Peer-reviewed publications

V Narayanan, K Baird & R Tay (2021), “Investment decisions: the trade-off between economic and environmental objectives”, The British Accounting Review 53, 100969

B Mashayekhi & M Saeedi (2020), “The position of balanced scorecard in stock selection decision making using PAPRIKA Technique”, Journal of Investment Knowledge 9, 295-315

M Namazi & R Gholami (2017), “Comprehensive ranking model of companies via accounting information, balanced scorecard and PAPRIKA technique”, Journal of Accounting Knowledge 7, 7-33

R Whiting, P Hansen & A Sen (2017), “A tool for measuring SMEs’ reputation, engagement and goodwill: A New Zealand exploratory study”, Journal of Intellectual Capital 18, 170-88

R Whiting, P Hansen & A Sen (2016), “A tool for measuring SMEs’ reputation, engagement and goodwill including internet and social media presence”, Proceedings of the 8th Asia-Pacific Interdisciplinary Research in Accounting (APIRA) Conference, Melbourne, Australia, 2016

J Ruhland (2006), “Strategic mobilization: What strategic management can learn from social movement research”, Management 11, 23-31

M McGillivray, S Feeny, S Knowles, P Hansen, F Ombler (2023), “What are valid weights for the Human Development Index? A discrete choice experiment for the United Kingdom”, Social Indicators Research 165, 679-94

M Genç, S Knowles & T Sullivan (2021), “In search of effective altruists”, Applied Economics 53, 805-19

S Feeny, P Hansen, S Knowles, M McGillivray & F Ombler (2019), “Donor motives, public preferences and the allocation of UK foreign aid: A discrete choice experiment approach”, Review of World Economics 155, 511-37

S Knowles (2019), “Why more Kiwis are not effective altruists”, EcoNZ@Otago 42, 8-9

N Aznam, W Hussain & F Bosli, “Preliminary study of zakat criteria to enhance existing zakat distribution methods using 1000Minds”, abstract, Guidebook 1st International Conference On Social Studies, Moral, and Character Education (ICSMC), Yogyakarta, Indonesia, 2018

H Cunningham, S Knowles & P Hansen (2017), “Bilateral foreign aid: How important is aid effectiveness to people for choosing countries to support?”, Applied Economics Letters 24, 306-10 [Economics Discussion Papers, No. 1605]

P Hansen, N Kergozou, S Knowles & P Thorsnes (2014), “Developing countries in need: Which characteristics appeal most to people when donating money?”, Journal of Development Studies 50, 1494-1509

P Hansen, N Kergozou & S Knowles (2013), “Charitable giving: How recipient-country characteristics influence donors’ behaviour”, EcoNZ@Otago 31, 1-3

L Laver, G Filardo, M Sanchez M et al (2025), “Use of injectable orthobiological products for osteoarthritis of the knee: An ESSKA-ORBIT European consensus. Part 1 – blood-derived products (platelet-rich plasma)”, Journal de Traumatologie du Sport 42, 7-20 [in French except for abstract]

A Pierobon, W Taylor, R Siegert et al (2024), “Exploring the perceived difficulty and importance of lower limb physical activities for people with and without osteoarthritis: a discrete choice experiment”, Musculoskeletal Care 22, e70011

S Zhu, K Bennell, R Hinman et al (2024), “Development of a 12-week unsupervised online tai chi program for people with hip and knee osteoarthritis: mixed methods study”, JMIR Aging 7, e55322

L Laver, G Filardo, M Sanchez et al (2024), “The use of injectable orthobiologics for knee osteoarthritis: A European ESSKA‐ORBIT consensus. Part 1 – Blood‐derived products (platelet‐rich plasma)”, Knee Surgery, Sports Traumatology, Arthroscopy 32, 783-97

D Laorden, E Zamarrón, D Romero et al (2023), “Evaluation of FEOS score and super-responder criteria in a real-life cohort treated with anti-IL5/IL5R”, Respiratory Medicine 211, 107216

S Murias, A Boteanu, I Calvo et al (2023), “What drives the decision to optimise biological treatment in children and youngsters with juvenile idiopathic arthritis? A discrete-choice experiment”, Reumatología Clínica 19, 26-33

Z Landis-Lewis, A Flynn, A Janda & N Shah (2022), “A scalable service to improve health care quality through precision audit and feedback: Proposal for a randomized controlled trial”, JMIR Research Protocols 11, e3499

I Teijeiro, I Peralta, L De Llano et al (2021), “Development of a tool to measure the clinical response to biologic therapy in uncontrolled severe asthma: the FEOS score”, abstract, 2021 European Respiratory Society (ERS) International Congress, virtual format, 2021, European Respiratory Journal 58(suppl 65), PA1098

L de Llano, I Dávila, E Martínez-Moragón et al (2021), “Development of a tool to measure the clinical response to biologic therapy in uncontrolled severe asthma: The FEV1, Exacerbations, Oral Corticosteroids, Symptoms Score” The Journal of Allergy and Clinical Immunology: In Practice 9, 2725-31

C Baggott, P Hansen, R Hancox et al (2020), “What matters most to patients when choosing treatment for mild-moderate asthma? Results from a discrete choice experiment”, Thorax 75, 842-48

M Anaka, D Chan, S Pattison et al (2020), “Understanding the treatment preferences of neuroendocrine tumor patients using discrete choice experiments”, abstract, 12th Annual Multidisciplinary Neuroendocrine Tumor Medical Symposium of the North American Neuroendocrine Tumor Society, Boston, USA, Pancreas 49, 461-91

D Pinto, S Prabhakaran, E Tipton & A Naidech (2020), “Why physicians prescribe prophylactic seizure medications after intracerebral hemorrhage: An adaptive conjoint analysis”, Journal of Stroke and Cerebrovascular Diseases 29, 104628

C Baggott, J Hardy, H Reddel et al (2019), “Discrete choice experiments identifying attributes influencing treatment preference in mild asthma”, abstract, 2019 European Respiratory Society (ERS) International Congress, Madrid, Spain, 2019, European Respiratory Journal 54(suppl 63), PA4189

P Teo, R Hinman, T Egerton, K Dziedzic & K Bennell (2019), “Identifying and prioritizing clinical guideline recommendations most relevant to physical therapy practice for hip and/or knee osteoarthritis”, Journal of Orthopaedic & Sports Physical Therapy 49, 501-12

R Cai, H Chaplin, P Livermore et al (2019), “Development of a benchmarking toolkit for adolescent and young adult rheumatology services (BeTAR)”, Pediatric Rheumatology 17, 23

D Pinto, U Bockenholt, J Lee et al (2019), “Preferences for physical activity: A conjoint analysis involving people with chronic knee pain”, Osteoarthritis & Cartilage 27, 240-47

A Liberman, D Pinto, S Rostanski et al (2019), “Clinical decision-making for thrombolysis of acute minor stroke using adaptive conjoint analysis”, The Neurohospitalist 9, 9-14

A Liberman, D Pinto, D Labovitz, A Naidech & S Prabhakaran (2018), “Evaluating thrombolysis decision making in minor stroke using adaptive discrete choice experimentation”, abstract, American Heart Association/American Stroke Association 2018 International Stroke Conference and State-of-the-Science Stroke Nursing Symposium, Los Angeles, USA, 2018, Stroke 49(suppl 1)

J Hart, R Hinman, A Van Ginckel et al (2018), “Factors influencing cane use for the management of knee osteoarthritis: a cross sectional survey”, Arthritis Care & Research 70, 1455-60

D Pinto, R Chang, U Bockenholt et al (2017), “What physical activity program features are important to patients with knee osteoarthritis? A discrete choice experiment”, poster abstract, World Congress on Osteoporosis, Osteoarthritis and Musculoskeletal Diseases 2017, Florence, Italy, Osteoporosis International 28(suppl1), S516-17

D Pinto, U Bockenholt, R Chang et al (2017), “Preferences for physical activity: A discrete choice experiment in people with chronic knee pain”, abstract, 2017 ACR/ARHP Annual Meeting, San Diego, USA, 2017, Arthritis & Rheumatology 69(suppl10)

D Pinto, M Danilovich, P Hansen et al (2017), “Qualitative development of a discrete choice experiment for physical activity interventions to improve knee osteoarthritis”, Archives of Physical Medicine and Rehabilitation 98, 1210-16

R Walsh, B Aliarzadeh & C Mastrogiacomo (2016), “Patient strength of preference for best practices in patient education”, Journal of Community Medicine & Health Education 6, 1-8

D Griffin, E Dickenson, J O’Donnell et al (2016), “The Warwick Agreement on femoroacetabular impingement syndrome (FAI syndrome): an international consensus statement”, British Journal of Sports Medicine 50, 1169-76

S French, K Bennell, P Nicolson et al (2014), “What do people with knee or hip osteoarthritis need to know? An international consensus list of essential statements for osteoarthritis”, Arthritis Care & Research 67, 809-16

P Nicolson, S French, R Hinman et al (2014), “Developing key messages for people with osteoarthritis: A delphi study”, Osteoarthritis & Cartilage 22, S305-S306

A Chan, M Tao, S Marsh & H Petousis-Harris (2024), “Vaccine decision making in New Zealand: a discrete choice experiment”, BMC Public Health 24, 1-11

V Jain, R Atun, P Hansen & P Lorgelly (2022), “Which countries need Covid-19 vaccines the most? Development of a prioritisation tool”, BMC Public Health 22, 1518

D Wesselbaum & P Hansen (2022), “Lockdown design: Which features of lockdowns are most important to Covid-19 experts?”, Journal of the Royal Society of New Zealand 52, 569-79

H Chaker, A Rhili, I Zamali et al (2022), “Multi-criteria decision analysis to prioritize people for Covid-19 vaccination when vaccines are in short supply”, Frontiers in Health Services 2, 760626

M Roy, P Hansen, T Sullivan, F Ombler, M Kiore, A Stapleton & C Carr (2021), “Rapid development of a tool for prioritizing Covid-19 patients for intensive care” Critical Care Explorations 3, e0368

P De Nardo, E Gentilotti, F Mazzaferri et al and Covid-19 MCDA Group (2020), “Multi-Criteria Decision Analysis to prioritize hospital admission of patients affected by Covid-19 in low-resource settings with hospital-bed shortage”, International Journal of Infectious Diseases 98, 494-500

V Chechnev (2025), “Using decision support systems in automation of decision-making processes”, Russian Digital Libraries Journal 28, 163-83 [in Russian]

M Hatefi (2023), “A typology scheme for the criteria weighting methods in MADM”, International Journal of Information Technology & Decision Making 22, 1439-88

E Petrova & R Ştefănescu (2022), “Decision making, some individual decision-making styles and software for decision making”, Defence Science Review 15, 1-12

C Labianca, S De Gisi & M Notarnicola (2022), “Multi-criteria decision-making”, In: Assessing Progress Towards Sustainability, Elsevier, 219-243

S Babashahi, P Hansen & R Peeters (2023), “External validity of multi-criteria preference data obtained from non-random sampling: measuring cohesiveness within and between groups”, Annals of Operations Research 325, 939-49

A Aramja & O Kamach (2022) “Decision support tool for manufacturing execution systems: Case study from the steel industry”, International Conference on Advanced Intelligent Systems for Sustainable Development Applied to Agriculture, Energy, Health, Environment, Industry, Education, Economy and Security, Tangier, Morocco 2020, In: J Kacprzyk, V Balas & M Ezziyyani (editors), Advances in Intelligent Systems and Computing 1417, 411-26

A Stipeč & B Boshkoska (2021), “Comparison of AHP, PAPRICA, PROMETHEE, DEX and TOPSIS on an application for employee selection”, International Conference on Decision Support System Technology, Loughborough, United Kingdom, In: U Jayawickrama, P Delias, M Escobar & J Papathanasiou (editors), Decision Support Systems XI: Decision Support Systems, Analytics and Technologies in Response to Global Crisis Management, Lecture Notes in Business Information Processing 414, 44-54

S Kadenko, V Tsyganok, O Andriichuk, A Karabchuk & M Fu (2020), “An overview of decision support software: strategic planning perspective”, Інформаційні Технології І Безпека, 34

S Babashahi, P Hansen, R Peeters & T Sullivan (2020), “Evaluating the reliability and validity of two prominent MCDA methods”, abstract, Biennial European Meeting of the Society for Medical Decision Making, Berlin, Germany, 2020, postponed to 2022, Medical Decision Making 40, E470

S Kadenko, V Tsyganok, O Andriichuk, A Karabchuk & M Fu (2020), “An overview of decision support software: Strategic planning perspective”, XX International Scientific and Practical Conference “Information Technologies and Security” 2020 (ITS 2020), Kyiv, Ukraine, CEUR Workshop Proceedings 2859, 142-56

V Lakhno, T Kartbayev, A Turginbayeva, Zh Alimseitova & G Beketova (2020), “Analysis of existing and development prospects of decision support systems for evaluating investment projects in the field of enterprise digitalization”, International Journal of Advanced Trends in Computer Science and Engineering 9, 8533-39

S Kadenko, V Tsyganok, O Andriichuk & A Karabchuk (2020), “Analysis of decision support tools in the context of solving strategic planning tasks” (in Ukrainian), Registration, Storage and Data Processing 22, 77-91

B Németh, A Molnár, S Bozóki et al (2019), “Comparison of weighting methods used in multicriteria decision analysis frameworks in healthcare with focus on low-and middle-income countries”, Journal of Comparative Effectiveness Research 8, 195-204

S Mirzaee, M Ruth & D Fannon (2019), “Reconciling diverse perspectives of decision makers on resilience and sustainability”, Chapter 19, In: M Ruth & S Goessling-Reisemann, Handbook on Resilience of Socio-Technical Systems, Elgar, 360-86

F Vergara-Solana, M Araneda & G Ponce-Díaz (2019), “Opportunities for strengthening aquaculture industry through multicriteria decision-making”, Reviews in Aquaculture 11, 105-18

S Gafar (2018), “Decision support top software products: A review”, Engineering and Technology Journal 3, 416-20

A Kumar, B Sah, A Singh et al (2017), “A review of multi criteria decision making (MCDM) towards sustainable renewable energy development”, Renewable and Sustainable Energy Reviews 69, 596-609

N Grima, S Singh & B Smetschka (2017), “Decision making in a complex world: Using OPTamos in a multi-criteria process for land management in the Cuitzmala watershed in Mexico”, Land Use Policy 67, 73-85

J Mustajoki & M Marttunen (2017), “Comparison of multi-criteria decision analytical software for supporting environmental planning processes”, Environmental Modelling & Software 93, 78-91

R Sengupta (2016), “Other decision-making models”, Chapter 5, In: Decision Sciences: Theory and Practice, CRC Press

HR Weistroffer & Y Li (2016), “Multiple criteria decision analysis software”, Chapter 12, In: S Greco, M Ehrgott & JR Figueira (editors), Multiple Criteria Decision Analysis. State of the Art Surveys, International Series in Operations Research & Management Science 233, 1301-41

U Baizyldayeva, O Vlasov, A Kuandykov & T Akhmetov (2013), “Multi-criteria decision support systems. Comparative analysis”, Middle-East Journal of Scientific Research 16, 1725-30

P Hansen & F Ombler (2008), “A new method for scoring multi-attribute value models using pairwise rankings of alternatives”, Journal of Multi-Criteria Decision Analysis 15, 87-107

Y Shen, Y Cai & X Wang (2024), “Intangible cultural heritage in industrial design”, Digital Scholarship in the Humanities 39, 354-72

