Backgrounds: The Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD). Method: We recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems). Results: LPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as “PSU cases” in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%). Conclusion: A potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

Background and Objectives: Internet gaming disorder (IGD) is a growing public health concern, especially among adolescents. However, most IGD studies are cross-sectional, leaving its developmental course poorly understood. This study examined IGD trajectories, their predictors, and their long-term mental health outcomes among Chinese adolescents. Methods: A cohort of 16,833 adolescent gamers (mean age = 13.40, 46.56% girls) was recruited from 76 middle schools in Zigong City through cluster sampling. Assessments were conducted in November 2020 (T1), November 2021 (T2), and November 2022 (T3). IGD was measured using the Internet Gaming Disorder Scale–Short Form (IGDS9-SF). Demographic, gaming, environmental, and psychological factors (e.g., depression, anxiety, sleep problems, suicidal ideation, conduct problems, hyperactivity, resilience, mental wellbeing, prosocial behavior) were also assessed. Growth mixture modeling (GMM) identified IGD trajectories, and logistic regression evaluated predictors and mental health outcomes at T3. Results: GMM identified four IGD trajectories: High-Risk Decreasing (4.5%), Moderate-Risk Stable (19.5%), Moderate-Risk Increasing (3.0%), and Low-Risk Stable (73.0%). Age, gaming time, anxiety, sleep problems, conduct problems, hyperactivity/inattention, and low prosocial behavior predicted worsening IGD symptoms. At T3, the Moderate-Risk Increasing group had significantly higher risks for adverse mental health outcomes compared to the Low-Risk Stable group, whereas the High-Risk Decreasing group showed no significant or minimal differences in most domains from the Low-Risk Stable group after adjusting for baseline characteristics. Discussion and Conclusions: These findings underscore the heterogeneous nature of IGD development and highlight the need for long-term monitoring and tailored interventions to mitigate adverse mental health outcomes in at-risk adolescents.

BACKGROUND This meta-analysis aimed to identify risk factors for suicide attempts (SA) in patients with depression to inform clinical practice. MATERIAL AND METHODS We searched multiple databases up to January 1, 2025, including MEDLINE and Embase. Case-control and cohort studies reporting risk factors for SA in patients with depression were included. Study quality was assessed using the Newcastle-Ottawa Scale (NOS), and meta-analyses were performed using Rev Man 5.4 software. Results are expressed as odds ratios (OR) and 95% confidence intervals (CI). Heterogeneity was assessed using I² and P values, and publication bias was evaluated using funnel plots and Egger's test. The registration information was deposited in the International Register of Systematic Reviews and Meta-Analyses (PROSPERO) trial registry (CRD420251061401; Retrospective registration). RESULTS Out of a total of 3792 records, 22 case-control studies were included. The overall heterogeneity (I2) ranged from 0% to 91.9%. Significant risk factors for SA included suicidal ideation (OR=4.98, 95% CI 3.21-7.22), previous hospitalizations (OR=1.38, 95% CI 1.18-1.61), family history of suicide (OR=2.59, 95% CI 1.89-3.57), psychotic symptoms (OR=2.77, 95% CI 1.98-3.88), frequent depressive episodes (OR=2.58, 95% CI 1.58-4.22), self-blame (OR=2.43, 95% CI 1.78-3.31), negative life events (OR=3.77, 95% CI 2.85-5.51), and delusion (OR=3.14, 95% CI 1.99-4.96). Publication bias was detected for family history of suicide and suicidal ideation, but OR values remained significant after correction. CONCLUSIONS Our findings highlight the need for comprehensive risk assessments and targeted interventions in clinical practice to prevent suicide attempts in patients with depression. Future research should explore the mechanisms and interactions of these risk factors to refine prevention strategies.

