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Background: There is a growing interest in developing scalable interventions, including internet-based cognitive behavioral therapy (iCBT), to meet the increasing demand for mental health services. Given the growth in diversity worldwide, it is essential that the clinical trials of iCBT for depression include diverse samples or, at least, report information on the race, ethnicity, or other background indicators of their samples. Unfortunately, the field lacks data on how well diversity is currently reported and represented in the iCBT literature., Objective: Thus, the main objective of this systematic review was to examine the overall reporting of racial and ethnic identities in published clinical trials of iCBT for depression. We also aimed to review the representation of specific racial and ethnic minoritized groups and the inclusion of alternative background indicators such as migration status or country of residence., Methods: Studies were included if they were randomized controlled trials in which iCBT was compared to a waiting list, care-as-usual, active control, or another iCBT. The included papers also had to have a focus on acute treatment (eg, 4 weeks to 6 months) of depression, be delivered via the internet on a website or a smartphone app and use guided or unguided self-help. Studies were initially identified from the METAPSY database (n=59) and then extended to include papers up to 2022, with papers retrieved from Embase, PubMed, PsycINFO, and Cochrane (n=3). Risk of bias assessment suggested that reported studies had at least some risk of bias due to use of self-report outcome measures., Results: A total of 62 iCBT randomized controlled trials representing 17,210 participants are summarized in this study. Out of those 62 papers, only 17 (27%) of the trials reported race, and only 12 (19%) reported ethnicity. Reporting outside of the United States was very poor, with the United States accounting for 15 (88%) out of 17 of studies that reported race and 9 (75%) out of 12 for ethnicity. Out of 3,623 participants whose race was reported in the systematic review, the racial category reported the most was White (n=2716, 74.9%), followed by Asian (n=209, 5.8%) and Black (n=274, 7.6%). Furthermore, only 25 (54%) out of the 46 papers conducted outside of the United States reported other background demographics., Conclusions: It is important to note that the underreporting observed in this study does not necessarily indicate an underrepresentation in the actual study population. However, these findings highlight the poor reporting of race and ethnicity in iCBT trials for depression found in the literature. This lack of diversity reporting may have significant implications for the scalability of these interventions., (©Robinson De Jesús-Romero, Amani R Holder-Dixon, John F Buss, Lorenzo Lorenzo-Luaces. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 01.02.2024.)

Depression is a leading cause of disability worldwide, but is often underdiagnosed and undertreated. Cognitive behavioural therapy holds that individuals with depression exhibit distorted modes of thinking, that is, cognitive distortions, that can negatively affect their emotions and motivation. Here, we show that the language of individuals with a self-reported diagnosis of depression on social media is characterized by higher levels of distorted thinking compared with a random sample. This effect is specific to the distorted nature of the expression and cannot be explained by the presence of specific topics, sentiment or first-person pronouns. This study identifies online language patterns that are indicative of depression-related distorted thinking. We caution that any future applications of this research should carefully consider ethical and data privacy issues.

Objective: Optimizing treatment selection may improve treatment outcomes in depression. A promising approach is the Personalized Advantage Index (PAI), which predicts the optimal treatment for a given individual. To determine the generalizability of the PAI, models needs to be externally validated, which has rarely been done. Method: PAI models were developed within each of two independent trials, with substantial between-study differences, that both compared CBT and IPT for depression (STEPd: n  = 151 and FreqMech: n  = 200). Subsequently, both PAI models were tested in the other dataset. Results: In the STEPd study, post-treatment depression was significantly different between individuals assigned to their PAI-indicated treatment versus those assigned to their non-indicated treatment ( d  = .57). In the FreqMech study, post-treatment depression was not significantly different between patients receiving their indicated treatment versus those receiving their non-indicated treatment ( d  = .20). Cross-trial predictions indicated that post-treatment depression was not significantly different between those receiving their indicated treatment and those receiving their non-indicated treatment ( d  = .16 and d  = .27). Sensitivity analyses indicated that cross-trial prediction based on only overlapping variables didn't improve the results. Conclusion: External validation of the PAI has modest results and emphasizes between-study differences and many other challenges.