J Vepsäläinen (2022), “Engineering idea generation framework for the digital era”, NordDesign 2022, Copenhagen, Denmark, Proceedings of NordDesign 2022, 1-12

F Martins, E Santos & L Vils (2017), “Organizational creativity in innovation – a multicriteria decision analysis”, Independent Journal of Management & Production8, 1223-45

L Dalgaard, T Heikkilä & J Koskinen (2014), “The R3-COP decision support framework for autonomous robotic system design”, Proceedings of the joint 45th International Symposium on Robotics and 8th German Conference on Robotics (ISR-Robotik 2014), München, Germany, 2014

L Dalgaard (2014), “Technology assessment in robotic systems design using PAPRIKA”, Proceedings of the 7th International Conference on Human Systems Interaction, Lisbon, Portugal, 2014

T Heikkilä, L Dalgaard & J Koskinen (2013), “Designing Autonomous Robot Systems – Evaluation of the R3-COP Decision Support System approach”, Proceedings of the ERCIM/EWICS Workshop on Dependable Embedded and Cyber-physical Systems (DECS’13) at the 32nd International Conference on Computer Safety, Reliability & Security (SAFECOMP 2013), Toulouse, France, 2013

T Heikkilä, L Dalgaard & J Koskinen (2013), “Decision support for designing autonomous robot systems”, Proceedings of AutomaatioXX. Automation and Systems without Borders – Beyond Future, Helsinki, Finland, 2013

P Isihara, C Shi, J Ward et al (2020), “Identifying most typical and most ideal attribute levels in small populations of expert decision makers: Studying the Go/No Go decision of disaster relief organizations”, Journal of Choice Modelling 35,100204

E Kay, J Stevenson, C Bowie, V Ivory & J Vargo (2019), The Resilience Warrant of Fitness Research Programme: Towards a method for applying the New Zealand Resilience Index in a regional context, June 2019 report, 1-26

R Jana, C Prakash & A Tiwari (2019), “Humanitarian aid delivery decisions during the early recovery phase of disaster using a discrete choice multi-attribute value method”, Annals of Operations Research 283, 1211-25

E Kay, J Stevenson & C Bowie (2018), “Weighting indicators of resilience: Expert opinions on the New Zealand Resilience Index”, Results Bulletin 2018-12

V Rypdal, H Brunner, B Feldman et al (2025), “Physician's global assessment of disease activity in juvenile idiopathic arthritis: consensus-based recommendations from an international task force”, Annals of the Rheumatic Diseases, early online version

T Uhlig, J Stjärne, L Karoliussen et al (2025), “Remission in gout is possible: 5-year follow-up in the NOR-Gout study”, Seminars in Arthritis and Rheumatism 72, 152698 

G Zanframundo, E Dourado, I Bauer-Ventura et al (2025), “The role of multi-criteria decision analysis in the development of candidate classification criteria for antisynthetase syndrome: analysis from the CLASS project”, Annals of the Rheumatic Diseases, early online version

Y Zhao, M Oliver, A Schnabel et al (2025), “EULAR/ACR classification criteria for paediatric chronic nonbacterial osteomyelitis (CNO)”, Annals of the Rheumatic Diseases, early online version

E Khaleva, C Brightling, T Eiwegger et al (2024), “Patient-centred composite scores as tools for assesment of response to biological therapy for paediatric and adult severe asthma”, European Respiratory Journal, early online version

P McDowell, J Busby, J Stone, C Butler & L Heaney (2024), “Longitudinal assessment of glucocorticoid toxicity reduction in patients with severe asthma treated with biologic therapies”, The Journal of Allergy and Clinical Immunology: In Practice 13, 298-307

T Uhlig (2024), “Remission is the mission in gout”, The Journal of Rheumatology 51, 1057-59

A Tabi-Amponsah, M Doherty, A Sarmanova et al (2024), “Post-hoc analysis of two gout remission definitions in a two-year randomized controlled trial of nurse-led versus usual gout care”, Seminars in Arthritis and Rheumatism 69, 152555

M Barbhaiya, S Zuily, M Amigo et al (2024), “Development of the 2023 ACR/EULAR antiphospholipid syndrome classification criteria, Phase III‐D Report: Multi Criteria Decision Analysis”, Arthritis Care & Research 76, 1617-25

A Tabi-Amponsah, L Stamp, A Horne et al (2024), “Analysis of gout remission definitions in a randomised controlled trial of colchicine prophylaxis for people with gout initiating allopurinol”, The Journal of Rheumatology 51, 1135-40

G Wells, F Guillemin, P Merkel et al (2024), “Advancing composite outcome measures: insights on weighting components from OMERACT 2023”, Seminars in Arthritis and Rheumatism 152503

G Zanframundo, E Dourado, I Bauer-Ventura et al (2024), “The role of multi-criteria decision analysis in the development of candidate classification criteria for antisynthetase syndrome: analysis from the class project”, abstract, EULAR 2024 European Congress of Rheumatology, Vienna, Austria, Annals of the Rheumatic Diseases 83(suppl 1), 92-93

V Rypdal, B Gottlieb, A Aggarwal et al (2024), “Toward the development of consensus-based guidelines for scoring the physician global assessment of disease activity in juvenile idiopathic arthritis”, abstract, EULAR 2024 European Congress of Rheumatology, Vienna, Austria, Annals of the Rheumatic Diseases 83(suppl 1), 224

I Haugen, D Felson, A Abhishek et al (2024), “2023 EULAR classification criteria for hand osteoarthritis”, Annals of the Rheumatic Diseases 83, 1428-35

F Del Galdo, L Bissell, S Huang et al (2023), “Development and validation of ranked composite important difference (RCID) score in diffuse cutaneous systemic sclerosis”, abstract, EULAR 2023 European Congress of Rheumatology, Milan, Italy, Annals of the Rheumatic Diseases 82(suppl 1), 416

A Abhishek, S Tedeschi, T Pascart et al (2023), “The 2023 ACR/EULAR classification criteria for calcium pyrophosphate deposition disease”, Annals of the Rheumatic Diseases 83, 1248-57

M Barbhaiya, S Zuily, R Naden et al (2023), “The 2023 ACR/EULAR antiphospholipid syndrome classification criteria”, Annals of the Rheumatic Diseases 82, 1258-70

A Abhishek, S Tedeschi, T Pascart et al (2023), “The 2023 ACR/EULAR classification criteria for calcium pyrophosphate deposition disease”, Arthritis & Rheumatology 75, 1703-13

M Barbhaiya, S Zuily, R Naden et al (2023), “The 2023 ACR/EULAR antiphospholipid syndrome classification criteria”, Arthritis & Rheumatology 75, 1687-1702

S Li, C Rabinovich, M Becker et al (2023), “Capturing the range of disease involvement in localized scleroderma: The Localized scleroderma Total Severity Scale (LoTSS)”, Arthritis Care & Research 76, 616-26

G Zanframundo, S Faghihi-Kashani, P Hansen et al (2023), “Preliminary steps for multicriteria decision analysis process in the development of classification criteria for antisynthetase syndrome: the use of 1000minds for the CLASS project”, abstract, 4th Global Conference on Myositis (GCOM), Prague, Czech Republic, 2022, Clinical and Experimental Rheumatology 41, 527

T Otobo, M Tolend, A Meyers et al (2023), “Determination of relative weightings for sacroiliac joint pathologies in the OMERACT Juvenile Arthritis Magnetic Resonance Imaging Sacroiliac Joint Score”, Journal of Clinical Medicine 12, 2729

L Bissell, D Furst, F Del Galdo et al (2022), “The development of the ranked composite important difference in diffuse cutaneous systemic sclerosis; a clinical and patient meaningful anchor to the ACR-Composite Response Index in SSc”, abstract, ACR Convergence 2022, Philadelphia, USA, 2022, Arthritis & Rheumatology, 74(suppl 9), 1052-54

