P-technique Factor Analysis Research Articles

An investigation of the potential clinical utility of critical slowing down as an early warning sign for recurrence of depression

Background and objectivesMuch of the burden of depressive illness is due to relapses that occur after treatment into remission. Prediction of an individual's imminent depressive relapse could lead to just-in-time interventions to prevent relapse, reducing depression's substantial burden of disability, costs, and suicide risk. Increasingly strong relationships in the form of autocorrelations between depressive symptoms, a signal of a phenomenon described as critical slowing down (CSD), have been proposed as a means of predicting relapse. MethodsIn the current study, four participants in remission from depression, one of whom relapsed, responded to daily smartphone surveys with depression symptoms. We used p-technique factor analysis to identify depression factors from over 100 survey responses. We then tested for the presence of CSD using time-varying vector autoregression and detrended fluctuation analysis. ResultsWe found evidence that CSD provided an early warning sign for depression in the participant who relapsed, but we also detected false positive indications of CSD in participants who did not relapse. Results from time-varying vector autoregression and detrended fluctuation analysis were not in agreement. LimitationsLimitations include use of secondary data and a small number of participants with daily responding to a subset of depression symptoms. ConclusionsCSD provides a compelling framework for predicting depressive relapse and future research should focus on improving detection of early warning signs reliably. Improving early detection methods for depression is clinically significant, as it would allow for the development of just-in-time interventions.

Characterizing emotional eating: Ecological momentary assessment with person-specific modeling

Emotional eating is a topic of clinical importance, with links to weight regulation and wellness. However, issues of concept clarity and measurement can interfere with efforts to understand and intervene on emotional eating. One explanation for prior difficulties in defining emotional eating may be that this construct is not uniform across individuals. The current study critically examined emotional eating by combining ecological momentary assessment (EMA) with an idiographic analytic approach. The study examined the heterogeneity in the emotions and dysregulated eating behaviors often thought to underlie emotional eating, by establishing and comparing latent factor profiles across individuals. Ten community adults with overweight or obesity completed a 21-day EMA protocol, with 5 daily prompts to report on relevant emotions and eating behaviors. P-technique factor analysis was used to examine the data. Results suggested variability across individuals in the number of factors that emerged, the items that loaded on each factor, and the strength of loadings. Dysregulated eating was not found to covary with affective states strongly enough to produce a distinct “emotional eating” factor for any individual, nor did the correlations between factors suggest strong relationships between emotions and dysregulated eating for most participants, even in this sample with 90% of participants self-identifying as “emotional eaters.” Findings are consistent with a growing body of literature questioning the validity of the “emotional eating” construct as currently defined and measured, and supports conceptualizing emotional eating as a locally heterogenous construct that varies between people. Combining EMA with an intra-individual modeling technique appears to be a promising approach for understanding emotional eating. Additional work with larger samples is needed to capture the full range in individual profiles.

Applying P-Technique Factor Analysis to Explore Person-Specific Models of Readiness-to-Exercise.

Recent research in exercise prescription and periodization has emphasized the importance of subjective experience, both in medium- and long-term monitoring, but also in the acute experience. Emerging evidence also highlights an important role of subjective readiness (pre-exercise mental and physical states) in determining how exercise is experienced, and in acutely modifying the prescribed exercise intensity. The concept of “readiness-to-exercise” shows promise in enabling and informing this acute decision-making to optimize the experiences and outcomes of exercise. While subjective experiences can be effectively assessed using psychometric scales and instruments, these are often developed and deployed using cross-sectional samples, with resulting structures that reflect a normative pattern (nomothetic). These patterns may fail to reflect individual differences in sensitivity, experience and saliency (idiographic). We conducted this research with the primary aim of comparing the nomothetical and idiographic approaches to modeling the relatively novel concept of readiness-to-exercise. Study 1 (nomothetic) therefore analyzed data collected from 572 participants who completed a one-time survey using R-technique factor analysis. Results indicated a four-factor structure that explained 60% of the variance: “health and fitness;” “fatigue;” “vitality” and “physical discomfort.” Study 2 (idiographic) included a sample of 29 participants who completed the scale multiple times, between 42 and 56 times: permitting intra-individual analysis using separate P-technique factor analyses. Our analyses suggested that many individuals displayed personal signature, or “profiles” of readiness-to-exercise that differed in structure from the nomothetic form: only two participants' personal signatures contained four structures as modeled in Study 1, whereas the majority demonstrated either two or three factors. These findings raise important questions about how experiential data should be collected and modeled, for use in research (conceptual development and measurement) and applied practice (prescribing, monitoring)—as well as in more applied research (implementation, effectiveness).

