The everyday lives of in- and outpatients when beginning therapy: The importance of values-consistent behavior

Background/ObjectiveThe manifestation of functional impairment in patients’ daily lives and interference with things they value is poorly understood. If values are compromised in patients, as theory suggests, social contexts (and the lack thereof) are especially important – though this is currently unexplored. We therefore examined whether daily values-consistent behavior was associated with the importance of a value and whether it involved social or non-social activity.MethodUsing Event Sampling Methodology, we examined daily values-consistent behavior in 57 transdiagnostic inpatients and 43 transdiagnostic outpatients at the beginning of treatment. Patients’ values-consistent behavior, its importance, and (social vs non-social) context was sampled six times per day during a one-week intensive longitudinal examination.ResultsAcross both groups, the probability of subsequent values-consistent behavior increased if (1) it was judged as more important by the patient or (2) if it was embedded in a social context. The probability of reporting values-consistent behavior was higher for outpatients than inpatients.ConclusionsClinicians are encouraged to examine the values of their patients more closely and to especially monitor important and/or social values. Incorporating these into clinical work might increase patients’ values-consistent behavior, which can play a role in reducing suffering.     

Experience Sampling Methodology reveals similarities in the experience of passage of time in young and elderly adults

Many people accept the idea that time seems to pass more quickly as they get older, as if this is a psychological reality. However, systematic investigations of differences in judgments of passage of time between young and elderly people are very rare and contradictory. The present study examined the experience of passage of time in daily life in young and elderly people using Experience Sampling Methodology (ESM), with 8 alerts per day for 5 days being delivered by smartphones. At each alert, a short questionnaire was filled in, asking questions about passage of present time, affective state, arousal level, and attention to current activities, among others. Our ESM study found no difference between the young and the old participants in the judgment of passage of present time. Irrespective of the participants' age, the experience of passage of time in every-day life was significantly related to affective states and current activities when they captured attention.     

Virtues in action – the new look of character traits

The present study aimed to take fresh look at the nature and psychological meaning of consistency in character traits and virtuous behaviour as manifested in everyday life. To this end, a 10‐day experience‐sampling study was conducted. Using smartphone technology, a sample of 83 working mothers and fathers provided a total of 4,342 momentary behavioural reports while being in the role of the parent versus being in the job role. Consistent with recent research on personality traits, the findings of the present study showed that people express a wide range of virtue states in their everyday lives. Within‐person changes in virtue states were not random but were contingent on people's current role context and also meaningfully related to their momentary affective experiences. At the same time, people's average level of virtue states, their degree of variation in virtue states, and their signature ways of reacting to role contexts turned out to be stable, trait‐like individual difference characteristics. Discussion focuses on the implications for the conception of character traits in scientific psychology and beyond.     

Who volunteers in psychology experiments? An empirical review of prosocial motivation in volunteering

The central purpose of the present research is to provide a review of social value orientation (i.e., prosocial, individualistic, and competitive orientation), a construct measured with methods rooted in game theory (i.e., decomposed games). Also, we examine its ability to predict volunteering in psychology experiments. Consistent with hypotheses, Study 1 revealed that prosocials are more likely to volunteer in psychological experiments than do individualists and competitors. Study 2 replicated these findings, and revealed also that social value orientation was strongly linked to the academic study they chose. In particular, among psychology students, prosocials (57%) was the largest group, followed by individualists (37%), and only a few competitors (6%); in contrast, among economics students, individualists appeared largest (47%), followed by prosocials (36%), and still a fairly sizeable percentage of competitors (17%). It is concluded that psychologists and economists tend to rely on samples (from their participant pools) that may systematically differ in terms of motivation and beliefs that are associated with differences in prosociality, selfishness, and competition.     

One and Done? Optimal Decisions From Very Few Samples

In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling‐based approximations are a common way to implement Bayesian inference, the very limited numbers of samples often used by humans seem insufficient to approximate the required probability distributions very accurately. Here, we consider this discrepancy in the broader framework of statistical decision theory, and ask: If people are making decisions based on samples—but as samples are costly—how many samples should people use to optimize their total expected or worst‐case reward over a large number of decisions? We find that under reasonable assumptions about the time costs of sampling, making many quick but locally suboptimal decisions based on very few samples may be the globally optimal strategy over long periods. These results help to reconcile a large body of work showing sampling‐based or probability matching behavior with the hypothesis that human cognition can be understood in Bayesian terms, and they suggest promising future directions for studies of resource‐constrained cognition.     

Sampling in developmental science: Situations,shortcomings, solutions,and standards

Sampling is a key feature of every study in developmental science. Although sampling has far-reaching implications, too little attention is paid to sampling. Here, we describe, discuss, and evaluate four prominent sampling strategies in developmental science: population-based probability sampling, convenience sampling, quota sampling, and homogeneous sampling. We then judge these sampling strategies by five criteria: whether they yield representative and generalizable estimates of a study’s target population, whether they yield representative and generalizable estimates of subsamples within a study’s target population, the recruitment efforts and costs they entail, whether they yield sufficient power to detect subsample differences, and whether they introduce “noise” related to variation in subsamples and whether that “noise” can be accounted for statistically. We use sample composition of gender, ethnicity, and socioeconomic status to illustrate and assess the four sampling strategies. Finally, we tally the use of the four sampling strategies in five prominent developmental science journals and make recommendations about best practices for sample selection and reporting.     

Adaptive sampling for active learning with genetic programming

Active learning is a machine learning paradigm allowing to decide which inputs to use for training. It is introduced to Genetic Programming (GP) essentially thanks to the dynamic data sampling, used to address some known issues such as the computational cost, the over-fitting problem and the imbalanced databases. The traditional dynamic sampling for GP gives to the algorithm a new sample periodically, often each generation, without considering the state of the evolution. In so doing, individuals do not have enough time to extract the hidden knowledge. An alternative approach is to use some information about the learning state to adapt the periodicity of the training data change. In this work, we propose an adaptive sampling strategy for classification tasks based on the state of solved fitness cases throughout learning. It is a flexible approach that could be applied with any dynamic sampling. We implemented some sampling algorithms extended with dynamic and adaptive controlling re-sampling frequency. We experimented them to solve the KDD intrusion detection and the Adult incomes prediction problems with GP. The experimental study demonstrates how the sampling frequency control preserves the power of dynamic sampling with possible improvements in learning time and quality. We also demonstrate that adaptive sampling can be an alternative to multi-level sampling. This work opens many new relevant extension paths.     

Participation profiles of current masters swimmers and their (lack of) retrospective associations with youth experiences

National athlete development models often give little consideration to the multiple ways in which adults might participate in sport (i.e., recreationally or competitively, through sampling or specialization), or their trajectories into specific patterns of adult sport participation. Using adult swimmers' current and retrospective (youth swimming) data, the purpose of this study was threefold: a) to identify profiles of masters swimmers based on participation characteristics, b) to explore demographic differences between profiles, and c) to retrospectively examine these profiles for meaningful associations with youth swimming experiences. Survey data were collected from 205 Canadian masters swimmers with previous competitive youth swimming experience (M age = 44.4, range = 18–85; 60% women, 40% men). Two-step clustering analysis of masters' current swimming participation resulted in three distinct profiles: 1) “low-competitive specializers,” 2) “high-competitive specializers,” and 3) “samplers.” These profiles were not significantly associated with any demographic variables in adulthood, nor did they differ in terms of youth swimming experiences and time to transition into masters swimming. The remarkable homogeneity of social-demographic variables suggests that further work is needed to make masters swimming more inviting to diverse adult populations. Retrospective data revealed disengagement and later re-engagement in swimming that was consistent across masters profiles. Implications of these findings for coaches and programmers, as well as the need to account for adults' potentially complex re-entries into sport after time away, are discussed.     

Unsymbolized thinking

Unsymbolized thinking—the experience of an explicit, differentiated thought that does not include the experience of words, images, or any other symbols—is a frequently occurring yet little known phenomenon. Unsymbolized thinking is a distinct phenomenon, not merely, for example, an incompletely formed inner speech or a vague image, and is one of the five most common features of inner experience (the other four: inner speech, inner seeing, feelings, and sensory awareness). Despite its high frequency, many people, including many professional students of consciousness, believe that such an experience is impossible. However, because the existence of unsymbolized thinking indicates that much experienced thinking takes place without any experience of words or other symbols, acknowledging the existence of unsymbolized thinking may have substantial theoretical import.