Association between consumption of nonessential energy-dense food and body mass index among Mexican school-aged children: a prospective cohort study.

BACKGROUND/OBJECTIVES: Obesity prevalence in Mexican children has increased rapidly and is among the highest in the world. We aimed to estimate the longitudinal association between nonessential energy-dense food (NEDF) consumption and body mass index (BMI) in school-aged children 5 to 11 years, using a cohort study with 6 years of follow-up. SUBJECTS/METHODS: We studied the offspring of women in the Prenatal omega-3 fatty acid supplementation, child growth, and development (POSGRAD) cohort study. NEDF was classified into four main groups: chips and popcorn, sweet bakery products, non-cereal based sweets, and ready-to-eat cereals. We fitted fixed effects models to assess the association between change in NEDF consumption and changes in BMI. RESULTS: Between 5 and 11 years, children increased their consumption of NEDF by 225 kJ/day (53.9 kcal/day). In fully adjusted models, we found that change in total NEDF was not associated with change in children's BMI (0.033 kg/m2, [p = 0.246]). However, BMI increased 0.078 kg/m2 for every 418.6 kJ/day (100 kcal/day) of sweet bakery products (p = 0.035) in fully adjusted models. For chips and popcorn, BMI increased 0.208 kg/m2 (p = 0.035), yet, the association was attenuated after adjustment (p = 0.303). CONCLUSIONS: Changes in total NEDF consumption were not associated with changes in BMI in children. However, increases in the consumption of sweet bakery products were associated with BMI gain. NEDF are widely recognized as providing poor nutrition yet, their impact in Mexican children BMI seems to be heterogeneous.

Pixels and perception: Mapping the association between digital media and psychotic-like experiences in adolescents.

INTRODUCTION: Psychotic-like experiences (PLEs) during adolescence can lead to psychotic disorders. Digital media usage has been suggested to link to PLEs, but research is limited on how different types of screen exposure may differentially relate to PLEs over time. This study aimed to examine longitudinal associations between screen usage patterns and PLEs in adolescents. METHODS: Participants comprised 11,876 adolescents assessed annually from ages 9-12 years as part of the Adolescent Brain Cognitive Development study (ABCD). Screen usage (TV, video games, online video, social media, texting, video chat) and PLEs were assessed via self-report. Longitudinal network analysis models were estimated to examine connections between screen usage types and PLEs across three time points. RESULTS: Two clusters were formed, including digital media for socializing (e.g., social media/texting/video chat) and digital media for entertainment (e.g., online video/video games/TV). Texting and online video(s) had the highest centrality at each time point, suggesting importance in the network. PLE symptoms of hallucinations and concentration difficulties exhibited higher centrality than other symptoms. Online video and TV were influential bridges between screen usage and PLEs. Network structure significantly differed between ages 9-10 and 10-12 years, but global strength was unchanged over time. DISCUSSION: Results highlight the importance of understanding the associations between specific screen usage types and PLE symptoms. Texting and online video usage appear most influential in the development of adolescent PLEs over time. Findings can inform targeted interventions to promote healthy screen habits and reduce PLEs in at-risk youth.

Comparative transcriptomics revealed parallel evolution and innovation of photosymbiosis molecular mechanisms in a marine bivalve.

Photosymbioses between heterotrophic hosts and autotrophic symbionts are evolutionarily prevalent and ecologically significant. However, the molecular mechanisms behind such symbioses remain less elucidated, which hinders our understanding of their origin and adaptive evolution. This study compared gene expression patterns in a photosymbiotic bivalve (Fragum sueziense) and a closely related non-symbiotic species (Trigoniocardia granifera) under different light conditions to detect potential molecular pathways involved in mollusc photosymbiosis. We discovered that the presence of algal symbionts greatly impacted host gene expression in symbiont-containing tissues. We found that the host immune functions were suppressed under normal light compared with those in the dark. In addition, we found that cilia in the symbiont-containing tissues play important roles in symbiont regulation or photoreception. Interestingly, many potential photosymbiosis genes could not be annotated or do not exhibit orthologues in T. granifera transcriptomes, indicating unique molecular functions in photosymbiotic bivalves. Overall, we found both novel and known molecular mechanisms involved in animal-algal photosymbiosis within bivalves. Given that many of the molecular pathways are shared among distantly related host lineages, such as molluscs and cnidarians, it indicates that parallel and/or convergent evolution is instrumental in shaping host-symbiont interactions and responses in these organisms.

