Internet-based psychological interventions can effectively reduce depressive symptoms in adults, but adherence remains challenging. In this preregistered individual participant data meta-analysis, we examined predictors of treatment adherence. We searched PubMed, Embase and PsycINFO on 6 February 2024 for randomized trials of internet-based interventions among adults with elevated depressive symptoms. We conducted a one-stage logit-link multilevel beta regression, with adherence defined as the proportion of completed modules post-intervention. This study included 71 trials (85 treatment arms, 8,082 participants). Lower adherence was associated with younger age (β = 0.005, standard error (SE) 0.002, P = 0.028), male gender (β = −0.163, SE 0.053, P = 0.002), lower education (β = −0.133, SE 0.05, P = 0.008) and employment (β = −0.113, SE 0.054, P = 0.037). No significant interactions were found between individual predictors and intervention format (guided versus self-guided). Higher adherence was associated with lower post-intervention depression severity, adjusting for baseline severity (β = −0.30, SE 0.04, P < 0.001). Identifying subgroups at risk of low adherence may inform targeted strategies to improve engagement and clinical effectiveness.

Background: Internet-based interventions for insomnia show promise, but understanding the process variables, such as knowledge acquisition and psychological acceptance, is crucial for enhancing digital adherence and clinical effectiveness.

Objective: This study aimed to evaluate the feasibility, adherence, and preliminary clinical signals of 2 therapist-assisted interventions-internet-delivered cognitive behavioral therapy (iCBT) and internet-delivered acceptance and commitment therapy (iACT)-for insomnia in a primary care setting.

Methods: This was a pilot randomized controlled trial. Adults seeking help for insomnia (n=18) were recruited via primary care and randomized to either a 5-module iCBT or iACT program delivered via a secure digital platform with weekly therapist feedback. Blinding of participants and therapists was not possible due to the nature of the interventions. Primary outcomes included the Insomnia Severity Index; secondary outcomes included the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, and WHO Disability Assessment Schedule. A novel sleep knowledge test was used as a process variable. The data were analyzed using split-plot analyses of variance (intention-to-treat or last observation carried forward and complete case analysis) and nonparametric Friedman and Kruskal-Wallis tests.

Results: A total of 18 participants were randomized (iCBT: n=9; iACT: n=9). High attrition was observed, with only 33.3% (n=3) of iCBT and 55.6% (n=5) of iACT participants completing all modules. The iACT group demonstrated a significant within-group reduction in insomnia severity (P=.01, Friedman test), whereas iCBT results were nonsignificant (P=.10, Friedman test). No significant between-group differences were found for any clinical or process variables. Participants rated both treatments as credible (Credibility/Expectancy Questionnaire scores remained stable), though qualitative feedback indicated a need for more flexible, less burdensome content.

Conclusions: This pilot study demonstrates that while internet-delivered insomnia treatments are feasible and credible in primary care, high attrition remains a significant barrier. Preliminary signals suggest that iACT may be a viable alternative to iCBT, potentially offering better adherence. Larger, fully powered pilot randomized controlled trials (estimated N=404) with refined recruitment and automated retention strategies are required to determine definitive comparative efficacy and the mediating role of sleep knowledge and acceptance.

The death of a loved one is associated with an increased risk of developing severe mental health complications such as prolonged grief disorder (PGD), post-traumatic stress disorder (PTSD) and depression. Research supports the efficacy of cognitive-behavioural therapies (CBT), delivered online or face-to-face, in treating post-loss mental health problems. However, evidence-based treatments for bereaved adults remain scarce within the Swedish healthcare system. The main aim of this study was to evaluate the feasibility and acceptability of grief-focused internet-delivered CBT (ICBT) for PGD in Swedish bereaved adults, using an uncontrolled multiple-methods design. A secondary aim was to assess the potential effect on symptoms of PGD, PTSD and depression. Fourteen participants who met criteria for probable PGD were enrolled in the study and received access to the online treatment for eight weeks. Ten participants completed post-treatment interviews and self-report questionnaires about their experiences of the treatment. Self-reported symptom-levels of PGD, PTSD and depression were assessed at baseline, mid-, posttreatment and at four-month follow-up. Overall, the grief-focused ICBT was perceived as helpful and emotionally engaging. Most participants reported satisfaction with the intervention. Reductions were observed in symptoms of PGD, PTSD and depression, although these findings should be interpreted as preliminary due to the small sample size and limited statistical power. Overall, the results suggest that grief-focused ICBT is a feasible and acceptable treatment for bereaved adults. A fully powered randomised controlled trial is warranted to establish the efficacy of the treatment.

Background: Scalable, low-threshold interventions for personality disorders and personality difficulties (ICD-11) remain limited. We developed GPM-I, a guided digital self-help adaptation of Good Psychiatric Management, to deliver structured psychoeducation and support early change efforts.