K Costenbader (2022), “Ever-evolving disease classification criteria for clinical trials and studies: the case of systemic lupus erythematosus”, In: M Lockshin, M Crow & M Barbhaiya (editors), Diagnoses Without Names, Springer, Cham

J Stone, P McDowell, D Jayne et al (2022), “The glucocorticoid toxicity index: Measuring change in glucocorticoid toxicity over time”, Seminars in Arthritis and Rheumatism 55, 152010

P Brogan, R Naden, S Ardoin et al (2022), “The pediatric glucocorticoid toxicity index”, Seminars in Arthritis and Rheumatism 56, 152068

A Damiani, G Sakellariou, A Adinolfi et al on behalf of the Italian society for Rheumatology (SIR) Ultrasound group (2022), “The first algorithm to integrate ultrasonography in the diagnostic process of differential diagnosis of inflammatory arthropathy in clinical practice: A study from the MSUS Working Group of the Italian Society of Rheumatology”, abstract, EULAR 2022 European Congress of Rheumatology, Copenhagen, Denmark, Annals of the Rheumatic Diseases 81(suppl1), 292-93

L Bissell, D Furst, F Del Galdo et al on behalf of Linear Criss (2022), “The development of the linear CRISS; a clinical and patient meaningful anchor to the ACR-CRISS in scleroderma”, abstract, Annual European Congress of Rheumatology, EULAR 2022, Copenhagen, Denmark, 2022, Annals of the Rheumatic Diseases 81(suppl1), 728

N Dalbeth, C Frampton, M Fung, S Baumgartner & H Choi (2022), “Predictors of patient and physician assessments of gout control”, Arthritis Care & Research, forthcoming

I Haugen, D Felson, A Abhishek et al (2022), “Development of radiographic classification criteria for hand osteoarthritis: Methodological report (Phase 2)”, RMD Open 8, 1-10

M Lockshin, M Crow & M Barbhaiya (2022), “When a diagnosis has no name: Uncertainty and opportunity”, ACR Open Rheumatology 4, 197-201

H Lythgoe, L McCann, C Hedrich & M Aringer (2022), “Classification of systemic lupus erythematosus in children and adults”, Clinical Immunology 234, 108898

M Tolend, T Junhasavasdikul, R Cron et al (2022), “Discrete choice experiment on a magnetic resonance imaging scoring system for temporomandibular joints in juvenile idiopathic arthritis” Arthritis Care & Research 74, 308-16

E Cipolletta, J Di Battista, M Di Carlo et al (2021), “Sonographic estimation of monosodium urate burden predicts the fulfillment of the 2016 remission criteria for gout: a 12-month study”, Arthritis Research Therapy 23, 185 

P McDowell, J Stone, Y Zhang et al (2021), “Quantification of glucocorticoid-associated morbidity in severe asthma using the Glucocorticoid Toxicity Index”, The Journal of Allergy and Clinical Immunology: In Practice 9, 365-72

K Quinn, S Monti, R Christensen et al (2021), “Developing a composite outcome tool to measure response to treatment in anca-associated vasculitis: A mixed methods study from OMERACT 2020”, Seminars in Arthritis and Rheumatism 51, 1134-38

A Mahmoudian, S Lohmander, M Englund, P Hansen, F Luyten & International Early-stage Knee OA Classification Criteria Expert Panel (2021), “Lack of agreement in experts’ classification of patients with early-stage knee osteoarthritis”, abstract, 2021 OARSI Virtual World Congress on Osteoarthritis: OARSI Connect ‘21, Osteoarthritis and Cartilage 29, S299-S300

C Shiboski & T Daniels (2021), “Historical background, classification, and diagnostic criteria”, Section 1.2, In: E Price & A Tappuni (editors), Oxford Textbook of Sjögren's Syndrome, Oxford University Press

N Dalbeth, L Stamp & W Taylor (2021), “What is remission in gout and how should we measure it?”, Rheumatology 60, 1007-9

M Aringer, N Leuchten & S Johnson (2020), “New criteria for Lupus”, Current Rheumatology Reports 22, 1-8

Z Wallace, R Naden, S Chari et al (2020), “The 2019 American College of Rheumatology/European League Against Rheumatism Classification Criteria for IgG4‐Related Disease”, Arthritis & Rheumatology 72, 7-19

M Aringer, C Costenbader, D Daikh, et al (2019), “2019 European League Against Rheumatism/American College of Rheumatology classification criteria for systemic lupus erythematosus”, Annals of the Rheumatic Diseases 78, 1151-59

M Aringer, C Costenbader, D Daikh, et al (2019), “2019 European League Against Rheumatism/American College of Rheumatology classification criteria for systemic lupus erythematosus”, Arthritis & Rheumatology 71, 1400-12

S Li, R Fuhlbrigge, R Laxer et al (2019), “Developing comparative effectiveness studies for a rare, understudied pediatric disease: lessons learned from the CARRA juvenile localized scleroderma consensus treatment plan pilot study”, Pediatric Rheumatology 17, 43

T Ribeiro, A Abad & B Feldman (2019), “Developing a new scoring scheme for the Hemophilia Joint Health Score 2.1”, Research and Practice in Thrombosis and Haemostasis 3, 405-11

M Finetti & M Gattorno (2019), “The role of international registries for rare autoinflammatory diseases”, Chapter 14, In: P Hashkes, R Laxer & A Simon (editors), Textbook of Autoinflammation, Springer

N ter Haar, M Piram & I Koné-Paut (2019), “Monitoring disease activity, damage and quality of life”, Chapter 13, In: P Hashkes, R Laxer & A Simon (editors), Textbook of Autoinflammation, Springer

S Tedeschi, S Johnson, D Boumpas et al (2019), “Multicriteria decision analysis process to develop new classification criteria for systemic lupus erythematosus”, Annals of the Rheumatic Diseases 78, 634-40

S Rosina, G Varnier, M Mazzoni et al (2018), “Innovative research design to meet the challenges of clinical trials for juvenile dermatomyositis”, Current Rheumatology Reports 20, 29

L Rider, R Aggarwal, P Machado et al (2018), “Update on outcome assessment in myositis”, Nature Reviews Rheumatology 14, 303-18

S Tedeschi, S Johnson, D Boumpas et al (2017), “Multicriteria decision analysis for developing new classification criteria for systemic lupus erythematosus”, oral presentation, Annual European Congress of Rheumatology, Madrid, Spain, 2017, Annals of the Rheumatic Diseases 76(suppl2), 50

S Zuily, M Barbhaiya, K Costenbader & D Erkan (2017), “15th International Congress on Antiphospholipid Antibodies Task Force on Antiphospholipid Syndrome Classification Report”, Chapter 15, In: D Erkan & M Lockshin (editors), Antiphospholipid Syndrome: Current Research Highlights and Clinical Insights, 279-80

L Rider, R Aggarwal, A Pistorio et al for the International Myositis Assessment and Clinical Studies Group and the Paediatric Rheumatology International Trials Organisation (2017), “American College of Rheumatology/European League Against Rheumatism criteria for minimal, moderate, and major clinical response in juvenile dermatomyositis”, Annals of the Rheumatic Diseases 76, 782-91

L Rider, R Aggarwal, A Pistorio et al for the International Myositis Assessment and Clinical Studies Group and the Paediatric Rheumatology International Trials Organisation (2017), “2016 American College of Rheumatology/European League Against Rheumatism Criteria for minimal, moderate, and major clinical response in juvenile dermatomyositis: An International Myositis Assessment and Clinical Studies Group/Paediatric Rheumatology International Trials Organisation Collaborative Initiative”, Arthritis & Rheumatology 69, 911-23

R Aggarwal, L Rider, N Ruperto et al for the International Myositis Assessment and Clinical Studies Group and the Paediatric Rheumatology International Trials Organisation (2017), “2016 American College of Rheumatology/European League Against Rheumatism criteria for minimal, moderate, and major clinical response in adult dermatomyositis and polymyositis: An International Myositis Assessment and Clinical Studies Group/Paediatric Rheumatology International Trials Organisation Collaborative Initiative”, Arthritis & Rheumatology 69, 898-910