Flexibility in coral-algal symbiosis is positively correlated with the host geographic range.

Generalists are thought to adapt to broader ecological conditions compared to less flexible specialists. However, few studies have systematically tested what ecological or life-history traits are associated with organisms' ecological flexibility. Here, we used stony corals to test the relative effects of host traits and ecological factors on corals' flexibility to form photosymbioses with algae. We analysed data from 211 stony coral species to test if coral's geographic distribution, depth range, symbiont transmission mode or colony morphology predict coral-algal flexibility. We report a novel positive correlation between coral-algal flexibility and coral species' geographic range. Symbiont transmission mode was also a predictor of flexibility, albeit the result is less robust against sampling bias. Coral depth range and morphology did not show significant effects. We highlight that host-symbiont dispersal abilities, interactions and evolutionary histories likely contribute to the observed patterns. We urge conservation efforts to consider the ecological implications of coral-algal flexibility.

Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning.

Background and aims: Gaming disorder [GD] risk has been associated with the way gamers bond with their visual representation (i.e., avatar) in the game-world. More specifically, a gamer's relationship with their avatar has been shown to provide reliable mental health information about the user in their offline life, such as their current and prospective GD risk, if appropriately decoded. Methods: To contribute to the paucity of knowledge in this area, 565 gamers (Mage = 29.3 years; SD =10.6) were assessed twice, six months apart, using the User-Avatar-Bond Scale (UABS) and the Gaming Disorder Test. A series of tuned and untuned artificial intelligence [AI] classifiers analysed concurrently and prospectively their responses. Results: Findings showed that AI models learned to accurately and automatically identify GD risk cases, based on gamers' reported UABS score, age, and length of gaming involvement, both concurrently and longitudinally (i.e., six months later). Random forests outperformed all other AIs, while avatar immersion was shown to be the strongest training predictor. Conclusion: Study outcomes demonstrated that the user-avatar bond can be translated into accurate, concurrent and future GD risk predictions using trained AI classifiers. Assessment, prevention, and practice implications are discussed in the light of these findings.

Identifying self-disclosed anxiety on Twitter: A natural language processing approach.

BACKGROUND: Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis. METHODS: A total of 233.000 tweets made by 605 users (300 reporting anxiety diagnosis and 305 not) over six months were comparatively analysed, considering user behavior, Linguistic Inquiry Word Count (LIWC), and sentiment analysis. Twitter users with a self-disclosed diagnosis of anxiety were classified as 'anxious' to facilitate group comparisons. RESULTS: Supervised machine learning models showed a high prediction accuracy (Naïve Bayes 81.1 %, Random Forests 79.8 %, and LASSO-regression 79.4 %) in identifying Twitter users' self-disclosed diagnosis of anxiety. Additionally, a Latent Profile Analysis (LPA) identified four profiles characterized by high sentiment (31 % anxious participants), low sentiment (68 % anxious), self-immersed (80 % anxious), and normative behavior (38 % anxious). CONCLUSION: The digital footprint of self-disclosed anxiety on Twitter posts presented a high frequency of words conveying either negative sentiment, a low frequency of positive sentiment, a reduced frequency of posting, and lengthier texts. These distinct patterns enabled highly accurate prediction of anxiety diagnosis. On this basis, appropriately resourced, awareness raising, online mental health campaigns are advocated.

Mapping the links between sexual addiction and gambling disorder: A Bayesian network approach.