Methods: We conducted a naturalistic feasibility study in routine psychiatric care in Stockholm, Sweden. Feasibility outcomes included engagement and standard program completion (Modules 1-2) and optional advanced module uptake (Modules 3-6). Acceptability was assessed with the Client Satisfaction Questionnaire (CSQ-8) and negative effects with the Negative Effects Questionnaire (NEQ). Weekly distress (CORE-10) was analyzed using linear mixed-effects models.

Results: Of 131 patients offered access, 78 (59.5%) initiated the program by completing Module 1 (engagement threshold). Participants were 71.8% women; mean age was 35.2 years. Participants were categorized as having personality disorder (n = 18), personality difficulties (n = 22), or other diagnoses (n = 38). Among initiators, standard program completion (Modules 1-2) was observed in 40/78 participants (51.3%), and 13/78 (16.7%) completed all available modules (Modules 1-6). CSQ-8 respondents (28/78, 35.9%) reported moderate satisfaction, with 85.7% rating overall satisfaction in the two highest categories, but completion of CSQ-8 and NEQ was low. Negative effects were reported by 25/27 NEQ respondents (92.6%), most often increased stress/ pressure or emotional strain. CORE-10 decreased significantly over time with a small effect size.

Conclusion: GPM-I showed moderate engagement and moderate acceptability among respondents, alongside generally mild-to-moderate negative effects. Findings support continued refinement of the procedures and can inform the design of a controlled trial.

Cognitive behavioral therapy (CBT) is a well-established, evidence-based treatment for common mental disorders such as depression, anxiety disorders, and obsessive-compulsive disorder (OCD). However, treatment outcomes vary widely, and a substantial proportion of patients do not achieve sufficient improvement. Robust predictors of individual differences in symptom change are currently lacking. Genetic differences have been suggested to play a role, but existing evidence is inconclusive. This study investigated the extent to which common genetic variants-single nucleotide polymorphisms (SNPs)-contribute to variability in symptom change. The sample was derived from the MULTI-PSYCH and NORDiC cohorts, comprising 3113 adults and children treated with CBT for depression, panic disorder, social anxiety disorder, or OCD. We performed a genome-wide association study (GWAS) of symptom change following CBT and estimated the proportion of variance attributed to SNPs. Secondary analyses included GWAS and SNP-based heritability estimation of additional clinically relevant outcomes: pre- and post-treatment symptom severity and remission status. No variants reached genome-wide significance. We estimated SNP-based heritability of symptom change at h²_SNP = 0.221 (SE = 0.123. These results suggest that common genetic variation may contribute modestly to treatment outcomes. Much larger samples would be required to obtain more precise estimates and to detect genome-wide significant loci.

Insomnia is prevalent, emphasizing the need for effective and sustainable treatments. While short-term use of sleep medication is recommended, long-term use remains common, underscoring the necessity for psychological treatments like Cognitive Behavioral Therapy for Insomnia (CBT-I) in clinical practice. This study aimed to evaluate the effectiveness of guided Internet-Based Cognitive Behavioral Therapy for insomnia (ICBT-I) when integrated into general practice. Participants (n = 177) were recruited from 33 primary health care centers (PCCs) and enrolled in an eight-week guided ICBT-I program. Eligible participants were at least 18 years old and reported sleep problems significantly affecting their daily lives. Significant reductions in insomnia were observed, with large improvements in sleep disturbances. ISI scores decreased significantly from pre- to post-treatment (β = 9.368, p < .001, Hedges’ g = 1.40). Depression (β = 5.496, g = 0.68) and anxiety (β = 3.982, g = 0.56) also showed moderate improvements (p < .001). All sleep diary measures improved significantly (p < .001), and sleep medication use dropped from 48.6% at pretreatment to 17.5% at posttreatment (p < .001). These findings suggest that guided ICBT-I in primary care effectively reduces insomnia and improves mental health, with outcomes comparable to specialized care.

Objective: Reliable and accurate measurement is fundamental to scientific progress; however, the dominant measurement practices in psychology, clinical psychology, and prediction research often lack rigor. Improving measures using Rasch Measurement Theory (RMT) offers advantages by fulfilling the key psychometric properties of unidimensionality, local independence of items, ordering of response categories, and invariance. Ordinal-level sum scores can be transformed into interval-level latent trait scores, thereby improving the measurement precision. However, the impact of using psychometrically advanced questionnaires with latent trait scores, as opposed to traditional sum scores, in predictive models is still unclear. This study evaluates whether using latent trait scores as predictors and outcomes, in accordance with RMT, improves predictive performance compared to using traditional sum scores when predicting treatment outcomes during psychological treatment.

Methods: Self-rated symptom data from three different questionnaires, collected over the first 4 weeks of psychological treatment from 6,464 patients undergoing a 12-week treatment program, were used to predict post-treatment outcomes on the same questionnaires. This was done in two ways: (1) using sum scores as the questionnaires were originally developed and (2) using a reformulated, more psychometrically robust version of the questionnaires based on Rasch analysis, which was also shorter. The prediction models used were linear regression, Bayesian ridge regression, and random forest. Multiple imputations were used to address missing data, and nested cross-validation was employed for hyperparameter tuning and scoring.

