scholarly journals Foundations of Idiographic Methods in Psychology and Applications for Psychotherapy

2019 ◽  
Author(s):  
Marilyn Piccirillo ◽  
Thomas Rodebaugh
Keyword(s):  
Longitudinal Data ◽  
Statistical Methods ◽  
Psychotherapy Research ◽  
Clinical Settings ◽  
Psychological Processes ◽  
Vector Autoregressive ◽  
Individual Level ◽  
Idiographic Approach ◽  
The Individual ◽  
Idiographic Methods

Researchers have long called for greater recognition and use of longitudinal, individual-level research in the study of psychopathology and psychotherapy. Much of our current research attempts to indirectly investigate individual-level, or idiographic, psychological processes via group-based, or nomothetic, designs. However, results from nomothetic research do not necessarily translate to the individual-level. In this review, we discuss how idiographic analyses can be integrated into psychotherapy and psychotherapy research. We examine and review key statistical methods for conducting idiographic analyses. These methods include factor-based and vector autoregressive approaches using longitudinal data. The theoretical framework behind each approach is reviewed and critically evaluated. Empirical examples of each approach are discussed, with the aim of helping interested readers consider how they may use idiographic methods to analyze longitudinal data and psychological processes. Finally, we conclude by citing key limitations of the idiographic approach, calling for greater development of these analyses to ease their successful integration into clinical settings.

scholarly journals Foundations of Idiographic Methods in Psychology and Applications for Psychotherapy

2019 ◽  
Author(s):  
Marilyn Piccirillo ◽  
Thomas Rodebaugh
Keyword(s):  
Longitudinal Data ◽  
Statistical Methods ◽  
Psychotherapy Research ◽  
Clinical Settings ◽  
Psychological Processes ◽  
Vector Autoregressive ◽  
Individual Level ◽  
Idiographic Approach ◽  
The Individual ◽  
Idiographic Methods

Researchers have long called for greater recognition and use of longitudinal, individual-level research in the study of psychopathology and psychotherapy. Much of our current research attempts to indirectly investigate individual-level, or idiographic, psychological processes via group-based, or nomothetic, designs. However, results from nomothetic research do not necessarily translate to the individual-level. In this review, we discuss how idiographic analyses can be integrated into psychotherapy and psychotherapy research. We examine and review key statistical methods for conducting idiographic analyses. These methods include factor-based and vector autoregressive approaches using longitudinal data. The theoretical framework behind each approach is reviewed and critically evaluated. Empirical examples of each approach are discussed, with the aim of helping interested readers consider how they may use idiographic methods to analyze longitudinal data and psychological processes. Finally, we conclude by citing key limitations of the idiographic approach, calling for greater development of these analyses to ease their successful integration into clinical settings.

Missing Data in Research on Youth and Family Programs

2021 ◽  
pp. 003329412110268
Author(s):  
Jaime Ballard ◽  
Adeya Richmond ◽  
Suzanne van den Hoogenhof ◽  
Lynne Borden ◽  
Daniel Francis Perkins
Keyword(s):  
Missing Data ◽  
Statistical Methods ◽  
Self Report ◽  
Program Participation ◽  
Multilevel Data ◽  
Individual Level ◽  
Level Data ◽  
Before And After ◽  
Post Test ◽  
The Individual

Background Multilevel data can be missing at the individual level or at a nested level, such as family, classroom, or program site. Increased knowledge of higher-level missing data is necessary to develop evaluation design and statistical methods to address it. Methods Participants included 9,514 individuals participating in 47 youth and family programs nationwide who completed multiple self-report measures before and after program participation. Data were marked as missing or not missing at the item, scale, and wave levels for both individuals and program sites. Results Site-level missing data represented a substantial portion of missing data, ranging from 0–46% of missing data at pre-test and 35–71% of missing data at post-test. Youth were the most likely to be missing data, although site-level data did not differ by the age of participants served. In this dataset youth had the most surveys to complete, so their missing data could be due to survey fatigue. Conclusions Much of the missing data for individuals can be explained by the site not administering those questions or scales. These results suggest a need for statistical methods that account for site-level missing data, and for research design methods to reduce the prevalence of site-level missing data or reduce its impact. Researchers can generate buy-in with sites during the community collaboration stage, assessing problematic items for revision or removal and need for ongoing site support, particularly at post-test. We recommend that researchers conducting multilevel data report the amount and mechanism of missing data at each level.