Contemporary literature and recent classification systems have expanded the field of addictions to include problematic behaviours such as gambling and sexual addiction. However, conceptualisation of behavioural addictions is poorly understood and gender-based differences have emerged in relation to how these behaviours are expressed. The current research conducted partial-correlation and Bayesian network analyses to assess the symptomatic structure of gambling disorder and sexual addiction. Convenience community sampling recruited 937 adults aged 18 to 64 years (315 females, Mage = 30.02; 622 males, Mage = 29.46). Symptoms of problematic behaviours were measured using the Online Gambling Disorder Questionnaire (OGDQ) and the Bergen Yale Sex Addiction Scale (BYSAS). Results indicate distinct gender-based differences in the symptom networks of sexual addiction and gambling disorder, with a more complex network observed amongst men for both conditions. Addiction salience, withdrawal and dishonesty/deception were important components of the addictive network. Interpersonal conflict was more central for women while intrapsychic conflict a more prominent issue for men. Differences in the two symptom networks indicate separate disorders as opposed to a single underlying construct. Treating practitioners and community initiatives aimed at addressing sexual addiction and disordered gambling should consider gender, when designing educational or therapeutic interventions.

Conceptualising social media addiction: a longitudinal network analysis of social media addiction symptoms and their relationships with psychological distress in a community sample of adults.

BACKGROUND: Problematic social media use has been identified as negatively impacting psychological and everyday functioning and has been identified as a possible behavioural addiction (social media addiction; SMA). Whether SMA can be classified as a distinct behavioural addiction has been debated within the literature, with some regarding SMA as a premature pathologisation of ordinary social media use behaviour and suggesting there is little evidence for its use as a category of clinical concern. This study aimed to understand the relationship between proposed symptoms of SMA and psychological distress and examine these over time in a longitudinal network analysis, in order better understand whether SMA warrants classification as a unique pathology unique from general distress. METHOD: N = 462 adults (Mage = 30.8, SDage = 9.23, 69.3% males, 29% females, 1.9% other sex or gender) completed measures of social media addiction (Bergen Social Media Addiction Scale), and psychological distress (DASS-21) at two time points, twelve months apart. Data were analysed using network analysis (NA) to explore SMA symptoms and psychological distress. Specifically, NA allows to assess the 'influence' and pathways of influence of each symptom in the network both cross-sectionally at each time point, as well as over time. RESULTS: SMA symptoms were found to be stable cross-sectionally over time, and were associated with, yet distinct, from, depression, anxiety and stress. The most central symptoms within the network were tolerance and mood-modification in terms of expected influence and closeness respectively. Depression symptoms appeared to have less of a formative effect on SMA symptoms than anxiety and stress. CONCLUSIONS: Our findings support the conceptualisation of SMA as a distinct construct occurring based on an underpinning network cluster of behaviours and a distinct association between SMA symptoms and distress. Further replications of these findings, however, are needed to strengthen the evidence for SMA as a unique behavioural addiction.

Exploratory structural equation modeling: a streamlined step by step approach using the R Project software.

Confirmatory Factor Analysis (CFA) has been a popular yet limited approach to assessing latent factor structures. Despite items rarely loading exclusively on one latent factor in multifactorial scales, CFA assumes all indicators/items should load uniquely on their allocated latent dimensions. To address this weakness, Exploratory Structural Equation Modeling (ESEM) combines exploratory factor analyses (EFA) and CFA procedures, allowing cross-loadings to occur when assessing hypothesized models. Although such advantages have enhanced ESEM popularity, its adoption is often limited by software rigidity and complex coding difficulties. To address these obstacles, the current tutorial presents a streamlined, step-by-step approach using the open-source software R while providing both R and Mplus ESEM syntax. The tutorial demonstrates the sequence of the ESEM stages by examining the frequently debated Strengths and Difficulties Questionnaire (SDQ) factor structure, using openly accessible data from the Longitudinal Study of Australian Children (LSAC). As ESEM may allow a better understanding of the complex associations in multidimensional scales, this tutorial may optimize the epidemiological and clinical assessment of common yet multifaceted psychiatric presentations.

