Dataset Information

Detecting Critical Decision Points during Cognitive-Behavioral Therapy and Light Therapy for Winter Depression Nonremission and Recurrence.

ABSTRACT: Using data from a clinical trial comparing cognitive-behavioral therapy (CBT-SAD) and light therapy (LT) for winter seasonal affective disorder (SAD; N = 177), we explored critical decision points, or treatment weeks, that predict likelihood of nonremission at post-treatment and depression recurrence following treatment. In receiver operator characteristic (ROC) curve analyses, we used weekly Structured Clinical Interview for the Hamilton Rating Scale for Depression-SAD Version (SIGH-SAD) scores during treatment to predict nonremission at post-treatment (Week 6) and recurrence one winter later (Winter 1), two winters later (Winter 2), and any recurrence. Although several C-statistics of ≥ .70 were found, only Week 4 SIGH-SAD scores in CBT-SAD for nonremission had enough predictive ability to inform clinical decision-making (C-statistic = .80; sensitivity = .91; specificity = .68). Week 4 of CBT-SAD may be a critical time point to identify likely nonremitters who need tailoring of intervention, based on SIGH-SAD cutpoint score ≥ 13. This study illustrates how clinical trial data can inform detecting optimal decision points in treatment for identifying patients unlikely to remit, a critical first step to developing adaptive treatment strategies using decision rules to operationalize when and for whom treatment should change to maximize clinical benefit.

SUBMITTER: Rohan KJ

PROVIDER: S-EPMC9524476 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Detecting Critical Decision Points during Cognitive-Behavioral Therapy and Light Therapy for Winter Depression Nonremission and Recurrence.

Rohan Kelly J KJ Camuso Julia J Perez Jessica J Iyiewuare Praise P Meyerhoff Jonah J DeSarno Michael J MJ Vacek Pamela M PM

Journal of behavioral and cognitive therapy 20201029 4

Using data from a clinical trial comparing cognitive-behavioral therapy (CBT-SAD) and light therapy (LT) for winter seasonal affective disorder (SAD; <i>N</i> = 177), we explored critical decision points, or treatment weeks, that predict likelihood of nonremission at post-treatment and depression recurrence following treatment. In receiver operator characteristic (ROC) curve analyses, we used weekly Structured Clinical Interview for the Hamilton Rating Scale for Depression-SAD Version (SIGH-SAD) ...[more]

PMID: 36186272

Similar Datasets

Project description:BackgroundSeasonal affective disorder (SAD) is a subtype of recurrent depression involving major depressive episodes during the fall and/or winter months that remit in the spring. The central public health challenge in the management of SAD is prevention of winter depression recurrence. Light therapy (LT) is the established and best available acute SAD treatment. However, long-term compliance with daily LT from first symptom through spontaneous springtime remission every fall/winter season is poor. Time-limited alternative treatments with effects that endure beyond the cessation of acute treatment are needed to prevent the annual recurrence of SAD.Methods/designThis is an NIMH-funded R01-level randomized clinical trial to test the efficacy of a novel, SAD-tailored cognitive-behavioral group therapy (CBT) against LT in a head-to-head comparison on next winter outcomes. This project is designed to test for a clinically meaningful difference between CBT and LT on depression recurrence in the next winter (the primary outcome). This is a concurrent two-arm study that will randomize 160 currently symptomatic community adults with major depression, recurrent with seasonal pattern, to CBT or LT. After 6 weeks of treatment in the initial winter, participants are followed in the subsequent summer, the next winter, and two winters later. Key methodological issues surround timing study procedures for a predictably recurrent and time-limited disorder with a focus on long-term outcomes.DiscussionThe chosen design answers the primary question of whether prior exposure to CBT is associated with a substantially lower likelihood of depression recurrence the next winter than LT. This design does not test the relative contributions of the cognitive-behavioral treatment components vs. nonspecific factors to CBT's outcomes and is not adequately powered to test for differences or equivalence between cells at treatment endpoint. Alternative designs addressing these limitations would have required more patients, increased costs, and reduced power to detect a difference in the primary outcome.Trial registrationClinicaltrials.gov identifier NCT01714050.

Project description:BackgroundMental disorders have become a major concern in public health, and they are one of the main causes of the overall disease burden worldwide. Social media platforms allow us to observe the activities, thoughts, and feelings of people's daily lives, including those of patients suffering from mental disorders. There are studies that have analyzed the influence of mental disorders, including depression, in the behavior of social media users, but they have been usually focused on messages written in English.ObjectiveThe study aimed to identify the linguistic features of tweets in Spanish and the behavioral patterns of Twitter users who generate them, which could suggest signs of depression.MethodsThis study was developed in 2 steps. In the first step, the selection of users and the compilation of tweets were performed. A total of 3 datasets of tweets were created, a depressive users dataset (made up of the timeline of 90 users who explicitly mentioned that they suffer from depression), a depressive tweets dataset (a manual selection of tweets from the previous users, which included expressions indicative of depression), and a control dataset (made up of the timeline of 450 randomly selected users). In the second step, the comparison and analysis of the 3 datasets of tweets were carried out.ResultsIn comparison with the control dataset, the depressive users are less active in posting tweets, doing it more frequently between 23:00 and 6:00 (P<.001). The percentage of nouns used by the control dataset almost doubles that of the depressive users (P<.001). By contrast, the use of verbs is more common in the depressive users dataset (P<.001). The first-person singular pronoun was by far the most used in the depressive users dataset (80%), and the first- and the second-person plural pronouns were the least frequent (0.4% in both cases), this distribution being different from that of the control dataset (P<.001). Emotions related to sadness, anger, and disgust were more common in the depressive users and depressive tweets datasets, with significant differences when comparing these datasets with the control dataset (P<.001). As for negation words, they were detected in 34% and 46% of tweets in among depressive users and in depressive tweets, respectively, which are significantly different from the control dataset (P<.001). Negative polarity was more frequent in the depressive users (54%) and depressive tweets (65%) datasets than in the control dataset (43.5%; P<.001).ConclusionsTwitter users who are potentially suffering from depression modify the general characteristics of their language and the way they interact on social media. On the basis of these changes, these users can be monitored and supported, thus introducing new opportunities for studying depression and providing additional health care services to people with this disorder.

