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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: 0] [Impact Index Per Article: 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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Hoefel L, Lewis KB, O’Connor A, Stacey D. 20th Anniversary Update of the Ottawa Decision Support Framework: Part 2 Subanalysis of a Systematic Review of Patient Decision Aids. Med Decis Making 2020; 40:522-539. [DOI: 10.1177/0272989x20924645] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background. The Ottawa Decision Support Framework (ODSF) has guided the development of patient decision aids (PtDAs) for 20 years and needs updating across a range of decisions and hypothesized outcomes. Purpose. To determine the effectiveness of ODSF-developed PtDAs on hypothesized outcomes and to recommend framework changes. Data Source. A subanalysis of randomized controlled trials included in the 2017 Cochrane review of PtDAs comparing PtDAs to usual care in adults considering health treatment or screening decisions (searched to 2015). Study Selection. Trials in the original review that evaluated ODSF-developed PtDAs. Data Synthesis. Meta-analyses of ODSF outcomes with similar measurements and descriptions of other reported outcomes. Results. Of 105 trials, 24 evaluated ODSF-developed PtDAs. Compared with usual care, ODSF PtDAs improved knowledge (mean difference [MD] 13.85; 95% confidence interval [CI] 10.32−17.37; 14 trials), increased accurate risk perceptions (risk ratio [RR] 2.41; 95% CI 1.66−3.48; 7 trials), and increased congruence between informed values and chosen options (RR 1.32; 95% CI 1.09−1.59; 4 trials). They reduced perceived decisional needs as measured using the Decisional Conflict Scale (MD −5.92; 95% CI −8.58 to −3.26; 15 trials) and the proportion of undecided patients (RR 0.65; 95% CI 0.50−0.83; 13 trials). Non-ODSF PtDAs, designed with or without a specific framework, also outperformed usual care. Few ODSF trials measured secondary outcomes. Limitations. The included trials had heterogeneity. Conclusion. ODSF PtDAs address decisional needs and improve decision quality; the best indicator of addressing perceived uncertainty is “proportion undecided.” Secondary ODSF outcomes should be reduced to adherence to one’s chosen option and use/costs of health services, which warrant further research.
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Affiliation(s)
- Lauren Hoefel
- School of Nursing, University of Ottawa, Ottawa, ON, Canada
| | | | | | - Dawn Stacey
- School of Nursing, University of Ottawa, Ottawa, ON, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Canada
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Gold N, Durlik C, Sanders JG, Thompson K, Chadborn T. Applying behavioural science to increase uptake of the NHS Health Check: a randomised controlled trial of gain- and loss-framed messaging in the national patient information leaflet. BMC Public Health 2019; 19:1519. [PMID: 31727030 PMCID: PMC6854644 DOI: 10.1186/s12889-019-7754-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 10/04/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND The NHS Health Check (NHSHC) is a national programme for the prevention of non-communicable diseases. Patients aged 40-74 without an existing cardiovascular-related condition should be invited quinquennially. Uptake is lower than anticipated. We assessed the impact on uptake of two new behaviourally-enhanced leaflets (with the current national leaflet as a control), enclosed with the invitation letter: the first trial on the leaflet. METHODS A double-blind three-armed randomized controlled trial was conducted. The new leaflets were shorter (two pages, instead of four); one was loss-framed ('don't miss out') and the other was gain-framed ('make the most of life'). The participants were patients from 39 practices in Lewisham and 17 practices in NE Lincolnshire, who were allocated to interventions using a random-number generator and received one of the leaflets with their invitation letter from April-September 2018. The outcome measure was uptake of an NHSHC by November 2018. The trial was powered to detect a 2% effect. RESULTS Uptake was 17.6% in the control condition (n = 3677), 17.4% in the loss-framed condition (n = 3664), and 18.2% in the gain-framed condition (n = 3697). Leaflet type was not a significant predictor of NHSHC uptake in a logistic regression that controlled for demographic variables, with GP practice as a random effect. Statistically significant predictors of uptake included location (higher uptake in Lewisham), age (increased age was associated with increased attendance) and sex (higher uptake in females). The Bayes Factor comparing the null to a hypothesis of differences between conditions was 416, which is extreme evidence in favour of the null hypothesis. CONCLUSION There was no evidence for a meaningful effect of either a loss-framed or gain-framed behaviourally-informed leaflet type on uptake, which is surprising, given that behaviourally informed letters have improved uptake of NHSHCs. It is possible that people do not pay attention to leaflets that are enclosed with letters, or that the leaflet continues to support informed decision-making but this does not affect uptake. TRIAL REGISTRATION Clinicaltrials.gov, NCT03524131. Registered May 14, 2018. Retrospectively registered.
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Affiliation(s)
- Natalie Gold
- Public Health England, Wellington House, 133-155 Waterloo Rd, Lambeth, London, SE1 8UG, UK.