Psychometric properties of the Bergen Social Media Addiction Scale: An analysis using item response theory.

Background: Social media use has become an everyday behavior in contemporary life resulting in increased participation. A minority of individuals, especially younger adults, may engage excessively with the medium, resulting in the emergence of problematic social media use (PSMU). One way of assessing PSMU is by administering the Bergen Social Media Addiction Scale (BSMAS). The present study investigated the psychometric properties and prevalence of the BSMAS using Item Response Theory (IRT). Additionally, it evaluated risk factors such as gender and age. Methods: A relatively large community sample (N = 968, Mage  = 29.5 years, SD = 9.36, 32.5% women) completed the BSMAS online. Results: IRT analyses showed differences regarding the BSMAS items' discrimination, difficulty, and reliability capacities, with a raw score exceeding 26 (out of 30) indicating a higher risk of PSMU (n = 11; 1.1%). Females and younger participants were at greater risk of developing PSMU. Conclusion: The BSMAS functions as a reliable measure of PSMU, particularly between average to high levels of the trait. Additionally, younger participants were shown to be at higher risk of PSMU suggesting that prevention and intervention protocols should focus on this group.

Suicidal behaviors in the entertainment industry: a preliminary exploration of the interplay between work scheduling, social support, and wellbeing in Australia.

OBJECTIVE: Workers of the Australian entertainment industry exhibit disproportionately high rates of impaired psychological wellbeing and suicidal behaviors, with such rates being exacerbated by the negative impact of working long and odd hours (Work Scheduling Impact; WSI). Nonetheless, stable and secure social support networks may buffer the risks associated with such systemic difficulties. METHODS: The responses of 1302 Australian entertainment industry workers (50.3% females, Mage 38.39 years) on the Multidimensional Scale of Perceived Social Support, the Short Form Health Survey, WSI, and suicidal behaviors questions were examined via moderation analyses. RESULTS: Higher social support and lower WSI appeared to reduce the suicidal ideation of those experiencing poorer mental health, while lower WSI further enhanced social support's positive effect. CONCLUSIONS: Findings highlight the likely detrimental effect of WSI regarding the suicidal ideation reported by vulnerable Australian entertainment industry workers and stress the importance of the social support they experience. PUBLIC HEALTH IMPLICATIONS: Interventions attempting to increase social support could improve inherent conditions associated with the Australian entertainment industry. Similarly, the negative effect of working long and odd hours on workers' mental health and suicidal behaviors indicates the need to regulate the industry appropriately.

The Online Flow Questionnaire: An Item Response Theory Examination.

Online flow refers to the rate of an individual's absorbance in an Internet activity in which they are engaged. It has been implicated with both the effectiveness of cyberhealth and online education applications, as well as excessive Internet use. One way of assessing it is the Online Flow Questionnaire (OFQ). Consequently, this study investigated the optimum measurement of online flow, as well as OFQ cutoff points, using Item Response Theory (IRT). A large sample of high school students from Greece (N = 1579, Mage = 16.12, SDage = 0.85; 50.5 percent females) completed the OFQ and the data were analyzed using IRT procedures. The analysis indicated that items in the OFQ possess differing levels of discrimination and difficulty, although all items were generally within acceptable ranges. An OFQ cutoff score of 5 represented an extremely high level of online flow experiences. The findings suggest that the OFQ generally functions as an acceptable marker of overall online flow. However, the current format of the OFQ appears to inhibit its ability to detect variability at the extreme low and high ends of the latent trait in the population assessed. Future revisions (potentially employing computerized adaptive tests) of the OFQ response format may enhance its utility.

Online Gambling Disorder Questionnaire (OGD-Q): An item r'esponse theory examination.

