Search

OBJECTIVE: The Personalized Advantage Index (PAI) is a method to guide treatment selection by investigating which of two or more treatments is optimal for a given individual. Recently, it was shown that, on average, twice-weekly sessions of psychotherapy for depression lead to better outcomes compared to once-weekly sessions. The present study applied the PAI method to assess if subgroups of patients may have a differential response to psychotherapy frequency.METHOD: Data came from a clinical trial (n = 200) randomizing depressed patients into different session frequencies: weekly sessions versus twice-weekly sessions. Machine-learning techniques were used to select pretreatment variables and develop a multivariable prediction model that calculated each patient's PAI. Differences in observed depression post-treatment scores (Beck Depression Inventory-II [BDI-II]) were tested between patients that received their PAI-indicated versus non-indicated session frequency. Between-group effect sizes (Cohen's d) were reported.RESULTS: We identified prognostic indicators generally associated with lower post-treatment BDI-II regardless of treatment assignment. In addition, we identified specific demographic and psychometric features associated with differential response to weekly- versus twice-weekly therapy sessions. Observed post-treatment BDI-II scores were significantly different between individuals receiving the PAI-indicated versus non-indicated session frequency (d = .37).CONCLUSIONS: Although a higher session frequency is more effective on average, different session frequencies seem beneficial for different patients. Future studies should externally validate these findings before they can be generalized to other settings. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Objectives\ud \ud To investigate associations between alcohol use, psychological treatment attendance, and clinical outcomes.\ud \ud \ud \ud Methods\ud \ud We analysed electronic health records for N = 7,986 patients accessing psychological treatment for common mental disorders. Data were collected for pre-treatment alcohol use (average units per week) and severity of dependence (SDS), number of therapy contacts attended, pre- and post-treatment anxiety (GAD-7), and depression (PHQ-9) symptom severity. Hierarchical regression was used to examine associations between alcohol use/dependence and post-treatment symptom severity controlling for intake severity and relevant confounders.\ud \ud \ud \ud Results\ud \ud After controlling for confounders, alcohol use had significant nonlinear associations with pre-treatment depression severity (R2 = .54, p

Objective: To provide a comprehensive assessment of the association between psychological treatment adherence/competence/integrity (ACI) and clinical outcomes. Method: The review protocol was preregistered (CRD42020193889). Studies that assessed ACI–outcome relationships for adult psychotherapy were searched across three databases (Scopus, PsycINFO, MEDLINE). Random effects meta-analyses were conducted on adherence–outcome, competence–outcome, and integrity–outcome relationships. Separate analyses were performed for studies with hierarchical (i.e., patients nested within therapist) versus nonhierarchical study designs. Moderator analyses were performed according to predefined clinical and methodological features. GRADE assessments rated the quality of each meta-analytic comparison. Results: The review identified 62 studies suitable for inclusion (45 adherence–outcome, 39 competence–outcome, and seven integrity–outcome effect sizes; N = 8,210 across all analyses). No significant adherence–outcome association was found. A small significant positive association was found only in nonhierarchical studies between competence and outcome, r = 0.17, 95% CI [0.07–0.26], p < .001, ∼d = .34, GRADE = moderate. Small-to-moderate significant positive associations between integrity and outcome were found for both nonhierarchical, r = 0.15, 95% CI [0.06–0.23], p < .001, ∼d = .30, GRADE = high, and hierarchical study designs, r = 0.23, 95% CI [0.01, 0.43], p < .044, ∼d = .47, GRADE = low. Diagnosis, treatment modality and year of publication significantly moderated the strength of ACI–outcome correlations. Conclusions: Competence and integrity are significantly associated with clinical outcome, with a magnitude comparable to wider common factors. Further research is required to study these process–outcome associations with greater precision in routine-care settings and to understand the role of moderating variables.