Human sleep/wake cycles follow a stable circadian rhythm associated with hormonal, emotional, and cognitive changes. Changes of this cycle are implicated in many mental health concerns. In fact, the bidirectional relation between major depressive disorder and sleep has been well-documented. Despite a clear link between sleep disturbances and subsequent disturbances in mood, it is difficult to determine from self-reported data which specific changes of the sleep/wake cycle play the most important role in this association. Here we observe marked changes of activity cycles in millions of twitter posts of 688 subjects who explicitly stated in unequivocal terms that they had received a (clinical) diagnosis of depression as compared to the activity cycles of a large control group (n = 8791). Rather than a phase-shift, as reported in other work, we find significant changes of activity levels in the evening and before dawn. Compared to the control group, depressed subjects were significantly more active from 7 PM to midnight and less active from 3 to 6 AM. Content analysis of tweets revealed a steady rise in rumination and emotional content from midnight to dawn among depressed individuals. These results suggest that diagnosis and treatment of depression may focus on modifying the timing of activity, reducing rumination, and decreasing social media use at specific hours of the day.

Background: Self-guided internet-based cognitive behavioral therapies (iCBTs) for depressive symptoms may substantially increase accessibility to mental health treatment. Despite this, questions remain as to the generalizability of the research on self-guided iCBT., Objective: We sought to describe the clinical entry criteria used in studies of self-guided iCBT, explore the criteria's effects on study outcomes, and compare the frequency of use of these criteria with their use in studies of face-to-face psychotherapy and antidepressant medications. We hypothesized that self-guided iCBT studies would use more stringent criteria that would bias the sample toward those with a less complex clinical profile, thus inflating treatment outcomes., Methods: We updated a recently published meta-analysis by conducting a systematic literature search in PubMed, MEDLINE, PsycINFO, and EMBASE. We conducted a meta-regression analysis to test the effect of the different commonly used psychiatric entry criteria on the treatment-control differences. We also compared the frequency with which exclusion criteria were used in the self-guided iCBT studies versus studies of face-to-face psychotherapy and antidepressants from a recently published review., Results: Our search yielded 5 additional studies, which we added to the 16 studies identified by Karyotaki and colleagues in 2017. Few self-guided iCBT studies excluded patients with severe depressive symptoms (6/21, 29%), but self-guided iCBT studies were more likely than antidepressant (14/170, 8.2%) studies to use this criterion. However, self-guided iCBT studies did not use this criterion more frequently than face-to-face psychotherapy studies (6/16, 38%). Beyond this, we found no evidence that self-guided iCBTs used more stringent entry criteria. Strong evidence suggested that they were actually less likely to use most entry criteria, especially exclusions on the basis of substance use or personality pathology. None of the entry criteria used had an effect on outcomes., Conclusions: A conservative interpretation of our findings is that the patient population sampled in the literature on self-guided iCBT is relatively comparable with that of studies of antidepressants or face-to-face psychotherapy. Alternatively, studies of unguided cognitive behavioral therapy may sample from a more heterogeneous and representative patient population. Until evidence emerges to suggest otherwise, the patient population sampled in self-guided iCBT studies cannot be considered as less complex than the patient population from face-to-face psychotherapy or antidepressant studies., (©Lorenzo Lorenzo-Luaces, Emily Johns, John R Keefe. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 09.11.2018.)

