Using network analysis for the prediction of treatment dropout in patients with mood and anxiety disorders: a methodological proof-of-concept study

There are large health, societal, and economic costs associated with attrition from psychological services. The recently emerged, innovative statistical tool of complex network analysis was used in the present proof-of-concept study to improve the prediction of attrition. Fifty-eight patients undergoing psychological treatment for mood or anxiety disorders were assessed using Ecological Momentary Assessments four times a day for two weeks before treatment (3,248 measurements). Multilevel vector autoregressive models were employed to compute dynamic symptom networks. Intake variables and network parameters (centrality measures) were used as predictors for dropout using machine-learning algorithms. Networks for patients differed significantly between completers and dropouts. Among intake variables, initial impairment and sex predicted dropout explaining 6% of the variance. The network analysis identified four additional predictors: Expected force of being excited, outstrength of experiencing social support, betweenness of feeling nervous, and instrength of being active. The final model with the two intake and four network variables explained 32% of variance in dropout and identified 47 out of 58 patients correctly. The findings indicate that patients’ dynamic network structures may improve the prediction of dropout. When implemented in routine care, such prediction models could identify patients at risk for attrition and inform personalized treatment recommendations.This work was supported by the German Research Foundation National Institute (DFG, Grant nos. LU 660/8-1 and LU 660/10-1 to W. Lutz). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript. The corresponding author had access to all data in the study and had final responsibility for the decision to submit for publication. Dr. Hofmann receives financial support from the Alexander von Humboldt Foundation (as part of the Humboldt Prize), NIH/NCCIH (R01AT007257), NIH/NIMH (R01MH099021, U01MH108168), and the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative. (LU 660/8-1 - German Research Foundation National Institute (DFG); LU 660/10-1 - German Research Foundation National Institute (DFG); Alexander von Humboldt Foundation; R01AT007257 - NIH/NCCIH; R01MH099021 - NIH/NIMH; U01MH108168 - NIH/NIMH; James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative)Accepted manuscrip

ORC-13661 protects sensory hair cells from aminoglycoside and cisplatin ototoxicity

Aminoglycoside (AG) antibiotics are widely used to prevent life-threatening infections, and cisplatin is used in the treatment of various cancers, but both are ototoxic and result in loss of sensory hair cells from the inner ear. ORC-13661 is a new drug that was derived from PROTO-1, a compound first identified as protective in a large-scale screen utilizing hair cells in the lateral line organs of zebrafish larvae. Here, we demonstrate, in zebrafish larvae and in mouse cochlear cultures, that ORC-13661 provides robust protection of hair cells against both ototoxins, the AGs and cisplatin. ORC-13661 also prevents both hearing loss in a dose-dependent manner in rats treated with amikacin and the loading of neomycin-Texas Red into lateral line hair cells. In addition, patch-clamp recordings in mouse cochlear cultures reveal that ORC-13661 is a high-affinity permeant blocker of the mechanoelectrical transducer (MET) channel in outer hair cells, suggesting that it may reduce the toxicity of AGs by directly competing for entry at the level of the MET channel and of cisplatin by a MET-dependent mechanism. ORC-13661 is therefore a promising and versatile protectant that reversibly blocks the hair cell MET channel and operates across multiple species and toxins

An in vivo Biomarker to Characterize Ototoxic Compounds and Novel Protective Therapeutics

There are no approved therapeutics for the prevention of hearing loss and vestibular dysfunction from drugs like aminoglycoside antibiotics. While the mechanisms underlying aminoglycoside ototoxicity remain unresolved, there is considerable evidence that aminoglycosides enter inner ear mechanosensory hair cells through the mechanoelectrical transduction (MET) channel. Inhibition of MET-dependent uptake with small molecules or modified aminoglycosides is a promising otoprotective strategy. To better characterize mammalian ototoxicity and aid in the translation of emerging therapeutics, a biomarker is needed. In the present study we propose that neonatal mice systemically injected with the aminoglycosides G418 conjugated to Texas Red (G418-TR) can be used as a histologic biomarker to characterize in vivo aminoglycoside toxicity. We demonstrate that postnatal day 5 mice, like older mice with functional hearing, show uptake and retention of G418-TR in cochlear hair cells following systemic injection. When we compare G418-TR uptake in other tissues, we find that kidney proximal tubule cells show similar retention. Using ORC-13661, an investigational hearing protection drug, we demonstrate in vivo inhibition of aminoglycoside uptake in mammalian hair cells. This work establishes how systemically administered fluorescently labeled ototoxins in the neonatal mouse can reveal important details about ototoxic drugs and protective therapeutics

Improving the Efficiency of Psychological Treatment using Outcome Feedback Technology

Aims: This study evaluated the impact of applying computerized outcome feedback (OF) technology in a stepped care psychological service offering low and high intensity therapies for depression and anxiety. Methods: A group of therapists were trained to use OF based on routine outcome monitoring using depression (PHQ-9) and anxiety (GAD-7) measures. Therapists regularly reviewed expected treatment response graphs with patients and discussed cases that were “not on track” in clinical supervision. Clinical outcomes data were collected for all patients treated by this group (N = 594), six months before (controls = 349) and six months after the OF training (OF cases = 245). Symptom reductions in PHQ-9 and GAD-7 were compared between controls and OF cases using longitudinal multilevel modelling. Treatment duration and costs were compared using MANOVA. Qualitative interviews with therapists (N = 15) and patients (N = 6) were interpreted using thematic analysis. Results: OF technology was generally acceptable and feasible to integrate in routine practice. No significant between-group differences were found in post-treatment PHQ-9 or GAD-7 measures. However, OF cases had significantly lower average duration and cost of treatment compared to controls. Conclusions: After adopting OF into their practice, this group of therapists attained similar clinical outcomes but within a shorter space of time and at a reduced average cost per treatment episode. We conclude that OF can improve the efficiency of stepped care