Background\ud \ud Previous reviews indicate that depressed patients with a comorbid personality disorder (PD) tend to benefit less from psychotherapies for depression and thus personality pathology needs to be the primary focus of treatment. This review specifically focused on studies of Cognitive Behavioural Therapy (CBT) for depression examining the influence of comorbid PD on post-treatment depression outcomes.\ud \ud \ud \ud Methods\ud \ud This was a systematic review and meta-analysis of studies identified through PubMed, PsychINFO, Web of Science, and Scopus. A review protocol was pre-registered in the PROSPERO database (CRD42019128590).\ud \ud \ud \ud Results\ud \ud Eleven eligible studies (N = 769) were included in a narrative synthesis, and ten (N = 690) provided sufficient data for inclusion in random effects meta-analysis. All studies were rated as having “low” or “moderate” risk of bias and there was no significant evidence of publication bias. A small pooled effect size indicated that patients with PD had marginally higher depression severity after CBT compared to patients without PD (g = 0.26, [95% CI: 0.10, 0.43], p = .002), but the effect was not significant in controlled trials (p = .075), studies with low risk of bias (p = .107) and studies that adjusted for intake severity (p = .827). Furthermore, PD cases showed symptomatic improvements across studies, particularly those with longer treatment durations (16–20 sessions).\ud \ud \ud \ud Conclusions\ud \ud The apparent effect of PD on depression outcomes is likely explained by higher intake severity rather than treatment resistance. Excluding these patients from evidence-based care for depression is unjustified, and adequately lengthy CBT should be routinely offered.

Objectives\ud \ud Selectively reported results from only well-performing cutoffs in diagnostic accuracy studies may bias estimates in meta-analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire-9 (PHQ-9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10–13) and compared accuracy estimates based on published cutoffs versus all cutoffs.\ud \ud \ud \ud Methods\ud \ud We conducted bivariate random effects meta-analyses using individual participant data to compare accuracy from published versus all cutoffs.\ud \ud \ud \ud Results\ud \ud For the PHQ-9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: −0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ-9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10.\ud \ud \ud \ud Conclusion\ud \ud Selective cutoff reporting was more pronounced for the PHQ-9 than EPDS.

Within the Routine Outcome Monitoring System “OQ‐Analyst”, the questionnaire “Assessment for Signal Cases” (ASC) supports therapists in detecting potential reasons for not‐on‐track trajectories. Factor analysis and a machine learning algorithm (Lasso with 10‐fold cross‐validation) were applied and potential predictors of not‐on‐track classifications were tested using logistic multilevel modelling methods. The factor analysis revealed a shortened (30‐item) version of the ASC with good internal consistency (α = 0.72 – 0.89) and excellent predictive value (AUC = 0.98; +PV = 0.95; ‐PV = 0.94). Item‐level analyses showed that interpersonal problems captured by specific ASC items (not feeling able to speak about problems with family members; feeling rejected or betrayed) are the most important predictors of not‐on‐track trajectories.