R Aggarwal, L Rider, N Ruperto et al for the International Myositis Assessment and Clinical Studies Group and the Paediatric Rheumatology International Trials Organisation (2017), “2016 American College of Rheumatology/European League Against Rheumatism criteria for minimal, moderate, and major clinical response in adult dermatomyositis and polymyositis”, Annals of the Rheumatic Diseases 76, 792-801

L Rider, N Ruperto, R Aggarwal et al (2017), “2016 ACR-EULAR adult dermatomyositis and polymyositis and juvenile dermatomyositis response criteria – methodological aspects”, Rheumatology 65, 1884-93

N ter Haar, K Annink, M Sulaiman et al (2017), “Development of the autoinflammatory disease damage index (ADDI)”, Annals of the Rheumatic Diseases 76, 821-30

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C Shiboski, S Shiboski, R Seror et al and the International Working Group on SS Classification Criteria (2017), “2016 American College of Rheumatology/European League Against Rheumatism Classification Criteria for primary Sjögren’s Syndrome: A consensus and data-driven methodology involving three international patient cohorts”, Arthritis & Rheumatology 69, 35-45

E Miloslavsky, R Naden, J Bijlsma et al (2017), “Development of a Glucocorticoid Toxicity Index (GTI) using multicriteria decision analysis”, Annals of the Rheumatic Diseases 76, 543-46

M.L Avila, L Brandão, S Williams et al (2016), “Development of CAPTSure™–a new index for the assessment of pediatric postthrombotic syndrome”, Journal of Thrombosis and Haemostasis 14, 2376-85

M Aringer, T Dörner, N Leuchten & S Johnson (2016), “Toward new criteria for systemic lupus erythematosus – a standpoint”, Lupus 25, 805-11

A Vargas-Santos, W Taylor & T Neogi (2016), “Gout classification criteria: Update and implications“, Current Rheumatology Reports 18, 1-10

W Taylor (2016), “Pros and cons of conjoint analysis of discrete choice experiments to define classification and response criteria in rheumatology”, Current Opinion in Rheumatology 28, 117-21

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T Neogi, T Jansen, N Dalbeth et al (2015), “2015 Gout Classification Criteria: An American College of Rheumatology/European League Against Rheumatism Collaborative Initiative”, Arthritis & Rheumatology 67, 2557-68

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D Aletaha (2015), “Classification of rheumatoid arthritis”, pp. 3-21, In: P Emery (editor), Atlas of Rheumatoid Arthritis, Springer

J Pope & S Johnson (2015), “New classification criteria for systemic sclerosis (scleroderma)”, Rheumatic Disease Clinics of North America 41, 383-98

S Johnson (2015), “New ACR EULAR Guidelines for Systemic Sclerosis Classification”, Current Rheumatology Reports 17, 1-8

S Johnson, R Naden, J Fransen et al (2014), “Multicriteria decision analysis methods with 1000minds for developing systemic sclerosis classification criteria”, Journal of Clinical Epidemiology 67, 706-14

L Rider, R Aggarwal, N Bayat et al (2014), “A hybrid conjoint analysis model is proposed as the definition of minimal, moderate and major clinical improvement in juvenile dermatomyositis clinical trials”, abstract, 2014 ACR/ARHP Annual Meeting, Boston, USA, 2014, Arthritis & Rheumatology 66(suppl), S404-5

H de Lautour, N Dalbeth & W Taylor (2014), “Development of preliminary remission criteria for gout using Delphi and 1000minds consensus exercises”, abstract, 2014 ACR/ARHP Annual Meeting, Boston, USA, 2014, Arthritis & Rheumatology 66(suppl), S68

R Aggarwal, L Rider, N Ruperto et al (2014), “A consensus hybrid definition using a conjoint analysis is proposed as response criteria for minimal and moderate improvement in adult polymyositis and dermatomyositis clinical trials”, abstract, 2014 ACR/ARHP Annual Meeting, Boston, USA, 2014, Arthritis & Rheumatology 66(suppl), S404-5

M Vinall (2013), “2013 ACR-EULAR Scleroderma Classification Criteria”, MD Conference Express 13, 12-13

F van den Hoogen, D Khanna, J Fransen et al (2013), “2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League Against Rheumatism collaborative initiative”, Arthritis & Rheumatism 65, 2737-47

F van den Hoogen, D Khanna, J Fransen et al (2013), “2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League Against Rheumatism collaborative initiative”, Annals of the Rheumatic Diseases 72, 1747-55

F van den Hoogen, D Khanna, J Fransen et al (2013), “Classification criteria for systemic sclerosis: Preliminary results”, abstract, 2014 Annual European Congress of Rheumatology, Madrid, Spain, 2013, Annals of the Rheumatic Diseases 72(suppl), A59

J Pope, D Khanna, J Fransen et al (2013), “The ACR/EULAR Classification Criteria for Systemic Sclerosis (SSc)”, CRA Abstracts, Canadian Rheumatology Association (CRA) Annual Scientific Meeting, Ottawa, Canada, 2013, The Journal of Rheumatology, 40, 951

M Mjaavatten & V Bykerk (2013), “Early rheumatoid arthritis: The performance of the 2010 ACR/EULAR criteria for diagnosing RA”, Best Practice & Research Clinical Rheumatology 27, 251-6

F Dobson, R Hinman, E Roos et al (2013), “OARSI recommended performance-based tests to assess physical function in people diagnosed with hip or knee osteoarthritis”, Osteoarthritis & Cartilage 21, 1042-52

F Dobson, R Hinman, E Roos et al (2013), “OARSI recommended performance-based tests to assess physical function in people with established hip and knee osteoarthritis”, abstract, 2013 Osteoarthritis Research Society International (OARSI) World Congress, Philadelphia, USA, Osteoarthritis & Cartilage 21(suppl), S39-S40

W Taylor, M Brown, O Aati et al (2013), “Do patient preferences for core outcome domains for chronic gout studies support the validity of composite response criteria?”, Arthritis Care & Research 65, 1259-64

J Pope, J Fransen, S Johnson et al (2012), “Report from the EULAR ACR Scleroderma Classification Criteria Committee”, Rheumatology 51(suppl 2), ii1

W Taylor, J Singh, K Saag et al (2011), “Bringing it all together: A novel approach to the development of response criteria for chronic gout clinical trials”, The Journal of Rheumatology 38, 1467-70

B Combe (2011), “The new classification criteria for rheumatoid arthritis and their impact on therapeutic decisions”, Editorial, Joint Bone Spine 78, 539-41

A Saraux, G Tobon, S Jousse-Joulin & V Devauchelle-Pensec (2010), “Les critères de classification et/ou de prédiction de la polyarthrite rhumatoïde”, Rhumatisme Monographies 77, 12-16

J Kay & K Upchurch (2012), “ACR/EULAR 2010 rheumatoid arthritis classification criteria”, Rheumatology 51, vi5-vi9

D Aletaha, T Neogi, A Silman et al (2010), “2010 Rheumatoid arthritis classification criteria: An American College of Rheumatology / European League Against Rheumatism collaborative initiative”, Annals of the Rheumatic Diseases 69, 1580-88

T Neogi, D Aletaha, D Silman et al (2010), “The 2010 American College of Rheumatology / European League Against Rheumatism classification criteria for rheumatoid arthritis: Phase 2 methodological report”, Arthritis & Rheumatism 62, 2582-91

E Stanisławska-Biernat, M Sierakowska & S Sierakowski (2010), “Recommendations for diagnosis and treatment. New rheumatoid arthritis classification criteria”, Reumatologia 48, 361-65

