Group-based trajectory modeling: a novel approach to examining symptom trajectories in acute bipolar episodes

Latent patterns of depression trajectory among adolescents during the covid-19 pandemic

Present study aimed to explore adolescent depression trajectory during the COVID-19 pandemic, and the impact of parental style on it. Five-wave data of adolescent sample in China mainland were collected, and the group-based trajectory modeling was used to examine the theory constructs. Findings showed that, during the COVID-19 pandemic, there are four distinct patterns of change in depression symptoms over time, namely, resistance (72.3 %), recovery (15.3 %), increasing (6.7 %), chronic (5.7 %). Differences about the impact of parental style and grade on depression trajectory were found. Findings contribute to the knowledge of the impact of the COVID-19 pandemic on depression trajectory among general population, and parental style and grade should be considered in adolescent psychological intervention in the pandemic.

Caractéristiques cliniques pour un meilleur choix thérapeutique dans la dépression bipolaire

Face aux difficultés persistantes pour traiter efficacement la dépression bipolaire et à face à la complexité des guidelines, il est indispensable d’identifier des prédicteurs de réponse aux traitements médicamenteux. Les dépressions bipolaires sont plus difficiles à traiter que les dépressions unipolaires en raison d’une moins bonne réponse aux traitements pharmacologiques et du risque de virage de l’humeur. Dans les recommandations internationales, on observe depuis quelques années une évolution qui donne une place plus importante aux thymorégulateurs classiques (lithium et valproate), puis une apparition des antipsychotiques et enfin une régression des antidépresseurs . Rien cependant n’indique dans ces recommandations comment orienter son choix, notamment en fonction de caractéristiques cliniques de la dépression. Des études cliniques avec une approche dimensionnelle ont montré que les dépressions bipolaires pouvaient être caractérisées par la réactivité émotionnelle mesurée par la Multidimensional Assessment of Thymic States Scale (MAThyS) , celle-ci pouvant constituer un marqueur d’intérêt de réponse aux traitements pharmacologiques. Dans cette perspective, l’utilisation de modèles statistiques originaux de trajectoire pour différencier des profils cliniques de réponses aux traitements a permis de montrer que l’hyperréactivité émotionnelle serait un facteur prédictif d’une bonne réponse aux antipsychotiques atypiques. La force de cette étude réalisée sur six semaines consécutives est de pouvoir observer la réponse aux traitements quel que soit l’épisode en cours sur un grand nombre de sujets, et l’une des limites était le faible effectif des patients sous antidépresseurs. Au vu de ces résultats prometteurs, nous prévoyons d’élargir l’échantillon et d‘utiliser la MAthyS pour suivre les réponses thérapeutiques.

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

The ability of early changes in motivation to predict later antidepressant treatment response

INTRODUCTION

Baseline values and early changes of emotional reactivity, cognitive speed, psychomotor function, motivation, and sensory perception have not been studied to any extent in unipolar depression, although they could help to characterize different dimensions of illness that are harder to capture by clinicians, give new insights on how patients improve, and offer new early clinical markers for later treatment response.

METHODS

About 1,565 adult outpatients with major depressive disorder receiving agomelatine completed the clinician-rated 16-item quick inventory of depressive symptoms, Clinical Global Impression, and Multidimensional Assessment of Thymic States (MAThyS) rating scales at inclusion, Week 2 and Week 6. The MAThyS includes a 20-item self-rated visual analog scale (from inhibition [0] to activation [10], with [5] representing the usual state) leading to five a priori dimensions (emotional reactivity, cognitive speed, psychomotor function, motivation, and sensory perception).

RESULTS

All MAThyS dimension scores increased from inclusion to Week 2 and from inclusion to Week 6 (P<0.001). Improvement was around 2 points (out of 10) for motivation, 1.5 points for psychomotor function, and 0.5 points for other dimensions. Motivation showed a trend to being more severely impaired at inclusion in future nonresponders (t=1.25, df=1,563, P=0.10). Its improvement at Week 2 was the most discriminating MAThyS dimension between future responders and nonresponders, and represents the best predictor of future response, with the highest area under the receptor operating characteristic curve (area under curve =0.616, 95% confidence interval [0.588-0.643], P<0.001). Finally, improvements in motivation correlated the most strongly with clinician-rated 16-item quick inventory of depressive symptoms improvement (r=-0.491, df=1,563, P<0.001).

