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.

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.

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.

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, M_age 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, M_age = 16.12, SD_age = 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.

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

An amendment to this paper has been published and can be accessed via the original article.

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.

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.

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, M_age = 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, M_age = 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.

ADHD symptoms, the current symptom scale, and exploratory structural equation modeling: A psychometric study

The aim of the study was to use exploratory structural equation modelling (ESEM) to investigate support for an ADHD factor model with group factors for inattention (IA), hyperactivity (HY), and impulsivity (IM), as proposed in in ICD-10. A total of 202 adults (121 females and 81 males), aged between 18 and 35 years, from the general community, completed the Current Symptoms Scale (CSS). The results for the model showed good global fit, good convergent and divergent validities. However, the IA and IM factors, but not the HY factor, were clearly defined and demonstrated acceptable reliabilities. Taken together, these finding indicate that a revised ESEM model without the HY factor (i.e. with only the IA and IM symptoms) is an appropriate structure for modeling adult ratings of the ADHD behaviors described in the CSS. The taxonomic, theoretical and clinical implications of the findings for ADHD in general are discussed.

Hippocampal-sparing radiotherapy: the new standard of care for World Health Organization grade II and III gliomas?

The neurocognitive effects of cranial radiotherapy in patients with gliomas are well-recognised and may be related to the dose delivered to the hippocampi. Intensity modulated radiotherapy (IMRT) is a radiotherapy technique that can be used to selectively spare the hippocampi without compromising the dose delivered to the tumour. This study aimed to evaluate if hippocampal-sparing IMRT is achievable in patients with World Health Organization (WHO) grade II and III gliomas. A retrospective review of consecutive patients with WHO grade II and III gliomas treated with IMRT at our institution between January 2009 and August 2012 was performed. Hippocampal-sparing was defined as a mean dose to at least one hippocampus of less than 30 Gy. The dose delivered to the tumour was never compromised to achieve the hippocampal dose constraint. Logistic regression analyses were performed to identify predictive factors for achieving hippocampal-sparing treatment. Eighteen patients were identified and hippocampal-sparing was achieved in 14 (78%). The median dose prescribed was 59.4 Gy in 33 fractions and 11 patients had WHO grade III gliomas. The mean dose to the contralateral hippocampus was 24.9 Gy. Planning target volumes less than 420.5 cm3 were more likely to enable hippocampal-sparing treatment to be given (hazard ratio 1.7, p=0.03) and there was a trend with oligodendrogliomas and anaplastic oligodendrogliomas. Hippocampal-sparing radiotherapy is feasible in patients with WHO grade II and III gliomas. Oncologic outcomes are yet to be assessed prospectively. The relationship between hippocampal dose and neurocognitive function in adults is currently under investigation.