Understanding the PxS Aspect of Within-Person Variation: A Variance Partitioning Approach

This article reviews a variance partitioning approach to within-person variation based on Generalizability (G) Theory and the Social Relations Model (SRM). The approach conceptualizes an important part of within-person variation as Person x Situation (PxS) interactions: differences among persons in their profiles of responses across the same situations. The approach provided the first quantitative method for capturing within-person variation and demonstrated very large PxS effects for a wide range of constructs. These include anxiety, five-factor personality traits, perceived social support, leadership, and task performance. Although PxS effects are commonly very large, conceptual and analytic obstacles have thwarted consistent progress. For example, how does one develop a psychological, versus purely statistical, understanding of PxS effects? How does one forecast future behavior when the criterion is a PxS effect? How can understanding PxS effects contribute to psychological theory? This review describes potential solutions to these and other problems developed in the course of conducting research on the PxS aspect of social support. Additional problems that need resolution are identified

Perceived and Capitalization Support Are Substantially Similar: Implications for Social Support Theory

Social support is typically thought to protect people from bad events, whereas capitalization support augments people’s reactions to good events. Because social support and capitalization support apply to different classes of events, most theory predicts that measures of perceived support and capitalization support should be empirically distinct. We tested a new theory that hypothesizes that the main effects between perceived support and mental health do not reflect stress and coping primarily, but instead reflect ordinary, yet affectively consequential conversations and shared activities, some of which include positive events. According to this view, perceived support and capitalization support should be substantially correlated, should have similar links to other constructs, and their links to favorable affect should overlap, yet not be completely redundant. In three samples, results were consistent with the new theory, when correlations reflected social influences. When correlations reflected trait influences, perceived and capitalization support showed greater overlap

The Information Used to Judge Supportiveness Depends on Whether the Judgment Reflects the Personality of Perceivers, Objective Characteristics of Targets or Their Unique Relationships

People who judge their relationships as more supportive enjoy better mental health than people who judge their relationships more negatively. We investigated how people made these judgments; specifically, how people weighed different types of information about targets under three different conditions: when judgments reflected the personality of perceivers, the objective characteristics of targets, and the unique relationships between perceivers and targets. Participants (i.e., perceivers) judged the same four videotaped targets on personality, similarity to perceivers and likely supportiveness. As in previous research, perceivers based their judgments on perceived target similarity to perceivers, and on target personality. However, how perceivers weighed personality and similarity information varied dramatically depending upon whether the judgment reflected the personality of perceivers, the objective characteristics of targets, or the relationship between perceivers and targets. Implications for understanding how people make support judgments were discussed

Symbolic Providers Help People Regulate Affect Relationally: Implications for Perceived Support

Relational regulation theory (Lakey & Orehek, 2011) predicts that the correlation between perceived support and mental health emerges through ordinary conversation and shared activities rather than through conversations about stress and how to cope with it. Observing the conversations and activities of others also helps regulate mental health. Symbolic providers (known only through media) mimic how real providers regulate affect in that recipients observe the conversations and shared activities of symbolic providers. Thus, many perceived support findings obtained for real providers should also be found for symbolic providers. We found the same links between perceived support and affect when recipients rated symbolic providers as when recipients rated real providers. When participants’ affect was worsened, viewing symbolic providers helped restore affect

Context-induced Contrast and Assimilation in Judging Supportiveness

Social support research increasingly draws from research on social cognition. Most of this research has studied assimilation and chronically accessible (i.e., frequently activated) social support constructs. This article presents three studies, in both laboratory and treatment settings, on context-induced contrast and assimilation in support judgments. In each study, participants exposed to positive social contexts subsequently rated supportive stimuli more negatively than participants exposed to negative social contexts. These effects were observed in ratings of participants’ own social networks, the social climate of a residential treatment environment, and a videotaped supportive interaction. In two studies, negative contexts also were associated with increased negative affect and affect-related assimilation. That is, participants with more negative affect rated social environments more negatively than participants with less negative emotion. In some circumstances, context- induced contrast and assimilation counteracted each other. These effects have implications for social support interventions

Forecasting the Student–Professor Matches that Result in Unusually Effective Teaching

Background. Two important influences on students’ evaluations of teaching are relationship and professor effects. Relationship effects reflect unique matches between students and professors such that some professors are unusually effective for some students, but not for others. Professor effects reflect inter-rater agreement that some professors are more effective than others, on average across students. Aims. We attempted to forecast students’ evaluations of live lectures from brief, video-recorded teaching trailers. Sample. Participants were 145 college students (74% female) enrolled in introductory psychology courses at a public university in the Great Lakes region of the United States. Methods. Students viewed trailers early in the semester and attended live lectures months later. Because subgroups of students viewed the same professors, statistical analyses could isolate professor and relationship effects. Results. Evaluations were influenced strongly by relationship and professor effects, and students’ evaluations of live lectures could be forecasted from students’ evaluations of teaching trailers. That is, we could forecast the individual students who would respond unusually well to a specific professor (relationship effects). We could also forecast which professors elicited better evaluations in live lectures, on average across students (professor effects). Professors who elicited unusually good evaluations in some students also elicited better memory for lectures in those students. Conclusions. It appears possible to forecast relationship and professor effects on teaching evaluations by presenting brief teaching trailers to students. Thus, it might be possible to develop online recommender systems to help match students and professors so that unusually effective teaching emerges

