Overuse of the smartphone causes negative consequences on the health and behavior of younger people. It is necessary to know which factors can determine the problematic use of the smartphone. The aim of the present study was to explore the relationship between problematic smartphone use, attachment styles, and perceived family functioning in young adults. Three hundred and thirteen Spanish young adults took part in the study (255 women, 58 men) and completed the following instruments: the Smartphone Addiction Scale (SAS), the Relationship Questionnaire (RQ), the Parental Bonding Instrument (PBI), and the Family Adaptability and Cohesion Evaluation Scale (FACES IV). The results of the path analyses show that the cohesion and enmeshed functioning variables were the best predictors of problematic smartphone use. The preoccupied attachment scale was the only one whose score also showed indirect effects on problematic smartphone use through the variable of enmeshed family functioning.

In this paper, a general overview regarding neural recording, classical signal processing techniques and machine learning classification algorithms applied to monitor brain activity is presented. Currently, several approaches classified as electrical, magnetic, neuroimaging recordings and brain stimulations are available to obtain neural activity of the human brain. Among them, non-invasive methods like electroencephalography (EEG) are commonly employed, as they can provide a high degree of temporal resolution (on the order of milliseconds) and acceptable space resolution. In addition, it is simple, quick, and does not create any physical harm or stress to patients. Concerning signal processing, once the neural signals are acquired, different procedures can be applied for feature extraction. In particular, brain signals are normally processed in time, frequency, and/or space domains. The features extracted are then used for signal classification depending on its characteristics such us the mean, variance or band power. The role of machine learning in this regard has become of key importance during the last years due to its high capacity to analyze complex amounts of data. The algorithms employed are generally classified in supervised, unsupervised and reinforcement techniques. A deep review of the most used machine learning algorithms and the advantages/drawbacks of most used methods is presented. Finally, a study of these procedures utilized in a very specific and novel research field of electroencephalography, i.e., autobiographical memory deficits in schizophrenia, is outlined.

Young adulthood is the life stage during which people are more prone to develop problematic smartphone use (PSU). Only one study investigated the relationship among attachment styles, family functioning, and PSU, but thus far, no research has shown the relative importance that such dimensions may have on PSU. The main aim of this study was to analyze to what extent insecure attachment styles and unbalanced family functioning are related to PSU, investigating the specific weight of each dimension in a sample of young adults (N = 301; 82.7% females; Mage = 22.89; SD = 3.02). Participants completed a self-report questionnaire, including the Relationship Questionnaire, the Family Adaptability and Cohesion Evaluation Scale IV, and the Smartphone Addiction Scale. The regression and relative weight analyses results showed that preoccupied attachment style and disengaged, chaotic, and enmeshed family functioning were positively related to PSU. Implications for future research and interventions were discussed.

Previous research with adults has shown mixed findings regarding the correlation between specificity and detailedness within autobiographical memories, and their associations with depressive symptoms. However, minimal research has tested these links in adolescents, despite the importance of this developmental period. The present investigation examined these associations in a sample of young community adolescents (N = 768; Mage = 11.04) by replicating methodology of existing studies. Cued recall was measured using the Autobiographical Memory Test and responses were subsequently coded for specificity (whether the memory referred to an event that lasted less than 24 hours) and amount of detail (time, place, sensory-perceptual information, etc.). Depressive symptoms were assessed using the Patient Reported Outcomes Measure Information System (PROMIS) measure. Two linear mixed models showed that young adolescents who retrieved more detail recalled a greater number of specific memories and that specific memories included a greater amount of detail than non-specific memories. However, neither memory specificity nor detail were associated with depressive symptoms. Our findings suggest that, in a population of young adolescents, memory specificity and detail are distinct, but interrelated, constructs. Further longitudinal research should examine whether specificity and detail predict depressive symptoms differentially over the course of adolescence; possible mediators and moderators within this association should also be investigated.

Sleep is a support for cognitive development in childhood. Most of the studies in the field have focused on school‐age children and sleep problems, but less research focuses on the relation between the normative course of sleep and executive functions in preschoolers. Thus, the aim of the present study was to analyze the association between nighttime sleep duration and executive functioning in a 158 non‐clinical sample of Spanish participants (Mage = 56.35 months, SD = 11.24; ages 38–78 months; 48.1% girls). Sleep habits were measured by parents' self‐reports; Shape School task was applied to assess inhibition and cognitive flexibility; Word Span task was used to assess working memory; and Vocabulary subtest from the Wechsler Preschool and Primary Scale of Intelligence‐III was used to assess verbal ability. The findings revealed that the relation between sleep and executive functioning was only significant in the cases of inhibition and working memory. Further, age and verbal ability were related and were predictors of inhibition, working memory, and cognitive flexibility. We consider it necessary to continue researching in this area given the importance of forming a correct sleep habit during the preschool age and its impact on health, cognition, and well‐being in childhood. In short, our results represent the first approach to the subject under study, which should be completed with objective sleep measures.