Prior studies have suggested that the association between the alliance and depression improvement varies as a function of prior history of depression. We sought to replicate these findings and extend them to short-term psychodynamic supportive psychotherapy (SPSP) in a sample of patients who were randomized to one of these treatments and were administered the Helping Alliance Questionnaire (N=282) at Week 5 of treatment. Overall, the alliance was a predictor of symptom change (d=0.33). In SPSP, the alliance was a modest but robust predictor of change, irrespective of prior episodes (d=0.25-0.33). By contrast, in CBT, the effects of the alliance on symptom change were large for patients with 0 prior episodes (d=0.86), moderate for those with 1 prior episode (d=0.49), and small for those with 2+ prior episodes (d=0.12). These findings suggest a complex interaction between patient features and common vs. specific therapy processes. In CBT, the alliance relates to change for patients with less recurrent depression whereas other CBT-specific processes may account for change for patients with more recurrent depression., (Copyright © 2016. Published by Elsevier Ltd.)

Background: Prognostic indices (PIs) combining variables to predict future depression risk may help guide the selection of treatments that differ in intensity. We develop a PI and show its promise in guiding treatment decisions between treatment as usual (TAU), treatment starting with a low-intensity treatment (brief therapy (BT)), or treatment starting with a high-intensity treatment intervention (cognitive-behavioral therapy (CBT))., Methods: We utilized data from depressed patients (N=622) who participated in a randomized comparison of TAU, BT, and CBT in which no statistically significant differences in the primary outcomes emerged between the three treatments. We developed a PI by predicting depression risk at follow-up using a LASSO-style bootstrap variable selection procedure. We then examined between-treatment differences in outcome as a function of the PI., Results: Unemployment, depression severity, hostility, sleep problems, and lower positive emotionality at baseline predicted a lower likelihood of recovery across treatments. The PI incorporating these variables produced a fair classification accuracy (c=0.73). Among patients with a high PI (75% percent of the sample), recovery rates were high and did not differ between treatments (79-86%). Among the patients with the poorest prognosis, recovery rates were substantially higher in the CBT condition (60%) than in TAU (39%) or BT (44%)., Limitations: No information on additional treatment sought. Prospective tests needed., Conclusion: Replicable PIs may aid treatment selection and help streamline stepped models of care. Differences between treatments for depression that differ in intensity may only emerge for patients with the poorest prognosis., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background and Objectives: Most outpatient treatment for depression is delivered by primary care physicians (PCPs), yet little is known about which patient variables affect PCPs' selection of high-intensity interventions, namely antidepressant medications or psychotherapy, as opposed to less-intensive treatment regimens (eg, watchful waiting, exercise). Our objective was to ascertain whether the patient's symptom severity, presenting psychosocial stress, and lifestyle habits influenced treatment recommendations., Methods: Forty-two PCPs from six Northeastern US primary care practices provided recommendations in response to vignettes depicting patients with major depressive disorder who varied in symptom severity, psychosocial stressors, and lifestyle habits., Results: Low-intensity-only interventions were recommended less than 25% of the time. Lower symptom severity and higher psychosocial stressors were associated with a greater likelihood of "low-intensity interventions only" recommendations. Less-intensive treatments were rarely recommended without more intensive treatments when the vignettes featured severe depression, whereas they were recommended 39% of the time with vignettes featuring mild/moderate symptoms. In response to the mild/moderate vignettes, the presence of psychosocial stressors led to a decreased likelihood of low-intensity-only recommendations., Conclusions: Although vignettes depicting depressed patients with mild/moderate symptoms were more likely to elicit low-intensity treatment recommendations, the frequency was still low. Given the evidence that antidepressants and psychotherapy for mild/moderate depression may be no more effective, and likely less cost-effective, than low-intensity treatments, the findings suggest a need to disseminate knowledge of less intensive treatment options to primary care physicians.

