Dataset Information

Identify depressive phenotypes by applying RDOC domains to the PHQ-9.

ABSTRACT: Major depression consists of multiple phenotypic traits. Our objective was to characterize depressive phenotypes in the patient health questionnaire (PHQ)-9 using the Research Domain Criteria (RDoC) research framework. Cross-sectional data were examined from the 2013-2014 (N = 5397) and 2015-2016 (N = 5164) National Health and Nutrition Examination Survey, a large, nationally representative U.S. sample. Using both factor analysis and qualitative analysis in mapping scale items along RDoC domains, a four factor model was found to be theoretically appropriate and had an excellent model fit for the PHQ-9. The factor structure consisted of phenotypes describing Negative Valence Systems and Externalizing (anhedonia and depression), Negative Valence Systems and Internalizing (depression, guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue and appetite) and Cognitive and Sensorimotor Systems (concentration and psychomotor). High correlation between these phenotypes did indicate screening and monitoring for depression study population using a single depression score is likely useful in most circumstances. In multiple indicator multiple cause analysis, differences in the means of the phenotypic traits were found by age, race/ethnicity, sex, and number of comorbidities. Future research should explore whether phenotype expression derived from readily available self-rated depression scales can help to inform more personalized care.

SUBMITTER: Gunzler D

PROVIDER: S-EPMC7434666 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Identify depressive phenotypes by applying RDOC domains to the PHQ-9.

Gunzler Douglas D Sehgal Ashwini R AR Kauffman Kelley K Davey Christine Horvat CH Dolata Jacqueline J Figueroa Maria M Huml Anne A Pencak Julie J Sajatovic Martha M

Psychiatry research 20200219

Major depression consists of multiple phenotypic traits. Our objective was to characterize depressive phenotypes in the patient health questionnaire (PHQ)-9 using the Research Domain Criteria (RDoC) research framework. Cross-sectional data were examined from the 2013-2014 (N = 5397) and 2015-2016 (N = 5164) National Health and Nutrition Examination Survey, a large, nationally representative U.S. sample. Using both factor analysis and qualitative analysis in mapping scale items along RDoC domains ...[more]

PMID: 32151848

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Project description:BackgroundPreliminary results from randomized controlled studies as well as identified molecular, cellular, and circuit targets of select psychedelics (e.g., psilocybin) suggest that their effects are transdiagnostic. In this review, we exploit the Research Domain Criteria (RDoC) transdiagnostic framework, to synthesize extant literature on psilocybin.ObjectiveWe aimed to identify RDoC-based effects of psilocybin and vistas for future mechanistic and interventional research.MethodsA systematic search in electronic databases (i.e., PubMed, Scopus, PsycINFO, and Web of Science) performed in January and February 2021 identified English articles published between 1990 and 2020 reporting the effects of psilocybin on mental health measures. Data from included articles were retrieved and organized according to the RDoC bio-behavioral matrix and its constituent six main domains, namely: positive valence systems, negative valence systems, cognitive systems, social processes, sensorimotor systems, and arousal and regulatory systems.ResultsThe preponderance of research with psilocybin has differentially reported beneficial effects on positive valence systems, negative valence system, and social process domains. The data from the included studies support both short-term (23 assessments) and long-term (15 assessments) beneficial effects of psilocybin on the positive valence systems. While 12 of the extracted outcome measures suggest that psilocybin use is associated with increases in the "fear" construct of the negative valence systems domain, 19 findings show no significant effects on this construct, and seven parameters show lowered levels of the "sustained threat" construct in the long term. Thirty-four outcome measures revealed short-term alterations in the social systems' construct namely, "perception and understanding of self," and "social communications" as well as enhancements in "perception and understanding of others" and "affiliation and attachment". The majority of findings related to the cognitive systems' domain reported dyscognitive effects. There have been relatively few studies reporting outcomes of psilocybin on the remaining RDoC domains. Moreover, seven of the included studies suggest the transdiagnostic effects of psilocybin. The dashboard characterization of RDoC outcomes with psilocybin suggests beneficial effects in the measures of reward, threat, and arousal, as well as general social systems.ConclusionsPsilocybin possesses a multi-domain effectiveness. The field would benefit from highly rigorous proof-of-mechanism research to assess the effects of psilocybin using the RDoC framework. The combined effect of psilocybin with psychosocial interventions with RDoC-based outcomes is a priority therapeutic vista.