Project description:BackgroundThis study is a confirmatory efficacy trial of two treatments for winter seasonal affective disorder (SAD): SAD-tailored group cognitive-behavioral therapy (CBT-SAD) and light therapy (LT). In our previous efficacy trial, post-treatment outcomes for CBT-SAD and LT were very similar, but CBT-SAD was associated with fewer depression recurrences two winters later than LT (27.3% in CBT-SAD vs. 45.6% in LT). CBT-SAD engaged and altered a specific mechanism of action, seasonal beliefs, which mediated CBT-SAD's acute antidepressant effects and CBT-SAD's enduring benefit over LT. Seasonal beliefs are theoretically distinct from LT's assumed target and mechanism: correction of circadian phase. This study applies the experimental therapeutics approach to determine how each treatment works when it is effective and to identify the best candidates for each. Biomarkers of LT's target and effect include circadian phase angle difference and the post-illumination pupil response. Biomarkers of CBT-SAD's target and effect include decreased pupillary and sustained frontal gamma-band EEG responses to seasonal words, which are hypothesized as biomarkers of seasonal beliefs, reflecting less engagement with seasonal stimuli following CBT-SAD. In addition to determining change mechanisms, this study tests the efficacy of a "switch" decision rule upon recurrence to inform clinical decision-making in practice.MethodsAdults with SAD (target N = 160) will be randomzied to 6-weeks of CBT-SAD or LT in winter 1; followed in winter 2; and, if a depression recurrence occurs, offered cross-over into the alternate treatment (i.e., switch from LT➔CBT-SAD or CBT-SAD➔LT). All subjects will be followed in winter 3. Biomarker assessments occur at pre-, mid-, and post-treatment in winter 1, at winter 2 follow-up (and again at mid-/post-treatment for those crossed-over), and at winter 3 follow-up. Primary efficacy analyses will test superiority of CBT-SAD over LT on depression recurrence status (the primary outcome). Mediation analyses will use parallel process latent growth curve modeling.DiscussionConsistent with the National Institute of Mental Health's priorities for demonstrating target engagement at the level of Research Domain Criteria-relevant biomarkers, this work aims to confirm the targets and mechanisms of LT and CBT-SAD to maximize the impact of future dissemination efforts.Trial registrationClinicalTrials.gov identifier: NCT03691792 . Registered on October 2, 2018.

Project description:IntroductionConsensus is lacking regarding the optimal strategy to influence surgeons' behaviors to reduce low-value surgical care. Comprehensively describing the existing body of literature that seeks to intervene on surgeons' preoperative decision-making may aid in structuring future behavior change strategies.MethodsWe performed a scoping review using four databases (Medical Literature Analysis and Retrieval System Online, Embase, Web of Science, and Cumulated Index to Nursing and Allied Health Literature) for articles that tested the effect of behavioral-based interventions on any aspect of surgeons' decision-making in the preoperative setting. Abstracted data were characterized by summative descriptions and analyzed using the Tailored Implementation for Chronic Disease framework, mapping aspects of deimplementation strategies in the studies onto the determinant(s) that they altered. Data abstraction and mapping tools were piloted and iteratively revised before two researchers independently assessing studies and categorizing determinants, and then meeting to discuss their decisions.ResultsThere were 1460 articles identified from the initial search, with 17 full text articles ultimately included in the scoping review. Eight studies relied on a multidisciplinary preoperative conference to accomplish their aims, while five were multifaceted in their approach to deimplementation, and four studies used only a clinical decision support tool to accomplish their aims. Mapping determinants addressed in these studies onto the Tailored Implementation for Chronic Disease framework demonstrated that most strategies attempted to close knowledge gaps, leverage communication between providers, and broadcast institutional prioritization of change.ConclusionsThere is a small but growing field of implementation and deimplementation strategies in preoperative surgical decision-making, and different approaches may be equally effective in varied clinical contexts. Deliberate measurement and comparison of outcomes, as well as selection of control groups, are areas for improvement in future work.

Dataset Information

Detecting Critical Decision Points during Cognitive-Behavioral Therapy and Light Therapy for Winter Depression Nonremission and Recurrence.

Publications

Detecting Critical Decision Points during Cognitive-Behavioral Therapy and Light Therapy for Winter Depression Nonremission and Recurrence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets