With the rise of online references, podcasts, webinars, self-test tools, and social media, it is worthwhile to understand whether textbooks continue to provide value in medical education, and to assess the capacity they serve during fellowship training.

A prospective mixed-methods study based on surveys that were disseminated to seven paediatric cardiology fellowship programmes around the world. Participants were asked to read an assigned chapter of Anderson’s Pediatric Cardiology 4th Edition textbook, followed by the completion of the survey. Open-ended questions included theming and grouping responses as appropriate.

The survey was completed by 36 participants. When asked about the content, organisation, and utility of the chapter, responses were generally positive, at greater than 89%. The chapters, overall, were rated relatively easy to read, scoring at 6.91, with standard deviations plus or minus 1.72, on a scale from 1 to 10, with higher values meaning better results. When asked to rank their preferences in where they obtain educational content, textbooks were ranked the second highest, with in-person teaching ranking first. Several themes were identified including the limitations of the use of textbook use, their value, and ways to enhance learning from their reading. There was also a near-unanimous desire for more time to self-learn and read during fellowship.

Textbooks are still highly valued by trainees. Many opportunities exist, nonetheless, to improve how they can be organised to deliver information optimally. Future efforts should look towards making them more accessible, and to include more resources for asynchronous learning.

The Korean Basketball League(KBL) holds an annual draft to allow teams to select new players, mostly graduates from the elite college basketball teams even though some are from high school teams. In sports games, many factors might influence the success of an athlete. In addition to possessing excellent physical and technical factors, success in a sports game is also influenced by remarkable psychological factors. Several studies reported that elite sports players can control their anxiety during competition, which may lead to better performance. In particular, the temperament and characteristics of players have been regarded as crucial determinants of the player’s performance and goal. In this regard, numerous studies suggest that personality is considered to be an important predictor of long-term success in professional sports

Based on previous reports and studies, we hypothesized that physical status, temperament and characteristics, and neurocognitive functions of basketball players could predict the result of KBL draft selection. Especially, temperament and characteristics were associated with the result of KBL selection. The basketball performances including average scores and average rebound were associated with emotional perception and mental rotation.

We recruited the number of 44 college elite basketball players(KBL selection, n=17; Non-KBL selection, n=27), and the number of 35 age-matched healthy comparison subjects who major in sports education in college. All participants were assessed with the Temperament and Character Inventory(TCI), Sports Anxiety Scales(SAS), Beck Depression Inventory(BDI), Perceived Stress Scale (PSS-10), Trail Making Test(TMT), and Computerized Neuro-cognitive Test(CNT) for Emotional Perception and Mental Rotation.

Current results showed that physical status, temperament and characteristics, and Neurocognitive functions of college basketball players could predict the KBL draft selection. Among temperament and characteristics, novelty seeking and reward dependence were associated with KBL draft selection. The basketball performances including average scores and average rebound were associated with emotional perception and mental rotation.

In order to be a good basketball player for a long time, it was confirmed that temperamental factors and Neurocognitive factors were very closely related. Furthermore, it is also judged that these results can be used as basic data to predict potential professional basketball players.

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Suicide has a complex relationship with several factors, and it is known that identifying high-risk groups of suicide and managing crisis in advance can help prevent suicide. Moreover in a previous study, it showed that people with chronic diseases often suffer from psychological difficulties such as depression and anxiety, which can influence one to commit suicide. Based on many studies about the relationship between diabetes and depression, 10% of diabetic patients experience major depression, and diabetic patients experience twice as much depression as the general population. But, there are few studies examining the relationship between diabetes and suicide risk, and most of them were targeted for type 1 diabetes only.

The objectives of this study were to investigate the suicide risk in diabetic patients, and evaluate the suicide risk varies by the duration of diabetes, using a large population sample in South Korea

Using the 2019 Korea National Health and Nutrition Examination Survey data, 6,296 adults (aged 19 years or older) were included. Suicidal ideation, suicidal plan, and suicidal behavior of diabetic patients were compared with the general population. After classifying the patients into ≤ 1 year, 2 to 9 years, and 10 years ≤ for the duration of diabetes, we evaluated the relationship between the duration of diabetes and the risk of suicide.

Diabetic patients had higher prevalence of suicidal ideation (9.1%, P<0.001) and suicidal plan (3.6%, P<0.001) than general population. After adjusting for potential confounding factors, suicidal plan (aOR = 3.011, 95% CI = 1.392-6.512) was significantly associated with diabetes. In the 2 to 9 year group of diabetes, we found an increase in risk of suicidal ideation (aOR=2.068, 95% CI=1.219-3.510), suicidal plan (aOR=3.640, 95% CI=1.592-8.320), and suicidal behavior (aOR=6.222, 95% CI=1.759-22.008) after adjusting covariates. However, increase in suicide risk was not observed in the ≤1 year and 10 years ≤ groups after diagnosis of diabetes.

In adults, diabetes is associated with increase in suicide risk. Suicide risk in diabetic patients shows an ‘inverted U-shaped’ depending on the duration of diabetes.

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Anxiety disorders are one of the most common mental disorders, yet only less than 20% of people with anxiety disorders receive adequate treatment. Digital interventions for anxiety disorders can potentially increase access to evidence-based treatment. However, there is no comprehensive meta-analysis study that covers all modalities of digital interventions and all anxiety disorders.

A preliminary meta-analysis was conducted to examine the treatment efficacy of digital interventions [e.g., virtual reality (VR)-, mobile application-, internet-based interventions] for anxiety disorders and to identify potential moderators that may lead to better treatment outcomes.

We searched Embase, PubMed, PsycINFO, Web of Science, and the Cochrane Library for randomized controlled trials examining the therapeutic efficacy of digital interventions for individuals with anxiety disorders from database inception to April 18, 2023. Search keywords were developed by combining the PICOS framework and MeSH terms. Data screening and extraction adhered to PRISMA guidelines. We used a random-effects model with effect sizes expressed as Hedge’s g. The quality of the studies was assessed using the Revised Cochrane risk-of-bias tool for randomized trials (RoB 2). The study protocol was registered in PROSPERO on April 22, 2023 (CRD42023412139).

A systematic literature search identified 19 studies with randomized controlled trials (21 comparisons; 1936 participants) with high overall heterogeneity (Q = 104.49; P < .001; I2 = 80.9%). Digital interventions reduced anxiety symptoms with medium to large effect sizes (g = 0.78; 95% CI: 0.55-1.02; P < .001), with interventions for specific phobia showing the largest effect size (n = 6; g = 1.22; 95% CI: 0.51-1.93; P < .001). VR-based interventions had a larger effect size (n = 6; g = 0.98; 95% CI: 0.39-1.57; P < .001) than mobile- or internet-based interventions, which had medium effect sizes. Meta-regression results exhibited that effect sizes of digital interventions were associated with the mean age of participants (β = 0.04; 95% CI: 0.02-0.06; P < .001).

The results of this study provide evidence for the efficacy of digital interventions for anxiety disorders. However, this also suggests that the degrees of effectiveness in reducing anxiety symptoms can be moderated by the specific diagnosis, the modalities of digital technologies, and mean age, implying that the application of digital interventions for anxiety disorders should be accompanied by personalized guidance.

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A large and accumulating body of evidence shows that loneliness is detrimental for various health and well-being outcomes. However, less is known about potentially modifiable factors that lead to decreased loneliness.

We used data from the Health and Retirement Study to prospectively evaluate a wide array of candidate predictors of subsequent loneliness. Importantly, we examined if changes in 69 physical-, behavioral-, and psychosocial-health factors (from t0;2006/2008 to t1;2010/2012) were associated with subsequent loneliness 4 years later (t2;2014/2016).

Adjusting for a large range of covariates, changes in certain health behaviors (e.g. increased physical activity), physical health factors (e.g. fewer functioning limitations), psychological factors (e.g. increased purpose in life, decreased depression), and social factors (e.g. greater number of close friends) were associated with less subsequent loneliness.

Our findings suggest that subjective ratings of physical and psychological health and perceived social environment (e.g. chronic pain, self-rated health, purpose in life, anxiety, neighborhood cohesion) are more strongly associated with subsequent loneliness. Yet, objective ratings (e.g. specific chronic health conditions, living status) show less evidence of associations with subsequent loneliness. The current study identified potentially modifiable predictors of subsequent loneliness that may be important targets for interventions aimed at reducing loneliness.

The COVID-19 pandemic significantly disrupted schools and learning formats. Children with epilepsy are at-risk for generalized academic difficulties. We investigated the potential impact of COVID-19 on learning in those with epilepsy by comparing achievement on well-established academic measures among school-age children with epilepsy referred prior to the COVID-19 pandemic and those referred during the COVID-19 pandemic.

This study included 466 children [52% male, predominately White (76%), MAge=10.75 years] enrolled in the Pediatric Epilepsy Research Consortium Epilepsy (PERC) Surgery database project who were referred for surgery and seen for neuropsychological testing. Patients were divided into two groups based on a proxy measure of pandemic timing completed by PERC research staff at each site (i.e., “were there any changes to typical in-person administration [of the evaluation] due to COVID?”). 31% of the sample (N = 144) were identified as having testing during the pandemic (i.e., “yes” response), while 69% were identified as having testing done pre-pandemic (i.e., “no” response). Of the 31% who answered yes, 99% of administration changes pertained to in-person testing or other changes, with 1% indicating remote testing. Academic achievement was assessed by performance measures (i.e., word reading, reading comprehension, spelling, math calculations, and math word problems) across several different tests. T-tests compared the two groups on each academic domain. Subsequent analyses examined potential differences in academic achievement among age cohorts that approximately matched grade level [i.e., grade school (ages 5-10), middle school (ages 11-14), and high school (ages 15-18)].

No significant differences were found between children who underwent an evaluation before the pandemic compared to those assessed during the pandemic based on age norms across academic achievement subtests (all p’s > .34). Similarly, there were no significant differences among age cohorts. The average performance for each age cohort generally fell in the low average range across academic skills. Performance inconsistently varied between age cohorts. The youngest cohort (ages 5-10) scored lower than the other cohorts for sight-word reading, whereas this cohort scored higher than the middle cohort (ages 11-14) for math word problems and reading comprehension. There were no significant differences between the two pandemic groups on demographic variables, intellectual functioning, or epilepsy variables (i.e., age of onset, number of seizure medications, seizure frequency).

Academic functioning was generally equivalent between children with epilepsy who underwent academic testing as part of a pre-surgical evaluation prior to the pandemic compared to those who received testing during the pandemic. Additionally, academic functioning did not significantly differ between age cohorts. Children with epilepsy may have entered the pandemic with effective academic supports and/or were accustomed to school disruptions given their seizure history. Replication is needed as findings are based on a proxy measure of pandemic timing and the extent to which children experienced in-person, remote, and hybrid learning is unknown. Children tested a year into the pandemic, after receiving instruction through varying educational methods, may score differently than those tested earlier. Future research can address these gaps. Although it is encouraging that academic functioning was not disproportionately impacted during the pandemic in this sample, children with epilepsy are at-risk for generalized academic difficulties and continued monitoring of academic functioning is necessary.

White matter hyperintensities (WMH) are a radiological marker of small vessel cerebrovascular disease that are related to cognition and memory decline in aging and Alzheimer’s disease (AD). However, the mechanisms that link WMH to memory impairment and whether they interact with or act independently of AD pathophysiology are unclear. The transentorhinal cortex (BA35) is among the earliest anatomical regions to show tau deposition and subsequent atrophy, and baseline posterior WMH is related to longitudinal cortical thinning of the entorhinal cortex. However, it is unclear whether regional WMH are related to BA35 volume specifically, and whether this relationship is influenced by amyloid-β (Aβ) burden. We hypothesized that WMH in the vascular territory of the posterior cerebral artery (PCA), which perfuses both posterior and medial temporal lobe regions, would be associated with reduced BA35 volume and with lower memory in older adults independently of Aβ.

114 older adults without dementia, aged 60 to 98 years (mean (SD) = 78.31 (11.02), 71 (62.8%) women), were included. Regional WMH volumes were derived from T2-FLAIR images using ANTs, a vascular territory atlas and manual editing. Global Aβ was assessed with 18F-florbetapir PET, using SUVR of a cortical composite region (FBP mean SUVR) with a cerebellar reference region. Total transentorhinal (BA35) volume was derived using T1 and T2-weighted images using ASHS. To assess hippocampal pattern separation ability, an index of episodic memory, participants completed both object (MDT-O) and spatial (MDT-S) versions of a mnemonic discrimination task, with the lure discrimination index as the outcome. Using linear regressions, we first tested for associations among PCA-defined WMH, Aβ, BA35 volume, and MDT-S and MDT-O scores. We then tested whether the relationship between PCA-defined WMH and MDT-O performance was mediated by BA35 volume and whether this mediation was moderated by Aβ. All models adjusted for age, sex, and education.

PCA-defined WMH were related to higher FBP mean SUVR (b=0.287, p=0.042) and lower BA35 volume (b=-0.222, p=0.038). PCA-defined WMH were also negatively related to MDT-O performance (b=-0.229, p=0.044), but not to MDT-S (b=-0.171, p=0.118). FBP mean SUVR was not related to BA35 volume (b=-0.131, p=0.344) or MDT performance (MDT-S: b=-0.138, p=0.348; MDT-O: b=0.059, p=0.690). Furthermore, FBP mean SUVR did not interact with PCA-defined WMH to predict memory performance (interaction b=-0.039, p=0.973), nor BA35 volume (interaction b=-0.140, p=0.894). The association of PCA-defined WMH to MDT-O was fully mediated by BA35 volume (indirect effect b=-0.0005, 95% CI (-0.0014, -0.0003)). This mediation was not moderated by FBP mean SUVR (indirect effect b=-0.00001, 95% CI (-0.001, 0.001)).

We found that PCA-defined WMH were related to memory performance in older adults, and this association is fully mediated by transentorhinal volume. While PCA-defined WMH are related to higher global Aβ burden, there is no interaction between PCA-defined WMH and Aβ on BA35 volume. These findings point to an amyloid-independent vascular pathway towards memory decline in aging and AD. Future work should examine whether the pathway linking PCA-defined WMH to transentorhinal cortex atrophy and subsequent memory decline is mediated by regional tau pathology.

The Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Database Project is a multisite collaborative that includes neuropsychological evaluations of children presenting for epilepsy surgery. There is some evidence for specific neuropsychological phenotypes within epilepsy (Hermann et al, 2016); however, this is less clear in pediatric patients. As a first step, we applied an empirically-based subtyping approach to determine if there were specific profiles using indices from the Wechsler scales [Verbal IQ (VIQ), Nonverbal IQ (NVIQ), Processing Speed Index (PSI), Working Memory Index (WMI)]. We hypothesized that there would be at least four profiles that are distinguished by slow processing speed and poor working memory as well as profiles with significant differences between verbal and nonverbal reasoning abilities.

Our study included 372 children (M=12.1 years SD=4.1; 77.4% White; 48% male) who completed an age-appropriate Wechsler measure, enough to render at least two index scores. Epilepsy characteristics included 84.4% with focal epilepsy (evenly distributed between left and right focus) and 13.5% with generalized or mixed seizure types; mean age of onset = 6.7 years, SD = 4.5; seizure frequency ranged from daily to less than monthly; 53% had structural etiology; 71% had an abnormal MRI; and mean number of antiseizure medications was two. Latent profile analysis was used to identify discrete underlying cognitive profiles based on intellectual functioning. Demographic and epilepsy characteristics were compared among profiles.

Based on class enumeration procedures, a 3-cluster solution provided the best fit for the data, with profiles characterized by generally Average, Low Average, or Below Average functioning. 32.8% were in the Average profile with mean index scores ranging from 91.7-103.2; 47.6% were in the Low Average profile with mean index ranging from 80.7 to 84.5; and 19.6% were in the Below Average profile with mean index scores ranging from 55.0-63.1. Across all profiles, the lowest mean score was the PSI, followed by WMI. VIQ and NVIQ represented relatively higher scores for all three profiles. Mean discrepancy between indices within a profile was as large as 11.5 IQ points. No demographics or epilepsy characteristics were significantly different across cognitive phenotypes.

Latent cognitive phenotypes in a pediatric presurgical cohort were differentiated by general level of functioning; however, across profiles, processing speed was consistently the lowest index followed by working memory. These findings across phenotypes suggest a common relative weakness which may result from a global effect of antiseizure medications and/or the widespread impact of seizures on neural networks even in a largely focal epilepsy cohort; similar to adult studies with temporal lobe epilepsy (Hermann et al, 2007). Future work will use latent profile analysis to examine phenotypes across other domains relevant to pediatric epilepsy including attention, naming, motor, and memory functioning. These findings are in line with collaborative efforts towards cognitive phenotyping which is the aim of our PERC Epilepsy Surgery Database Project that has already established one of the largest pediatric epilepsy surgery cohorts.

Children with epilepsy are at greater risk of lower academic achievement than their typically developing peers (Reilly and Neville, 2015). Demographic, social, and neuropsychological factors, such as executive functioning (EF), mediate this relation. While research emphasizes the importance of EF skills for academic achievement among typically developing children (e.g., Best et al., 2011; Spiegel et al., 2021) less is known among children with epilepsy (Ng et al., 2020). The purpose of this study is to examine the influence of EF skills on academic achievement in a nationwide sample of children with epilepsy.

Participants included 427 children with epilepsy (52% male; MAge= 10.71), enrolled in the Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Database who had been referred for surgery and underwent neuropsychological testing. Academic achievement was assessed by performance measures (word reading, reading comprehension, spelling, and calculation and word-based mathematics) and parent-rating measures (Adaptive Behavior Assessment System (ABAS) Functional Academics and Child Behavior Checklist (CBCL) School Performance). EF was assessed by verbal fluency measures, sequencing, and planning measures from the Delis Kaplan Executive Function System (DKEFS), NEPSY, and Tower of London test. Rating-based measures of EF included the 'Attention Problems’ subscale from the CBCL and 'Cognitive Regulation’ index from the Behavior Rating Inventory of Executive Function (BRIEF-2). Partial correlations assessed associations between EF predictors and academic achievement, controlling for fullscale IQ (FSIQ; A composite across intelligence tests). Significant predictors of each academic skill or rating were entered into a two-step regression that included FSIQ, demographics, and seizure variables (age of onset, current medications) in the first step with EF predictors in the second step.

Although zero-order correlations were significant between EF predictors and academic achievement (.29 < r’s < .63 for performance; -.63 < r’s < -.50 for rating measures), partial correlations controlling for FSIQ showed fewer significant relations. For performance-based EF, only letter fluency (DKEFS Letter Fluency) and cognitive flexibility (DKEFS Trails Condition 4) demonstrated significant associations with performance-based academic achievement (r’s > .29). Regression models for performance-based academic achievement indicated that letter fluency (ß = .22, p = .017) and CBCL attention problems (ß = -.21, p =.002) were significant predictors of sight-word reading. Only letter fluency (ß = .23, p =.006) was significant for math calculation. CBCL Attention Problems were a significant predictor of spelling performance (ß = -.21, p = .009) and reading comprehension (ß = -.18, p =.039). CBCL Attention Problems (ß = -.38, p <.001 for ABAS; ß = -.34, p =.002 for CBCL School) and BRIEF-2 Cognitive Regulation difficulties (ß = -.46, p < .001 for ABAS; ß = -.46, p =.013 for CBCL School) were significant predictors of parent-rated ABAS Functional Academics and CBCL School Performance.

Among a national pediatric epilepsy dataset, performance-based and ratings-based measures of EF predicted performance academic achievement, whereas only ratings-based EF predicted parent-rated academic achievement, due at least in part to shared method variance. These findings suggest that interventions that increase cognitive regulation, reduce symptoms of attention dysfunction, and promote self-generative, flexible thinking, may promote academic achievement among children with epilepsy.

Pediatric patients with frontal lobe epilepsy (FLE) have higher rates of attention deficit hyperactivity disorder (ADHD), as well as executive functioning (EF) and fine motor (FM) challenges. Relations between these constructs have been established in youth with ADHD and are supported by FM and EF skill involvement in frontal-subcortical systems. Still, they are not well understood in pediatric FLE. We hypothesized that poorer FM performance would be related to greater executive dysfunction and ADHD symptomatology in this group.

47 children and adolescents with FLE (AgeM=12.47, SD=5.18; IQM=84.07; SD=17.56; Age of Seizure OnsetM=6.85, SD=4.64; right-handed: n=34; left-handed: n=10; Unclear: n=3) were enrolled in the Pediatric Epilepsy Research Consortium dataset as part of their phase I epilepsy surgical evaluation. Participants were selected if they had unifocal FLE and completed the Lafayette Grooved Pegboard (GP). Seizure lateralization (left-sided: n=19; right-sided: n=26; bilateral: n=2) and localization were established via data (e.g., EEG, MRI) presented at a multidisciplinary team case conference. Patients completed neuropsychological measures of FM, attention, and EF. Parents also completed questionnaires inquiring about their child’s everyday EF and ADHD symptomatology. Correlational analyses were conducted to examine FM, EF, and ADHD relations.

