy-Weighted Zero-InConsistency (FWZIC) method extended to p, q-quasirung orthopair fuzzy set (p, q-QROFS) for weighing evaluation criteria. This extension enables the handling of uncertainties inherent in medical decision-making processes. The approach accommodates the imprecise and multifaceted nature of real-world medical data and criteria by incorporating fuzzy logic principles. The MultiAtributive Ideal-Real Comparative Analysis (MAIRCA) method is employed for the assessment of medical LLMs utilized in the case study of this research. The results of this research revealed that "Medical Relation Extraction" criteria with its sub-levels had more importance with (0.504) than "Clinical Concept Extraction" with (0.495). For the LLMs evaluated, out of 6 alternatives, ( A 4 ) "GatorTron S 10B" had the 1st rank as compared to ( A 1 ) "GatorTron 90B" had the 6th rank. The implications of this study extend beyond academic discourse, directly impacting healthcare practices and patient outcomes. The proposed framework can help healthcare professionals make more informed decisions regarding the adoption and utilization of LLMs in medical settings.
    Matched MeSH terms: Decision Making
  17. Kim ARJ, Chew KS, Ngian HU
    Med J Malaysia, 2024 Nov;79(6):800-802.
    PMID: 39614801
    In a dynamic healthcare environment, patient safety is crucial. A "Conscious Actions Reduce Errors" (C.A.R.E) approach is needed to safeguard safety and reduce medical errors. The dual process theory highlights two thinking modes: intuitive (fast, automatic) and analytical (slow, deliberate). Intuitive thinking, though quick and often effective, can lead to cognitive biases like anchoring and availability heuristics. A C.A.R.E approach incorporating tools like the TWED checklist (Threat, What if I'm wrong? What else?, Evidence, Dispositional factors) and Shisa Kanko (Japanese method of pointing and calling) can help to improve decision-making and action precision in clinical settings.
    Matched MeSH terms: Decision Making
  18. Masoumik SM, Abdul-Rashid SH, Olugu EU
    PLoS One, 2015;10(11):e0143115.
    PMID: 26618353 DOI: 10.1371/journal.pone.0143115
    To maintain a competitive position, companies are increasingly required to integrate their proactive environmental strategies into their business strategies. The shift from reactive and compliance-based to proactive and strategic environmental management has driven companies to consider the strategic factors while identifying the areas in which they should focus their green initiatives. In previous studies little attention was given to providing the managers with a basis from which they could strategically prioritise these green initiatives across their companies' supply chains. Considering this lacuna in the literature, we present a decision-making method for prioritising green supply chain initiatives aligned with the preferred green strategies alternatives for the manufacturing companies. To develop this method, the study considered a position between determinism and the voluntarism orientation of environmental management involving both external pressures and internal competitive drivers and key resources as decision factors. This decision-making method was developed using the analytic network process (ANP) technique. The elements of the decision model were derived from the literature. The causal relationships among the multiple decision variables were validated based on the results of structural equation modelling (SEM) using a dataset collected from a survey of the ISO 14001-certified manufacturers in Malaysia. A portion of the relative weights required for computation in ANP was also calculated using the SEM results. A case study is presented to demonstrate the applicability of the method.
    Matched MeSH terms: Decision Making*
  19. Zulkifley MA, Mustafa MM, Hussain A, Mustapha A, Ramli S
    PLoS One, 2014;9(12):e114518.
    PMID: 25485630 DOI: 10.1371/journal.pone.0114518
    Recycling is one of the most efficient methods for environmental friendly waste management. Among municipal wastes, plastics are the most common material that can be easily recycled and polyethylene terephthalate (PET) is one of its major types. PET material is used in consumer goods packaging such as drinking bottles, toiletry containers, food packaging and many more. Usually, a recycling process is tailored to a specific material for optimal purification and decontamination to obtain high grade recyclable material. The quantity and quality of the sorting process are limited by the capacity of human workers that suffer from fatigue and boredom. Several automated sorting systems have been proposed in the literature that include using chemical, proximity and vision sensors. The main advantages of vision based sensors are its environmentally friendly approach, non-intrusive detection and capability of high throughput. However, the existing methods rely heavily on deterministic approaches that make them less accurate as the variations in PET plastic waste appearance are too high. We proposed a probabilistic approach of modeling the PET material by analyzing the reflection region and its surrounding. Three parameters are modeled by Gaussian and exponential distributions: color, size and distance of the reflection region. The final classification is made through a supervised training method of likelihood ratio test. The main novelty of the proposed method is the probabilistic approach in integrating various PET material signatures that are contaminated by stains under constant lighting changes. The system is evaluated by using four performance metrics: precision, recall, accuracy and error. Our system performed the best in all evaluation metrics compared to the benchmark methods. The system can be further improved by fusing all neighborhood information in decision making and by implementing the system in a graphics processing unit for faster processing speed.
    Matched MeSH terms: Decision Making*
  20. Olesen AP, Nor SN, Amin L
    Sci Eng Ethics, 2016 Feb;22(1):133-46.
    PMID: 25724710 DOI: 10.1007/s11948-015-9639-z
    While pre-implantation genetic diagnosis (PGD) is available and legal in Malaysia, there is an ongoing controversy debate about its use. There are few studies available on individuals' attitudes toward PGD, particularly among those who have a genetic disease, or whose children have a genetic disease. To the best of our knowledge, this is, in fact, the first study of its kind in Malaysia. We conducted in-depth interviews, using semi-structured questionnaires, with seven selected potential PGD users regarding their knowledge, attitudes and decisions relating to the use PGD. The criteria for selecting potential PGD users were that they or their children had a genetic disease, and they desired to have another child who would be free of genetic disease. All participants had heard of PGD and five of them were considering its use. The participants' attitudes toward PGD were based on several different considerations that were influenced by various factors. These included: the benefit-risk balance of PGD, personal experiences of having a genetic disease, religious beliefs, personal values and cost. The study's findings suggest that the selected Malaysian participants, as potential PGD users, were supportive but cautious regarding the use of PGD for medical purposes, particularly in relation to others whose experiences were similar. More broadly, the paper highlights the link between the participants' personal experiences and their beliefs regarding the appropriateness, for others, of individual decision-making on PGD, which has not been revealed by previous studies.
    Matched MeSH terms: Decision Making*
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