1
|
Keij SM, Lie HC, Laidsaar-Powell R, Kunneman M, de Boer JE, Moaddine S, Stiggelbout AM, Pieterse AH. Corrigendum to 'Patient-related characteristics considered to affect patient involvement in shared decision making about treatment: A scoping review of the qualitative literature' Patient Education and Counseling 111 (2023) 107677. Patient Educ Couns 2024; 124:108257. [PMID: 38538384 DOI: 10.1016/j.pec.2024.108257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2024]
Affiliation(s)
- Sascha M Keij
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands.
| | - Hanne C Lie
- Department of Behavioural Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Norway
| | - Rebekah Laidsaar-Powell
- Centre for Medical Psychology and Evidence-Based Decision-Making (CeMPED), School of Psychology, The University of Sydney, Sydney, NSW, Australia
| | - Marleen Kunneman
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands; Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Joyce E de Boer
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
| | - Saïda Moaddine
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
| | - Anne M Stiggelbout
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands; Erasmus School of Health Policy and Management, Erasmus University Rotterdam, the Netherlands
| | - Arwen H Pieterse
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
| |
Collapse
|
2
|
Keij SM, Branda ME, Montori VM, Brito JP, Kunneman M, Pieterse AH. Patient Characteristics and the Extent to Which Clinicians Involve Patients in Decision Making: Secondary Analyses of Pooled Data. Med Decis Making 2024; 44:346-356. [PMID: 38563311 PMCID: PMC10988989 DOI: 10.1177/0272989x241231721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 01/22/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND The occurrence of shared decision making (SDM) in daily practice remains limited. Various patient characteristics have been suggested to potentially influence the extent to which clinicians involve patients in SDM. OBJECTIVE To assess associations between patient characteristics and the extent to which clinicians involve patients in SDM. METHODS We conducted a secondary analysis of data pooled from 10 studies comparing the care of adult patients with (intervention) or without (control) a within-encounter SDM conversation tool. We included studies with audio(-visual) recordings of clinical encounters in which decisions about starting or reconsidering treatment were discussed. MAIN MEASURES In the original studies, the Observing Patient Involvement in Decision Making 12-items (OPTION12 item) scale was used to code the extent to which clinicians involved patients in SDM in clinical encounters. We conducted multivariable analyses with patient characteristics (age, gender, race, education, marital status, number of daily medications, general health status, health literacy) as independent variables and OPTION12 as a dependent variable. RESULTS We included data from 1,614 patients. The between-arm difference in OPTION12 scores was 7.7 of 100 points (P < 0.001). We found no association between any patient characteristics and the OPTION12 score except for education level (p = 0.030), an association that was very small (2.8 points between the least and most educated), contributed mostly by, and only significant in, control arms (6.5 points). Subanalyses of a stroke prevention trial showed a positive association between age and OPTION12 score (P = 0.033). CONCLUSIONS Most characteristics showed no association with the extent to which clinicians involved patients in SDM. Without an SDM conversation tool, clinicians devoted more efforts to involve patients with higher education, a difference not observed when the tool was used. HIGHLIGHTS Most sociodemographic patient characteristics show no association with the extent to which clinicians involve patients in shared decision making.Clinicians devoted less effort to involve patients with lower education, a difference that was not observed when a shared decision-making conversation tool was used.SDM conversation tools can be useful for clinicians to better involve patients and ensure patients get involved equally regardless of educational background.
Collapse
Affiliation(s)
- Sascha M. Keij
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands
| | - Megan E. Branda
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Victor M. Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Juan P. Brito
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Marleen Kunneman
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Arwen H. Pieterse
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands
| |
Collapse
|
3
|
Keij SM, Stiggelbout AM, Pieterse AH. Patient readiness for shared decision making about treatment: Conceptualisation and development of the Ready SDM. Health Expect 2024; 27:e13995. [PMID: 38400633 PMCID: PMC10891436 DOI: 10.1111/hex.13995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/24/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
INTRODUCTION Shared decision making (SDM) requires an active role of both clinicians and patients. We aimed to conceptualise patient readiness for SDM about treatment, and to develop a patient questionnaire to assess readiness. METHODS We used the results of a scoping review and a qualitative study to inform the patient readiness construct. We conducted five additional rounds of data collection to finalise the construct definition and develop the Patient Readiness for SDM Questionnaire (ReadySDM ) in an oncological setting: (1) longitudinal interviews with patients with cancer during and after a treatment decision-making process; (2) a pilot study among experts, clinicians, and patients for feedback on the concept and items; (3) a field test among (former) patients with cancer to test item format and content validity, and to reduce the number of items; (4) cognitive interviews with people with low literacy to test the comprehensibility of the questionnaire; and (5) a field test among (former) patients who faced a cancer treatment decision in the last year, to test the content validity of the final version of the questionnaire. RESULTS A total of 251 people participated in the various rounds of data collection. We identified eight elements of patient readiness for SDM about treatment: (1) understanding of and attitude towards SDM; (2) information skills; (3) skills in communicating and claiming space; (4) self-awareness; (5) consideration skills; (6) self-efficacy; (7) emotional distress; and (8) experienced time. We developed the 20-item ReadySDM to retrospectively measure these elements in an oncological setting. CONCLUSION We conducted a thorough procedure to conceptualise patient readiness and to develop the ReadySDM . The questionnaire aims to provide novel insights into ways to enhance SDM in daily practice. PATIENT OR PUBLIC CONTRIBUTION Multiple people with lived experience were involved in various phases of the study. They were asked for input on the study design, the conceptualisation of readiness, and the development of the questionnaire.
