ABSTRACT
BACKGROUND: Depression is characterized by poor executive function, but - counterintuitively - in some studies, it has been associated with highly accurate performance on certain cognitively demanding tasks. The psychological mechanisms responsible for this paradoxical finding are unclear. To address this issue, we applied a drift diffusion model (DDM) to flanker task data from depressed and healthy adults participating in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study. METHOD: One hundred unmedicated, depressed adults and 40 healthy controls completed a flanker task. We investigated the effect of flanker interference on accuracy and response time, and used the DDM to examine group differences in three cognitive processes: prepotent response bias (tendency to respond to the distracting flankers), response inhibition (necessary to resist prepotency), and executive control (required for execution of correct response on incongruent trials). RESULTS: Consistent with prior reports, depressed participants responded more slowly and accurately than controls on incongruent trials. The DDM indicated that although executive control was sluggish in depressed participants, this was more than offset by decreased prepotent response bias. Among the depressed participants, anhedonia was negatively correlated with a parameter indexing the speed of executive control (r = -0.28, p = 0.007). CONCLUSIONS: Executive control was delayed in depression but this was counterbalanced by reduced prepotent response bias, demonstrating how participants with executive function deficits can nevertheless perform accurately in a cognitive control task. Drawing on data from neural network simulations, we speculate that these results may reflect tonically reduced striatal dopamine in depression.
Subject(s)
Cognition , Depression/psychology , Executive Function , Reaction Time , Adolescent , Adult , Aged , Female , Humans , Male , Middle Aged , Models, Psychological , Neuropsychological Tests , Randomized Controlled Trials as Topic , Surveys and Questionnaires , Young AdultABSTRACT
BACKGROUND: The present study provides additional data on the psychometric properties of the 30-item Inventory of Depressive Symptomatology (IDS) and of the recently developed Quick Inventory of Depressive Symptomatology (QIDS), a brief 16-item symptom severity rating scale that was derived from the longer form. Both the IDS and QIDS are available in matched clinician-rated (IDS-C30; QIDS-C16) and self-report (IDS-SR30; QIDS-SR16) formats. METHOD: The patient samples included 544 out-patients with major depressive disorder (MDD) and 402 out-patients with bipolar disorder (BD) drawn from 19 regionally and ethnicically diverse clinics as part of the Texas Medication Algorithm Project (TMAP). Psychometric analyses including sensitivity to change with treatment were conducted. RESULTS: Internal consistencies (Cronbach's alpha) ranged from 0.81 to 0.94 for all four scales (QIDS-C16, QIDS-SR16, IDS-C30 and IDS-SR30) in both MDD and BD patients. Sad mood, involvement, energy, concentration and self-outlook had the highest item-total correlations among patients with MDD and BD across all four scales. QIDS-SR16 and IDS-SR30 total scores were highly correlated among patients with MDD at exit (c = 0.83). QIDS-C16 and IDS-C30 total scores were also highly correlated among patients with MDD (c = 0.82) and patients with BD (c = 0.81). The IDS-SR30, IDS-C30, QIDS-SR16, and QIDS-C16 were equivalently sensitive to symptom change, indicating high concurrent validity for all four scales. High concurrent validity was also documented based on the SF-12 Mental Health Summary score for the population divided in quintiles based on their IDS or QIDS score. CONCLUSION: The QIDS-SR16 and QIDS-C16, as well as the longer 30-item versions, have highly acceptable psychometric properties and are treatment sensitive measures of symptom severity in depression.