Dominant hand (DH) manual dexterity (GP) was related to parent-reported EF (Behavior Rating Inventory of Executive Function, Second Edition [BRIEF-2]-Global Executive Composite [GEC]: r(15) =-.70, p<.01, d=1.96). While not statistically significant, medium to large effect sizes were found for GP DH and parent-reported inattention (Behavior Assessment System for Children, Third Edition [BASC-3]-Attention Problems: r(12)=-.39, p=.17, d=.85) and hyperactivity/impulsivity (BASC-3-Hyperactivity: r(11)= -.44, p=.13, d=.98), as well as performance-based attention (Conners Continuous Performance Test, Third Edition -Omission Errors: r(12)=-.35, p=.22, d=.41), working memory (Wechsler Intelligence Scale for Children - Fifth Edition [WISC-V]-Digit Span [DS]: r(19)=.38, p=.09, d=.82) and cognitive flexibility (Delis-Kaplan Executive Function System (D-KEFS) Verbal Fluency Category Switching: r(13)=.46, p=.08, d=1.04); this suggests that these relations may exist but that our study was underpowered to detect them. Non-dominant hand (NDH) manual dexterity was related to performance-based working memory (WISC-V-DS: r(19)=.50, p<.01, d=1.12) and cognitive flexibility (D-KEFS-Trails Making Test Number-Letter Switching: r(17)=.64, p<.01, d=1.67). Again, while underpowered, medium to large effect sizes were found for GP NDH and parent-reported EF (BRIEF-2 GEC: r(15) =-.45, p=.07, d=1.01) and performance-based phonemic fluency (D-KEFS-Letter Fluency: r(13)=.31, p=.20, d=.65).

Our findings suggest that FM, EF, and ADHD are related in youth with FLE; however, these relations appear to vary by skill and hand. We posit that our findings are due in part to the frontal-cerebellar networks given their anatomic proximity between frontal motor areas and the dorsolateral prefrontal cortex - as well as their shared functional involvement in these networks. Future studies should evaluate the predictive validity of initial FM skills for later executive dysfunction and ADHD symptomatology in FLE. If such relations emerge, contributions of early FM interventions on EF development should be examined. Further replication of these findings with a larger sample is warranted.

During the COVID-19 pandemic, care for the elderly in the community was greatly limited. Accordingly, the demand for alternative community care have increased to cope with changing situations.

In this study, we tried to find out whether the companion robot improved mood state and related problem in depressive or isolated community dwelling elderly

For 186 community dwelling elderly who have received social welfare service due to depression or social isolation, we provided companion robot that could support their daily living. The robot was equipped with special program that could recognize and respond to the participant’s own emotion. It was part of behavioral activation techniques which is one of powerful treatment for depression. The self-report questionnaires were used to measure changes in cognitive function, depression, suicidality, loneliness, resilience and satisfaction of life. Outcomes were measured before using companion robot and after 3 months, and we compared them.

The elderly using companion robot for 3 months showed improved cognitive function (45.7% to 30.1%), depression (p<0.001), suicidality(p<0.001), and loneliness (p=0.033) in the self-report questionnaire. Resilience(p=0.749) and satisfaction of life (p=0.246) were also improved but not reached significance.

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These findings showed that the use of companion robot with emotional recognition coaching program could help improve depression, cognitive function, loneliness and suicidal ideation. In particular, this effect was also useful for those who were diagnosed with depression. Also if we can put more techniques of behavioral activation programs into robot, it could be useful in community care for depressive and isolated elderly.

None Declared

Maintaining a good sleep-wake cycle is an important factor for the prognosis and management of bipolar disorder. However, studies on the to various technological advances including smartphoe usage affecting inter-episodic sleep quality are yet relatively less thoroughly investigated.

This study aims to identify the association between smartphone usage and inter-episodic sleep quality of bipolar patients.

A total 52 Bipolar I or II subjects who were euthymic for at lest 6 months were included in this analysis. Pearson correlation analysis was used to examine the association among psychological assessments, including the Pittsburgh Sleep Quality Index (PSQI-K), Smartphone Addiction Scale (SAS), Hamilton Depression Rating Scale (K-HDRS), Young Mania Rating Scale (K-YMRS), and Multidimensional Scale of Perceived Social Support (MDPSS). Significant results were then analyzed using a multiple linear regression analysis with PSQI-K as the dependent variable to assess the impact of clinical variables on sleep quality.

PSQI-K was positively correlated with SAS (r = 0.457, p < 0.001), K-HDRS (r = 0.447, p < 0.001), and negatively correlated with MDPSS (r = -0.336, p < 0.05). Smartphone use, depressive symptoms, and perceived social support seemed to explain 35.7% of sleep quality. After adjusting for confounders, more smartphone use and more severe depressive symptoms were associated with poor sleep quality (SAS: β = 0.383, p = 0.002; K-HDRS: β = 0.339, p = 0.006), but perceived social support did not reach statistical significance (MDPSS: β = -0.204, p = 0.086).

The results of this study show that the more a person uses a smartphone, the worse their sleep is. This effect is significant, even when other factors are taken into account. These results support the possibility that improving the degree of smartphone use could be an essential intervention target for improving sleep quality during the inter-episode period in patients with bipolar disorder.

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