scholarly journals Physicians' Shared Decision-Making Behaviors in Attention-Deficit/Hyperactivity Disorder Care

2011 ◽  
Vol 165 (11) ◽  
pp. 1013 ◽  
Author(s):  
William B. Brinkman
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Shared Decision Making ◽  
Attention Deficit ◽  
Shared Decision ◽  
Hyperactivity Disorder

scholarly journals Shared decision-making to improve attention-deficit hyperactivity disorder care

2013 ◽  
Vol 93 (1) ◽  
pp. 95-101 ◽  
Author(s):  
William B. Brinkman ◽  
Jessica Hartl Majcher ◽  
Lauren M. Poling ◽  
Gaoyan Shi ◽  
Mike Zender ◽  
...  
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Shared Decision Making ◽  
Attention Deficit ◽  
Shared Decision ◽  
Hyperactivity Disorder

scholarly journals Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder

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.

scholarly journals Disentangling ADHD's Presentation-Related Decision-Making—A Meta-Analytic Approach on Predominant Presentations

2021 ◽  
Vol 12 ◽  
Author(s):  
Marcel Schulze ◽  
David Coghill ◽  
Silke Lux ◽  
Alexandra Philipsen
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Reinforcement Learning ◽  
Risk Taking ◽  
Attention Deficit ◽  
Meta Analysis ◽  
Analytic Approach ◽  
Effect Sizes ◽  
Hyperactivity Disorder ◽  
The Relationship

Background: Deficient decision-making (DM) in attention deficit/hyperactivity disorder (ADHD) is marked by altered reward sensitivity, higher risk taking, and aberrant reinforcement learning. Previous meta-analysis aggregate findings for the ADHD combined presentation (ADHD-C) mostly, while the ADHD predominantly inattentive presentation (ADHD-I) and the predominantly hyperactive/impulsive presentation (ADHD-H) were not disentangled. The objectives of the current meta-analysis were to aggregate findings from DM for each presentation separately.Methods: A comprehensive literature search of the PubMed (Medline) and Web of Science Database took place using the keywords “ADHD,” “attention-deficit/hyperactivity disorder,” “decision-making,” “risk-taking,” “reinforcement learning,” and “risky.” Random-effects models based on correlational effect-sizes were conducted. Heterogeneity analysis and sensitivity/outlier analysis were performed, and publication biases were assessed with funnel-plots and the egger intercept.Results: Of 1,240 candidate articles, seven fulfilled criteria for analysis of ADHD-C (N = 193), seven for ADHD-I (N = 256), and eight for ADHD-H (N = 231). Moderate effect-size were found for ADHD-C (r = 0.34; p = 0.0001; 95% CI = [0.19, 0.49]). Small effect-sizes were found for ADHD-I (r = 0.09; p = 0.0001; 95% CI = [0.008, 0.25]) and for ADHD-H (r = 0.1; p = 0.0001; 95% CI = [−0.012, 0.32]). Heterogeneity was moderate for ADHD-H. Sensitivity analyses show robustness of the analysis, and no outliers were detected. No publication bias was evident.Conclusion: This is the first study that uses a meta-analytic approach to investigate the relationship between the different presentations of ADHD separately. These findings provide first evidence of lesser pronounced impairment in DM for ADHD-I and ADHD-I compared to ADHD-C. While the exact factors remain elusive, the current study can be considered as a starting point to reveal the relationship of ADHD presentations and DM more detailed.

Aeromedical Decision Making in Attention-Deficit/Hyperactivity Disorder

2011 ◽  
Vol 82 (5) ◽  
pp. 550-554
Author(s):  
David J. P. Fitzgerald ◽  
Pooshan D. Navathe ◽  
A. Michael Drane
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Hyperactivity Disorder

Multiple Approaches to the Diagnosis of Attention Deficit Hyperactivity Disorder

2013 ◽  
Vol 8 (4) ◽  
pp. 44-57 ◽  
Author(s):  
Rui Rijo ◽  
Ricardo Martinho ◽  
Xiaocheng Ge
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Clinical Decision Making ◽  
Adult Life ◽  
Clinical Decision ◽  
School Age Children ◽  
Free Text ◽  
Clinical Decisions ◽  
Hyperactivity Disorder

Studies indicate that about 3-7% of school-age children have attention deficit hyperactivity disorder (ADHD). If these disorders are not diagnosed and treated early, its consequences can harshly impair the adult life of the individual. In this context, early diagnosis is critical. Clinical reasoning is a key contributor to the quality of health care. Clinical decisions at the policy level are made within a stochastic domain; decisions for individuals are usually more qualitative. In both cases, poor reasoning can result in an undesirable outcome. Clinical decisions are most typically communicated in a document through free text. Text has significant limitations (particularly ambiguity and poor structuring) whether used for analysis, or to explain the decision-making process. In safety engineering, similar problems are faced in conveying safety arguments to support certification. As a result, approaches have been developed to conveying arguments in ways which improve communication and which are more amenable to analysis. The Goal Structuring Notation (GSN) – a graphical argumentation notation for safety – was developed for those reasons. It has evolved to be one of the most widely used techniques for representing safety arguments. The use of text-mining techniques is another approach in the process of achieving or suggesting a diagnosis to the physician. This paper investigates the relative feasibility of these two approaches and discuss their complementation. Based on a case example, the benefits and problems of adopting GSN and ontology approach in clinical decision-making for ADHD are discussed and illustrated.

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