Culture’s Constraints

2018 ◽  
pp. 61-78 ◽  
Author(s):  
Michele J. Gelfand ◽  
Nava Caluori ◽  
Sarah Gordon ◽  
Jana Raver ◽  
Lisa Nishii ◽  
...  
Keyword(s):  
Cultural Differences ◽  
Psychological Processes ◽  
Social Situations ◽  
Individual Level ◽  
Societal Factors ◽  
Wide Range ◽  
Cultural Processes ◽  
The Individual

Research on culture has generally ignored social situations, and research on social situations has generally ignored culture. In bringing together these two traditions, we show that nations vary considerably in the strength of social situations, and this is a key conceptual and empirical bridge between macro and distal cultural processes and micro and proximal psychological processes. The model thus illustrates some of the intervening mechanisms through which distal societal factors affect individual processes. It also helps to illuminate why cultural differences persist at the individual level, as they are adaptive to chronic differences in the strength of social situations. The strength of situations across cultures can provide new insights into cultural differences in a wide range of psychological processes.

scholarly journals Identifying atypical change at the individual level from childhood to adolescence

2018 ◽  
Author(s):  
Eduardo Estrada
Keyword(s):  
Linear Regression ◽  
Longitudinal Data ◽  
Statistical Model ◽  
Verbal Ability ◽  
Individual Change ◽  
Important Goal ◽  
Individual Level ◽  
Statistical Procedures ◽  
Potential Applications ◽  
The Individual

Identifying change at the individual level is an important goal for researchers, educators, and clinicians. We present a set of statistical procedures for identifying individuals who depart from a normative change. Using Latent Change Scores models (LCS), we illustrate how the Individual Likelihood computed from a statistical model for change (IL) and from an alternative unrestricted model (ILsat) can be used to identify atypical trajectories in situations with several measurement occasions. Using LCS and linear regression, we also show how the observed and latent change residuals can be used to identify atypical individual change between 2 measurement occasions. We apply these methods to a measure of general verbal ability (from WISC–R), from a large sample of individuals assessed every 2 years from Grade 1 to 9. We demonstrate the efficiency of these techniques, illustrate their use to identify individual change in longitudinal data, and discuss potential applications in developmental research.

scholarly journals Trends in Social Capital: Membership of Associations in Great Britain, 1991–98

2003 ◽  
Vol 33 (3) ◽  
pp. 515-525 ◽  
Author(s):  
ALAN WARDE ◽  
GINDO TAMPUBOLON ◽  
BRIAN LONGHURST ◽  
KATHRYN RAY ◽  
MIKE SAVAGE ◽  
...  
Keyword(s):  
Social Capital ◽  
Great Britain ◽  
Longitudinal Data ◽  
Panel Study ◽  
Aggregate Stability ◽  
Voluntary Association ◽  
Individual Level ◽  
The Individual ◽  
Voluntary Association Membership

This Note uses the British Household Panel Study (BHPS) to consider the changing volume and distribution of voluntary association membership (and hence social capital) in Great Britain. We aim to supplement Hall's study of trends in social capital published in this Journal with more recent and longitudinal data. This allows us to show that whilst the volume of social capital is not declining, it is becoming increasingly class specific, and that its relative aggregate stability masks considerable turnover at the individual level. These findings are significant for current debates on social capital.

scholarly journals Current trends in the application of causal inference methods to pooled longitudinal observational infectious disease studies—A protocol for a methodological systematic review