Background: Internalizing, externalizing, and somatoform disorders are the most common and disabling forms of psychopathology. Our understanding of these clinical problems is limited by a reliance on self-report along with research using small samples. Social media has emerged as an exciting channel for collecting a large sample of longitudinal data from individuals to study psychopathology. Objective: This study reported the results of 2 large ongoing studies in which we collected data from Twitter and self-reported clinical screening scales, the Studies of Online Cohorts for Internalizing Symptoms and Language (SOCIAL) I and II. Methods: The participants were a sample of Twitter-using adults (SOCIAL I: N=1123) targeted to be nationally representative in terms of age, sex assigned at birth, race, and ethnicity, as well as a sample of college students in the Midwest (SOCIAL II: N=1988), of which 61.78% (1228/1988) were Twitter users. For all participants who were Twitter users, we asked for access to their Twitter handle, which we analyzed using Botometer, which rates the likelihood of an account belonging to a bot. We divided participants into 4 groups: Twitter users who did not give us their handle or gave us invalid handles (invalid), those who denied being Twitter users (no Twitter, only available for SOCIAL II), Twitter users who gave their handles but whose accounts had high bot scores (bot-like), and Twitter users who provided their handles and had low bot scores (valid). We explored whether there were significant differences among these groups in terms of their sociodemographic features, clinical symptoms, and aspects of social media use (ie, platforms used and time). Results: In SOCIAL I, most individuals were classified as valid (580/1123, 51.65%), and a few were deemed bot-like (190/1123, 16.91%). A total of 31.43% (353/1123) gave no handle or gave an invalid handle (eg, entered "N/A"). In SOCIAL II, many individuals were not Twitter users (760/1988, 38.23%). Of the Twitter users in SOCIAL II (1228/1988, 61.78%), most were classified as either invalid (515/1228, 41.94%) or valid (484/1228, 39.41%), with a smaller fraction deemed bot-like (229/1228, 18.65%). Participants reported high rates of mental health diagnoses as well as high levels of symptoms, especially in SOCIAL II. In general, the differences between individuals who provided or did not provide their social media handles were small and not statistically significant. Conclusions: Triangulating passively acquired social media data and self-reported questionnaires offers new possibilities for large-scale assessment and evaluation of vulnerability to mental disorders. The propensity of participants to share social media handles is likely not a source of sample bias in subsequent social media analytics. [ABSTRACT FROM AUTHOR]

Background: Common mental disorders, including depression and anxiety, are leading causes of disability worldwide. Digital mental health interventions, such as web-based self-help and other low-intensity treatments (LITs) that are not digital (eg, bibliotherapy), have the potential to reach many individuals by circumventing common barriers present in traditional mental health care. It is unclear how often LITs are used in clinical practice, or whether providers would be interested in their use for treatment waiting lists. Objective: The aims of this study were to (1) describe current practices for treatment waiting lists, (2) describe providers’ attitudes toward digital and nondigital LITs for patients on a waiting list, and (3) explore providers’ willingness to use digital and nondigital LITs and their decisions to learn about them. Methods: We surveyed 141 practicing mental health care providers (eg, therapists and psychologists) and provided an opportunity for them to learn about LITs. Results: Most participants reported keeping a waiting list. Few participants reported currently recommending digital or nondigital LITs, though most were willing to use at least one for patients on their waiting list. Attitudes toward digital and nondigital LITs were neutral to positive. Guided digital and nondigital LITs were generally perceived to be more effective but less accessible, and unguided interventions were perceived to be less effective but more accessible. Most participants selected to access additional information on LITs, with the most popular being web-based self-help. Conclusions: Results suggest providers are currently not recommending LITs for patients on treatment waiting lists but would be willing to recommend them. Future work should explore barriers and facilitators to implementing digital and nondigital LITs for patients on treatment waiting lists. [ABSTRACT FROM AUTHOR]

