心理学最新文献

The left ventral occipitotemporal cortex (lvOT) has been consistently identified as a crucial structure in word reading, and its function varies across subregions. Nevertheless, the specific function of the lvOT and its subregions remains controversial because the obvious grapheme-to-phoneme correspondence rules of alphabetic languages make it difficult to disentangle the contributions of orthography and phonology to neural activations. To explore information processing in lvOT subregions, the present study manipulated the orthography and phonology in a factorial design and used the fMRI rapid adaptation paradigm. The results revealed a posterior-to-anterior functional gradient in lvOT in Chinese word reading and specified that the functional transition from sublexical to lexical processing occurred in the middle subregion close to the classic VWFA. More importantly, we found that the middle and posterior subregions of lvOT are responsible for processing both orthographic and phonological information during Chinese word reading. These results elaborated the function of the lvOT in Chinese word reading.

Lay abstract: What is already known about the topic?Autistic children frequently often have accompanying physical health problems. However, this has been much less studied in autistic men and women during adulthood.What does this article add?This is one of the first studies to investigate the associations between autistic and somatic problems in adults from the general population. Using a continuous measure of autistic symptom scores and a categorical definition of autism (referred to below as probable autism) which considered symptom severity, childhood age of onset, and functional impairment, we found that autistic problems and irritable bowel syndrome, food allergy, pain, and fatigue were associated in adults. Sex differences were present for pain and fatigue, for which the associations with autistic symptom scores were somewhat stronger in females than males. Regarding age differences, the associations with fatigue and having food allergy were more pronounced in younger adults. Conversely, older individuals had a higher risk of developing irritable bowel syndrome or experiencing pain if they met the criteria for probable autism.Implications for practice, research, or policyThere is a need for providing routine programs of screening, assessment, and treatment of autism-related somatic problems and developing evidence-based interventions for autistic individuals. These could be tailored to the needs of specific autistic populations. For example, autistic females could be given extra attention about the potential presence of pain and fatigue, younger adults about the potential presence of food allergy and fatigue, and older adults concerning the potential presence of irritable bowel syndrome and pain.

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational speed. This study introduces a novel "divide- and-conquer" parallel algorithm built on the Wasserstein posterior approximation concept, aiming to enhance computational speed while maintaining accurate parameter estimation. This algorithm enables drawing parameters from segmented data subsets in parallel, followed by an amalgamation of these parameters via Wasserstein posterior approximation. Theoretical support for the algorithm is established through asymptotic optimality under certain regularity assumptions. Practical validation is demonstrated using real-world data from the Programme for International Student Assessment. Ultimately, this research proposes a transformative approach to managing educational big data, offering a scalable, efficient, and precise alternative that promises to redefine traditional practices in educational assessments.

Sijtsma, Ellis, and Borsboom (Psychometrika, 89:84-117, 2024. https://doi.org/10.1007/s11336-024-09964-7 ) provide a thoughtful treatment in Psychometrika of the value and properties of sum scores and classical test theory at a depth at which few practicing psychometricians are familiar. In this note, I offer comments on their article from the perspective of evidentiary reasoning.

Objective: Most individuals attending detoxification clinics do not pursue subsequent treatment. Earlier research has suggested that emerging technologies like mHealth interventions could address the postdetoxification treatment gap, yet it remains unclear whether patients themselves endorse such approaches. Our study aimed to qualitatively explore perceived treatment barriers and assessed potential of mHealth among individuals who have undergone alcohol detoxification.

Method: We conducted a single-interview-per-participant qualitative study, sampling participants (n = 23) that had visited the Stockholm substance use disorder emergency department for alcohol-related reasons, of whom n = 8 were purposively included due to having missed their scheduled follow-up outpatient appointment. Semistructured telephone interviews were conducted (2021-2022) and then systematically analyzed using reflexive thematic analysis.

Results: Across both areas of analysis, we identified six themes in total. We clustered barriers to postdetoxification treatment into three themes (10 subthemes) that may offer a nuancing perspective on previous research: "Misalignment between the treatment system and the individual," "Practical hurdles" and "Between reaching out and retreating." We identified three themes in participants' perspectives on mHealth as aftercare support, revealing expectations that such an approach may promote "self-awareness on own terms," assist in "navigating from solitary substance use struggles to supportive connections," and "offer a lifeline when needed most," thereby potentially resolving several barriers to treatment.

Conclusions: This first qualitative study on barriers to alcohol treatment and mHealth potential postdetoxification offered various insights that may be translated into effective, real-world solutions to bridge the postdetoxification treatment gap. A natural next step for future research is to evaluate the impact of mHealth postdetoxification. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Lay abstract: This study explores the experiences and identities of nonbinary autistic people. The relationship between autistic and nonbinary identities has not been researched in detail. Few studies focus specifically on nonbinary autistic adults. We interviewed 44 nonbinary individuals for this study. Participants had thought-out opinions on gender identity and emphasized identifying with fluidity rather than traditional gender roles. Participants discussed the connection of their autistic and nonbinary identities and how it affected how people saw them and how they saw themselves. We have recommendations for programming, policy, and research from these findings.

