Dataset Information

Bridging the gap between complexity science and clinical practice by formalizing idiographic theories: a computational model of functional analysis.

ABSTRACT:

Background

The past decades of research have seen an increase in statistical tools to explore the complex dynamics of mental health from patient data, yet the application of these tools in clinical practice remains uncommon. This is surprising, given that clinical reasoning, e.g., case conceptualizations, largely coincides with the dynamical system approach. We argue that the gap between statistical tools and clinical practice can partly be explained by the fact that current estimation techniques disregard theoretical and practical considerations relevant to psychotherapy. To address this issue, we propose that case conceptualizations should be formalized. We illustrate this approach by introducing a computational model of functional analysis, a framework commonly used by practitioners to formulate case conceptualizations and design patient-tailored treatment.

Methods

We outline the general approach of formalizing idiographic theories, drawing on the example of a functional analysis for a patient suffering from panic disorder. We specified the system using a series of differential equations and simulated different scenarios; first, we simulated data without intervening in the system to examine the effects of avoidant coping on the development of panic symptomatic. Second, we formalized two interventions commonly used in cognitive behavioral therapy (CBT; exposure and cognitive reappraisal) and subsequently simulated their effects on the system.

Results

The first simulation showed that the specified system could recover several aspects of the phenomenon (panic disorder), however, also showed some incongruency with the nature of panic attacks (e.g., rapid decreases were not observed). The second simulation study illustrated differential effects of CBT interventions for this patient. All tested interventions could decrease panic levels in the system.

Conclusions

Formalizing idiographic theories is promising in bridging the gap between complexity science and clinical practice and can help foster more rigorous scientific practices in psychotherapy, through enhancing theory development. More precise case conceptualizations could potentially improve intervention planning and treatment outcomes. We discuss applications in psychotherapy and future directions, amongst others barriers for systematic theory evaluation and extending the framework to incorporate interactions between individual systems, relevant for modeling social learning processes. With this report, we hope to stimulate future efforts in formalizing clinical frameworks.

SUBMITTER: Burger J

PROVIDER: S-EPMC7333286 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Publications

Bridging the gap between complexity science and clinical practice by formalizing idiographic theories: a computational model of functional analysis.

Burger Julian J van der Veen Date C DC Robinaugh Donald J DJ Quax Rick R Riese Harriëtte H Schoevers Robert A RA Epskamp Sacha S

BMC medicine 20200408 1

<h4>Background</h4>The past decades of research have seen an increase in statistical tools to explore the complex dynamics of mental health from patient data, yet the application of these tools in clinical practice remains uncommon. This is surprising, given that clinical reasoning, e.g., case conceptualizations, largely coincides with the dynamical system approach. We argue that the gap between statistical tools and clinical practice can partly be explained by the fact that current estimation t ...[more]

PMID: 32264914

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Project description:BackgroundTraining programs for advanced practice providers (APP) often have significant variability in their curriculum, including electrocardiogram (ECG) education. Despite limitations in formal ECG training, APPs in the emergency department (ED) may be the first practitioner to interpret an ECG. Foundations of Emergency Medicine (FoEM) offers free, open-access curricula that are widely used for resident education. We sought to improve APP ECG interpretation skills by implementing the FoEM ECG I course.MethodsThis was a single-site, pre- and post-intervention study of 23 APPs at our high-acuity, urban ED. In the fall of 2020, APP learners enrolled in a FoEM ECG I course led by faculty and senior resident instructors. The course consisted of six virtual, small-group, active-learning ECG workshops. Participants completed a 15-question multiple-choice test before, immediately after, and six months post-intervention to quantify knowledge acquisition. Additionally, a pre- and post-intervention knowledge, attitudes, and practices survey was administered on ECG interpretation skills and to evaluate the course. We evaluated change in ECG knowledge scores using a Wilcoxon signed-rank test. Changes in self-assessed knowledge were evaluated using an ordinal logistic mixed-effects regression.ResultsA total of 23 APPs enrolled in the course. Knowledge assessments showed APPs improved from the pre-test (median 9/15, interquartile range [IQR] 7-11) to the post-test (median 12/15, IQR 10-13; P = 0.001). Test scores did not significantly change from the post-test to the delayed post-test (median 12/15, IQR 12-13; P = 0.30). Respondents' subjective rating of their skill did not significantly change (P = 0.06). Respondents reported no change in their likelihood of approaching an attending when uncertain of the correct interpretation of an ECG (P = 0.16). Overall, 91% were satisfied with the course and 96% agreed that the course difficulty was appropriate.ConclusionThe FoEM ECG course provided a standardized curriculum that improved APP knowledge for interpreting ECGs. Despite this, the course did not alter APPs' willingness to approach physicians for guidance with interpretation of abnormal ECGs. These findings may inform expansion of this concept for other programs who desire formalized APP ECG education.

Dataset Information

Bridging the gap between complexity science and clinical practice by formalizing idiographic theories: a computational model of functional analysis.

Background

Methods

Results

Conclusions

Publications

Bridging the gap between complexity science and clinical practice by formalizing idiographic theories: a computational model of functional analysis.

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