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250778
Author(s):  
Heather Hufstedler ◽  
Ellicott C. Matthay ◽  
Sabahat Rahman ◽  
Valentijn M. T. de Jong ◽  
Harlan Campbell ◽  
...  
Keyword(s):  
Systematic Review ◽  
Longitudinal Data ◽  
Full Text ◽  
Empirical Studies ◽  
Joint Estimation ◽  
Related Research ◽  
Individual Level ◽  
The Face ◽  
Business Source Premier ◽  
The Individual

Introduction Pooling (or combining) and analysing observational, longitudinal data at the individual level facilitates inference through increased sample sizes, allowing for joint estimation of study- and individual-level exposure variables, and better enabling the assessment of rare exposures and diseases. Empirical studies leveraging such methods when randomization is unethical or impractical have grown in the health sciences in recent years. The adoption of so-called “causal” methods to account for both/either measured and/or unmeasured confounders is an important addition to the methodological toolkit for understanding the distribution, progression, and consequences of infectious diseases (IDs) and interventions on IDs. In the face of the Covid-19 pandemic and in the absence of systematic randomization of exposures or interventions, the value of these methods is even more apparent. Yet to our knowledge, no studies have assessed how causal methods involving pooling individual-level, observational, longitudinal data are being applied in ID-related research. In this systematic review, we assess how these methods are used and reported in ID-related research over the last 10 years. Findings will facilitate evaluation of trends of causal methods for ID research and lead to concrete recommendations for how to apply these methods where gaps in methodological rigor are identified. Methods and analysis We will apply MeSH and text terms to identify relevant studies from EBSCO (Academic Search Complete, Business Source Premier, CINAHL, EconLit with Full Text, PsychINFO), EMBASE, PubMed, and Web of Science. Eligible studies are those that apply causal methods to account for confounding when assessing the effects of an intervention or exposure on an ID-related outcome using pooled, individual-level data from 2 or more longitudinal, observational studies. Titles, abstracts, and full-text articles, will be independently screened by two reviewers using Covidence software. Discrepancies will be resolved by a third reviewer. This systematic review protocol has been registered with PROSPERO (CRD42020204104).

scholarly journals Inter-Individual Differences in Multivariate Time-Series

2020 ◽  
Vol 36 (3) ◽  
pp. 482-491
Author(s):  
Anja F. Ernst ◽  
Casper J. Albers ◽  
Bertus F. Jeronimus ◽  
Marieke E. Timmerman
Keyword(s):  
Time Series ◽  
Individual Differences ◽  
Latent Class ◽  
Multivariate Time Series ◽  
Time Series Models ◽  
Vector Autoregressive ◽  
Individual Level ◽  
Diurnal Patterns ◽  
Emotion Dynamics ◽  
The Individual

Abstract. Theories of emotion regulation posit the existence of individual differences in emotion dynamics. Current multi-subject time-series models account for differences in dynamics across individuals only to a very limited extent. This results in an aggregation that may poorly apply at the individual level. We present the exploratory method of latent class vector-autoregressive modeling (LCVAR), which extends the time-series models to include clustering of individuals with similar dynamic processes. LCVAR can identify individuals with similar emotion dynamics in intensive time-series, which may be of unequal length. The method performs excellently under a range of simulated conditions. The value of identifying clusters in time-series is illustrated using affect measures of 410 individuals, assessed at over 70 time points per individual. LCVAR discerned six clusters of distinct emotion dynamics with regard to diurnal patterns and augmentation and blunting processes between eight emotions.

scholarly journals Applying SCA for high-accuracy cortical auditory ERPs in children

2020 ◽  
Author(s):  
S.E.P. Bruzzone ◽  
N. T. Haumann ◽  
M. Kliuchko ◽  
P. Vuust ◽  
E. Brattico
Keyword(s):  
Event Related Potentials ◽  
Component Analysis ◽  
High Accuracy ◽  
Clinical Settings ◽  
List Type ◽  
Spike Density ◽  
Individual Level ◽  
Related Potentials ◽  
Auditory Erps ◽  
The Individual