In this conceptual paper, we outline the many challenges on the road to personalized psychotherapy, using the example of cognitive behavior therapy (CBT) for depression. To optimize psychotherapy for the individual patient, we need to find out how therapy works (identification of mechanisms of change) and for whom it works (identification of moderators). To date, psychotherapy research has not resulted in compelling evidence for or against common or specific factors that have been proposed as mechanisms of change. Our central proposition is that we need to combine the "how does it work?"-question with the "for whom does it work?"-question in order to advance the field. We introduce the personalized causal pathway hypothesis that emphasizes the links and distinction between individual patient differences, therapeutic procedures and therapy processes as a paradigm to facilitate und understand the concept of personalized psychotherapy. We review the mechanism of change literature for CBT for depression to see what we have learned so far, and describe preliminary observational evidence supporting the personalized causal pathway hypothesis. We then propose a research agenda to push the ball forward: exploratory studies into the links between individual differences, therapeutic procedures, therapy processes and outcome that constitute a potential causal pathway, making use of experience sampling, network theory, observer ratings of therapy sessions, and moderated mediation analysis; testing and isolation of CBT procedures in experiments; and testing identified causal pathways of change as part of a personalized CBT package against regular CBT, in order to advance the application of personalized psychotherapy. [ABSTRACT FROM AUTHOR]

Introduction: Researchers have proposed that predicting who is a likely placebo responder may help guide treatment allocations to treatment regimens that differ in intensity. Methods: We used data from the Treatment of Adolescent Depression Study (TADS) in which adolescents (n = 439) were randomized 1:1:1:1 to placebo, cognitive-behavioral therapy (CBT), medications (MEDs), or their combination (COMB). We developed a prognostic index (PI) in the placebo group to predict self-reported (RADS) and observer-rated (CDRS) depression outcomes using elastic net regularization. We explored whether the PIs moderated outcomes in the treatment conditions. Results: PI-CDRS was predicted by multiple variables but it did not moderate outcomes. PI-RADS was predicted by baseline severity, age, sleep problems, expectations, maternal depression, and the action stage of change. It moderated outcomes such that there were treatment differences for less placebo-responsive patients. For participants prone to placebo response, type of treatment had no statistically significant impact on outcomes. Baseline depression severity accounted for this effect: treatment differences were small and non-significant for patients with milder depression but larger in more severely depressed patients. Discussion: Future work should investigate whether multiple variable explain outcomes beyond severity as well as complex interactions between severity and other variables. [ABSTRACT FROM AUTHOR]

Although effective treatments for common mental health problems are available, individual responses to treatments are difficult to predict. Treatment efficacy could be optimized by targeting interventions using individual predictions of treatment outcomes. The aim of this study was to develop a prediction algorithm using data from one of the largest randomized controlled trials on psychological interventions for common mental health problems. This is a secondary analysis of the Enhancing Recovery in Coronary Heart Disease study investigating the effectiveness of cognitive behavioral therapy (CBT) and care as usual (CAU) for depression and low perceived social support following acute myocardial infarction. 2481 participants were randomly assigned to CBT and CAU. Baseline social-demographics, depression characteristics, comorbid symptoms, and stress and adversity measures were used to build an algorithm predicting post-treatment depression severity using elastic net regularization. Performance and generalizability of this algorithm were determined in a hold-out sample (n = 1203). Treatment matching based on predictions in the hold-out sample resulted in inconsistent and small effects (d = 0.15), that were more pronounced for individuals matched to CBT (d = 0.22). We identified a small subgroup of individuals for which CBT did not appear more efficacious than CAU. Limitations are a poorly defined CAU condition, a low-severity sample, specific exclusion criteria and unavailability of certain baseline variables. Small matching effects are likely a realistic representation of the performance and generalizability of multivariable prediction algorithms based on clinical measures. Results indicate that future work and new approaches are needed. • Machine learning predictions were made for targeted psychological interventions. • Predictions relied on self-report and clinical observation. • Predictions were developed and tested in a large dataset. • Predictions resulted in small matching effects. • Improvements are needed to guarantee clinical relevance of these prediction models. [ABSTRACT FROM AUTHOR]