Collapse
Affiliation(s)
- Sascha M. Keij
- Department of Biomedical Data Sciences, Medical Decision MakingLeiden University Medical CenterLeidenThe Netherlands
| | - Anne M. Stiggelbout
- Department of Biomedical Data Sciences, Medical Decision MakingLeiden University Medical CenterLeidenThe Netherlands
- Erasmus School of Health Policy and ManagementErasmus University RotterdamRotterdamThe Netherlands
| | - Arwen H. Pieterse
- Department of Biomedical Data Sciences, Medical Decision MakingLeiden University Medical CenterLeidenThe Netherlands
| |
Collapse
|
4
|
Keij SM, Lie HC, Laidsaar-Powell R, Kunneman M, de Boer JE, Moaddine S, Stiggelbout AM, Pieterse AH. Patient-related characteristics considered to affect patient involvement in shared decision making about treatment: A scoping review of the qualitative literature. Patient Educ Couns 2023; 111:107677. [PMID: 36857803 DOI: 10.1016/j.pec.2023.107677] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/13/2023] [Accepted: 02/16/2023] [Indexed: 05/17/2023]
Abstract
OBJECTIVE To identify patient-related characteristics considered to affect patient involvement in shared decision making (SDM) about treatment. METHODS We conducted a scoping review of qualitative studies. We searched for literature across seven databases until March 2022, and included qualitative studies that focused on associations between patient-related characteristics and SDM about treatment in adults. We analyzed studies using an inductive thematic approach. RESULTS The search yielded 5948 articles, of which 70 were included. We identified many different patient-related characteristics, which we grouped into four categories related to: (1) the individual who is facing the decision, (2) the decision, (3) the relationship between the patient and the clinician and others involved in the decision, and (4) the healthcare context. CONCLUSIONS Studies report a variety of patient-related characteristics that may affect patient involvement in SDM. Amongst others, patients may need to feel informed, to understand their role in SDM, and be able to communicate. Involvement may be challenging with characteristics such as perceived time pressure, poor patient-clinician relationships, emotional distress, and severe illness. PRACTICE IMPLICATIONS In order to truly involve patients in SDM, we might need to focus on characteristics such as patient emotions and relationship building, besides information provision and values clarification.
Collapse
Affiliation(s)
- Sascha M Keij
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands.
| | - Hanne C Lie
- Department of Behavioural Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Norway
| | - Rebekah Laidsaar-Powell
- Centre for Medical Psychology and Evidence-Based Decision-Making (CeMPED), School of Psychology, The University of Sydney, Sydney, NSW, Australia
| | - Marleen Kunneman
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands; Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Joyce E de Boer
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
| | - Saïda Moaddine
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
| | - Anne M Stiggelbout
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands; Erasmus School of Health Policy and Management, Erasmus University Rotterdam, the Netherlands
| | - Arwen H Pieterse
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
| |
Collapse
|
5
|
Keij SM, de Boer JE, Stiggelbout AM, Bruine de Bruin W, Peters E, Moaddine S, Kunneman M, Pieterse AH. How are patient-related characteristics associated with shared decision-making about treatment? A scoping review of quantitative studies. BMJ Open 2022; 12:e057293. [PMID: 35613791 PMCID: PMC9174801 DOI: 10.1136/bmjopen-2021-057293] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
OBJECTIVES To identify what patient-related characteristics have been reported to be associated with the occurrence of shared decision-making (SDM) about treatment. DESIGN Scoping review. ELIGIBILITY CRITERIA Peer-reviewed articles in English or Dutch reporting on associations between patient-related characteristics and the occurrence of SDM for actual treatment decisions. INFORMATION SOURCES COCHRANE Library, Embase, MEDLINE, PsycInfo, PubMed and Web of Science were systematically searched for articles published until 25 March 2019. RESULTS The search yielded 5289 hits of which 53 were retained. Multiple categories of patient characteristics were identified: (1) sociodemographic characteristics (eg, gender), (2) general health and clinical characteristics (eg, symptom severity), (3) psychological characteristics and coping with illness (eg, self-efficacy) and (4) SDM style or preference. Many characteristics showed no association or unclear relationships with SDM occurrence. For example, for female gender positive, negative and, most frequently, non-significant associations were seen. CONCLUSIONS A large variety of patient-related characteristics have been studied, but for many the association with SDM occurrence remains unclear. The results will caution often-made assumptions about associations and provide an important step to target effective interventions to foster SDM with all patients.