Testing P-Technique Factor Analysis With Non-Normal Time Series

There is an increasing need to analyze multivariate time series data due to the rapid development of data collection tools such as smartphone APPs, wearable sensors, and brain imaging techniques. P-technique factor analysis allows researchers to establish a measurement model for these time series. Analyzing such data is challenging because they are often non-normal (e.g., steps, heart rate, sleep, mood, and brain signals) and correlated at nearby time points. We propose using a bootstrap procedure to accommodate both the non-normality and the dependency of nearby time points. We explore the statistical properties with simulated data and illustrate the test with two empirical data sets. The results of the simulation study include (1) the bootstrap procedure performed better than an existing analytic procedure for time series data with excessive kurtosis (2) an existing analytic procedure performed better than the bootstrap procedure for normal time series and skewed time series.

Quantifying Model Error in P-technique Factor Analysis

P-technique factor analysis is an exploratory factor model for multivariate time series data. Assessing model fit of P-technique factor models is non-trivial because time series data are correlated at nearby time points. We present a test statistic that is appropriate for P-technique factor analysis. In addition, the test statistic allows researchers to quantify the amount of model error. We explore the statistical properties of the test statistic with simulated data and we illustrate its use with an empirical study of personality states. Results of the simulation study include (1) the empirical distributions of the test statistic approximately followed their respective theoretical chi-square distributions, (2) the empirical Type I error rates of the test of perfect fit are close to the nominal level and the empirical Type I error rates of the test of close fit are slightly lower than the nominal level, and (3) the empirical power rates of the test of perfect fit are satisfactory but the empirical power rates of the test of close fit are only satisfactory for small models.

Testing Process Factor Analysis Models Using the Parametric Bootstrap

ABSTRACTProcess factor analysis (PFA) is a latent variable model for intensive longitudinal data. It combines P-technique factor analysis and time series analysis. The goodness-of-fit test in PFA is currently unavailable. In the paper, we propose a parametric bootstrap method for assessing model fit in PFA. We illustrate the test with an empirical data set in which 22 participants rated their effects everyday over a period of 90 days. We also explore Type I error and power of the parametric bootstrap test with simulated data.

Modeling Heterogeneity in Momentary Interpersonal and Affective Dynamic Processes in Borderline Personality Disorder.

Borderline personality disorder (BPD) is a diagnosis defined by impairments in several dynamic processes (e.g., interpersonal relating, affect regulation, behavioral control). Theories of BPD emphasize that these impairments appear in specific contexts, and emerging results confirm this view. At the same time, BPD is a complex construct that encompasses individuals with heterogeneous pathology. These features-dynamic processes, situational specificity, and individual heterogeneity-pose significant assessment challenges. In the current study, we demonstrate assessment and analytic methods that capture both between-person differences and within-person changes over time. Twenty-five participants diagnosed with BPD completed event-contingent, ambulatory assessment protocols over 21 days. We used p-technique factor analyses to identify person-specific psychological structures consistent with clinical theories of personality. Five exemplar cases are selected and presented in detail to showcase the potential utility of these methods. The presented cases' factor structures reflect not only heterogeneity but also suggest points of convergence. The factors also demonstrated significant associations with important clinical targets (self-harm, interpersonal violence).

Determining the number of factors in P-technique factor analysis

ABSTRACTDetermining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A novel feature of P-technique data is that observations are usually sequentially dependent in some way. The current study evaluates 10 criteria for determining the number of factors for data simulated to resemble intensive repeated-measures data for which P-technique is usually applied. The number of factors, loading size, observed-to-latent ratio, serial-dependency, and sample size were simulation design factors with conditions simulated to resemble P-technique data. The methods are compiled from various statistical techniques and have been demonstrated in previous R-technique simulations. Finally, a real data example demonstrates applying the acceleration factor method to several time series data sets.

Age-Related Differences in the Dynamic Architecture of Intrinsic Networks

Correlations among low-frequency spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal reflect the connectivity of intrinsic large-scale networks in the brain. These correlations have typically been characterized over the entire timecourse (mean connectivity), but the mean correlations between regions vary dynamically. By focusing on the linear relationship between activity in network nodes within the default mode network (DMN), dorsal attention network (DAN), and fronto-parietal task control network (FPTC) captured by their inter-correlations, we demonstrate that this dynamic pattern of fluctuations reveals a detailed substructure, that this substructure is robust across individuals, and that the expression of specific factors is correlated with age. To do this, we conducted a chained P-technique factor analysis of the correlations in nonoverlapping temporal windows across N=145 normal aging subjects (age 56-89). The expression of factors within the DMN, FPTC, and DAN was highly correlated with age: Decreased intercorrelations within nodes in each factor were correlated with advanced age. Although these findings converge with those from stationary analysis, the ability to quantify age-related changes in the coherence of fluctuating connectivity may yield more insights into age-related cognitive decline.