D Aletaha, T Neogi, A Silman et al (2010), “2010 Rheumatoid arthritis classification criteria: An American College of Rheumatology / European League Against Rheumatism collaborative initiative”, Arthritis & Rheumatism 62, 2569-81

H Sati, E Carrara, A Savoldi et al and the WHO Pathogens Priority List advisory group (2025), “The WHO Bacterial Priority Pathogens List 2024: a prioritisation study to guide research, development, and public health strategies against antimicrobial resistance”, The Lancet Infectious Diseases, early online version

World Health Organization, “WHO bacterial priority pathogens list, 2024: bacterial pathogens of public health importance, to guide research, development, and strategies to prevent and control antimicrobial resistance”, World Health Organization, 2024

B Ukoaka, O Okesanya, F Daniel et al (2024), “Updated WHO list of emerging pathogens for a potential future pandemic: Implications for public health and global preparedness”, Le Infezioni in Medicina 32, 463

T Jesudason (2024), “WHO publishes updated list of bacterial priority pathogens”, The Lancet Microbe 5, 100940

M Hasso-Agopsowicz, A Hwang, M Hollm-Delgado et al (2024), “Identifying WHO global priority endemic pathogens for vaccine research and development (R&D) using multi-criteria decision analysis (MCDA): an objective of the Immunization Agenda 2030”, EBioMedicine 110, 105424

S Babashahi, P Hansen & T Sullivan (2021), “Creating a priority list of non-communicable diseases to support health research funding decision-making”, Health Policy 125, 221-28

S Babashahi (2019), “Using Multiple Criteria Decision Analysis (MCDA) to create a priority list of chronic noncommunicable diseases (CNCD) to guide health research spending”, abstract, 2019 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Europe Conference, Copenhagen, Denmark, Value in Health 22(Suppl 3), S712

P Hansen (2018), “The world’s deadliest diseases: The WHO priority list of antibiotic-resistant bacteria”, EcoNZ@Otago 40, 4-6

E Tacconelli, E Carrara, A Savoldi et al and the WHO Pathogens Priority List working group (2018), “Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis”, The Lancet Infectious Diseases 18, 318-27

K Weyer, E Tacconelli, N Magrini & Co-ordinating Group (2017), “Prioritization of pathogens to guide discovery, research and development of new antibiotics for drug-resistant bacterial infections, including tuberculosis”, World Health Organization (WHO/EMP/IAU/2017.12)

European Centre for Disease Prevention and Control (2017), ECDC Tool for the Prioritisation of Infectious Disease Threats – Handbook and Manual, ECDC

E Tacconelli, N Magrini & Co-ordinating Group, “Global priority list of antibiotic-resistant bacteria to guide research, discovery, and development of new antibiotics”, WHO Short Summary, 2017

S Dash, S Chakravarty, N Giri, U Ghugar & G Fotis (2024), “Performance assessment of different sustainable energy systems using multiple-criteria decision-making model and self-organizing maps”, Technologies 12, 42

J Weber (2023), “Gridlock in compromise, or is multi-objective optimisation possible in renewable energy planning? A stakeholder analysis using scenario-MCDA”, International Journal of Sustainable Energy 42, 1538-68

M Ismail, M Alham & D Ibrahim (2023), “A novel approach for optimal hybrid energy decarbonization using multi-criteria decision analysis: Abu Rudeis, Egypt as a case study”, Energy Conversion and Management 290, 117199

C Francis, P Hansen, B Guðlaugsson, D Ingram & C Thomson (2022), “Weighting key performance indicators of smart local energy systems: A discrete choice experiment”, Energies 15, 9305

D Agar, P Hansen, M Rudolfsson & B Blagojević, “Combining behavioural TOPSIS and six multi-criteria weighting methods to rank biomass fuel pellets for energy use in Sweden”, Energy Reports 10, 706-18

K Kons, B Blagojević, B Mola-Yudego et al (2022), “Industrial end-users’ preferred characteristics for wood biomass feedstocks”, Energies 15, 3721

W Ogden & P Thorsnes (2019), “Electric or petrol/diesel? Which car would you choose?”, EcoNZ@Otago 42, 1-4

R Ford, S Walton, J Stephenson et al (2016), “Emerging energy transitions: PV uptake beyond subsidies”, Technological Forecasting and Social Change 117, 138-50

R Ford, O Sumavsk, A Clarke & P Thorsnes (2014), “Personalized energy priorities: a user-centric application for energy advice”, In: A Marcus (editor), Design, User Experience, and Usability. User Experience Design for Everyday Life Applications and Services, Lecture Notes in Computer Science 8519, 542-53

R Pomeroy (2013), “Harvesting solar energy in sunny Dunedin”, EcoNZ@Otago 31, 9-11

A Brock, I Williams & S Kemp (2023), “’I'll take the easiest option please’. Carbon reduction preferences of the public”, Journal of Cleaner Production 429, 139398

J Hartmann, E Rorije, P Wassenaar & E Verbruggen (2023), “Screening and prioritising persistent, mobile and toxic chemicals: development and application of a robust scoring system”, Environmental Sciences Europe 35, 40

F Mansour, M Al-Hindi, A Yassine & E Najjar, (2022), “Multi-criteria approach for the selection of water, energy, food nexus assessment tools and a case study application”, Journal of Environmental Management 322, 116139

V Macknight & F Medvecky (2021) “‘It’s not like any survey I’ve ever seen before’: discrete choice experiments as a valuation technology”, Valuation Studies 8, 7-31

J Whitehead, C MacLeod & H Campbell (2020), “Improving the adoption of agricultural sustainability tools: A comparative analysis”, Ecological Indicators 111, 106034

T Derkley, D Biggs, M Holden & C Phillips (2019), “A framework to evaluate animal welfare implications of policies on rhino horn trade”, Biological Conservation 235, 236-49

E de Olde, H Moller, F Marchand et al (2017), “When experts disagree: The need to rethink indicator selection for assessing sustainability of agriculture”, Environment, Development and Sustainability 19, 1327–42

S Chhun, V Kahui & P Thorsnes (2015), “Advancing marine policy towards ecosystem based management by eliciting public preferences”, Marine Resources Economics 30, 261-75

P Graff & S McIntyre (2014), “Using ecological attributes as criteria for the selection of plant species under three restoration scenarios”, Austral Ecology 39, 907-17

G Crozier & A Schulte-Hostedde (2014), “Towards improving the ethics of ecological research”, Science and Engineering Ethics, 1-18

S Chhun, P Thorsnes & H Moller (2013), “Preferences for management of near-shore marine ecosystems: A choice experiment in New Zealand”, Resources 2, 406-38

P Boyd, C Law & S Doney (2011), “Commentary: A climate change atlas for the ocean”, Oceanography 24, 13-16

T Sullivan, E Wyeth, R Turner et al (2025), “Can adolescents value the EQ-5D-Y-5L and EQ-5D-5L, and how do the values compare? A feasibility study”, Value in Health, early online version

A Pak, T Pols, S Kondalsamy-Chennakesavan et al (2024), “A preference-based value framework to assess healthcare provision in an oil and gas industry”, Australian Health Review 48, 524-29

T Sullivan, G McCarty, F Ombler, R Turner, B Mulhern, P Hansen (2024), “Creating an SF-6Dv2 social value set for New Zealand”, Social Science & Medicine 354, 117073

T Sullivan, G McCarty, E Wyeth, R Turner & S Derrett (2023), “Describing the health-related quality of life of Māori adults in Aotearoa me Te Waipounamu (New Zealand)”, Quality Life Research, 1-10

T Sullivan, R Turner, S Derrett & P Hansen (2021), “New Zealand population norms for the EQ-5D-5L constructed from the personal value sets of participants in a national survey”, Value in Health 24, 1308-18

A Pathak, S Sharma, A Heinemann et al (2021), “Development and assessment of a verbal response scale for the Patient-Specific Functional Scale (PSFS) in a low-literacy, non-western population”, Quality of Life Research 30, 613-28