- Radcliffe Humanities, University of Oxford, Woodstock Road, Oxford, OX2 6GG, UK.
| | - Caroline Durlik
- Public Health England, Wellington House, 133-155 Waterloo Rd, Lambeth, London, SE1 8UG, UK
| | - Jet G Sanders
- Public Health England, Wellington House, 133-155 Waterloo Rd, Lambeth, London, SE1 8UG, UK
- Department of Psychological and Behavioural Science, London School of Economics and Political Science, Houghton St, Holborn, London, WC2A 2AE, UK
| | - Katherine Thompson
- Public Health England, Wellington House, 133-155 Waterloo Rd, Lambeth, London, SE1 8UG, UK
| | - Tim Chadborn
- Public Health England, Wellington House, 133-155 Waterloo Rd, Lambeth, London, SE1 8UG, UK
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Leinweber KA, Columbo JA, Kang R, Trooboff SW, Goodney PP. A Review of Decision Aids for Patients Considering More Than One Type of Invasive Treatment. J Surg Res 2019; 235:350-366. [PMID: 30691817 PMCID: PMC10647019 DOI: 10.1016/j.jss.2018.09.017] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 07/29/2018] [Accepted: 09/07/2018] [Indexed: 10/27/2022]
Abstract
With continuous advances in medicine, patients are faced with several medical or surgical treatment options for their health conditions. Decision aids may be useful in helping patients navigate these options and choose based on their goals and values. We reviewed the literature to identify decision aids and better understand the effect on patient decision-making. We identified 107 decision aids designed to help patients make decisions between medical treatment or screening options; 39 decision aids were used to help patients choose between a medical and surgical treatment, and five were identified that aided patients in deciding between a major open surgical procedure and a less invasive option. Many of the decision aids were used to help patients decide between prostate, colorectal, and breast cancer screening or treatment options. Although most decision aids were not associated with a significant effect on the actual decision made, they were largely associated with increased patient knowledge, decreased decisional conflict, more accurate perception of risks, increased satisfaction with their decision, and no increase in anxiety surrounding their decision. These data identify a gap in use of decision aids in surgical decision-making and highlight the potential to help surgical patients make value-based, knowledgeable decisions regarding their treatment.
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Affiliation(s)
| | - Jesse A Columbo
- Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; Section of Vascular Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire; VA Quality Scholars Program, Veterans Health Association, White River Junction, Vermont; VA Outcomes Group, Veterans Health Association, White River Junction, Vermont; The Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire
| | - Ravinder Kang
- Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; VA Quality Scholars Program, Veterans Health Association, White River Junction, Vermont; VA Outcomes Group, Veterans Health Association, White River Junction, Vermont; The Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire
| | - Spencer W Trooboff
- VA Quality Scholars Program, Veterans Health Association, White River Junction, Vermont; VA Outcomes Group, Veterans Health Association, White River Junction, Vermont; The Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire
| | - Philip P Goodney
- Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; Section of Vascular Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire; VA Quality Scholars Program, Veterans Health Association, White River Junction, Vermont; VA Outcomes Group, Veterans Health Association, White River Junction, Vermont; The Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire.
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McDermott L, Wright AJ, Cornelius V, Burgess C, Forster AS, Ashworth M, Khoshaba B, Clery P, Fuller F, Miller J, Dodhia H, Rudisill C, Conner MT, Gulliford MC. Enhanced invitation methods and uptake of health checks in primary care: randomised controlled trial and cohort study using electronic health records. Health Technol Assess 2018; 20:1-92. [PMID: 27846927 DOI: 10.3310/hta20840] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND A national programme of health checks to identify risk of cardiovascular disease (CVD) is being rolled out but is encountering difficulties because of low uptake. OBJECTIVE To evaluate the effectiveness of an enhanced invitation method using the question-behaviour effect (QBE), with or without the offer of a financial incentive to return the QBE questionnaire, at increasing the uptake of health checks. The research went on to evaluate the reasons for the low uptake of invitations and compare the case mix for invited and opportunistic health checks. DESIGN Three-arm randomised trial and cohort study. PARTICIPANTS All participants invited for a health check from 18 general practices. Individual participants were randomised. INTERVENTIONS (1) Standard health check invitation only; (2) QBE questionnaire followed by a standard invitation; and (3) QBE questionnaire with offer of a financial incentive to return the questionnaire, followed by a standard invitation. MAIN OUTCOME MEASURES The primary outcome was completion of the health check within 6 months of invitation. A p-value of 0.0167 was used for significance. In the cohort study of all health checks completed during the study period, the case mix was compared for participants responding to invitations and those receiving 'opportunistic' health checks. Participants were not aware that several types of invitation were in use. The research team were blind to trial arm allocation at outcome data extraction. RESULTS In total, 12,459 participants were included in the trial and health check uptake was evaluated for 12,052 participants for whom outcome data were collected. Health check uptake was as follows: standard invitation, 590 out of 4095 (14.41%); QBE questionnaire, 630 out of 3988 (15.80%); QBE questionnaire and