Project description:BackgroundAccurate reporting of patient symptoms is critical for diagnosis and therapeutic monitoring in psychiatry. Smartphones offer an accessible, low-cost means to collect patient symptoms in real time and aid in care.ObjectiveTo investigate adherence among psychiatric outpatients diagnosed with major depressive disorder in utilizing their personal smartphones to run a custom app to monitor Patient Health Questionnaire-9 (PHQ-9) depression symptoms, as well as to examine the correlation of these scores to traditionally administered (paper-and-pencil) PHQ-9 scores.MethodsA total of 13 patients with major depressive disorder, referred by their clinicians, received standard outpatient treatment and, in addition, utilized their personal smartphones to run the study app to monitor their symptoms. Subjects downloaded and used the Mindful Moods app on their personal smartphone to complete up to three survey sessions per day, during which a randomized subset of PHQ-9 symptoms of major depressive disorder were assessed on a Likert scale. The study lasted 29 or 30 days without additional follow-up. Outcome measures included adherence, measured by the percentage of completed survey sessions, and estimates of daily PHQ-9 scores collected from the smartphone app, as well as from the traditionally administered PHQ-9.ResultsOverall adherence was 77.78% (903/1161) and varied with time of day. PHQ-9 estimates collected from the app strongly correlated (r=.84) with traditionally administered PHQ-9 scores, but app-collected scores were 3.02 (SD 2.25) points higher on average. More subjects reported suicidal ideation using the app than they did on the traditionally administered PHQ-9.ConclusionsPatients with major depressive disorder are able to utilize an app on their personal smartphones to self-assess their symptoms of major depressive disorder with high levels of adherence. These app-collected results correlate with the traditionally administered PHQ-9. Scores recorded from the app may potentially be more sensitive and better able to capture suicidality than the traditional PHQ-9.

Project description:BackgroundMedication errors harm hospitalised patients and increase health care costs. Electronic Medication Management Systems (EMMS) have been shown to reduce medication errors. However, nurses do not always use EMMS as intended, largely because implementation of such patient safety strategies requires clinicians to change their existing practices, routines and behaviour. This study uses the Theoretical Domains Framework (TDF) to identify barriers and targeted interventions to enhance nurses' appropriate use of EMMS in two Australian hospitals.MethodsThis qualitative study draws on in-depth interviews with 19 acute care nurses who used EMMS. A convenience sampling approach was used. Nurses working on the study units (N = 6) in two hospitals were invited to participate if available during the data collection period. Interviews inductively explored nurses' experiences of using EMMS (step 1). Data were analysed using the TDF to identify theory-derived barriers to nurses' appropriate use of EMMS (step 2). Relevant behaviour change techniques (BCTs) were identified to overcome key barriers to using EMMS (step 3) followed by the identification of potential literature-informed targeted intervention strategies to operationalise the identified BCTs (step 4).ResultsBarriers to nurses' use of EMMS in acute care were represented by nine domains of the TDF. Two closely linked domains emerged as major barriers to EMMS use: Environmental Context and Resources (availability and properties of computers on wheels (COWs); technology characteristics; specific contexts; competing demands and time pressure) and Social/Professional Role and Identity (conflict between using EMMS appropriately and executing behaviours critical to nurses' professional role and identity). The study identified three potential BCTs to address the Environmental Context and Resources domain barrier: adding objects to the environment; restructuring the physical environment; and prompts and cues. Seven BCTs to address Social/Professional Role and Identity were identified: social process of encouragement; pressure or support; information about others' approval; incompatible beliefs; identification of self as role model; framing/reframing; social comparison; and demonstration of behaviour. It proposes several targeted interventions to deliver these BCTs.ConclusionsThe TDF provides a useful approach to identify barriers to nurses' prescribed use of EMMS, and can inform the design of targeted theory-based interventions to improve EMMS implementation.

Project description:Imaging techniques are a potentially powerful method of identifying phenotypes that are associated with, or are indicative of, a vulnerability to developing major depressive disorder (MDD). Here we identify seven promising MDD-associated traits identified by magnetic resonance imaging (MRI) or positron emission tomography (PET). We evaluate whether these traits are state-independent, heritable endophenotypes, or state-dependent phenotypes that may be useful markers of treatment efficacy. In MDD, increased activity of the amygdala in response to negative stimuli appears to be a mood-congruent phenomenon, and is likely moderated by the 5-HT transporter gene (SLC6A4) promoter polymorphism (5-HTTLPR). Hippocampal volume loss is characteristic of elderly or chronically-ill samples and may be impacted by the val66met brain-derived neurotrophic factor (BDNF) gene variant and the 5-HTTLPR SLC6A4 polymorphism. White matter pathology is salient in elderly MDD cohorts but is associated with cerebrovascular disease, and is unlikely to be a useful marker of a latent MDD diathesis. Increased blood flow or metabolism of the subgenual anterior cingulate cortex (sgACC), together with gray matter volume loss in this region, is a well-replicated finding in MDD. An attenuation of the usual pattern of fronto-limbic connectivity, particularly a decreased temporal correlation in amygdala-anterior cingulate cortex (ACC) activity, is another MDD-associated trait. Concerning neuroreceptor PET imaging, decreased 5-HT(1A) binding potential in the raphe, medial temporal lobe, and medial prefrontal cortex (mPFC) has been strongly associated with MDD, and may be impacted by a functional single nucleotide polymorphism in the promoter region of the 5-HT(1A) gene (HTR1A: -1019 C/G; rs6295). Potentially indicative of inter-study variation in MDD etiology or mood state, both increased and decreased binding potential of the 5-HT transporter has been reported. Challenges facing the field include the problem of phenotypic and etiological heterogeneity, technological limitations, the confounding effects of medication, and non-disease related inter-individual variation in brain morphology and function. Further advances are likely as epigenetic, copy-number variant, gene-gene interaction, and genome-wide association (GWA) approaches are brought to bear on imaging data.

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Identify depressive phenotypes by applying RDOC domains to the PHQ-9.

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Identify depressive phenotypes by applying RDOC domains to the PHQ-9.

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