Importance:The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9. Objective:To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression. Data Sources:MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-May 2018). Study Selection:Eligible data sets compared PHQ-2 scores with major depression diagnoses from a validated diagnostic interview. Data Extraction and Synthesis:Individual participant data were synthesized with bivariate random-effects meta-analysis to estimate pooled sensitivity and specificity of the PHQ-2 alone among studies using semistructured, fully structured, or Mini International Neuropsychiatric Interview (MINI) diagnostic interviews separately and in combination with the PHQ-9 vs the PHQ-9 alone for studies that used semistructured interviews. The PHQ-2 score ranges from 0 to 6, and the PHQ-9 score ranges from 0 to 27. Results:Individual participant data were obtained from 100 of 136 eligible studies (44 318 participants; 4572 with major depression [10%]; mean [SD] age, 49 [17] years; 59% female). Among studies that used semistructured interviews, PHQ-2 sensitivity and specificity (95% CI) were 0.91 (0.88-0.94) and 0.67 (0.64-0.71) for cutoff scores of 2 or greater and 0.72 (0.67-0.77) and 0.85 (0.83-0.87) for cutoff scores of 3 or greater. Sensitivity was significantly greater for semistructured vs fully structured interviews. Specificity was not significantly different across the types of interviews. The area under the receiver operating characteristic curve was 0.88 (0.86-0.89) for semistructured interviews, 0.82 (0.81-0.84) for fully structured interviews, and 0.87 (0.85-0.88) for the MINI. There were no significant subgroup differences. For semistructured interviews, sensitivity for PHQ-2 scores of 2 or greater followed by PHQ-9 scores of 10 or greater (0.82 [0.76-0.86]) was not significantly different than PHQ-9 scores of 10 or greater alone (0.86 [0.80-0.90]); specificity for the combination was significantly but minimally higher (0.87 [0.84-0.89] vs 0.85 [0.82-0.87]). The area under the curve was 0.90 (0.89-0.91). The combination was estimated to reduce the number of participants needing to complete the full PHQ-9 by 57% (56%-58%). Conclusions and Relevance:In an individual participant data meta-analysis of studies that compared PHQ scores with major depression diagnoses, the combination of PHQ-2 (with cutoff ≥2) followed by PHQ-9 (with cutoff ≥10) had similar sensitivity but higher specificity compared with PHQ-9 cutoff scores of 10 or greater alone. Further research is needed to understand the clinical and research value of this combined approach to screening.

Background: Trauma focused cognitive behavioral therapy (Tf-CBT) and eye movement desensitization and reprocessing (EMDR) are two highly effective treatment options for post-traumatic stress disorder (PTSD). Yet, on an individual level, PTSD patients vary substantially in treatment response. The aim of the paper is to test the application of a treatment selection method based on a personalized advantage index (PAI). Method: The study used clinical data for patients accessing treatment for PTSD in a primary care mental health service in the north of England. PTSD patients received either EMDR (N = 75) or Tf-CBT (N = 242). The Patient Health Questionnaire (PHQ-9) was used as an outcome measure for depressive symptoms associated with PTSD. Variables predicting differential treatment response were identified using an automated variable selection approach (genetic algorithm) and afterwards included in regression models, allowing the calculation of each patient’s personalized advantage index (PAI). Results: Age, employment status, gender and functional impairment were identified as relevant variables for Tf-CBT. For EMDR, baseline depressive symptoms as well as prescribed antidepressant medication were selected as predictor variables. Fifty-six percent of the patients (n = 125) had a PAI equal or higher than one standard deviation. From those patients, 62 (50%) did not receive their model-predicted treatment and could have benefited from a treatment assignment based on the PAI. Conclusions: Using a PAI-based algorithm has the potential to improve clinical decision-making and to enhance individual patient outcomes, although further replication is necessary before such an approach can be implemented in prospective studies.

International audience

This study aimed at investigating the effect of electrical current profile upon the iontophoretic transport of (i) ascorbic acid (AA) and (ii) ellagic acid (EA), into porcine skin in vitro, and the impact of the physicochemical properties of both actives on their mechanism of transport when formulated in cosmetic compositions. The experiments were performed using a proprietary iontophoretic device containing a roller to apply the formulation. Three current profiles were tested: (i) galvanic direct current (DC), (ii) square unipolar pulse current (SPC), and (iii) galvanic direct current (DC) + pulse current (PC). The skin samples were collected at different sampling points, extracted and analyzed by HPLC. Results suggested that the DC + PC mode for only 5 min was able to significantly increase the delivery of AA from o/w cosmetic compositions. The use of this current profile might improve the skin penetration of AA due to electromigration and passive diffusion, the latter being facilitated by the physical enhancement method. The SPC mode significantly improved the passage of EA in its neutral form from cosmetic o/w formulations by electroosmosis. Tailoring specific electrical current modes considering the ionization state of active ingredients would allow the design of short and personalized cosmetic treatments that significantly improve the penetration efficiency of the active ingredients and possibly reduce the doses applied.