AbstractOverlapping neurophysiological signals are the main obstacle preventing from using cortical event-related potentials (ERPs) in clinical settings. Children ERPs are particularly affected by this problem, as their cerebral cortex is still maturing. To overcome this problem, we applied a new version of Spike-density Component Analysis (SCA), an analysis method recently introduced, to isolate with high accuracy the neural components of auditory ERP responses (AEPs) in 8-year-old children. Electroencephalography was used with 33 children to record AEPs to auditory stimuli varying in spectrotemporal features. Three different analysis approaches were adopted: the standard ERP analysis procedure, SCA with template-match (SCA-TM), and SCA with half-split average consistency (SCA-HSAC). SCA-HSAC most successfully allowed the extraction of AEPs for each child, revealing that the most consistent components were P1 and N2. An immature N1 component was also detected.Superior accuracy in isolating neural components at the individual level even in children was demonstrated for SCA-HSAC over other SCA approaches. Reliable methods of extraction of neurophysiological signals at the individual level are crucial for the application of cortical AEPs for routine diagnostic exams in clinical settings both in children and adults.HighlightsSpike-density component analysis (SCA) was validated on children ERPsSCA extracted overlapping neural components from auditory ERPs (AEPs)Child AEPs were modelled at the individual level

scholarly journals An Idiographic Approach to Personality Development: Examining Change and Consistency in Self-Concept

2019 ◽  
Author(s):  
Joshua James Jackson ◽  
Peter Harms
Keyword(s):  
Individual Differences ◽  
Rank Order ◽  
Personality Development ◽  
Wide Distribution ◽  
Self Concept ◽  
Individual Level ◽  
Self Evaluation ◽  
Level Change ◽  
Idiographic Approach ◽  
The Individual

The field of personality development almost exclusively relies on nomothetic measures (i.e., measures that are designed to capture universal, shared characteristics). Over-reliance on nomothetic measures can neglect important, individualized aspects of personality that are not captured with standard nomothetic measures. The current study takes an individual, idiographic approach to studying personality development by examining the development of one’s self-concept. Participants (N = 507) provided 20 answers to the question “who am I?” four times across a four-year period in college. These self-defining statements were categorized into seven categories (loci, activities and interests, traits, self-evaluation, goals, ideology, and student), and their change and consistency were examined in multiple ways—using rank-order consistency, mean-level change, individual differences in change, and ipsative consistency. Analyses revealed that self-concept is moderately consistent across time, but that mean-level changes occurred in six of the seven categories. Further, mean-level change in self-complexity, or the number of categories used, was also found. Mean-level changes were qualified by significant individual differences in change as well as by a wide distribution of ipsative consistency. The results suggest that young adults are both changing and maintaining the ways they describe themselves over time, some more than others. The diverse content and consistency at the individual-level demonstrates the need for more individual, idiographic assessments to thoroughly examine personality development.

scholarly journals Inter-individual differences in multivariate time series: Latent class vector-autoregressive modelling

2020 ◽  
Author(s):  
Anja Franziska Ernst ◽  
Casper J Albers ◽  
Bertus F. Jeronimus ◽  
Marieke Timmerman
Keyword(s):  
Time Series ◽  
Individual Differences ◽  
Latent Class ◽  
Multivariate Time Series ◽  
Time Series Models ◽  
Autoregressive Modelling ◽  
Vector Autoregressive ◽  
Individual Level ◽  
Emotion Dynamics ◽  
The Individual

Theories of emotion regulation posit the existence of individual differences in emotion dynamics. Current multi-subject time-series models account for differences in dynamics across individuals only to a very limited extent. This results in an aggregation that may poorly apply at the individual level. We present the exploratory method of latent class vector-autoregressive modelling (LCVAR), which extends the time-series models to include clustering of individuals with similar dynamic processes. LCVAR can identify individuals with similar emotion dynamics in intensive time-series, which may be of unequal length. The method performs excellently under a range of simulated conditions. The value of identifying clusters in time-series is illustrated using affect measures of 410 individuals, assessed at over 70 time points per individual. LCVAR discerned six clusters of distinct emotion dynamics with regard to diurnal patterns and augmentation and blunting processes between eight emotions.

Sign in / Sign up

Export Citation Format

Share Document