Identifying differences in the clinical response to specific interventions is an important challenge in the field of Clinical Psychology. This is especially true in the treatment of depression where many treatments appear to have comparable outcomes. In a controlled trial, we compared a positive psychology group intervention, the Integrative Positive Psychological Intervention for Depression (IPPI-D; n = 62) to a cognitive-behavioral therapy group intervention (CBT; n = 66) for depression. No statistically or clinically-significant differences between the treatments were found, but a slight advantage was observed, on average, for IPPI-D. The aim of the present study was to identify and combine moderators of the differential efficacy of these two psychological interventions for clinical depression. For this purpose, a secondary analysis using the Personalized Advantage Index (PAI) was performed to identify the intervention predicted to produce the better outcome for each patient. Six of the 21 potential moderators were found to predict differential efficacy between the treatments. IPPI-D was predicted to be the optimal treatment for 73% of the sample. Baseline features that characterized these individuals were: mental and physical comorbidity, prior antidepressant medication, higher levels of negative thoughts, and higher personal growth. The 27% who were predicted to achieve better outcomes in CBT than in IPPI-D tended to have these baseline features: no comorbidities, no prior antidepressant medication, lower levels of negative thoughts, and lower personal growth. [ABSTRACT FROM AUTHOR]

Background: The generalizability of findings from studies exploring the efficacy of psychotherapy and antidepressants has been called into question in part because studies exclude many patients. Despite this, the frequency with which psychotherapy and antidepressant studies use specific inclusion and exclusion criteria has never been compared. We explored the exclusion criteria used in psychotherapy and pharmacotherapy studies from 1995 to 2014.Method: Systematic literature searches were conducted in PubMed, Medline, PsycINFO, and Embase of published randomized controlled trials (RCTs) of the treatment of major depressive disorder (MDD) in adults with either antidepressants (vs. placebos) or psychotherapy (vs. placebos, treatments as usual, or other controls).Results: Most psychotherapy (81%) and antidepressant (100%) trials excluded patients with milder symptoms as well as patients with elevated suicidal risk (56-75%), psychotic symptoms (84-88%), or substance misuse (75-81%). Psychotherapy studies were less likely to exclude patients on the basis of brief episode duration (0% vs. 48%) and co-morbid Axis I disorders (6% vs. 27%). However, psychotherapy studies excluded patients with more severe symptoms more frequently (38%) than antidepressant studies (8%).Conclusions: Overall, psychotherapy studies appear somewhat more inclusive than antidepressant studies. On average, antidepressant studies appear to target patients with more chronic and severe, as well as more purely depressive presentations. [ABSTRACT FROM AUTHOR]

Objectives We examined differences in treatment outcome between Diagnostic and Statistical Manual Fourth Edition (DSM-IV)-defined rapid cycling and average lifetime-defined rapid cycling in subjects with bipolar II disorder. We hypothesized that, compared with the DSM-IV definition, the average lifetime definition of rapid cycling may better identify subjects with a history of more mood lability and a greater likelihood of hypomanic symptom induction during long-term treatment. Methods Subjects ≥18 years old with a bipolar II major depressive episode (n=129) were categorized into DSM-IV- and average lifetime-defined rapid cycling and prospectively treated with either venlafaxine or lithium monotherapy for 12 weeks. Responders (n=59) received continuation monotherapy for six additional months. Results These exploratory analyses found moderate agreement between the two rapid-cycling definitions (κ=0.56). The lifetime definition captured subjects with more chronic courses of bipolar II depression, whereas the DSM-IV definition captured subjects with more acute symptoms of hypomania. There was no difference between rapid-cycling definitions with respect to the response to acute venlafaxine or lithium monotherapy. However, the lifetime definition was slightly superior to the DSM-IV definition in identifying subjects who went on to experience hypomanic symptoms during continuation therapy. Conclusions Although sample sizes were limited, the findings suggest that the lifetime definition of rapid cycling may identify individuals with a chronic rapid-cycling course and may also be slightly superior to the DSM-IV definition in identifying individuals with hypomania during relapse-prevention therapy. These findings are preliminary in nature and need replication in larger, prospective, bipolar II studies. [ABSTRACT FROM AUTHOR]