T Sullivan, P Hansen, F Ombler, S Derrett & N Devlin (2020), “A new tool for creating personal and social EQ-5D-5L value sets, including valuing ‘dead’”, Social Science & Medicine 246, 112707

P Hansen, F Ombler & T Sullivan (2019), “An online tool for valuing people’s health, including valuing ‘dead’”, EcoNZ@Otago 43, 6-9

R Norman, B Craig, P Hansen et al (2019), “Issues in the design of discrete choice experiments”, The Patient – Patient-Centered Outcomes Research 12, 281-85

F Ombler, M Albert & P Hansen (2018), “How significant are ‘high’ correlations between EQ-5D value sets?”, Medical Decision Making 38, 635-45

S Wallace,T Bucknall, A Forbes & P Myles (2025), “A mixed-methods study to identify the top 10 research priorities for perioperative medicine in Australia”, British Journal of Anaesthesia, early online version

S Wallace,T Bucknall, A Forbes & P Myles (2023), “A mixed methods study protocol to identify research priorities for perioperative medicine in Australia”, BJA Open 8, 100235

W Taylor, H Tuffaha, C Hawley et al (2023), “Embedding stakeholder preferences in setting priorities for health research: using a discrete choice experiment to develop a multi-criteria tool for evaluating research proposals”, PLOS One 18, e0295304

K Groom, C Mossinger, J Lawrence et al (2022), “The priorities for future clinical trials and large cohort studies addressing health and healthcare for mothers and babies in Aotearoa New Zealand”, New Zealand Medical Journal 135, 43-61

D Hunter, P Nicolson, C Little et al (2019), “Developing strategic priorities in osteoarthritis research: Proceedings and recommendations arising from the 2017 Australian Osteoarthritis Summit”, BMC Musculoskeletal Disorders 20, 74

Y Mei, S Guan, H Zhang, D Hunter, Z Zhang (2018), “Priorities for osteoarthritis research should be done in China”, abstract, Annual European Congress of Rheumatology, EULAR 2018, Amsterdam, The Netherlands, 2018, Annals of the Rheumatic Diseases 77(suppl 2), 1613

Y Mei, S Guan, H Zhang et al (2018), “Priorities for osteoarthritis research in China”, abstract, 2018 OARSI World Congress on Osteoarthritis, Liverpool, UK, 2018, Osteoarthritis & Cartilage 26(suppl 1), S220

S French, P Beliveau, P Bruno et al (2017), “Research priorities of the Canadian chiropractic profession: a consensus study using a modified Delphi technique”, Chiropractic & Manual Therapies 25, 38

I Goranitis, D Sheen, Z Fehlberg et al (2024), “A standardised measurement and valuation scale of genomic utility for policy decisions: the GUV-scale”, Value in Health 28, 184-190

S Khanal, S Nghiem, M Miller, P Scuffham & J Byrnes (2024), “Development of a prioritisation framework to aid healthcare funding decision-making in health technology assessment (HTA) in Australia: application of multi-criteria decision analysis”, Value in Health 27, 1585-93

L Jackson, K Saag, S Johnson & M Danila (2024), “Defining the key clinician skills and attributes for competency in managing patients with osteoporosis and fragility fractures”, Journal of Bone and Mineral Research 39, 425-32

M Anaka, D Chan, S Pattison et al (2024), “Patient priorities concerning treatment decisions for advanced neuroendocrine tumors identified by discrete choice experiments”, The Oncologist 29, 227-34

R Wilson, J Chua, Y Pryymachenko, A Pathak, S Sharma & J Abbott (2022), “Prioritizing healthcare interventions: a comparison of multicriteria decision analysis and cost-effectiveness analysis”, Value in Health 25, 268-75

S Khanal, KA Schmidtke, U Talat, A Turner & I Vlaev (2003), “Using multi-criteria decision analysis to describe stakeholder preferences for new quality improvement initiatives that could optimise prescribing in England”, Frontiers in Health Services 3, 1-11

K Beny, A Dubromel, B du Sartz de Vigneulles et al (2022), “Multiple criteria decision analysis for therapeutic innovations in a hemophilia care center: A pilot study of the organizational impact of innovation in hemophilia care management”, PLOS One, 17, e0273775

M Zozaya González, R Villoro, F Abdalla et al (2022), “Unmet needs in the management of moderate-to-severe psoriasis in Spain: A multidimensional evaluation”, Acta Dermato-Venereologica 102, 1-9

K Beny, A Dubromel, B du Sartz de Vigneulles et al (2022), “Multiple criteria decision analysis for therapeutic innovations in a hemophilia care center: A pilot study of the organizational impact of innovation in hemophilia care management”, PLOS One 17, e0273775 

M Jakubczyk, M Niewada, R Plisko et al (2022), “What matters in treating non-oncological rare diseases? – Eliciting experts’ preferences in Poland with PAPRIKA”, Journal of Multi-Criteria Decision Analysis 29, 110-21

J Chua, P Hansen, A Briggs et al (2020), “Stakeholders’ preferences for osteoarthritis interventions in health services: a cross-sectional study using multi-criteria decision analysis”, Osteoarthritis and Cartilage Open 2, 100110

V Lvovschi, M Maignan, K Tazarourte et al (2020), “Multiple criteria decision analysis approach to consider therapeutic innovations in the emergency department: The methoxyflurane organizational impact in acute trauma pain”, PLOS One 15, e0231571

A Moreno-Calderón, T Tong & P Thokala (2020), “Multi-criteria Decision Analysis software in healthcare priority setting: A systematic review”, PharmacoEconomics 38, 269-83

J Eyles, D Hunter, K Bennell et al (2019), “Priorities for the effective implementation of osteoarthritis management programs: an OARSI international consensus exercise”, Osteoarthritis and Cartilage 27, 1270-79

J Chua, P Hansen, A Briggs, R Wilson, D Gwynne-Jones & J Abbott (2019), “Integrating values and preferences with the best available evidence: a multi-criteria decision analysis approach”, abstract, 2019 OARSI World Congress on Osteoarthritis: Promoting Clinical and Basic Research in Osteoarthritis, Toronto, Canada, 2019, Osteoarthritis and Cartilage 27, S308-S309

J Chua, P Hansen, A Briggs, & J Abbott (2019), “What attributes of interventions for osteoarthritis drive preferences? A discrete choice experiment involving cross-sectoral and multi-disciplinary stakeholder groups”, abstract, 2019 OARSI World Congress on Osteoarthritis: Promoting Clinical and Basic Research in Osteoarthritis, Toronto, Canada, 2019, Osteoarthritis and Cartilage 27, S302

J Eyles, K Bennell, K Dziedzic et al (2019), “Implementation priorities for osteoarthritis management programs”, abstract, 2019 OARSI World Congress on Osteoarthritis: Promoting Clinical and Basic Research in Osteoarthritis, Toronto, Canada, 2019, Osteoarthritis and Cartilage 27, S307-S308

P Hansen & N Devlin (2019), “Multi-Criteria Decision Analysis (MCDA) in health care decision making”, In: Oxford Research Encyclopedia of Economics and Finance, Oxford University Press

I Lasorsa, E Padoano, S Marceglia & A Accardo (2019), “Multi-criteria decision analysis for the assessment of non-clinical hospital services: Methodology and case study”, Operations Research for Health Care 23, 100171

S Howard, I Scott, H Ju, L McQueen & P Scuffham (2019), “Multicriteria decision analysis (MCDA) for health technology assessment: the Queensland Health experience”, Australian Health Review 43, 591-99

M Espinoza, R Rojas & H de Patiño (2018), “Knowledge translation in practice: Exploring the potential use of MCDA in Central America and the Caribbean”, Value in Health Regional Issues 17, 148-9

J Drake, J Carlos T de Hart, C Monleón, W Toro & J Valentim (2017), “Utilization of multiple-criteria decision analysis (MCDA) to support healthcare decision-making FIFARMA, 2016”, Journal of Market Access & Health Policy 5, 1360545