P-Technique Factor Analysis of an extensive time series of hypnagogic hallucinations.

P-Technique Factor Analysis of an extensive time series of hypnagogic hallucinations.

Analyzing Intra-person Variation: Hybridizing the ACE Model with P-Technique Factor Analysis and the Idiographic Filter

Integrating idiographic and nomothetic approaches to the study of behavior has met with success via the idiographic filter (IF) which separates irrelevant inter-individual differences from relevant inter-individual similarities at the level of construct measurement in order to facilitate drawing conclusions regarding nomothetic relationships among the constructs. We propose an integration of the IF and the ACE behavior genetics models through the use of P-technique factor analysis and its dynamic factor analysis extensions and examine how it can strengthen the modeling of genetic and environmental effects in behavioral data representing intra-person variation, change, and process.

Investigating Change in Intraindividual Factor Structure Over Time

The investigation of change in factor structure over time can provide new opportunities for the development of theory in psychology. The method proposed to investigate change in intraindividual factor structure over time is an extension of P-technique factor analysis, in which the P-technique factor model is fit within relatively small windows of time, followed by modeling the factor model parameter trajectories. This article describes a Monte Carlo study undertaken to evaluate the proposed estimation procedure and approach to model fit. An illustrative example is provided to motivate the proposed model, and directions for future research are outlined.

The Recoverability of P-technique Factor Analysis

It seems that just when we are about to lay P–technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables—dynamic factor models—it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even though it does not explicitly model lagged information, P–technique's ability to recover the parameters of underlying dynamic processes involving lagged relations among the manifest variables is apparently robust and accurate. An empirical example is presented using 103 days of affective mood self-ratings from a young pregnant woman. Implications of the simulation and empirical findings are briefly discussed.

Multivariate, replicated, single-subject, repeated measures designs and P-technique factor analysis: a review of intraindividual change studies.

The precise, quantitative portrayal of intraindividual change is a key goal of developmental researchers. Research designs particularly appropriate to selected aspects of this goal are multivariate, replicated, single-subject, repeated measures (MRSRM) designs. Data collected with these designs may be factor analyzed with P-technique factor analysis to elucidate, for each individual studied, patterns of systematic change. The nature of the factor patterns obtained for each individual can then be compared across individuals to determine the relative idiosyncrasy or generality of patterns of change. This paper extends an earlier review (Luborsky & Mintz, 1972) of studies using multivariate, single-subject, repeated measures designs and P-technique factor analysis. The emphasis here is on both more recent studies and the value of subject replication in creating a confluence of idiographic and nomothetic approaches to the study of behavior and behavioral development across the lifespan.

Idiodynamic profiles of cardiovascular activity: A P-technique approach

A study was conducted to expand the conventional view of cardiovascular (CV) reactivity by using the idiodynamic paradigm for investigation of individuals. Patterns of autonomic CV regulation were assessed in six subjects across diverse laboratory tasks on three separate occasions. Individual CV profiles were derived from these data with P-technique factor analysis, and then group aggregated with chain P-technique. The composite pattern suggested a three-component solution consisting of cardiac rate, cardiac contractility, and peripheral resistance factors. Individual profiles were compared to the composite pattern; these profiles differed in the number of components derived, percentage variance explained by these components, and relative dominance of specific CV components. A hypothesis that emerged is that the subjects differed in the complexity of CV control. It appears that the idiodynamic framework, combined with novel research designs and statistical methods, may help expand the view of CV reactivity beyond the traditional unitary view as response magnitude.

Variability in constraints and functional competence in adults with multiple sclerosis.

Examine intraindividual change in physical and psychological impairments associated with multiple sclerosis and assess the relationship between changes in specific deficits and functional competence in activities of daily living. A multivariate, replicated, single-subject, repeated-measures design was used to examine variability patterns across subjects. Five adults with multiple sclerosis were assessed on leg strength, upright postural control, mood, fatigue, stress, and self-efficacy for 4 mo. Functional competence in three activities of daily living was also evaluated. P-technique factor analyses were performed to examine which variables covaried with time. Analyses revealed covariation among physical and psychological variables for four of the five participants. Across all participants, coefficients of variation revealed greater variability in stress (32.3%-53.4%) and fatigue (23.4%-5.9%) than in any of the physical variables (<20%), and variability in all impairments was greater than variability in the functional tasks (0%-12.6%). The greater stability in functional performance compared with both physical and psychological constraints provides important insight into symptom management and clinical intervention. The magnitude of variability found in the psychological variables across individuals also has implications concerning psychological adjustment to the disease.