Predicting Poor Outcomes Among Individuals Seeking Care for Major Depressive Disorder

OBJECTIVE: To develop and validate algorithms to identify individuals with major depressive disorder (MDD) at elevated risk for suicidality or for an acute care event. METHODS: We conducted a retrospective cohort analysis among adults with MDD diagnosed between January 1, 2018 and February 28, 2019. Generalized estimating equation models were developed to predict emergency department (ED) visit, inpatient hospitalization, acute care visit (ED or inpatient), partial-day hospitalization, and suicidality in the year following diagnosis. Outcomes (per 1000 patients per month, PkPPM) were categorized as all-cause, psychiatric, or MDD-specific and combined into composite measures. Predictors included demographics, medical and pharmacy utilization, social determinants of health, and comorbid diagnoses as well as features indicative of clinically relevant changes in psychiatric health. Models were trained on data from 1.7M individuals, with sensitivity, positive predictive value, and area-under-the-curve (AUC) derived from a validation dataset of 0.7M. RESULTS: Event rates were 124.0 PkPPM (any outcome), 21.2 PkPPM (psychiatric utilization), and 7.6 PkPPM (suicidality). Among the composite models, the model predicting suicidality had the highest AUC (0.916) followed by any psychiatric acute care visit (0.891) and all-cause ED visit (0.790). Event-specific models all achieved an AUC \u3e0.87, with the highest AUC noted for partial-day hospitalization (AUC = 0.938). Select predictors of all three outcomes included younger age, Medicaid insurance, past psychiatric ED visits, past suicidal ideation, and alcohol use disorder diagnoses, among others. CONCLUSIONS: Analytical models derived from clinically-relevant features identify individuals with MDD at risk for poor outcomes and can be a practical tool for health care organizations to divert high-risk populations into comprehensive care models

The Atacama Cosmology Telescope: A Measurement of the DR6 CMB Lensing Power Spectrum and its Implications for Structure Growth

We present new measurements of cosmic microwave background (CMB) lensing over $9400$ sq. deg. of the sky. These lensing measurements are derived from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) CMB dataset, which consists of five seasons of ACT CMB temperature and polarization observations. We determine the amplitude of the CMB lensing power spectrum at $2.3\%$ precision ($43\sigma$ significance) using a novel pipeline that minimizes sensitivity to foregrounds and to noise properties. To ensure our results are robust, we analyze an extensive set of null tests, consistency tests, and systematic error estimates and employ a blinded analysis framework. The baseline spectrum is well fit by a lensing amplitude of $A_{\mathrm{lens}}=1.013\pm0.023$ relative to the Planck 2018 CMB power spectra best-fit $\Lambda$CDM model and $A_{\mathrm{lens}}=1.005\pm0.023$ relative to the $\text{ACT DR4} + \text{WMAP}$ best-fit model. From our lensing power spectrum measurement, we derive constraints on the parameter combination $S^{\mathrm{CMBL}}_8 \equiv \sigma_8 \left({\Omega_m}/{0.3}\right)^{0.25}$ of $S^{\mathrm{CMBL}}_8= 0.818\pm0.022$ from ACT DR6 CMB lensing alone and $S^{\mathrm{CMBL}}_8= 0.813\pm0.018$ when combining ACT DR6 and Planck NPIPE CMB lensing power spectra. These results are in excellent agreement with $\Lambda$CDM model constraints from Planck or $\text{ACT DR4} + \text{WMAP}$ CMB power spectrum measurements. Our lensing measurements from redshifts $z\sim0.5$--$5$ are thus fully consistent with $\Lambda$CDM structure growth predictions based on CMB anisotropies probing primarily $z\sim1100$. We find no evidence for a suppression of the amplitude of cosmic structure at low redshiftsComment: 45+21 pages, 50 figures. Prepared for submission to ApJ. Also see companion papers Madhavacheril et al and MacCrann et a

The Atacama Cosmology Telescope: High-resolution component-separated maps across one-third of the sky

Observations of the millimeter sky contain valuable information on a number of signals, including the blackbody cosmic microwave background (CMB), Galactic emissions, and the Compton-$y$ distortion due to the thermal Sunyaev-Zel'dovich (tSZ) effect. Extracting new insight into cosmological and astrophysical questions often requires combining multi-wavelength observations to spectrally isolate one component. In this work, we present a new arcminute-resolution Compton-$y$ map, which traces out the line-of-sight-integrated electron pressure, as well as maps of the CMB in intensity and E-mode polarization, across a third of the sky (around 13,000 sq.~deg.). We produce these through a joint analysis of data from the Atacama Cosmology Telescope (ACT) Data Release 4 and 6 at frequencies of roughly 93, 148, and 225 GHz, together with data from the \textit{Planck} satellite at frequencies between 30 GHz and 545 GHz. We present detailed verification of an internal linear combination pipeline implemented in a needlet frame that allows us to efficiently suppress Galactic contamination and account for spatial variations in the ACT instrument noise. These maps provide a significant advance, in noise levels and resolution, over the existing \textit{Planck} component-separated maps and will enable a host of science goals including studies of cluster and galaxy astrophysics, inferences of the cosmic velocity field, primordial non-Gaussianity searches, and gravitational lensing reconstruction of the CMB.Comment: The Compton-y map and associated products will be made publicly available upon publication of the paper. The CMB T and E mode maps will be made available when the DR6 maps are made publi