financial incentive, 629 out of 3969 (15.85%). The increase in uptake associated with the QBE questionnaire was 1.43% [95% confidence interval (CI) -0.12% to 2.97%; p = 0.070] and the increase in uptake associated with the QBE questionnaire and offer of financial incentive was 1.52% (95% CI -0.03% to 3.07%; p = 0.054). The difference in uptake associated with the offer of an incentive to return the QBE questionnaire was -0.01% (95% CI -1.59% to 1.58%; p = 0.995). During the study period, 58% of health check cardiovascular risk assessments did not follow a trial invitation. People who received an 'opportunistic' health check had greater odds of a ≥ 10% CVD risk than those who received an invited health check (adjusted odds ratio 1.70, 95% CI 1.45 to 1.99; p < 0.001). CONCLUSIONS Uptake of a health check following an invitation letter is low and is not increased through an enhanced invitation method using the QBE. The offer of a £5 incentive did not increase the rate of return of the QBE questionnaire. A high proportion of all health checks are performed opportunistically and not in response to a standard invitation letter. Participants receiving opportunistic checks are at higher risk of CVD than those responding to standard invitations. Future research should aim to increase the accessibility of preventative medical interventions to increase uptake. Research should also explore the wider use of electronic health records in delivering efficient trials. TRIAL REGISTRATION Current Controlled Trials ISRCTN42856343. FUNDING This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 84. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Lisa McDermott
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Alison J Wright
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Victoria Cornelius
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Caroline Burgess
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Alice S Forster
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Mark Ashworth
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Bernadette Khoshaba
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Philippa Clery
- Department of Primary Care and Public Health Sciences, King's College London, London, UK
| | - Frances Fuller
- Public Health Directorate, Lewisham Borough Council, London, UK
| | - Jane Miller
- Public Health Directorate, Lewisham Borough Council, London, UK
| | - Hiten Dodhia
- Public Health Directorate, Lambeth Borough Council, London, UK
| | - Caroline Rudisill
- Department of Social Policy, London School of Economics and Political Science, London, UK
| | - Mark T Conner
- School of Psychology, University of Leeds, Leeds, UK
| | - Martin C Gulliford
- Department of Primary Care and Public Health Sciences, King's College London, London, UK.,NIHR Biomedical Research Centre at Guy's and St Thomas' Hospitals, Guy's Hospital, London, UK
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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: 1180] [Impact Index Per Article: 168.6] [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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Michie S, Wood CE, Johnston M, Abraham C, Francis JJ, Hardeman W. Behaviour change techniques: the development and evaluation of a taxonomic method for reporting and describing behaviour change interventions (a suite of five studies involving consensus methods, randomised controlled trials and analysis of qualitative data). Health Technol Assess 2016; 19:1-188. [PMID: 26616119 DOI: 10.3310/hta19990] [Citation(s) in RCA: 326] [Impact Index Per Article: 40.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Meeting global health challenges requires effective behaviour change interventions (BCIs). This depends on advancing the science of behaviour change which, in turn, depends on accurate intervention reporting. Current reporting often lacks detail, preventing accurate replication and implementation. Recent developments have specified intervention content into behaviour change techniques (BCTs) - the 'active ingredients', for example goal-setting, self-monitoring of behaviour. BCTs are 'the smallest components compatible with retaining the postulated active ingredients, i.e. the proposed mechanisms of change. They can be used alone or in combination with other BCTs' (Michie S, Johnston M. Theories and techniques of behaviour change: developing a cumulative science of behaviour change. Health Psychol Rev 2012;6:1-6). Domain-specific taxonomies of BCTs have been developed, for example healthy eating and physical activity, smoking cessation and alcohol consumption. We need to build on these to develop an internationally shared language for specifying and developing interventions. This technology can be used for synthesising evidence, implementing effective interventions and testing theory. It has enormous potential added value for science and global health. OBJECTIVE (1) To develop a method of specifying content of BCIs in terms of component BCTs; (2) to lay a foundation for a comprehensive methodology applicable to different types of complex interventions; (3) to develop resources to support application of the taxonomy; and (4) to achieve multidisciplinary and international acceptance for future development. DESIGN AND PARTICIPANTS Four hundred participants (systematic reviewers, researchers, practitioners, policy-makers) from 12 countries engaged in investigating, designing and/or delivering BCIs. Development of the taxonomy involved a Delphi procedure, an iterative process of revisions and consultation with 41 international experts; hierarchical structure of the list was developed using inductive 'bottom-up' and theory-driven 'top-down' open-sort procedures (n = 36); training in use of the taxonomy (1-day workshops and distance group tutorials) (n = 161) was evaluated by changes in intercoder reliability and validity (agreement with expert consensus); evaluating the taxonomy for coding interventions was assessed by reliability (intercoder; test-retest) and validity (n = 40 trained coders); and evaluating the taxonomy for writing descriptions was assessed