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Stacey D, Lewis KB, Smith M, Carley M, Volk R, Douglas EE, Pacheco-Brousseau L, Finderup J, Gunderson J, Barry MJ, Bennett CL, Bravo P, Steffensen K, Gogovor A, Graham ID, Kelly SE, Légaré F, Sondergaard H, Thomson R, Trenaman L, Trevena L. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2024; 1:CD001431. [PMID: 38284415 PMCID: PMC10823577 DOI: 10.1002/14651858.cd001431.pub6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
BACKGROUND Patient decision aids are interventions designed to support people making health decisions. At a minimum, patient decision aids make the decision explicit, provide evidence-based information about the options and associated benefits/harms, and help clarify personal values for features of options. This is an update of a Cochrane review that was first published in 2003 and last updated in 2017. OBJECTIVES To assess the effects of patient decision aids in adults considering treatment or screening decisions using an integrated knowledge translation approach. SEARCH METHODS We conducted the updated search for the period of 2015 (last search date) to March 2022 in CENTRAL, MEDLINE, Embase, PsycINFO, EBSCO, and grey literature. The cumulative search covers database origins to March 2022. SELECTION CRITERIA We included published randomized controlled trials comparing patient decision aids to usual care. Usual care was defined as general information, risk assessment, clinical practice guideline summaries for health consumers, placebo intervention (e.g. information on another topic), or no intervention. DATA COLLECTION AND ANALYSIS Two authors independently screened citations for inclusion, extracted intervention and outcome data, and assessed risk of bias using the Cochrane risk of bias tool. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made (informed values-based choice congruence) and the decision-making process, such as knowledge, accurate risk perceptions, feeling informed, clear values, participation in decision-making, and adverse events. Secondary outcomes were choice, confidence in decision-making, adherence to the chosen option, preference-linked health outcomes, and impact on the healthcare system (e.g. consultation length). We pooled results using mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs), applying a random-effects model. We conducted a subgroup analysis of 105 studies that were included in the previous review version compared to those published since that update (n = 104 studies). We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the certainty of the evidence. MAIN RESULTS This update added 104 new studies for a total of 209 studies involving 107,698 participants. The patient decision aids focused on 71 different decisions. The most common decisions were about cardiovascular treatments (n = 22 studies), cancer screening (n = 17 studies colorectal, 15 prostate, 12 breast), cancer treatments (e.g. 15 breast, 11 prostate), mental health treatments (n = 10 studies), and joint replacement surgery (n = 9 studies). When assessing risk of bias in the included studies, we rated two items as mostly unclear (selective reporting: 100 studies; blinding of participants/personnel: 161 studies), due to inadequate reporting. Of the 209 included studies, 34 had at least one item rated as high risk of bias. There was moderate-certainty evidence that patient decision aids probably increase the congruence between informed values and care choices compared to usual care (RR 1.75, 95% CI 1.44 to 2.13; 21 studies, 9377 participants). Regarding attributes related to the decision-making process and compared to usual care, there was high-certainty evidence that patient decision aids result in improved participants' knowledge (MD 11.90/100, 95% CI 10.60 to 13.19; 107 studies, 25,492 participants), accuracy of risk perceptions (RR 1.94, 95% CI 1.61 to 2.34; 25 studies, 7796 participants), and decreased decisional conflict related to feeling uninformed (MD -10.02, 95% CI -12.31 to -7.74; 58 studies, 12,104 participants), indecision about personal values (MD -7.86, 95% CI -9.69 to -6.02; 55 studies, 11,880 participants), and proportion of people who were passive in decision-making (clinician-controlled) (RR 0.72, 95% CI 0.59 to 0.88; 21 studies, 4348 participants). For adverse outcomes, there was high-certainty evidence that there was no difference in decision regret between the patient decision aid and usual care groups (MD -1.23, 95% CI -3.05 to 0.59; 22 studies, 3707 participants). Of note, there was no difference in the length of consultation when patient decision aids were used in preparation for the consultation (MD -2.97 minutes, 95% CI -7.84 to 1.90; 5 studies, 420 participants). When patient decision aids were used during the consultation with the clinician, the length of consultation was 1.5 minutes longer (MD 1.50 minutes, 95% CI 0.79 to 2.20; 8 studies, 2702 participants). We found the same direction of effect when we compared results for patient decision aid studies reported in the previous update compared to studies conducted since 2015. AUTHORS' CONCLUSIONS Compared to usual care, across a wide variety of decisions, patient decision aids probably helped more adults reach informed values-congruent choices. They led to large increases in knowledge, accurate risk perceptions, and an active role in decision-making. Our updated review also found that patient decision aids increased patients' feeling informed and clear about their personal values. There was no difference in decision regret between people using decision aids versus those receiving usual care. Further studies are needed to assess the impact of patient decision aids on adherence and downstream effects on cost and resource use.