Emotional support from friends is a crucial source of social support for adolescents, significantly influencing their psychological development. However, previous research has primarily focused on how this support correlates with general levels of socioemotional problems among adolescents, neglecting the significance of daily fluctuations in these problems. The aim of this study was to explore the relationship between friend emotional support and both the average and dynamic indicators of daily emotional and peer problems in adolescents. These dynamic indicators include within-domain dynamics-such as inertia, which reflects the temporal dependence of experiences, and volatility, which indicates within-person variance-and cross-domain dynamics, such as transactional effects, which measure the strength of concurrent or lagged associations between daily emotional and peer problems. Participants were 315 seventh-grade Chinese adolescents (M_age = 13.05 years, SD = 0.77 years; 48.3% girls). Adolescents reported on their friends' emotional support at baseline and then completed measures of daily emotion and peer problems over a 10-day period. Using dynamic structural equation models, the results revealed that higher levels of friend emotional support were associated with fewer daily socioemotional problems. This was evident both in terms of average levels and dynamic aspects, characterized by lower mean levels of daily emotional and peer problems, reduced inertia and volatility of these problems, and a weaker spillover effect from daily emotional issues to peer problems. These findings highlight the significant role of friend-emotional support in mitigating adolescents' daily socioemotional challenges.

Eye tracking provides direct, temporally and spatially sensitive measures of eye gaze. It can capture visual attention patterns from infancy through adulthood. However, commonly used screen-based eye tracking (SET) paradigms are limited in their depiction of how individuals process information as they interact with the environment in "real life". Mobile eye tracking (MET) records participant-perspective gaze in the context of active behavior. Recent technological developments in MET hardware enable researchers to capture egocentric vision as early as infancy and across the lifespan. However, challenges remain in MET data collection, processing, and analysis. The present paper aims to provide an introduction and practical guide to starting researchers in the field to facilitate the use of MET in psychological research with a wide range of age groups. First, we provide a general introduction to MET. Next, we briefly review MET studies in adults and children that provide new insights into attention and its roles in cognitive and socioemotional functioning. We then discuss technical issues relating to MET data collection and provide guidelines for data quality inspection, gaze annotations, data visualization, and statistical analyses. Lastly, we conclude by discussing the future directions of MET implementation. Open-source programs for MET data quality inspection, data visualization, and analysis are shared publicly.

The Integrated Change Model describes several social and cognitive factors (e.g., health attitudes, social support, self-efficacy) that can affect medication adherence. Guided by this model, we sought to identify profiles of socio-cognitive facilitators of ART (antiretroviral therapy) adherence among diversely minoritized persons living with HIV enrolled in a behavioral intervention trial in Atlanta, Georgia (N = 477). To do this, we performed latent profile analysis on baseline responses to scales assessing 6 indicators of interest: HIV-care self-efficacy, social support, TasP (treatment-as-prevention) beliefs, trust in healthcare providers, perceived need for ART, and trust in ART. We regressed emergent profiles on internalized, enacted, and microaggressive HIV stigma and compared prospective 30-day ART adherence and several cross-sectional HIV outcomes across profiles. Mean age was 29 years; 83% of participants were non-Hispanic Black, 53% were gay/homosexual-identifying, and 12% were gender expansive. Three profiles emerged: "Constrained/Capable" (6%), featuring high self-efficacy but low-moderate provider trust, social support, TasP beliefs, ART trust, and ART need; "Conflicted" (13%), featuring high TasP beliefs, provider trust, and ART need but moderate self-efficacy, ART trust, and social support; and "Motivated" (81%), featuring high levels of all indicators. Greater internalized, enacted, and microaggressive stigma were positively associated with "Conflicted" relative to "Motivated" profile membership. ART-nonadherence, unsuppressed viral load, and viral load unawareness were more likely for the "Conflicted" relative to the "Motivated" profile. Personalized HIV care tailored to such profiles may improve ART adherence and related outcomes for minoritized persons living with HIV.

Bayes factor hypothesis testing provides a powerful framework for assessing the evidence in favor of competing hypotheses. To obtain Bayes factors, statisticians often require advanced, non-standard tools, making it important to confirm that the methodology is computationally sound. This paper seeks to validate Bayes factor calculations by applying two theorems attributed to Alan Turing and Jack Good. The procedure entails simulating data sets under two hypotheses, calculating Bayes factors, and assessing whether their expected values align with theoretical expectations. We illustrate this method with an ANOVA example and a network psychometrics application, demonstrating its efficacy in detecting calculation errors and confirming the computational correctness of the Bayes factor results. This structured validation approach aims to provide researchers with a tool to enhance the credibility of Bayes factor hypothesis testing, fostering more robust and trustworthy scientific inferences.