CONCLUSION

Motivation had the most capacity for early improvement, the best predictive value for response, and the largest global margin of progress in depressed outpatients. Assessing the evolution of self-reported motivation over time in major depressive disorder could offer an interesting complementary approach to predict response.

Symptom trajectories and psychosis onset in a clinical high-risk cohort: the relevance of subthreshold thought disorder

BACKGROUND

Prior studies have implicated baseline positive and negative symptoms as predictors of psychosis onset among individuals at clinical high risk (CHR), but none have evaluated latent trajectories of symptoms over time. This study evaluated the dynamic evolution of symptoms leading to psychosis onset in a CHR cohort.

METHOD

100 CHR participants were assessed quarterly for up to 2.5 years. Latent trajectory analysis was used to identify patterns of symptom change. Logistic and proportional hazards models were employed to evaluate the predictive value for psychosis onset of baseline symptoms and symptom trajectories.

RESULTS

Transition rate to psychosis was 26%. Disorganized communication (i.e., subthreshold thought disorder) presented an increased hazard for psychosis onset, both at baseline (Hazard Ratio (95% CI)=1.4 (1.1-1.9)) and as a trajectory of high persistent disorganized communication (Hazard Ratio (95% CI)=2.2 (1.0-4.9)). Interval clinical data did not improve the predictive value of baseline symptoms for psychosis onset.

CONCLUSIONS

High baseline disorganized communication evident at ascertainment tended to persist and lead to psychosis onset, consistent with prior behavioral and speech analysis studies in similar cohorts. Remediation of language dysfunction therefore may be a candidate strategy for preventive intervention.

Distinctive trajectory groups of mental health functioning among assertive community treatment clients: an application of growth mixture modelling analysis

OBJECTIVE

Assertive community treatment (ACT) studies that have used conventional, statistical growth modelling methods have not examined different trajectories of outcomes or covariates that could influence different trajectories, even though heterogeneity in outcomes has been established in other research on severe mental illness. The purpose of our study was to examine the general trend in mental health functioning of ACT clients over a 2-year follow-up time period, to discover groups of ACT clients with distinctive longitudinal trajectories of mental health functioning, and to examine if some of the key sociodemographic and illness-related factors influence group membership.

METHOD

A 2-year, prospective, within-subjects study of 216 ACT clients within southern Ontario, collected functional outcome data at baseline and 12 and 24 months using the Colorado Client Assessment Record. Baseline covariates included sex, primary diagnosis, number of comorbidities, hospitalization history, and duration of illness. Growth mixture modelling (GMM) was used to examine trajectories.

RESULTS

Clinical staff assessments of ACT clients showed a statistically significant improvement in functioning and 84% achieved successful community tenure. GMM analysis identified 2 classes of ACT clients: class 1 (79.63% of clients) experienced lower and stable overall functioning, and class 2 (20.37%) showed a better baseline functioning score and improvement in the overall functioning over time. Class membership was predicted by the number of comorbidities and diagnosis.

CONCLUSIONS

Our study suggests general stability in overall functioning for the sampled ACT clients over 2 years, but significant heterogeneity in trajectories of functioning.

Mixed states in DSM-5: implications for clinical care, education, and research

The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) nomenclature for the co-occurrence of manic and depressive symptoms (mixed states) has been revised in the new DSM-5 version to accommodate a mixed categorical-dimensional concept. The new classification will capture subthreshold non-overlapping symptoms of the opposite pole using a "with mixed features" specifier to be applied to manic episodes in bipolar disorder I (BD I), hypomanic, and major depressive episodes experienced in BD I, BD II, bipolar disorder not otherwise specified, and major depressive disorder. The revision will have a substantial impact in several fields: epidemiology, diagnosis, treatment, research, education, and regulations. The new concept is data-driven and overcomes the problems derived from the extremely narrow definition in the DSM-IV-TR. However, it is unclear how clinicians will deal with the possibility of diagnosing major depression with mixed features and how this may impact the bipolar-unipolar dichotomy and diagnostic reliability. Clinical trials may also need to address treatment effects according to the presence or absence of mixed features. The medications that are effective in treating mixed episodes per the DSM-IV-TR definition may also be effective in treating mixed features per the DSM-5, but new studies are needed to demonstrate it.