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Affiliation(s)
- Dawn Stacey
- School of Nursing, University of Ottawa, Ottawa, Canada
- Centre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | | | - Meg Carley
- Centre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Robert Volk
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Elisa E Douglas
- Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Jeanette Finderup
- Department of Renal Medicine, Aarhus University Hospital, Aarhus, Denmark
| | | | - Michael J Barry
- Informed Medical Decisions Program, Massachusetts General Hospital, Boston, MA, USA
| | - Carol L Bennett
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Paulina Bravo
- Education and Cancer Prevention, Fundación Arturo López Pérez, Santiago, Chile
| | - Karina Steffensen
- Center for Shared Decision Making, IRS - Lillebælt Hospital, Vejle, Denmark
| | - Amédé Gogovor
- VITAM - Centre de recherche en santé durable, Université Laval, Quebec, Canada
| | - Ian D Graham
- Centre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada
- School of Epidemiology, Public Health and Preventative Medicine, University of Ottawa, Ottawa, Canada
| | - Shannon E Kelly
- Cardiovascular Research Methods Centre, University of Ottawa Heart Institute, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - France Légaré
- Centre de recherche sur les soins et les services de première ligne de l'Université Laval (CERSSPL-UL), Université Laval, Quebec, Canada
| | | | - Richard Thomson
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Logan Trenaman
- Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, USA
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Shepherd V, Wood F, Griffith R, Sheehan M, Hood K. Development of a decision support intervention for family members of adults who lack capacity to consent to trials. BMC Med Inform Decis Mak 2021; 21:30. [PMID: 33509169 PMCID: PMC7842028 DOI: 10.1186/s12911-021-01390-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 01/10/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Informed consent is required for participation in clinical trials, however trials involving adults who lack capacity to consent require different enrolment processes. A family member usually acts as a proxy to make a decision based on the patient's 'presumed will', but these decisions can be challenging and families may experience an emotional and decisional burden. Decisions made on behalf of others are conceptually different from those made for ourselves. Innovations have been developed to improve informed consent processes for research, including a number of decision aids, however there are no interventions for proxies who are faced with more complex decisions. This article outlines the development of a novel decision aid to support families making decisions about research participation on behalf of an adult who lacks capacity to consent. METHODS Decision support interventions should be developed using rigorous and evidence-based methods. This intervention was developed using MRC guidance for the development of complex interventions, and a conceptual framework for the development and evaluation of decision aids for people considering taking part in a clinical trial. The intervention was informed by a systematic review and analysis of existing information provision. Previous qualitative research with families who acted as proxies enabled the development of a theoretical framework to underpin the intervention. The intervention was iteratively developed with the involvement of lay advisors and relevant stakeholders. RESULTS Previous research, theoretical frameworks, and decision aid development frameworks were used to identify and develop the intervention components. The decision aid includes information about the proxy's role and utilises a values clarification exercise and decision support methods to enable a more informed and better-quality decision. Stakeholders, including those representing implementers and receivers of the intervention, contributed to the design and comprehensibility of the decision aid to ensure that it would be acceptable for use. CONCLUSIONS Frameworks for the development of decision aids for people considering participating in a clinical trial can be used to develop interventions for family members acting as proxy decision-makers. The decision support tool is acceptable to users. Feasibility testing and outcome measure development is required prior to any evaluation of its effectiveness.
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Affiliation(s)
- Victoria Shepherd
- Centre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.
| | - Fiona Wood
- PRIME Centre Wales, Division of Population Medicine, Cardiff University, Heath Park, Cardiff, CF14 4YS, UK
| | - Richard Griffith
- College of Human and Health Studies, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Mark Sheehan
- Ethox Centre, University of Oxford, Big Data Institute, Old Road Campus, Oxford, OX3 7LF, UK
| | - Kerenza Hood
- Centre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK
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Dobler CC, Sanchez M, Gionfriddo MR, Alvarez-Villalobos NA, Singh Ospina N, Spencer-Bonilla G, Thorsteinsdottir B, Benkhadra R, Erwin PJ, West CP, Brito JP, Murad MH, Montori VM. Impact of decision aids used during clinical encounters on clinician outcomes and consultation length: a systematic review. BMJ Qual Saf 2018; 28:499-510. [PMID: 30301874 DOI: 10.1136/bmjqs-2018-008022] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 08/21/2018] [Accepted: 09/03/2018] [Indexed: 11/04/2022]
Abstract
BACKGROUND Clinicians' satisfaction with encounter decision aids is an important component in facilitating implementation of these tools. We aimed to determine the impact of decision aids supporting shared decision making (SDM) during the clinical encounter on clinician outcomes. METHODS We searched nine databases from inception to June 2017. Randomised clinical trials (RCTs) of decision aids used during clinical encounters with an unaided control group were eligible for inclusion. Due to heterogeneity among included studies, we used a narrative evidence synthesis approach. RESULTS Twenty-five papers met inclusion criteria including 22 RCTs and 3 qualitative or mixed-methods studies nested in an RCT, together representing 23 unique trials. These trials evaluated healthcare decisions for cardiovascular prevention and treatment (n=8), treatment of diabetes mellitus (n=3), treatment of osteoporosis (n=2), treatment of depression (n=2), antibiotics to treat acute respiratory infections (n=3), cancer prevention and treatment (n=4) and prenatal diagnosis (n=1). Clinician outcomes were measured in only a minority of studies. Clinicians' satisfaction with decision making was assessed in only 8 (and only 2 of them showed statistically significantly greater satisfaction with the decision aid); only three trials asked if clinicians would recommend the decision aid to colleagues and only five asked if clinicians would use decision aids in the future. Outpatient consultations were not prolonged when a decision aid was used in 9 out of 13 trials. The overall strength of the evidence was low, with the major risk of bias related to lack of blinding of participants and/or outcome assessors. CONCLUSION Decision aids can improve clinicians' satisfaction with medical decision making and provide helpful information without affecting length of consultation time. Most SDM trials, however, omit outcomes related to clinicians' perspective on the decision making process or the likelihood of using a decision aid in the future.
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Affiliation(s)
- Claudia Caroline Dobler
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA .,Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Manuel Sanchez
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael R Gionfriddo
- Center for Pharmacy Innovation and Outcomes, Geisinger, Forty Fort, Pennsylvania, USA
| | - Neri A Alvarez-Villalobos
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA.,Facultad de Medicina y Hospital Universitario, Unidad de Investigación Clínica, Universidad Autonoma de Nuevo León, Monterrey, Mexico
| | - Naykky Singh Ospina
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA.,Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Bjorg Thorsteinsdottir
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.,Division of Primary Care Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Raed Benkhadra
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Colin P West
- Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA.,Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Juan P Brito
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Mohammad Hassan Murad
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
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Moroe NF. Occupational noise-induced hearing loss in South African large-scale mines: exploring hearing conservation programmes as complex interventions embedded in a realist approach. INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS 2018; 26:753-761. [PMID: 29987970 DOI: 10.1080/10803548.2018.1498183] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Background. Complex interventions have been conducted in the field of public health to improve health at the individual, organizational policy or population level. In occupational audiology, hearing conservation programmes (HCPs), which are interventions to minimize or eliminate occupational noise-induced hearing loss, are currently not defined as complex interventions, despite them fitting the definition and features of complex interventions. Therefore, this study aimed to explore whether HCPs are a complex intervention, fitting the predefined criteria for complex interventions. Method. A qualitative, descriptive research design was conducted using three sources of data - document analysis, interviews and systematic review - to allow for triangulation. Data were collected through purposive sampling and qualitative content analysis was used. Results. This study confirmed that HCPs are a complex intervention founded on solid and consolidated theories. Therefore, these results paved the way for realist reviews to be conducted in the mining sector in South Africa in order to understand the mechanisms influencing the success or failure of HCPs locally. Conclusion. The success of HCPs in the mining sector depends on conducting contextually evidence-based evaluations such as realist reviews which can provide policy-makers with contextual evidence for why certain programmes do or do not work in certain settings.
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Affiliation(s)
- Nomfundo F Moroe
- School of Human and Community Development, University of the Witwatersrand, South Africa
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Klaassen L, Dirksen C, Boersma L, Hoving C. Developing an aftercare decision aid; assessing health professionals' and patients' preferences. Eur J Cancer Care (Engl) 2017; 27:e12730. [PMID: 28727259 PMCID: PMC5900871 DOI: 10.1111/ecc.12730] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/22/2017] [Indexed: 01/04/2023]
Abstract
Personalising aftercare for curatively treated breast cancer patients is expected to improve patient satisfaction with care. A patient decision aid can support women in making decisions about their aftercare trajectory, but is currently not available. The aim of this study was to assess the needs of patients and health professionals with regard to an aftercare decision aid to systematically develop such a decision aid. Focus groups with patients and individual interviews with health professionals were digitally recorded and coded using the Framework analysis. Although most patients felt few aftercare options were available to them, health professionals reported to provide various options on the patients' request. Patients reported difficulty in expressing their need for options to their health professional. Although most patients were unfamiliar with decision aids, the majority preferred a paper‐based patient decision aid, while most health professionals preferred an online tool. The practical implications for the intended patient decision aid are: that a digital tool with paper‐based element should be developed, the patient decision aid should facilitate both rational and intuitive processes and should provide insight in patients' preferences concerning aftercare to discuss these explicitly.
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Affiliation(s)
- Linda Klaassen
- Department of Health Promotion/CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
| | - Carmen Dirksen
- Department of KEMTA/CAPHRI Care and Public Health Research Institute, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Liesbeth Boersma
- Department of Radiation oncology (MAASTRO Clinic)/GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Ciska Hoving
- Department of Health Promotion/CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
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Stacey D, Légaré F, Lewis K, Barry MJ, Bennett CL, Eden KB, Holmes‐Rovner M, Llewellyn‐Thomas H, Lyddiatt A, Thomson R, Trevena L. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2017; 4:CD001431. [PMID: 28402085 PMCID: PMC6478132 DOI: 10.1002/14651858.cd001431.pub5] [Citation(s) in RCA: 1248] [Impact Index Per Article: 178.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Decision aids are interventions that support patients by making their decisions explicit, providing information about options and associated benefits/harms, and helping clarify congruence between decisions and personal values. OBJECTIVES To assess the effects of decision aids in people facing treatment or screening decisions. SEARCH METHODS Updated search (2012 to April 2015) in CENTRAL; MEDLINE; Embase; PsycINFO; and grey literature; includes CINAHL to September 2008. SELECTION CRITERIA We included published randomized controlled trials comparing decision aids to usual care and/or alternative interventions. For this update, we excluded studies comparing detailed versus simple decision aids. DATA COLLECTION AND ANALYSIS Two reviewers independently screened citations for inclusion, extracted data, and assessed risk of bias. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made and the decision-making process.Secondary outcomes were behavioural, health, and health system effects.We pooled results using mean differences (MDs) and risk ratios (RRs), applying a random-effects model. We conducted a subgroup analysis of studies that used the patient decision aid to prepare for the consultation and of those that used it in the consultation. We used GRADE to assess the strength of the evidence. MAIN RESULTS We included 105 studies involving 31,043 participants. This update added 18 studies and removed 28 previously included studies comparing detailed versus simple decision aids. During the 'Risk of bias' assessment, we rated two items (selective reporting and blinding of participants/personnel) as mostly unclear due to inadequate reporting. Twelve of 105 studies were at high risk of bias.With regard to the attributes of the choice made, decision aids increased participants' knowledge (MD 13.27/100; 95% confidence interval (CI) 11.32 to 15.23; 52 studies; N = 13,316; high-quality evidence), accuracy of risk perceptions (RR 2.10; 95% CI 1.66 to 2.66; 17 studies; N = 5096; moderate-quality evidence), and congruency between informed values and care