Development and field testing of a decision aid to facilitate shared decision making for adults newly diagnosed with attention‐deficit hyperactivity disorder

BACKGROUND A rural community-based Cardiology practice implemented shared decision making supported by an evidence-based decision aid booklet to improve the quality of anticoagulant therapy decisions in patients with atrial fibrillation. OBJECTIVE To develop a practical workflow for implementation of an anticoagulant therapy decision aid and to assess the impact on patients’ knowledge and process for anticoagulant medication decision making. METHODS The organization surveyed all patients with atrial fibrillation being seen at Copley Hospital to establish a baseline level of knowledge, certainty about the decision and process for decision making. The intervention surveys included the same knowledge, certainty, process and demographic questions as the baseline surveys, but also included questions asking for feedback on the decision aid booklet. Stroke risk scores (CHA2DS2-VASc score) were calculated by Copley staff for both groups using EMR data. RESULTS We received 46 completed surveys in the baseline group (64% response rate) and 50 surveys in the intervention group (72% response rate). The intervention group had higher knowledge score than the baseline group (3.6 out of 4 correct answers vs 3.1, p=0.036) and Decision Process Score (2.89 out of 4 vs 2.09, p=0.0023) but similar scores on the SURE scale (3.12 out of 4 vs 3.17, p=0.79). Knowledge and Process score differences were sustained even after adjusting for co-variates in stepwise linear regression analyses. Patients with high school or lower education appeared to benefit the most from shared decision making, as demonstrated by their knowledge scores. CONCLUSIONS It is feasible and practical to implement shared decision making supported by decision aids in a community-based Cardiology practice. Shared decision making can improve knowledge and process for decision making for patients with atrial fibrillation. CLINICALTRIAL None

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InformedTogether: A decision aid to support shared decision making about mechanical ventilation in severe COPD patients

10.2196/preprints.9877.a ◽

2018 ◽

Author(s):

Meliss Basile ◽

Johanna Andrews ◽

Sonia Jacome ◽

Meng Zhang ◽

Andrzej Kozikowski ◽

...

Keyword(s):

Decision Making ◽

Mechanical Ventilation ◽

Shared Decision Making ◽

Decision Aid ◽

Shared Decision ◽

Copd Patients ◽

Severe Copd

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CP-021 The impact of a decision aid on depressed patient’s involvement in shared decision making: A pilot randomised controlled double blind study

European Journal of Hospital Pharmacy ◽

10.1136/ejhpharm-2016-000875.21 ◽

2016 ◽

Vol 23 (Suppl 1) ◽

pp. A9.3-A10 ◽

Cited By ~ 1

Author(s):

K Aljumah ◽

A Nwaf ◽

A Amed ◽

A Alhoutan ◽

M Aldhiab

Keyword(s):

Decision Making ◽

Shared Decision Making ◽

Decision Aid ◽

Blind Study ◽

Double Blind Study ◽

Shared Decision ◽

Double Blind ◽

Randomised Controlled ◽

The Impact

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Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder

Translational Psychiatry ◽

10.1038/s41398-020-01118-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Alekhya Mandali ◽

Arjun Sethi ◽

Mara Cercignani ◽

Neil A. Harrison ◽

Valerie Voon

Keyword(s):

Decision Making ◽

Attention Deficit Hyperactivity Disorder ◽

Attention Deficit ◽

Computational Models ◽

Risky Choice ◽

Risk Tolerance ◽

Healthy Population ◽

Hyperactivity Disorder ◽

Risky Choices ◽

Cardinal Symptom

AbstractRisk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift–diffusion model to extract parameters such as threshold (‘a’—amount of evidence accumulated before making a decision), drift rate (‘v’—information processing speed) and response bias (‘z’ apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population.

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Patient decision aid based on multi-criteria decision analysis for disease-modifying drugs for multiple sclerosis: prototype development

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01479-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

I. E. H. Kremer ◽

P. J. Jongen ◽

S. M. A. A. Evers ◽

E. L. J. Hoogervorst ◽

W. I. M. Verhagen ◽

...

Keyword(s):

Decision Making ◽

Shared Decision Making ◽

Decision Aid ◽

Healthcare Professionals ◽

Treatment Options ◽

Shared Decision ◽

Patient Decision Aid ◽

Disease Modifying Drugs ◽

Patient Decision ◽

Further Development

Abstract Background Since decision making about treatment with disease-modifying drugs (DMDs) for multiple sclerosis (MS) is preference sensitive, shared decision making between patient and healthcare professional should take place. Patient decision aids could support this shared decision making process by providing information about the disease and the treatment options, to elicit the patient’s preference and to support patients and healthcare professionals in discussing these preferences and matching them with a treatment. Therefore, a prototype of a patient decision aid for MS patients in the Netherlands—based on the principles of multi-criteria decision analysis (MCDA) —was developed, following the recommendations of the International Patient Decision Aid Standards. MCDA was chosen as it might reduce cognitive burden of considering treatment options and matching patient preferences with the treatment options. Results After determining the scope to include DMDs labelled for relapsing-remitting MS and clinically isolated syndrome, users’ informational needs were assessed using focus groups (N = 19 patients) and best-worst scaling surveys with patients (N = 185), neurologists and nurses (N = 60) to determine which information about DMDs should be included in the patient decision aid. Next, an online format and computer-based delivery of the patient decision aid was chosen to enable embedding of MCDA. A literature review was conducting to collect evidence on the effectiveness and burden of use of the DMDs. A prototype was developed next, and alpha testing to evaluate its comprehensibility and usability with in total thirteen patients and four healthcare professionals identified several issues regarding content and framing, methods for weighting importance of criteria in the MCDA structure, and the presentation of the conclusions of the patient decision aid ranking the treatment options according to the patient’s preferences. Adaptations were made accordingly, but verification of the rankings provided, validation of the patient decision aid, evaluation of the feasibility of implementation and assessing its value for supporting shared decision making should be addressed in further development of the patient decision aid. Conclusion This paper aimed to provide more transparency regarding the developmental process of an MCDA-based patient decision aid for treatment decisions for MS and the challenges faced during this process. Issues identified in the prototype were resolved as much as possible, though some issues remain. Further development is needed to overcome these issues before beta pilot testing with patients and healthcare professionals at the point of clinical decision-making can take place to ultimately enable making conclusions about the value of the MCDA-based patient decision aid for MS patients, healthcare professionals and the quality of care.

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