Since the introduction of Beck's cognitive theory of emotional disorders, and their treatment with psychotherapy, cognitive-behavioral approaches have become the most extensively researched psychological treatment for a wide variety of disorders. Despite this, the relative contribution of cognitive to behavioral approaches to treatment are poorly understood and the mechanistic role of cognitive change in therapy is widely debated. We critically review this literature, focusing on the mechanistic role of cognitive change across cognitive and behavioral therapies for depressive and anxiety disorders. [ABSTRACT FROM AUTHOR]

Objective This study examined the relationship between the number of prior antidepressant treatment trials and step-wise increase in pharmacodynamic tolerance (or progressive loss of effectiveness) in subjects with bipolar II depression. Methods Subjects ≥18 years old with bipolar II depression (n=129) were randomized to double-blind venlafaxine or lithium carbonate monotherapy for 12 weeks. Responders (n=59) received continuation monotherapy for six additional months. Results After controlling for baseline covariates of prior medications, there was a 25% reduction in the likelihood of response to treatment with each increase in the number of prior antidepressant trials (odds ratio [ OR]=0.75, unstandardized coefficient [B]=−0.29, standard error ( SE)=0.12; χ2=5.70, P<.02], as well as a 32% reduction in the likelihood of remission with each prior antidepressant trial ( OR=0.68, B=−0.39, SE=0.13; χ2=9.71, P=.002). This step-wise increase in pharmacodynamic tolerance occurred in both treatment conditions. Prior selective serotonin reuptake inhibitor ( SSRI) therapy was specifically associated with a step-wise increase in tolerance, whereas other prior antidepressants or mood stabilizers were not associated with pharmacodynamic tolerance. Neither the number of prior antidepressants, nor the number of prior SSRIs, or mood stabilizers, were associated with an increase in relapse during continuation therapy. Conclusions The odds of responding or remitting during venlafaxine or lithium monotherapy were reduced by 25% and 32%, respectively, with each increase in the number of prior antidepressant treatment trials. There was no relationship between prior antidepressant exposure and depressive relapse during continuation therapy of bipolar II disorder. [ABSTRACT FROM AUTHOR]

Objective: Little is known about the variability of the alliance-outcome correlation across identifiable client subsets. This question was explored in a sample of 60 clients receiving cognitive therapy for depression, from which an overall correlation of .23 was observed between alliance ratings and subsequent symptom change. Method: We examined interactions between the observer-rated version of the Working Alliance Inventory-Short Observer-Rated version (WAI-O; Tracey & Kokotovic, 1989) and client demographics, features of depression, personality, and other clinical features in predicting subsequent symptom change. Results: After correcting for multiple comparisons, interactions between the WAI-0 and the number of prior depressive episodes, as well as the severity of baseline anxiety symptoms, were significant predictors of symptom change. When both interactions were controlled for, number of prior depressive episodes emerged as a statistically significant moderator. The alliance predicted outcome in the subgroup of clients with 0-2 prior episodes (r = .52), but not in those with 3 or more prior episodes (r = -.02). These findings were obtained despite similar univariate distributions on the alliance and symptom change in the 2 subgroups. Discussion: Differences that were observed in the predictive relation of alliance to outcome as a function of number of prior episodes suggest that different therapy processes may account for change in these subgroups. If the pattern observed in the present study is replicated, it would suggest that the alliance-outcome association has been both under-and overestimated. [ABSTRACT FROM AUTHOR]

It has been reported that approximately one of out of every ten Puerto Rican adolescents has serious suicidal ideation. In this study we evaluated the predictive value of some cognitive, behavioral, and affective variables to explain suicidal ideation from a cognitive-behavioral perspective. The sample was comprised of 179 adolescents (ages 13-18) who filled self-report surveys. Approximately 17% of the sample reported thinking about suicide 'sometimes' or 'very frequently'. These adolescents were more depressed, had more dysfunctional thoughts, lower self-concept, and less healthy coping strategies than those who did not report suicidal ideation. These variables also predicted suicidal ideation. These results evidence the large prevalence of suicidal ideation in Puerto Rican adolescents. [ABSTRACT FROM AUTHOR]

