Occupational differentiation among white men in the first decade after high school

Most research on career development is concerned with the fate of individuals, but portraits of the heterogeneity and development of whole populations or aggregates of individuals can also be useful for understanding the needs and development of different client populations. Two population-level concepts are proposed and defined: differentiation and distribution. This report then charts the rate at which occupational differentiation proceeds among 3730 young white men and investigates the personal and family attributes by which these men are distributed, or distribute themselves, to jobs. Data from the National Longitudinal (Parnes) Survey of the Labor Force Experience of Young Men are used to examine employment among men aged 16 to 28 in different levels and fields of work. Results suggest that the rate of labor force participation stabilizes in the early twenties, differentiation among men by education and the distribution of men among different broad levels and fields of work stabilize by the mid-twenties, and the sorting of men with different socioeconomic backgrounds into different occupational groups continues through the late twenties at which age it appears to have been largely completed. Discriminant analyses suggest that the distribution of men to jobs is primarily along an occupational status dimension, and secondarily according to field of work. Among the variables used in the analyses, academic achievement is the major dimension by which men are sorted or sort themselves to different jobs.     

Antidepressive behaviour: A preliminary report

Outside the psychological literature it is common knowledge that when people feel depressed they ordinarily try to do something about it. In the clinical literature, this commonplace fact is in danger of being forgotten. Using an empirically-derived checklist of activities consensually identified as being ‘the thing to do when feeling depressed’, the present study examines (1) the distribution of reported antidepressive behaviour (ADB) in a group consisting of depressed and non-depressed psychiatric patients and normals and (2) the relationship between an individual's sex, personality (locus of control), and patient status and (a) the amount of ADB he reports and (b) how much of it he regards as helpful. All Ss reported some ADB but not all reported any that was helpful. In an analysis of variance, no main effects of sex, personality or patient status were found, but sex interacting with personality was significantly related both to the overall amount of ADB reported and to the amount found helpful. The findings have implications for the sorts of concepts that a theoretical formulation of ADB will require as well as for the ways in which clinicians conceptualize depressed patients.     

Some cognitive dimensions of antidepressive behaviour

This study examines the accuracy with which psychology students predict how they, as a group, will answer questions about how frequently they and the ‘average person’ feel depressed, try to do something about it when feeling depressed, and find that what they do works. Subjects circled responses on 5-point frequency scales to describe their own experience and that which they attributed to the ‘average person’. They also estimated what percentages of their group would circle each point on the scales. Comparison of percentages actually observed with the group's mean predictions showed a striking congruence when represented graphically. The high degree of agreement suggests that these first year undergraduates with no previous instruction in abnormal psychology already have cognitions about depression and antidepressive behaviour of a high order of complexity. The implications of the finding for psychological research on human depression are discussed.     

What Happens After the Demonstration Phase? The Sustainability of Canada's At Home/Chez Soi Housing First Programs for Homeless Persons with Mental Illness

This research examined the sustainability of Canada's At Home/Chez Soi Housing First (HF) programs for homeless persons with mental illness 2 years after the end of the demonstration phase of a large (more than 2000 participants enrolled), five‐site, randomized controlled trial. Qualitative interviews were conducted with 142 participants (key informants, HF staff, and persons with lived experience) to understand sustainability outcomes and factors that influenced those outcomes. Also, a self‐report HF fidelity measure was completed for nine HF programs that continued after the demonstration project. A cross‐site analysis was performed, using the five sites as case studies. The findings revealed that nine of the 12 HF programs (75%) were sustained, and that seven of the nine programs reported a high level of fidelity (achieving an overall score of 3.5 or higher on a 4‐point scale). The sites varied in terms of the level of systems integration and expansion of HF that were achieved. Factors that promoted or impeded sustainability were observed at multiple ecological levels: broad contextual (i.e., dissemination of research evidence, the policy context), community (i.e., partnerships, the presence of HF champions), organizational (i.e., leadership, ongoing training, and technical assistance), and individual (i.e., staff turnover, changes, and capacity). The findings are discussed in terms of the implementation science literature and their implications for how evidence‐based programs like HF can be sustained.     

Fathers’ and Mothers’ Involvement with Their Adolescents

We explored mothers’ and fathers’ time spent with their adolescents and found that mothers reported spending more time with their adolescents than did fathers. Developmental patterns were found for some aspects of time involvement, with both mothers and fathers reporting higher involvement with younger adolescents. Ratings of time-spent were not associated with adolescents’ self-reported emotional/behavioral problems. Both mothers and fathers agreed that mothers had more responsibility for adolescents’ discipline, daily care, and recreational activities. Mothers and fathers reported comparable levels of satisfaction with this arrangement. Mothers, and to a lesser extent fathers, reported greater satisfaction with the division of labor when fathers showed higher levels of responsibility for adolescents’ activities. Satisfaction with the division of labor was inversely related to interparental conflict. Few differences were found based on adolescent gender for any of these variables. Results are discussed within the context of mother–child and father–child relationships and family functioning.     

Timing of dietary change in response to a telephone counseling intervention: evidence from the WHEL study

OBJECTIVE: Little is known about temporal patterns of diet change within interventions, nor about predictors of early and sustained successful change. Social-cognitive theory asserts that early successes in achieving behavior change increase self-efficacy, leading to longer-term success. DESIGN: The authors conducted exploratory cluster analyses using dietary data from the first month of the telephone counseling intervention of the Women's Healthy Eating and Living (WHEL) Study. MAIN OUTCOME MEASURE: Change in dietary pattern at three early intervention timepoints. RESULTS: Three clusters were identified: Cluster 1 (25%) was close to meeting study goals at baseline, but still made major changes; Cluster 2 (49%) and Cluster 3 (26%) were not achieving study goals at baseline, but Cluster 2 made substantial immediate changes, while Cluster 3 changed their diet more gradually. Baseline demographic and behavioral variables were associated with cluster membership; however, the strongest predictors of cluster were self-efficacy, motivation, and approaches to study goals. Cluster membership predicted dietary pattern at 12 months. CONCLUSION: These data suggest that a one-on-one telephone counseling intervention that is intensive in the early weeks may maximize the level of change achieved in a study.     

Investigating the Relationships Between Mobility Behaviours and Indicators of Subjective Well-Being Using Smartphone-Based Experience Sampling and GPS Tracking

People interact with their physical environments every day by visiting different places and moving between them. Such mobility behaviours likely influence and are influenced by people's subjective well-being. However, past research examining the links between mobility behaviours and well-being has been inconclusive. Here, we provide a comprehensive investigation of these relationships by examining individual differences in two types of mobility behaviours (movement patterns and places visited) and their relationship to six indicators of subjective well-being (depression, loneliness, anxiety, stress, affect, and energy) at two different temporal levels of analysis (two-week tendencies and daily level). Using data from a large smartphone-based longitudinal study (N = 1765), we show that (i) movement patterns assessed via GPS data (distance travelled, entropy, and irregularity) and (ii) places visited assessed via experience sampling reports (home, work, and social places) are associated with subjective well-being at the between and within person levels. Our findings suggest that distance travelled is related to anxiety, affect, and stress, irregularity is related to depression and loneliness, and spending time in social places is negatively associated with loneliness. We discuss the implications of our work and highlight directions for future research on the generalizability to other populations as well as the characteristics of places. © 2020 European Association of Personality Psychology     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.