Gambling disorder behaviours, such as one's preoccupation with gambling and/or mood modification due to gambling, have been proposed to differ in their diagnostic weight/importance, especially when informing diagnostic scales. Such potential differences are imperative to be considered to improve assessment accuracy. The latter is particularly important in the light of the rapidly increasing gambling opportunities offered online. To contribute to this area of knowledge, the current study assessed an online adult community sample (N = 968, Mage  = 29.5 years, SDage  = 9.36 years) regarding their responses on the Online Gambling Disorder Questionnaire (OGD-Q). Item response theory (IRT) procedures examined the psychometric properties of the instrument, at both the item and the scale level. Results indicated that the OGD-Q demonstrated good capacity to reliably assess problem gambling and differentiate between individuals at similar levels of the trait, particularly between 1 and 3 SDs above the mean. The findings also showed OGD-Q components/items possess varying discrimination capacities, whilst they also differ in reliability across respondents with different levels of disordered gambling behaviours. Thus, it is supported that consideration is required regarding the differential weighting of one's item responses in the assessment procedure, taking concurrently into account their severity of disordered gambling behaviours.

Problematic Shopping Behavior: An Item Response Theory Examination of the Seven-Item Bergen Shopping Addiction Scale.

There has been an increasing amount of research examining problematic shopping behavior (PSB), often referred to in the psychological literature as "compulsive buying" or "shopping addiction." A popular scale for assessing the risk of PSB is the seven-item Bergen Shopping Addiction Scale (BSAS). To expand our knowledge of the psychometric properties of this instrument, the present study employed Item Response Theory (IRT) and differential item functioning analyses (DIF) while concurrently attempting to determine a preliminary cut-off point. A relatively large community sample completed the BSAS online (N = 968, M age = 29.5 years, SD age = 9.36, 32.5% women). IRT analyses showed differences regarding the BSAS items' discrimination, difficulty, and precision, with a raw score exceeding 23 (out of 28) indicating a higher risk of shopping addiction. Finally, while most BSAS items operated equally among males and females, Item 2 (mood modification) required a higher level of shopping addiction behaviors to be endorsed by males. The BSAS functions as a reliable assessment of the risk of shopping addiction, particularly between average and high levels of the trait. Clinical implications are discussed in light of these findings.

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence.

BACKGROUND: This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively. AIMS: Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology. RESULTS: Overall, 118 studies were assessed as eligible. Considering the terms employed, "EMA", "ESM", and "DP" were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps' information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales. CONCLUSIONS: Findings suggest links between a person's digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person's broader contextual and developmental circumstances in relation to their digital data/records.

Unravelling the web of addictions: A network analysis approach.

Common elements across different forms of addiction suggest the possibility of comorbid addictions, as well as the transition/replacement of one form of addiction with another. This study aimed to conduct a Network analysis of symptoms of 10 forms of addictive behaviors to examine their behavioral commonalities/ interrelations. Methods: To address this aim, an online community sample of 968 adult participants (33.6% women, 66.4% men) completed self-rating questionnaires covering a range of addictive behaviors including alcohol, drugs, tobacco, sex, online gambling, internet use, internet gaming, social media use, shopping, and exercise. Their responses were examined with regularized partial correlation network analysis (EBICglasso) and a community detection algorithm (Walktrap) to identify: (a) specific links between neighboring forms of addiction; and (b) clustering of symptoms of addiction. Results: Findings showed positive network connections across different addictive behaviors, with addictive tendencies towards gambling showing the highest centrality, sequentially followed by addictive tendencies towards internet use, internet gaming, alcohol, shopping, social media use, drugs, sex, smoking, and exercise. Conclusion: Symptoms associated with disordered drug use and gambling are suggested to maintain severity of addictive disorders and increase the likelihood of developing cross addictive behaviors. Clinical implications for the assessment and treatment of addiction comorbidities and the replacement of one form of addiction with another are discussed considering these findings.

Warwick Edinburgh Mental Well-Being Scale (WEMWBS): measurement invariance across genders and item response theory examination.