Background: Adolescents with major depressive disorder (MDD) who exhibit psychotic symptoms (MDD-Psy) often show greater clinical severity and higher suicide risk than those without psychosis (MDD-NonPsy). It remains unclear whether prefrontal hemodynamic responses during cognitive challenge can differ between these subgroups. Methods: We recruited 273 adolescents aged 14–16 years (110 MDD-NonPsy, 163 MDD-Psy). All completed a 60-s verbal fluency task (VFT) while 53-channel functional near-infrared spectroscopy recorded oxy- and deoxyhemoglobin (HbO, HbR) from six frontal ROIs. Whole-brain FDR correction identified baseline-deviated channels, and ROC analyses tested the discriminative value of significant channels/ROIs. Clinical severity was indexed by the Kutcher Adolescent Depression Scale (KDAS) and the Brief Psychiatric Rating Scale (BPRS). Results: Compared with MDD-NonPsy, adolescents with MDD-Psy exhibited higher KDAS (median 16 vs 13; z = -7.07, p < 0.001) and BPRS total scores (median 35 vs 28; z = -11.02, p < 0.001). After FDR correction, MDD-NonPsy showed positive deviations at channels 8 and 23 (t = 2.10-2.70, pFDR=0.038), whereas MDD-Psy exhibited negative deviation at channel 2 (MNI –60, 19, 18; left middle frontal gyrus; t =-2.89, pFDR = 0.004). Across ROIs, only right inferior frontal gyrus HbR differed between groups (median –0.03 vs 0.00 mM·mm; z = -2.18, pFDR = 0.030). No ROI-level HbO differences survived correction. At the single-channel level, HbO at channel 2 and HbR in IFG_R correlated modestly with lower KDAS and restlessness scores (ρ = –0.14 to –0.16, p <0.050). ROC analyses indicated modest but significant classification accuracy for psychosis (AUC = 0.577-0.581, p = 0.030). Conclusions: Left dorsolateral and right inferior prefrontal hemodynamic signatures differ between adolescents with MDD who present with versus without psychotic features. However, given the absence of healthy control or other psychiatric comparison groups, these findings cannot establish diagnostic specificity. Pending replication in independent samples, these fNIRS−derived hemodynamic signatures may inform future hypothesis−driven research.

BACKGROUND Internet gaming disorder (IGD) has been associated with suicidal outcomes in adolescents, but most evidence is cross-sectional or has examined only whether IGD predicts later suicidality. Whether suicidal ideation and suicidal attempts are also associated with subsequent IGD remains unclear. OBJECTIVE This study aimed to examine prospective associations in both directions between IGD and suicidal ideation and suicidal attempts among Chinese adolescent gamers. METHODS This school-based, 2-wave prospective cohort study was conducted in Zigong, China, with assessments in November 2021 and November 2022. The analytic sample included 57,985 adolescents who completed both waves and reported gaming in the past 12 months at baseline. Students were recruited through school-based cluster sampling and completed electronic questionnaires during school sessions. IGD was assessed using the 9-item Internet Gaming Disorder Scale-Short Form (IGDS9-SF), with probable IGD defined as a score of 32 or higher. Suicidal ideation referred to serious consideration of suicide during the past month, whereas suicidal attempt was assessed over the lifetime. Both outcomes were assessed at both waves. Incident outcomes were defined among participants without the corresponding outcome at baseline. Logistic regression models estimated cross-sectional and prospective associations with sequential adjustment for demographic, lifestyle, and mental health covariates. RESULTS At baseline, 1333 of 57,985 adolescents had IGD (2.3%, 95% CI 2.2%-2.4%), 8450 had suicidal ideation (14.6%, 95% CI 14.3%-14.9%), and 6666 reported a suicidal attempt (11.5%, 95% CI 11.2%-11.8%). IGD was associated with higher baseline prevalence of suicidal ideation (crude odds ratio [COR] 6.45, 95% CI 5.78-7.20, P<.001; adjusted odds ratio [AOR] 1.50, 95% CI 1.31-1.72, P<.001) and suicidal attempt (COR 5.38, 95% CI 4.81-6.02, P<.001; AOR 1.48, 95% CI 1.29-1.69, P<.001). Prospectively, baseline IGD was associated with incident suicidal ideation (COR 2.49, 95% CI 2.02-3.06, P<.001; AOR 1.38, 95% CI 1.11-1.73, P=.004) and incident suicidal attempt (COR 2.99, 95% CI 2.47-3.61, P<.001; AOR 1.37, 95% CI 1.12-1.68, P=.002). Conversely, baseline suicidal ideation was associated with incident IGD (COR 2.98, 95% CI 2.58-3.45, P<.001; AOR 1.37, 95% CI 1.14-1.64, P<.001), as was baseline suicidal attempt (COR 2.63, 95% CI 2.24-3.08, P<.001; AOR 1.37, 95% CI 1.14-1.64, P<.001). CONCLUSIONS This study is innovative in testing prospective associations in both directions within an adolescent gamer cohort while examining suicidal ideation and suicidal attempts separately. Unlike previous studies that were predominantly cross-sectional or treated IGD only as a predictor of later suicidality, it identifies suicidal outcomes as prospective predictors of incident IGD. The findings add longitudinal evidence that IGD and suicidality are interrelated prevention targets, although they do not establish causality. In practice, school-based and clinical screening should assess problematic gaming, suicide risk, and co-occurring mental health symptoms together, with timely referral and integrated intervention for adolescents who screen positive in either domain.