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology:The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual’s emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient’s ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation

Do therapist effects really impact estimates of within-patient mechanisms of change? A Monte Carlo simulation study

Objective:Existing evidence highlights the importance of modeling differential therapist effectiveness when studying psychotherapy outcome. However, no study to date examined whether this assertion applies to the study of within-patient effects in mechanisms of change. The study investigated whether therapist effects should be modeled when studying mechanisms of change on a within-patient level. Methods:We conducted a Monte Carlo simulation study, varying patient- and therapist level sample sizes, degree of therapist-level nesting (intra-class correlation), balanced vs. unbalanced assignment of patients to therapists, and fixed vs random within-patient coefficients. We estimated all models using longitudinal multilevel and structural equation models that ignored (2-level model) or modeled therapist effects (3-level model). Results:Across all conditions, 2-level models performed equally or were superior to 3-level models. Within-patient coefficients were unbiased in both 2- and 3-level models. In 3-level models, standard errors were biased when number of therapists was small, and this bias increased in unbalanced designs. Ignoring random slopes led to biased standard errors when slope variance was large; but 2-level models still outperformed 3-level models. Conclusions:In contrast to treatment outcome research, when studying mechanisms of change on a within-patient level, modeling therapist effects may even reduce model performance and increase bias.Funding Agencies|National Institute of Mental HealthUnited States Department of Health &amp; Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [T32 MH01913]</p

The Complex Interplay of Pain, Depression, and Anxiety Symptoms in Patients with Chronic Pain

OBJECTIVES: This study aimed to analyze the associations among depressive/anxiety and pain symptoms in patients diagnosed with chronic pain. METHODS: Four hundred and fifty-four inpatients who were consecutively admitted in a multimodal 3-weeks treatment in a tertiary psychosomatic university clinic completed 25 items from the Brief Pain Inventory and the Hospital Anxiety and Depression Scale at baseline and after treatment termination. Associations among symptoms were explored by network analyses using the graphical least absolute shrinkage and selection operator to estimate their partial correlations, while Extended Bayesian Information Criterion was used to select the best network solution for the data. We explored symptoms' centrality and expected influence within the network as well as the minimum spanning tree for the network. RESULTS: Besides expected associations within depressive/anxiety and pain symptoms, the estimated network showed several local associations between depressive and pain interference symptoms. The lacks of being cheerful and of laughing are two of the depressive symptoms that showed the greatest associations with pain interference and a strong centrality within the network. Sleep problems were both associated with anxiety/depressive symptoms and pain intensity symptoms. Although at post-treatment, most of the symptoms showed a significant decrease, the strength of the associations between the symptoms within the network were significantly higher than at baseline. DISCUSSION: The results support focusing psychosocial interventions in chronic pain treatment not only on reducing pain, anxiety and sleep symptoms but also on enhancing positive affect. Future research is needed to replicate these findings using repeated within-person measures designs

Dynamic norms drive sustainable consumption : Norm-based nudging helps café customers to avoid disposable to-go-cups

Excess use of disposable to-go-cups constitutes a severe sustainability threat. Behavioral economics and economic psychology suggest various antidotes. In the present paper, we report two studies – a large-scale intervention field study and an experiment – that constitute independent, pre-registered, and open replication attempts of a recently-introduced intervention procedure: dynamic social norms. We tested whether a dynamic norm, along the lines of “more and more customers are switching from to-go-cups to a sustainable alternative. Be part of this movement and choose a reusable mug” – can help café customers to avoid disposable to-go-cups. Data from a fourteen-week intervention experiment with a total of 23,946 hot beverages sold – 18,019 in disposable cups and 5927 in reusable mugs – suggest that a dynamic-norm intervention for sustainable consumption helps customers avoid disposable cups and increases their use of reusable alternatives by 17.3% (or 4.1 percentage points). A follow-up online experiment corroborates this pattern and shows advantageous effects of a dynamic norm relative to a no-norm control condition, a static norm, an injunctive norm, and a combination of static-and-injunctive norm. In light of inconsistent and, at times, failed or even reversed replication results for seminal social norms studies, the present pre-registered studies indicate that dynamic norms are an effective means to facilitate sustainable behavior. We discuss scientific and applied implications and avenues for future research

The working alliance in manualized CBT for generalized anxiety disorder Does it lead to change and does the effect vary depending on manual implementation flexibility?

Objective: The investigation of session-to-session effects of working alliance on symptoms and coping experiences in patients diagnosed with GAD. Additionally, investigating these effects dependent on whether therapists are primed to work with patients strength (resource priming) or to adhere to the treatment manual (adherence priming). Method: Data was drawn from a randomized controlled trial in which 57 patient were randomly assigned to either the resource priming condition or the adherence priming condition. Within- and between patient associations were disentangled using dynamic structural equation modeling. Results: The total score of the working alliance as well as all its overlapping components (i.e., goal agreement, task consensus, bond) showed significant within-patient effects on next session coping experiences. More specifically, better alliance scores in one session were followed by more coping experiences in the subsequent session. With regard to anxiety symptoms, an association was found only with the working alliance total score as well as for the bonds component, but not for the goals and task components of the working alliance. The priming condition (resource priming vs adherence priming) had no influence on the within-patient alliance-outcome association. Between-patient alliance associations were only present with coping experiences, but not with anxiety symptoms. Conclusion: The findings provide further empirical evidence for the hypothesis that the working alliance may be a robust facilitative factor for change in CBT treatments for GAD which evolves irrespective of the strictness with which therapists adhere to the treatment manual.</p