Idiodynamics Vis-à-vis Psychophysiology: An Idiodynamic Portrayal of Cardiovascular Reactivity

Idiodynamics offers a conceptual foundation upon which alternatives to the prevailing model of cardiovascular reactivity could be advanced, built upon systematic investigations of individuals. The origins of a union of idiodynamics and psychophysiology are described, accompanied by an empirical study that exemplifies this synthesis. In the study, a montage of cardiovascular measures was used to assess autonomic patterns in six subjects across a range of laboratory tasks on three occasions. Cardiovascular profiles were derived with p-technique factor analysis and then group aggregated with chain p-technique. The group pattern suggested three components: rate, contractility, and peripheral resistance. When individual profiles were compared to the group, consistencies and disparities appeared. Differences in the number of factors, percentage of variance explained, and dominance of specific components distinguished subjects from one another, leading to a hypothesis about underlying cardiovascular complexity. Idiodynamics, combined with novel methodologies, can expand the construct of reactivity beyond traditional stimulus-response conceptualizations.

Community-based psychosocial rehabilitation and prospective change in functional, clinical, and subjective experience variables in schizophrenia.

In a previous study, we found that the intensity, specificity, and longitudinality of community-based psychosocial rehabilitation services were related to superior functional outcomes for individuals diagnosed with schizophrenia. The purpose of this study was to assess the degree to which the intensity and longitudinality of services were related to improvements in subjective experience and clinical outcomes, and to examine the relationships among prospective changes in functional, clinical, and subjective experience variables. One hundred seventy-two individuals diagnosed with a schizophrenia spectrum disorder were followed for 36 months in three distinct models of community-based care. Functional, clinical, and subjective experience outcome data were gathered every 6 months over a 3-year period. Data were analyzed using hierarchical linear modeling (HLM) and P-technique factor analysis. The results indicated that (1) greater service intensity and the longitudinality of services were associated with improvement in client self-esteem; (2) there was evidence for three distinct factors of prospective rehabilitative change that corresponded to the conceptual domains of clinical, functional, and subjective experience outcomes; and (3) there was no differential program impact on symptom levels or the intrapsychic deficits. In addition, the three-factor model of outcome consisting of functional change, clinical change, and subjective experience change was similar to Strauss and Carpenter's "open-linked" system of outcome in schizophrenia. The implications of these findings for research and practice in the area of community-based rehabilitation for individuals with schizophrenia are discussed.

Intra-individual Change and Inter-individual Differences in Negative Mood States of Older Women

The primary purpose of this exploratory study was to examine the stability and lability of negative mood from a health perspective. Negative mood factor structure was examined in order to evaluate intra-individual change. Few studies have addressed factorial invariance across individuals and across time. The sample was comprised of four women in their 60s and four women in their 80s. Short-term intra-individual change and inter-individual differences in negative mood were assessed with a replicated single-subject design. Participants completed items from the 8SQ questionnaire for 100 consecutive days. P-technique factor analysis was used to examine the structure of negative mood factors, which were than graphed to determine level change over time. The number of factors were consistent, however, the items comprising the factors were not consistent across all participants. Patterns of intra-individual change in the negative mood factor of “ fatigue” was found to be highly individualised.

The Missouri Psychoanalytic Counseling Research Project: Relation of changes in counseling process to client outcomes.

A short-term psychoanalytic counseling model was used to identify process dimensions and client outcomes. Six counselors saw 16 clients over the course of 2 semesters. Clients responded to measures at pre- and posttest and after each session, and counselors filled out measures following each session. Sessions were audio- and videotaped and viewed by trained raters. P-technique factor analysis identified 4 dimensions: Psychoanalytic Technique, Working Alliance, Client Resistance, and Client Transference. Results of hierarchical linear modeling indicated that counselor use of psychoanalytic technique and the working alliance increased steadily across the sessions, whereas client resistance steadily decreased. The alliance dimension also changed in a quadratic fashion. The process dimensions also influenced each other and were related to better client outcomes. Implications are discussed and suggestions for future research are provided. The research reported here is about the process and outcomes of time-limited psychoanalytic counseling and is based on a program of theory-driven inquiry derived from the work of Patton and Meara (1992). The need for the study arises from the absence of systematic empirical knowledge about the key elements of the psychoanalytic counseling process, particularly as those are continuously measured over the course of counseling. Given our own understanding of psychoanalyti c counseling as both researchers and practitioners, we were interested in answering the following questions: (a) What are the important dimensions of the psychoanalytic counseling process? (b) What is the nature of changes in these dimensions over time? (c) What are the ways in which these dimensions are related to each other over time? (d) How are changes in these dimensions related to client outcomes? To help us examine these questions we formulated a model to guide our inquiry.