• Psychometric properties of the Sydney Melancholia Prototype Index (SMPI) are unexplored. • We did not find evidence of unidimensionality. • The SMPI measures at least five different constructs. Parker and colleagues developed the Sydney Melancholia Prototype Index (SMPI), a 24-item measure to assess a potential subtype of depression: melancholia. While research supports the validity of the measure, no study has assessed its psychometric properties. We recruited 1633 participants online, of whom 487 reported a lifetime period of depressed mood or anhedonia and were administered the SMPI. We conducted confirmatory factor analyses (CFA) of the SMPI, to assess the proposed fit of the measure. We also conducted exploratory factor analyses (EFA) to explore the structure implied by the current data. CFA did not support the hypothesized factor structure of the SMPI, no matter what structure we assumed as primary (i.e., a one factor, two factor, or bifactor model). An EFA suggested a five-factor solution wherein several items did not appear to co-vary reliably and other factors captured the severity of melancholic symptoms, negative mood reactivity, positive mood reactivity, emotionality and family relationships, and early life adversity. The SMPI may not measure a single construct. Future research should explore the longitudinal association between depression severity, contaminant symptoms, positive and negative mood reactivity, and early life experiences. [ABSTRACT FROM AUTHOR]

Studies suggest that depression severity and duration interact to predict outcomes in depression treatment. To our knowledge, no study has explored this question in a sample with a placebo control, two therapies, and their combination nor with adolescents. We used data from the Treatment of Adolescent Depression Study (N = 439), in which adolescent were randomized to placebo (PBO), cognitive-behavioral therapy (CBT), antidepressants medications (MEDs), or their combination (COMB). We explore the interaction between depression severity, chronicity, and treatments (vs. placebo) in predicting outcomes. There was interaction between severity and chronicity when comparing COMB and CBT with PBO, but not MEDs. In non-chronic depression, the effects of CBT were inversely related to severity to the point that CBT appeared iatrogenic with more severe depression. In chronic depression, the effects of CBT did not vary by severity, but the relative effects of COMB grew, being smallest in milder, more dysthymic-like depression, and largest in chronic-severe depression. These findings support calls to classify depression by severity and chronicity as well efforts to risk stratify patients to different intensity of care according to these variables. • Depression severity and chronicity may interact to predict treatment outcomes. • We explored this question in the Treatment for Adolescent Depression Study (TADS). • In non-chronic depression, greater severity predicted lower response to CBT (vs. placebo). • In chronic depression, greater severity predicted better response to combination treatment. • Adding medications to CBT may potentiate its efficacy in high risk depression subgroups. [ABSTRACT FROM AUTHOR]

• Most RCT-tested iCBTs are not accessible to the public. • A significant number of RCT-tested iCBTs are geographically restricted. • iCBTs are more likely to contain evidence-based components, than popular MH apps. We examined the availability and components of internet-based cognitive-behavioral therapies (iCBTs) for depression tested in randomized-controlled trials (RCTs). The objectives of this literature review were to determine the extent to which research-validated iCBTs were available to the public, as well as to determine their therapeutic content. A literature review of RCTs for iCBTs was conducted on July 30, 2021. For each iCBT, interventions were rated by content and compared to commercially available smartphone apps. Our search yielded 80 studies using 41 unique iCBTs. Of these, only 6 (15%) were completely available to the public, more than half were not publicly available (46%), and the remaining 39% were available to the public with some restrictions (e.g., those based on the user's geographical location). When comparing iCBTs evaluated in RCTs to commercially available smartphone apps, we found that iCBTs were more likely to contain psychoeducation, cognitive restructuring, behavioral activation, problem solving, and interpersonal communication components. iCBTs from RCTs contain evidence-based content but few are available to the public. Extending beyond efficacy, attention should be paid to the dissemination of iCBTs. [ABSTRACT FROM AUTHOR]