choices (RR 2.06; 95% CI 1.46 to 2.91; 10 studies; N = 4626; low-quality evidence) compared to usual care.Regarding attributes related to the decision-making process and compared to usual care, decision aids decreased decisional conflict related to feeling uninformed (MD -9.28/100; 95% CI -12.20 to -6.36; 27 studies; N = 5707; high-quality evidence), indecision about personal values (MD -8.81/100; 95% CI -11.99 to -5.63; 23 studies; N = 5068; high-quality evidence), and the proportion of people who were passive in decision making (RR 0.68; 95% CI 0.55 to 0.83; 16 studies; N = 3180; moderate-quality evidence).Decision aids reduced the proportion of undecided participants and appeared to have a positive effect on patient-clinician communication. Moreover, those exposed to a decision aid were either equally or more satisfied with their decision, the decision-making process, and/or the preparation for decision making compared to usual care.Decision aids also reduced the number of people choosing major elective invasive surgery in favour of more conservative options (RR 0.86; 95% CI 0.75 to 1.00; 18 studies; N = 3844), but this reduction reached statistical significance only after removing the study on prophylactic mastectomy for breast cancer gene carriers (RR 0.84; 95% CI 0.73 to 0.97; 17 studies; N = 3108). Compared to usual care, decision aids reduced the number of people choosing prostate-specific antigen screening (RR 0.88; 95% CI 0.80 to 0.98; 10 studies; N = 3996) and increased those choosing to start new medications for diabetes (RR 1.65; 95% CI 1.06 to 2.56; 4 studies; N = 447). For other testing and screening choices, mostly there were no differences between decision aids and usual care.The median effect of decision aids on length of consultation was 2.6 minutes longer (24 versus 21; 7.5% increase). The costs of the decision aid group were lower in two studies and similar to usual care in four studies. People receiving decision aids do not appear to differ from those receiving usual care in terms of anxiety, general health outcomes, and condition-specific health outcomes. Studies did not report adverse events associated with the use of decision aids.In subgroup analysis, we compared results for decision aids used in preparation for the consultation versus during the consultation, finding similar improvements in pooled analysis for knowledge and accurate risk perception. For other outcomes, we could not conduct formal subgroup analyses because there were too few studies in each subgroup. AUTHORS' CONCLUSIONS Compared to usual care across a wide variety of decision contexts, people exposed to decision aids feel more knowledgeable, better informed, and clearer about their values, and they probably have a more active role in decision making and more accurate risk perceptions. There is growing evidence that decision aids may improve values-congruent choices. There are no adverse effects on health outcomes or satisfaction. New for this updated is evidence indicating improved knowledge and accurate risk perceptions when decision aids are used either within or in preparation for the consultation. Further research is needed on the effects on adherence with the chosen option, cost-effectiveness, and use with lower literacy populations.
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Affiliation(s)
- Dawn Stacey
- University of OttawaSchool of Nursing451 Smyth RoadOttawaONCanada
- Ottawa Hospital Research InstituteCentre for Practice Changing Research501 Smyth RdOttawaONCanadaK1H 8L6
| | - France Légaré
- CHU de Québec Research Center, Université LavalPopulation Health and Optimal Health Practices Research Axis10 Rue de l'Espinay, D6‐727Québec CityQCCanadaG1L 3L5
| | - Krystina Lewis
- University of OttawaSchool of Nursing451 Smyth RoadOttawaONCanada
| | | | - Carol L Bennett
- Ottawa Hospital Research InstituteClinical Epidemiology ProgramAdministrative Services Building, Room 2‐0131053 Carling AvenueOttawaONCanadaK1Y 4E9
| | - Karen B Eden
- Oregon Health Sciences UniversityDepartment of Medical Informatics and Clinical EpidemiologyBICC 5353181 S.W. Sam Jackson Park RoadPortlandOregonUSA97239‐3098
| | - Margaret Holmes‐Rovner
- Michigan State University College of Human MedicineCenter for Ethics and Humanities in the Life SciencesEast Fee Road956 Fee Road Rm C203East LansingMichiganUSA48824‐1316
| | - Hilary Llewellyn‐Thomas
- Dartmouth CollegeThe Dartmouth Center for Health Policy & Clinical Practice, The Geisel School of Medicine at DartmouthHanoverNew HampshireUSA03755
| | - Anne Lyddiatt
- No affiliation28 Greenwood RoadIngersollONCanadaN5C 3N1
| | - Richard Thomson
- Newcastle UniversityInstitute of Health and SocietyBaddiley‐Clark BuildingRichardson RoadNewcastle upon TyneUKNE2 4AX
| | - Lyndal Trevena
- The University of SydneyRoom 322Edward Ford Building (A27)SydneyNSWAustralia2006
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