No abstract

Over the course of March 2020, the everyday life of most people changed from normal to extraordinary around the globe. By the beginning of March, there had been serious outbreaks of COVID-19 in a limited number of countries, such as China, South Korea, Iran and Italy, while many others experienced a lull before the storm. People in unaffected countries understood that the Corona SARS CoV-2 virus might reach their shores at one point; the question was when and how hard it would hit. By the end of March, many governments had ordered drastic measures. Schools and university campuses were shut down. Shops, restaurants and companies were closed. People in many different jobs were asked to work from home, and many were in quarantines.

ObjectivesTo (1) provide an up-to-date overview of shared decision making (SDM)-models, (2) give insight in the prominence of components present in SDM-models, (3) describe who is identified as responsible within the components (patient, healthcare professional, both, none), (4) show the occurrence of SDM-components over time, and (5) present an SDM-map to identify SDM-components seen as key, per healthcare setting.DesignSystematic review.Eligibility criteriaPeer-reviewed articles in English presenting a new or adapted model of SDM.Information sourcesAcademic Search Premier, Cochrane, Embase, Emcare, PsycINFO, PubMed, and Web of Science were systematically searched for articles published up to and including September 2, 2019.ResultsForty articles were included, each describing a unique SDM-model. Twelve models were generic, the others were specific to a healthcare setting. Fourteen were based on empirical data, 26 primarily on analytical thinking. Fifty-three different elements were identified and clustered into 24 components. Overall, Describe treatment options was the most prominent component across models. Components present in >50% of models were: Make the decision (75%), Patient preferences (65%), Tailor information (65%), Deliberate (58%), Create choice awareness (55%), and Learn about the patient (53%). In the majority of the models (27/40), both healthcare professional and patient were identified as actors. Over time, Describe treatment options and Make the decision are the two components which are present in most models in any time period. Create choice awareness stood out for being present in a markedly larger proportion of models over time.ConclusionsThis review provides an up-to-date overview of SDM-models, showing that SDM-models quite consistently share some components but that a unified view on what SDM is, is still lacking. Clarity about what SDM constitutes is essential though for implementation, assessment, and research purposes. A map is offered to identify SDM-components seen as key.Trial registrationPROSPERO registration CRD42015019740

BackgroundConsensus guidelines have recommended that decision aids include a process for helping patients clarify their values. We sought to examine the theoretical and empirical evidence related to the use of values clarification methods in patient decision aids.MethodsBuilding on the International Patient Decision Aid Standards (IPDAS) Collaboration’s 2005 review of values clarification methods in decision aids, we convened a multi-disciplinary expert group to examine key definitions, decision-making process theories, and empirical evidence about the effects of values clarification methods in decision aids. To summarize the current state of theory and evidence about the role of values clarification methods in decision aids, we undertook a process of evidence review and summary.ResultsValues clarification methods (VCMs) are best defined as methods to help patients think about the desirability of options or attributes of options within a specific decision context, in order to identify which option he/she prefers. Several decision making process theories were identified that can inform the design of values clarification methods, but no single “best” practice for how such methods should be constructed was determined. Our evidence review found that existing VCMs were used for a variety of different decisions, rarely referenced underlying theory for their design, but generally were well described in regard to their development process. Listing the pros and cons of a decision was the most common method used. The 13 trials that compared decision support with or without VCMs reached mixed results: some found that VCMs improved some decision-making processes, while others found no effect.ConclusionsValues clarification methods may improve decision-making processes and potentially more distal outcomes. However, the small number of evaluations of VCMs and, where evaluations exist, the heterogeneity in outcome measures makes it difficult to determine their overall effectiveness or the specific characteristics that increase effectiveness.

ObjectiveTo inventory instruments assessing the process of shared decision making and appraise their measurement quality, taking into account the methodological quality of their validation studies.MethodsIn a systematic review we searched seven databases (PubMed, Embase, Emcare, Cochrane, PsycINFO, Web of Science, Academic Search Premier) for studies investigating instruments measuring the process of shared decision making. Per identified instrument, we assessed the level of evidence separately for 10 measurement properties following a three-step procedure: 1) appraisal of the methodological quality using the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) checklist, 2) appraisal of the psychometric quality of the measurement property using three possible quality scores, 3) best-evidence synthesis based on the number of studies, their methodological and psychometrical quality, and the direction and consistency of the results. The study protocol was registered at PROSPERO: CRD42015023397.ResultsWe included 51 articles describing the development and/or evaluation of 40 shared decision-making process instruments: 16 patient questionnaires, 4 provider questionnaires, 18 coding schemes and 2 instruments measuring multiple perspectives. There is an overall lack of evidence for their measurement quality, either because validation is missing or methods are poor. The best-evidence synthesis indicated positive results for a major part of instruments for content validity (50%) and structural validity (53%) if these were evaluated, but negative results for a major part of instruments when inter-rater reliability (47%) and hypotheses testing (59%) were evaluated.ConclusionsDue to the lack of evidence on measurement quality, the choice for the most appropriate instrument can best be based on the instrument’s content and characteristics such as the perspective that they assess. We recommend refinement and validation of existing instruments, and the use of COSMIN-guidelines to help guarantee high-quality evaluations.

No abstract

(266 words)Background. Values clarification is a recommended element of patient decision

PurposeThe SDM-Q-9 and SDM-Q-Doc measure patient and physician perception of the extent of shared decision making (SDM) during a physician-patient consultation. So far, no self-report instrument for SDM was available in Dutch, and validation of the scales in other languages has been limited. The aim of this study was to translate both scales into Dutch and assess their psychometric characteristics.MethodsParticipants were patients and their treating physicians (general practitioners and medical specialists). Patients (N = 182) rated their consultation using the SDM-Q-9, 43 physicians rated their consultations using the SDM-Q-Doc (N = 201). Acceptability, reliability (internal consistency), and the factorial structure of the instruments were determined. For convergent validity the CPSpost was used.ResultsReliabilities of both scales were high (alpha SDM-Q-9 0.88; SDM-Q-Doc 0.87). The SDM-Q-9 and SDM-Q-Doc total scores correlated as expected with the CPSpost (SDM-Q-9: r = 0.29; SDM-Q-Doc: r = 0.48) and were significantly different between the CPSpost categories, with lowest mean scores when the physician made the decision alone. Principal Component Analyses showed a two-component model for each scale. A confirmatory factor analysis yielded a mediocre, but acceptable, one-factor model, if Item 1 was excluded; for both scales the best indices of fit were obtained for a one-factor solution, if both Items 1 and 9 were excluded.ConclusionThe Dutch SDM-Q-9 and SDM-Q-Doc demonstrate good acceptance and reliability; they correlated as expected with the CPSpost and are suitable for use in Dutch primary and specialised care. Although the best model fit was found when excluding Items 1 and 9, we believe these items address important aspects of SDM. Therefore, also based on the coherence with theory and comparability with other studies, we suggest keeping all nine items of the scale. Further research on the SDM-concept in patients and physicians, in different clinical settings and different countries, is necessary to gain a better understanding of the SDM-construct and its measurement.