BACKGROUND: The Warwick Edinburgh Mental Well-Being Scale (WEMWBS) is a measure of subjective well-being and assesses eudemonic and hedonic aspects of well-being. However, differential scoring of the WEMWBS across gender and its precision of measurement has not been examined. The present study assesses the psychometric properties of the WEMWBS using measurement invariance (MI) between males and females and item response theory (IRT) analyses. METHOD: A community sample of 386 adults from the United States of America (USA), United Kingdom, Ireland, Australia, New Zealand, and Canada were assessed online (N = 394, 54.8% men, 43.1% women, Mage = 27.48, SD = 5.57). RESULTS: MI analyses observed invariance across males and females at the configural level and metric level but non-invariance at the scalar level. The graded response model (GRM) conducted to observe item properties indicated that all items demonstrated, although variable, sufficient discrimination capacity. CONCLUSIONS: Gender comparisons based on WEMWBS scores should be cautiously interpreted for specific items that demonstrate different scalar scales and similar scores indicate different severity. The items showed increased reliability for latent levels of ∓ 2 SD from the mean level of SWB. The WEMWBS may also not perform well for clinically low and high levels of SWB. Including assessments for clinical cases may optimise the use of the WEMWBS.

Body Appreciation Scale (BAS-2): measurement invariance across genders and item response theory examination.

BACKGROUND: The present study considers a measure of positive body image, the Body Appreciation Scale-2, which assesses acceptance and/or favourable opinions towards the body (BAS-2). Potential variations of the psychometric properties of the scale across males and females, as well as across its different items invite for further investigation. The present study contributes to this area of knowledge via the employment of gender Measurement Invariance (MI) and Item Response Theory (IRT) analyses. METHODS: A group of 386 adults from Australia, Canada, New Zealand, Ireland, the United Kingdom, and the United States of America (USA) were assessed online (N = 394, 54.8% men, 43.1% women, Mage = 27.48; SD = 5.57). RESULTS: MI analyses observed invariance across males and females at the configural level, and non-invariance at the metric level. Further, the graded response model employed to observe IRT properties indicated that all items demonstrated, although variable, strong discrimination capacity. CONCLUSIONS: The items showed increased reliability for latent levels of ∓ 2 SD from the mean level of Body Appreciation (BA). Gender comparisons based on BAS-2 should be cautiously interpreted for selected items, due to demonstrating different metric scales and same scores indicating different severity. The BAS-2 may also not perform well for clinically low and high BA levels. Thus, it should optimally be accompanied by clinical interviews for formal assessment in such cases.

Symptom Checklist-90-Revised: A structural examination in relation to family functioning.

The accurate assessment of psychopathological behaviours of adolescents and young adults is imperative. Symptom Checklist-90-Revised (SCL-90-R) is one of the most comprehensive and widely used scales addressing this purpose internationally. Interestingly, associations between the different SCL-90 symptoms and family functioning have been highlighted. Nevertheless, the scale's factorial structure has often been challenged. To contribute in this area, this study scrutinizes the psychopathological dimensions of the Symptom Checklist-90-Revised (SCL-90-R) in a large cohort of high school students (Mean age = 16.16; SD = .911) from Greece. It addresses this aim by: a) using first order and bi-factor confirmatory factor analysis, and exploratory structural equation models and; b) investigating the factors' associations with family functioning. A total of 2090 public Greek High School students completed the SCL-90-R and the Family Adaptability and Cohesion Scale IV (FACES-IV) covering family functioning, satisfaction and communication. Six different solutions, yielded by separate permutations of CFA, ESEM, and bifactor models, were evaluated. Based on global fit, the clarity, reliabilities and the family functioning links of the dimensions in the models, the ESEM oblique model with the theorized nine factors emerged as the optimum. This model had adequate fit, and symptom dimensions were well defined. Also six of the nine factors demonstrated external associations with family functioning, satisfaction and communication. The clinical assessment benefits of these results are discussed.