Risk and Protective Factors for the Sexual and Reproductive Health of Young Adolescents: Lessons Learnt in the Past Decade and Research Priorities Moving Forward.

PURPOSE: To review the published literature on what has been reported on risk and protective factors for early adolescent sexual and reproductive health (SRH) in the recent decade. METHODS: A scoping review of English language, peer-reviewed literature on risk and protective factors for early adolescent (aged 10-14 years) SRH published between January 2010 and January 2023 using Medline, Web of Science, PsycInfo, CINAHL, and Google Scholar. Articles reporting only on nonmodifiable demographic factors, or on the effect of interventions, were beyond the scope of this review. RESULTS: Of 11,956 screened records, 118 were included of which half (49.2%) were published since 2018. Most articles (44.9%) presented research conducted in North America, followed by sub-Saharan Africa (20.3%) and East Asia and Pacific (16.1%). Five percent were based on multicountry studies or reported on pooled global data. Two-thirds (61.0%) reported on quantitative cross-sectional research designs, and 78.8% included both females and males. The most common SRH outcomes were sexual behaviors (34.7%); sexual and dating violence (28.8%); and sexual attitudes, beliefs, and intentions (19.5%). Most (83.0%) articles reported on risk/protective factors at the individual level, followed by interpersonal (family 58.5%, peers 33.0%, partners 11.9%), school (21.2%), and community (15.2%) factors. None of the included articles reported on macro/structural-level factors. DISCUSSION: While there has been growing attention to risk/protective factors for early adolescent SRH, gaps remain with regards to study contexts (mainly North America), focus (mostly individual factors), and conceptualizations (generally risk-oriented). We offer recommendations for research priorities over the coming decade.

Clinical and Behavioral Research at the National Institute on Aging-50 Years of Innovation.

This Viewpoint discusses multicomplexity and dementia, 2 areas of clinical and behavioral research where the National Institute on Aging has made integral and distinctive contributions.

Beyond Pearson's Correlation: Modern Nonparametric Independence Tests for Psychological Research.

When examining whether two continuous variables are associated, tests based on Pearson's, Kendall's, and Spearman's correlation coefficients are typically used. This paper explores modern nonparametric independence tests as an alternative, which, unlike traditional tests, have the ability to potentially detect any type of relationship. In addition to existing modern nonparametric independence tests, we developed and considered two novel variants of existing tests, most notably the Heller-Heller-Gorfine-Pearson (HHG-Pearson) test. We conducted a simulation study to compare traditional independence tests, such as Pearson's correlation, and the modern nonparametric independence tests in situations commonly encountered in psychological research. As expected, no test had the highest power across all relationships. However, the distance correlation and the HHG-Pearson tests were found to have substantially greater power than all traditional tests for many relationships and only slightly less power in the worst case. A similar pattern was found in favor of the HHG-Pearson test compared to the distance correlation test. However, given that distance correlation performed better for linear relationships and is more widely accepted, we suggest considering its use in place or additional to traditional methods when there is no prior knowledge of the relationship type, as is often the case in psychological research.

Responsible inclusion: A systematic review of consent to social-behavioral research with adults with intellectual disability in the US.

BACKGROUND: In recognition of their status as a health disparities population, there is growing emphasis on conducting research inclusive of adults with intellectual disability to generate new knowledge and opportunities to improve health and equity. Yet they are often excluded from research, and human research participant protection experts and researchers lack agreement on effective consent protocols for their inclusion. OBJECTIVE: We sought to identify approaches to consent in US-based social-behavioral research with adults with intellectual disability. METHODS: We conducted a systematic review on approaches to self-consent with adults with intellectual disability published between 2009 and 2023, identified via searching eight databases and reference list hand searches. We identified 13 manuscripts and conducted a thematic analysis. RESULTS: Our analysis identified themes related to guiding principles, strategies to enhance informed and voluntary consent, approaches to consent capacity, involving individuals subject to guardianship, and strategies for expressing decisions and enhancing ongoing decisions. CONCLUSIONS: Manuscripts largely reflected an emphasis on identifying approaches to consent that reflect disability rights principles to promote the right to be included and make one's own decisions based on assessment of relevant information, risks and benefits, and to employ reasonable modifications to achieve inclusion. To avoid the risks of exclusion and advance the responsible inclusion of adults with intellectual disability, we make recommendations to align consent approaches anchored in contemporary thinking about human research participant protections, including through integration with disability rights.

A jsPsych touchscreen extension for behavioral research on touch-enabled interfaces.

Online experiments are increasingly gaining traction in the behavioral sciences. Despite this, behavioral researchers have largely continued to use keyboards as the primary input devices for such online studies, overlooking the ubiquity of touchscreens in everyday use. This paper presents an open-source touchscreen extension for jsPsych, a JavaScript framework designed for conducting online experiments. We additionally evaluated the touchscreen extension assessing whether typical behavioral findings from two distinct perceptual decision-making tasks - the random-dot kinematogram and the Stroop task - can similarly be observed when administered via touchscreen devices compared to keyboard devices. Our findings indicate similar performance metrics for each paradigm between the touchscreen and keyboard versions of the experiments. Specifically, we observe similar psychometric curves in the random-dot kinematogram across the touchscreen and keyboard versions. Similarly, in the Stroop task, we detect significant task, congruency, and sequential congruency effects in both experiment versions. We conclude that our open-source touchscreen extension serves as a promising tool for data collection in online behavioral experiments on forced-choice tasks.

An Exact Bayesian Model for Meta-Analysis of the Standardized Mean Difference with Its Simultaneous Credible Intervals.

While Bayesian methodology is increasingly favored in behavioral research for its clear probabilistic inference and model structure, its widespread acceptance as a standard meta-analysis approach remains limited. Although some conventional Bayesian hierarchical models are frequently used for analysis, their performance has not been thoroughly examined. This study evaluates two commonly used Bayesian models for meta-analysis of standardized mean difference and identifies significant issues with these models. In response, we introduce a new Bayesian model equipped with novel features that address existing model concerns and a broader limitation of the current Bayesian meta-analysis. Furthermore, we introduce a simple computational approach to construct simultaneous credible intervals for the summary effect and between-study heterogeneity, based on their joint posterior samples. This fully captures the joint uncertainty in these parameters, a task that is challenging or impractical with frequentist models. Through simulation studies rooted in a joint Bayesian/frequentist paradigm, we compare our model's performance against existing ones under conditions that mirror realistic research scenarios. The results reveal that our new model outperforms others and shows enhanced statistical properties. We also demonstrate the practicality of our models using real-world examples, highlighting how our approach strengthens the robustness of inferences regarding the summary effect.

What ergodicity means for you.

This paper explores the relation between within-person and between-person research designs using the concept of ergodicity from statistical mechanics in physics. We demonstrate the consequences of ergodicity using several real data examples from previously published studies. We then create several simulated examples that illustrate the independence of within-person processes from between-person differences, and pair these examples with analytic results that reinforce our conclusions. Finally, we discuss the plausibility of ergodicity being the general rule rather than the exception for social and behavioral processes, address common arguments against heeding the implications of ergodicity for behavioral research, and offer several possible solutions.

Exploration of factors affecting webcam-based automated gaze coding.

Online experiments have been transforming the field of behavioral research, enabling researchers to increase sample sizes, access diverse populations, lower the costs of data collection, and promote reproducibility. The field of developmental psychology increasingly exploits such online testing approaches. Since infants cannot give explicit behavioral responses, one key outcome measure is infants' gaze behavior. In the absence of automated eyetrackers in participants' homes, automatic gaze classification from webcam data would make it possible to avoid painstaking manual coding. However, the lack of a controlled experimental environment may lead to various noise factors impeding automatic face detection or gaze classification. We created an adult webcam dataset that systematically reproduced noise factors from infant webcam studies which might affect automated gaze coding accuracy. We varied participants' left-right offset, distance to the camera, facial rotation, and the direction of the lighting source. Running two state-of-the-art classification algorithms (iCatcher+ and OWLET) revealed that facial detection performance was particularly affected by the lighting source, while gaze coding accuracy was consistently affected by the distance to the camera and lighting source. Morphing participants' faces to be unidentifiable did not generally affect the results, suggesting facial anonymization could be used when making online video data publicly available, for purposes of further study and transparency. Our findings will guide improving study design for infant and adult participants during online experiments. Moreover, training algorithms using our dataset will allow researchers to improve robustness and allow developmental psychologists to leverage online testing more efficiently.

Automatic object detection for behavioural research using YOLOv8.

Observational studies of human behaviour often require the annotation of objects in video recordings. Automatic object detection has been facilitated strongly by the development of YOLO ('you only look once') and particularly by YOLOv8 from Ultralytics, which is easy to use. The present study examines the conditions required for accurate object detection with YOLOv8. The results show almost perfect object detection even when the model was trained on a small dataset (100 to 350 images). The detector, however, does not extrapolate well to the same object in other backgrounds. By training the detector on images from a variety of backgrounds, excellent object detection can be restored. YOLOv8 could be a game changer for behavioural research that requires object annotation in video recordings.

Relevance of Behavioral Research in the Evolving State of Anti-obesity Medications: Is the Glass Half Empty or Half Full?

Obesity continues to be a significant public health challenge. While weight loss medications have been studied and available for several years, the newest generation of highly effective anti-obesity medications (AOMs) will shift how behavioral science professionals approach obesity treatment and research. With the unique skill set of behavioral science professionals, this commentary suggests ways to integrate behavioral science into the rapidly evolving landscape of AOM use to accelerate better obesity care and generate new lines of research. The goal of this commentary is to stimulate discussion and encourage responsive and relevant action to improve population health.

Variability in odor hedonic perception: A challenge for neurosensory and behavioral research.

Odor hedonic perception (pleasant/unpleasant character) is considered to be the first and one of the most important dimensions in olfaction and is known to be highly variable and dependent on several factors related to the stimulus, individual characteristics, and context. Although numerous experimental studies have been published on this topic, there is no comprehensive general review on the variability in odor hedonic perception. Therefore, the aim of this article was to describe and detail all the factors involved in the variability in odor hedonic perception. Stimulus properties-related variability includes the concentration/intensity and the physicochemical properties. Individual-related variability includes sex, age, and physiological state characteristics, while context-related variability involves factors associated with the stimulation context, such as stimulation pathway, exposure frequency, verbal influences, cross-modal associations, hedonic contrast, and cultural background. Subsequently, a section is devoted to the brain processing of odor hedonicity, although its role in odor hedonic variability is largely unknown. Finally, the article discusses the relationship between the hedonic qualities of odors and the resulting behavioral responses in both animals and humans. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Tucker3-PCovR: The Tucker3 principal covariates regression model.

In behavioral research, it is very common to have manage multiple datasets containing information about the same set of individuals, in such a way that one dataset attempts to explain the others. To address this need, in this paper the Tucker3-PCovR model is proposed. This model is a particular case of PCovR models which focuses on the analysis of a three-way data array and a two-way data matrix where the latter plays the explanatory role. The Tucker3-PCovR model reduces the predictors to a few components and predicts the criterion by using these components and, at the same time, the three-way data is fitted by the Tucker3 model. Both the reduction of the predictors and the prediction of the criterion are done simultaneously. An alternating least squares algorithm is proposed to estimate the Tucker3-PCovR model. A biplot representation is presented to facilitate the interpretation of the results. Some applications are made to empirical datasets from the field of psychology.

Research and mentorship in behavior analysis from a lens of cultural responsiveness and antiracism.

Although scientific endeavors strive to be objective, they are the work of individuals whose unique perspectives and experiences influence their research and interpretations of the world and data. Much has been said and written lately about the need to embed cultural responsiveness in behavior analysis and the need to enhance diversity in the field. In fact, similar conversations are taking place in many areas of science. Despite the current buzz, many behavioral researchers may be left wondering what they can do or whether it is incumbent on them to act. For the field of behavior analysis to move toward adopting the values of diversity, equity, inclusion, and access, members of the scientific community must actively engage in behaviors that foster inclusive and safe learning environments for students, engage in collaborative work, and incorporate culturally responsive research and mentorship practices. This article will describe some current practices, showcase exemplars of culturally responsive research and mentorship, and provide resources for researchers and mentors.

Ouvrai opens access to remote virtual reality studies of human behavioural neuroscience.

Modern virtual reality (VR) devices record six-degree-of-freedom kinematic data with high spatial and temporal resolution and display high-resolution stereoscopic three-dimensional graphics. These capabilities make VR a powerful tool for many types of behavioural research, including studies of sensorimotor, perceptual and cognitive functions. Here we introduce Ouvrai, an open-source solution that facilitates the design and execution of remote VR studies, capitalizing on the surge in VR headset ownership. This tool allows researchers to develop sophisticated experiments using cutting-edge web technologies such as WebXR to enable browser-based VR, without compromising on experimental design. Ouvrai's features include easy installation, intuitive JavaScript templates, a component library managing front- and backend processes and a streamlined workflow. It integrates with Firebase, Prolific and Amazon Mechanical Turk and provides data processing utilities for analysis. Unlike other tools, Ouvrai remains free, with researchers managing their web hosting and cloud database via personal Firebase accounts. Ouvrai is not limited to VR studies; researchers can also develop and run desktop or touchscreen studies using the same streamlined workflow. Through three distinct motor learning experiments, we confirm Ouvrai's efficiency and viability for conducting remote VR studies.