A Shmueli (2017), “Do the equity-efficiency preferences of the Israeli Basket Committee match those of Israeli health policy makers?”, Israel Journal of Health Policy Research 6, 20

A Shmueli, O Golan, F Paolucci & E Mentzakis (2017), “Efficiency and equity considerations in the preferences of health policymakers in Israel”, Israel Journal of Health Policy Research 6, 18

T Sullivan & P Hansen (2017), “Determining criteria and weights for prioritising health technologies based on the preferences of the general population: A New Zealand pilot study”, Value in Health 20, 679-86

N Martelli, P Hansen, H van den Brink et al (2016), “Combining multi-criteria decision analysis and mini-health technology assessment: A funding decision-support tool for medical devices in a university hospital setting”, Journal of Biomedical Informatics 59, 201-08

I Lasorsa, G Abis, B Podda & A Accardo (2015), “Multi-criteria decision analysis to redesign an Italian Clinical Engineering Service under specific needs and regulation requirements”, In: D Jaffray (editor), World Congress on Medical Physics and Biomedical Engineering, 2015, Toronto, Canada, IFMBE Proceedings 51, Springer International Publishing, 1562-5

T Sullivan & P Hansen (2015), “Which drugs, medical procedures and equipment should be funded?”, EcoNZ@Otago 34, 8-12

T Sullivan & P Hansen (2014), “Determining benefits-related criteria and weights for prioritising health technologies”, Occasional Report, 14/01, Centre for Health Systems, University of Otago

O Golan & P Hansen (2012), “Which health technologies should be funded? A prioritization framework based explicitly on value for money”, Israel Journal of Health Policy Research 1, 44

O Golan, P Hansen, G Kaplan & O Tal (2011), “Health technology prioritisation: Which criteria for prioritising new technologies and what are their relative weights?”, Health Policy 102, 126-35

N Devlin & J Sussex (2011), “Incorporating multiple criteria in HTA. Methods and processes”, OHE Report, Office of Health Economics

S Agarwal & H Bansal (2024), “eHTrust: Model for trust evaluation in content-driven health websites”, Multimedia Tools and Applications 83, 86425-55

E Hindalong, J Johnson, G Carenini & T Munzner (2022), “Abstractions for visualizing preferences in group decisions”, Proceedings of the ACM on Human-Computer Interaction 6, 1-44

M Saha, S Panda & S Panigrahi (2022), “A survey on applications of multi-attribute decision making algorithms in cloud computing”, ECS Transactions 107, 12887 

S Thanuskodi (2020), “Use of digital resources among social scientists: an evaluative study”, Chapter 1 In: Challenges and Opportunities of Open Educational Resources Management, pp. 1-23, IGI Global

L Romeo, J Loncarski, M Paolanti et al (2020), “Machine learning-based design support system for the prediction of heterogeneous machine parameters in Industry 4.0”, Expert Systems with Applications 140, 1128691

K Vaghela, P Tanna & A Lathigara (2018), “Job scheduling heuristics and simulation tools in cloud computing environment: A survey”, International Journal of Advanced Networking and Applications 10, 3782-87

H Bansal, P Shukla & M Dhar (2018), “Trust and Credibility Analysis of Websites: Role of trust and credibility in evaluating online content”, Chapter 13, In: H Bansal, G Shrivastava, G Nguyen, L-M Stanciu, Social Network Analytics for Contemporary Business Organizations, IGI Global, pp 259-86

H Alabool, A Kamil, N Arshad & D Alarabiat (2018), “Cloud service evaluation method-based multi-criteria decision-making: A systematic literature review”, Journal of Systems and Software, 139, 161-88

G Hernández-Ledesma, E Ramos, C Fernández-y-Fernández et al (2017), “Selection of best software engineering practices: A Multi-Criteria Decision Making approach”, Research in Computing Science 136, 47-60

S Alismaili, M Li, J Shen & Q He (2017), “A consumer-oriented decision-making approach for selecting the cloud storage service: From PAPRIKA perspective”, In: M Fan, J Heikkilä, H Li, M Shaw & H Zhang (editors), pp. 1-12, Internetworked World, Lecture Notes in Business Information Processing 296, Revised Selected Papers from 15th Workshop on e-Business, WeB 2016, Dublin, Ireland, 2016

S Al Isma’ili, M Li, J Shen & Q He (2016), “Cloud computing adoption decision modelling for SMEs: a conjoint analysis”, International Journal of Web and Grid Services 12, 296-327

S Alismaili, M Li & J Shen (2016), “Cloud computing adoption decision modelling for SMEs: From the PAPRIKA perspective”, In: J Hung, N Yen & K-C Li (editors), pp. 597-615, Frontier Computing: Theory, Technologies and Applications, Lecture Notes in Electrical Engineering 375, proceedings of the 4th International Conference on Frontier Computing, Bangkok, Thailand, 2015

D Kalra & M Birdi (2015), “Differentiating algorithms of cloud task scheduling based on various parameters”, IOSR Journal of Computer Engineering, 17, 35-38

A Mancini, E Frontoni & P Zingaretti (2015), “Embedded multisensor system for safe point-to-point navigation of impaired users”, IEEE Transactions on Intelligent Transportation Systems, 16, 3543-55

S Aggarwal, H Van Oostendorp, Y Reddy & B Indurkhya (2014), “Providing web credibility assessment support”, Proceedings of the 2014 European Conference on Cognitive Ergonomics, Vienna, Austria, 2014

H Lawrence & S Silas (2013), “Efficient Qos based resource scheduling using PAPRIKA method for cloud computing”, International Journal of Engineering Science & Technology 5, 638-43

S Aggarwal & H Van Oostendorp (2011), “An attempt to automate the process of source evaluation”, ACEEE International Journal on Communication 2, 18-20

S Aggarwal & H Van Oostendorp (2011), “An attempt to automate the process of source evaluation”, International Conference on Advances in Computer Engineering, Trivandrum, 2011, ACE Proceedings 2011, 49-51

V Patwardhan, N Ahmed, H Unnikrishnan & J Mallya (2025), “Understanding consumer preferences of whiskey attributes: a conjoint study”, Cogent Business & Management 12, 2472023

S Mandolesi, E Cubero Dudinskaya, S Naspetti et al (2024), “Organic consumers’ preferences for dried pasta made with ancient wheat varieties”, LVIII Società Italiana di Economia Agraria (SIDEA), Conference, Palermo, Italy, 2022. In: A Cavicchi et al, “Innovation and Knowledge in Agri-food and Environmental Systems”, Springer Proceedings in Business and Economics, 207-13

E Sumatra (2024), “Examining how candidate attributes shape Gen Z perceptions for the 2025 Philippine senate elections using conjoint analysis”, Journal of Interdisciplinary Perspectives 3, 172-83

P Patel, M Stenmark, V Parida & P Tran (2023), “A socio-institutional perspective on the reluctance among the elderly concerning the commercialization of 3D surgical video technology in Sweden”, Journal of Innovation & Knowledge 8, 100361

V Payini, J Mallya & S Piramanayagam (2022), “Indian women consumers’ wine choice: a study based on conjoint analysis”, International Journal of Wine Business Research 34, 469-94

T Phan, P Bremer & M Mirosa (2020), “Vietnamese consumers’ preferences for functional milk powder attributes: A segmentation-based conjoint study with educated consumers”, Sustainability 12, 5258

M Mirosa, Y Liu & P Bremer (2020), “Determining how Chinese consumers that purchase Western food products prioritize food safety cues: A conjoint study on adult milk powder”, Journal of Food Products Marketing 26, 358-71

C Parsad, C Chandra & S Suman (2019), “A product feature prioritization-based segmentation model of consumer market for health drink”, International Journal of Strategic Decision Sciences 10, 70-83

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