Collapse
Affiliation(s)
- Sascha M Keij
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Joyce E de Boer
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Anne M Stiggelbout
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Wändi Bruine de Bruin
- Schaeffer Center for Health Policy and Economics, Dornsife Department of Psychology, and Price School of Public Policy, University of Southern California, Los Angeles, California, USA
| | - Ellen Peters
- Center for Science Communication Research, School of Journalism and Communication, University of Oregon, Eugene, Oregon, USA
| | - Saïda Moaddine
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Marleen Kunneman
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Arwen H Pieterse
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| |
Collapse
|
6
|
Keij SM, van Duijn-Bakker N, Stiggelbout AM, Pieterse AH. What makes a patient ready for Shared Decision Making? A qualitative study. Patient Educ Couns 2021; 104:571-577. [PMID: 32962880 DOI: 10.1016/j.pec.2020.08.031] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 06/10/2020] [Accepted: 08/20/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES Shared decision making (SDM) requires an active role from patients, which might be difficult for some. We aimed to identify what patients need to be ready (i.e., well-equipped and enabled) to participate in SDM about treatment, and what patient- and decision-related characteristics may influence readiness. METHODS We conducted semi-structured interviews with patients and professionals (physicians, nurses, general practitioners, and researchers). Interviews were analyzed inductively. RESULTS We identified five elements of patient readiness: 1) understanding of and attitude towards SDM, 2) health literacy, 3) skills in communicating and claiming space, 4) self-awareness, and 5) consideration skills. We identified 10 characteristics that may influence elements of readiness: 1) age, 2) cultural background, 3) educational background, 4) close relationships, 5) mental illness, 6) emotional distress, 7) acceptance of diagnosis, 8) clinician-patient relationship, 9) decision type, and 10) time. CONCLUSIONS We identified a wide range of elements that may constitute patient readiness for SDM. Readiness might vary between and within patients. This variation may result from differences in patient- and decision-related characteristics. PRACTICE IMPLICATIONS Clinicians should be aware that not all patients may be ready for SDM at a given moment and may need support to enhance their readiness.
Collapse
Affiliation(s)
- Sascha M Keij
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
| | - Nanny van Duijn-Bakker
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
| | - Anne M Stiggelbout
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
| | - Arwen H Pieterse
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
| |
Collapse
|
7
|
Winkley K, Upsher R, Keij SM, Chamley M, Ismail K, Forbes A. Healthcare professionals' views of group structured education for people with newly diagnosed Type 2 diabetes. Diabet Med 2018; 35:911-919. [PMID: 29633382 DOI: 10.1111/dme.13637] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/29/2018] [Indexed: 11/28/2022]
Abstract
AIM To determine healthcare professionals' (HCP) views of group structured education for people with newly diagnosed Type 2 diabetes. METHODS This was a qualitative study using semi-structured interviews to ascertain primary care HCPs' views and experiences of education for people with newly diagnosed Type 2 diabetes. A thematic framework method was applied to analyse the data. Participants were HCPs (N = 22) from 15 general practices in three south London boroughs. RESULTS All but one HCP viewed diabetes education favourably and all identified that low attendance was a problem. Three key themes emerged from the qualitative data: (1) benefits of diabetes education, including the group mode of delivery, improved patient interactions, saving HCPs' time and improved patient outcomes; (2) factors limiting uptake of education, including patient-level problems such as access and the appropriateness of the programme for certain groups, and difficulties communicating the benefits to patients and integration of education management plans into ongoing diabetes care; and (3) suggestions for improvement, including strategies to improve attendance at education with more localized and targeted marketing and enhanced programme content including follow-up sessions and support for people with pre-existing psychological issues. CONCLUSIONS Most HCPs valued diabetes education and all highlighted the lack of provision for people with different levels of health literacy. Because there was wide variation in terms of the level of knowledge regarding the education on offer, future studies may want to focus on how to help HCPs encourage their patients to attend.
Collapse
Affiliation(s)
- K Winkley
- Diabetes Psychiatry & Psychology, Department of Psychological Medicine and Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - R Upsher
- Diabetes Psychiatry & Psychology, Department of Psychological Medicine and Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - S M Keij
- Diabetes Psychiatry & Psychology, Department of Psychological Medicine and Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - M Chamley
- Lambeth Clinical Commissioning Group Diabetes Intermediate Care Team, London, UK
| | - K Ismail
- Diabetes Psychiatry & Psychology, Department of Psychological Medicine and Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - A Forbes
- Florence Nightingale Faculty of Nursing & Midwifery, King's College London, London, UK
| |
Collapse
|