Subject(s)
Bipolar Disorder/diagnosis , Depressive Disorder, Major/diagnosis , Psychiatric Status Rating Scales/standards , Psychometrics/instrumentation , Severity of Illness Index , Adult , Bipolar Disorder/classification , Bipolar Disorder/physiopathology , Depressive Disorder, Major/classification , Depressive Disorder, Major/physiopathology , Female , Humans , Male , Middle Aged , Sensitivity and Specificity , Texas , Treatment OutcomeABSTRACT
This study compared the performance of an itemized symptom self-report (Inventory of Depressive Symptomatology - Self-Report; IDS-SR), patient global ratings, and clinician global ratings with an itemized clinician-rated symptom severity measure (Inventory of Depressive Symptomatology - Clinician-Rated; IDS-C) in detecting treatment effects in patients with major depressive disorder (MDD). A total of 28 inpatients (30.8% psychotic) and 34 outpatients (17.9% psychotic) with MDD began treatment that followed the Texas medication algorithm. The clinicians completed the IDS-C and a Physician Global Rating Scale (PhGRS) at each assessment visit, while the patients completed the IDS-SR and a Patient Global Rating Scale (PtGRS). Change scores from the baseline to subsequent weeks were computed for all subjects, utilizing all four measures. The IDS-SR was a significant independent predictor of the response to treatment as compared to the two global ratings. The IDS-SR was as sensitive to change as the IDS-C. While the clinician-rated itemized symptom severity rating scale remains the standard to assess the symptomatic outcome of the treatment of MDD, a self-report of identical symptomatology may be a reasonable alternative for many patients.
Subject(s)
Depression/diagnosis , Depressive Disorder, Major/drug therapy , Outcome Assessment, Health Care/methods , Psychiatric Status Rating Scales/standards , Psychotropic Drugs/therapeutic use , Adult , Algorithms , Depressive Disorder, Major/diagnosis , Diagnosis, Differential , Feasibility Studies , Female , Humans , Logistic Models , Male , Middle Aged , Pilot Projects , Practice Guidelines as Topic , Prognosis , Self-Assessment , Severity of Illness Index , TexasABSTRACT
This study compared the performance of an itemized symptom self-report (Inventory of Depressive Symptomatology - Self-Report; IDS-SR), patient global ratings, and clinician global ratings with an itemized clinician-rated symptom severity measure (Inventory of Depressive Symptomatology - Clinician-Rated; IDS-C) in detecting treatment effects in patients with major depressive disorder (MDD). A total of 28 inpatients (30.8% psychotic) and 34 outpatients (17.9% psychotic) with MDD began treatment that followed the Texas medication algorithm. The clinicians completed the IDS-C and a Physician Global Rating Scale (PhGRS) at each assessment visit, while the patients completed the IDS-SR and a Patient Global Rating Scale (PtGRS). Change scores from the baseline to subsequent weeks were computed for all subjects, utilizing all four measures. The IDS-SR was a significant independent predictor of the response to treatment as compared to the two global ratings. The IDS-SR was as sensitive to change as the IDS-C. While the clinician-rated itemized symptom severity rating scale remains the standard to assess the symptomatic outcome of the treatment of MDD, a self-report of identical symptomatology may be a reasonable alternative for many patients.
Subject(s)
Depressive Disorder, Major/diagnosis , Personality Assessment/statistics & numerical data , Personality Inventory/statistics & numerical data , Adult , Algorithms , Antidepressive Agents/therapeutic use , Depressive Disorder, Major/drug therapy , Depressive Disorder, Major/psychology , Female , Humans , Male , Middle Aged , Pilot Projects , Psychometrics , Reproducibility of Results , Treatment OutcomeABSTRACT
This article provides an overview of the issues involved in developing, using, and evaluating specific medication guidelines for patients with psychiatric disorders. The potential advantages and disadvantages, as well as the essential elements in the structure of algorithms, are illustrated by experience to date with the Texas Medication Algorithm Project, a public-academic collaboration. Phase 1 entailed assembling research findings on the efficacy of medications for schizophrenic, bipolar, and major depressive disorders. This knowledge was evaluated for its quality and relevance, integrated with expert clinical judgment as well as input by practicing clinicians, family advocates, and patients. Phase 1 (the design and development of the algorithms) was followed by a feasibility test (Phase 2). Phase 3 is an ongoing evaluation comparing the clinical and economic effects of using specific medication guidelines (algorithms) versus treatment as usual in public sector patients with severe and persistent mental illnesses.