by reliability (intercoder; test-retest) and by experimentally testing its value (n = 190). RESULTS Ninety-three distinct, non-overlapping BCTs with clear labels and definitions formed Behaviour Change Technique Taxonomy version 1 (BCTTv1). BCTs clustered into 16 groupings using a 'bottom-up' open-sort procedure; there was overlap between these and groupings produced by a theory-driven, 'top-down' procedure. Both training methods improved validity (both p < 0.05), doubled the proportion of coders achieving competence and improved confidence in identifying BCTs in workshops (both p < 0.001) but did not improve intercoder reliability. Good intercoder reliability was observed for 80 of the 93 BCTs. Good within-coder agreement was observed after 1 month (p < 0.001). Validity was good for 14 of 15 BCTs in the descriptions. The usefulness of BCTTv1 to report descriptions of observed interventions had mixed results. CONCLUSIONS The developed taxonomy (BCTTv1) provides a methodology for identifying content of complex BCIs and a foundation for international cross-disciplinary collaboration for developing more effective interventions to improve health. Further work is needed to examine its usefulness for reporting interventions. FUNDING This project was funded by the Medical Research Council Ref: G0901474/1. Funding also came from the Peninsula Collaboration for Leadership in Applied Health Research and Care.
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Affiliation(s)
- Susan Michie
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Caroline E Wood
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Marie Johnston
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK.,Institute of Applied Health Sciences, College of Life Science and Medicine, University of Aberdeen, Health Sciences Building, Aberdeen, UK
| | - Charles Abraham
- University of Exeter Medical School, University of Exeter, St Luke's Campus, Exeter, UK
| | - Jill J Francis
- School of Health Sciences, City University London, London, UK
| | - Wendy Hardeman
- Primary Care Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK
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Stacey D, Légaré F, Col NF, Bennett CL, Barry MJ, Eden KB, Holmes-Rovner M, Llewellyn-Thomas H, Lyddiatt A, Thomson R, Trevena L, Wu JHC. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2014:CD001431. [PMID: 24470076 DOI: 10.1002/14651858.cd001431.pub4] [Citation(s) in RCA: 834] [Impact Index Per Article: 83.4] [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 intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. OBJECTIVES To assess the effects of decision aids for people facing treatment or screening decisions. SEARCH METHODS For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). SELECTION CRITERIA We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. DATA COLLECTION AND ANALYSIS Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:A) 'choice made' attributes;B) 'decision-making process' attributes.Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. MAIN RESULTS This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29 studies).A) Criteria involving 'choice made' attributes:Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13).B) Criteria involving 'decision-making process' attributes:Decision aids compared to usual care interventions resulted in:a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18);b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); andc) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18).Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice.C) Secondary outcomes Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more conservative options (RR 0.79; 95% CI 0.68 to 0.93; n = 15). Exposure to decision aids compared to usual care reduced the number of people choosing to have prostate-specific antigen screening (RR 0.87; 95% CI 0.77 to 0.98; n = 9). When detailed compared to simple decision aids were used, fewer people chose menopausal hormone therapy (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable.The effect of decision aids on length of consultation varied from 8 minutes shorter to 23 minutes longer (median 2.55 minutes longer) with 2 studies indicating statistically-significantly longer, 1 study shorter, and 6 studies reporting no difference in consultation length. Groups of patients receiving decision aids do not appear to differ from comparison groups in terms of anxiety (n = 30), general health outcomes (n = 11), and condition-specific health outcomes (n = 11). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive. AUTHORS' CONCLUSIONS There is high-quality evidence that decision aids compared to usual care improve people's knowledge regarding options, and reduce their decisional conflict related to feeling uninformed and unclear about their personal values. There is moderate-quality evidence that decision aids compared to usual care stimulate people to take a more active role in decision making, and improve accurate risk perceptions when probabilities are included in decision aids, compared to not being included. There is low-quality evidence that decision aids improve congruence between the chosen option and the patient's values.New for this updated review is further evidence indicating more informed, values-based choices, and improved patient-practitioner communication. There is a variable effect of decision aids on length of consultation. Consistent with findings from the previous review, decision aids have a variable effect on choices. They reduce the number of people choosing discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, cost-effectiveness, use with lower literacy populations, and level of detail needed in decision aids need further evaluation. Little is known about the degree of detail that decision aids need in order to have a positive effect on attributes of the choice made, or the decision-making process.
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Affiliation(s)
- Dawn Stacey
- School of Nursing, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, Canada
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