Results: Latent scores calculated using the psychometrically optimized shorter version, which comprises 23% of the full scale, showed similar predictive performance compared to the sum score of the full scale. Overall, there was a statistically significant but practically negligible difference of 0.007-0.008 in the root mean squared error (RMSE) when comparing the original sum score to the latent trait scores.

Conclusion: Initial findings comparing psychometrically improved questionnaires with the original ordinal sum scores within a predictive framework indicate that using latent trait scores derived from these improvements showed the predictive performance similar to the sum score of the full scale. The small differences suggest that the improved versions remain valuable owing to their enhanced psychometric qualities and the reduction in response burden by using considerably fewer items. Further research is needed to explore the use of latent trait scores compared to ordinal sum scores in predictive research.

Psychological symptoms tend to change over time, even in the absence of clinical intervention. For example, self-ratings are often higher at screening compared to start of treatment. A plausible hypothesis is that this is due to patients' self-referring when their gradually fluctuating symptoms are worse than usual. That hypothesis predicts that patients that wait longer will have had longer time to return to their average symptom level. On the other hand, other processes related to measurement reactivity, contact with a clinician, or regression towards the mean, do not predict a time-dependent relationship. Our aim was to estimate the extent of this hypothesized symptom reduction in depression, social anxiety disorder, panic disorder, health anxiety and insomnia (both total reduction and the relationship with time). The sample included adults (N = 8744) from an outpatient psychiatric clinic providing ICBT in Swedish routine care. Time-dependent effects were estimated with linear regression for both primary symptoms and secondary depressive symptoms. A simulation of symptom fluctuations was built to estimate power and further contextualize the effects. Patients improved on average from screening to the start of the intervention, but this varied substantially depending on diagnosis and questionnaire used. The waiting time weakly predicted the degree of improvement both for primary depressive symptoms and comorbid depressive symptoms. The estimate for primary depressive symptoms was sensitive to modeling choices, shrinking towards zero when modeled with fat-tailed residuals. The preponderance of "immediate" reductions in symptoms have implications for reporting standards of pretreatment-measurements, especially in single-group intervention studies.

Background: Up to 50% of patients treated with internet-delivered cognitive behavioral therapy (ICBT) for depression and anxiety disorders do not experience clinically significant symptom reduction. Identifying these patients prior to the initiation of ICBT can support treatment planning. Objective: The aim of this study was to enhance baseline prediction of clinically meaningful improvement in patients treated with ICBT for common psychiatric disorders in routine care, which could ultimately inform treatment planning at intake. Methods: We developed multimodal predictive models integrating clinical, sociodemographic, and genetic data available pretreatment to predict clinically meaningful improvement in a sample of 1790 patients treated with ICBT for major depressive disorder, panic disorder, and social anxiety disorder. We applied machine learning algorithms of varying complexity (logistic regression, random forest [RF], extreme gradient boosting, support vector machines, soft voting, and stacking ensemble), with nested cross-validation, elastic net variable selection, multiple imputation, and temporal validation in a 20% holdout test set (n=356). The primary performance measure was the area under the receiver operating characteristic curve (AUC). Results: All full phenotypic models showed comparable performance (AUCtest 0.732-0.749), with RF achieving the best holdout discrimination (AUC_test 0.749, 95% CI 0.698-0.797). Compared with the benchmark model based on self-reported screening data (AUCtest 0.695, 95% CI 0.637-0.748), RF and both ensemble models incorporating register data showed higher discrimination in paired DeLong tests (P=.04, P=.02, and P=.03, respectively), whereas polygenic scores added no independent predictive value in this cohort and modeling setup (P=.97). Conclusions: These promising results support the feasibility of baseline prognostic prediction of clinically meaningful improvement after ICBT and provide a basis for the prospective validation of model-informed risk stratification.

Therapist-guided internet-based cognitive behavioural therapy (iCBT) has improved access to treatment for depression and anxiety, but scalability is limited by reliance on trained therapists. This feasibility trial evaluated a tailored digital self-help intervention for adults with depressive and anxiety symptoms, delivered with or without clinician guidance. In total, 124 participants in Sweden with at least mild depressive or anxiety symptoms were recruited through social media and randomized (1:1) to an eight-week program with (n = 63) or without (n = 61) clinician guidance. All participants completed telephone assessments before and after the intervention. The primary aim was to assess feasibility of both versions, while considering outcome advantages of guidance and reduced clinician time with self-help. Feasibility outcomes included adherence, credibility, satisfaction, and adverse events. The intervention was perceived as credible, with high satisfaction and engagement: most participants used the program weekly, and two thirds completed at least three of five modules. Outcomes were similar across groups, though participants with guidance reported higher satisfaction. Clinician time averaged 36 minutes for self-help participants and 66 minutes for those receiving guidance. Both groups showed large symptom reductions (Cohen's d = 1.05-1.10), supporting feasibility and motivating future trials comparing self-help and clinician-guided delivery.