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Many of the theories used in behavioral cybersecurity research have been applied with a nomothetic approach, which is characterized by cross-sectional data (e.g., one-time surveys) that identify patterns across a population of individuals. Although this can provide valuable between-person, point-in-time insights (e.g., employees who use neutralization techniques, such as denying responsibility for cybersecurity policy violations, tend to comply less), it is unable to reveal within-person patterns that account for varying experiences and situations over time. This paper articulates why an idiographic approach, which undertakes a within-person analysis of longitudinal data, can: (1) help validate widely used theories in behavioral cybersecurity research that imply patterns of behavior within a given person over time and (2) provide distinct theoretical insights on behavioral cybersecurity phenomena by accounting for such within-person patterns. To these ends, we apply an idiographic approach to an established theory in behavioral cybersecurity research--neutralization theory--and empirically test a within-person variant of this theory using a four-week experience sampling study. Our results support a more granular application of neutralization theory in the cybersecurity context that considers the behavior of a given person over time. We conclude the paper by highlighting the contexts and theories that provide the most promising opportunities for future behavioral cybersecurity research using an idiographic approach. [ABSTRACT FROM AUTHOR]

This paper explores Seasonal Affective Disorder (SAD) as an idiopathic and idiographic phenomenon in a discussion about (low) light and social relations. Tracing a history of unsuccessful biosociality around SAD via archived and contemporary testimony, the paper uses narrative responses from a recent qualitative survey to explore how and why winter depression might be a difficult experience around which to form community. With brief reflections on a series of public workshops led by the research team in Scotland, we suggest that social and cultural geographies of creative practice are one vehicle for fostering new kinds of environmental biosolidarities, arguably rendered essential in the face of uncertain climatic futures that threaten increasingly disruptive light-mental health relations. More broadly, we discuss our contributions to human geographies of light-dark relations, SAD and biosociality. We conclude the paper with a call for more nuanced account of social, cultural, and emotional geographies of environmental illness. [ABSTRACT FROM AUTHOR]

This special issue is a collection of papers inspired by Dr. Molenaar's work and innovations – a tribute to his passion for advancing science and his ability to ignite a spark of creativity and innovation in multiple generations of scientists. Following Dr. Molenaar's creative breadth, the papers address a wide variety of topics – sharing of new methodological developments, ideas, and findings in idiographic science, study of intraindividual variation, behavioral genetics, model inference/identification/selection, and more. [ABSTRACT FROM AUTHOR]

Gender is person-specific, and it influences and is influenced by a breadth of multidimensional psychological factors, including cognition. Directionality is important for research on gender and cognition, as debate surrounds, for instance, whether masculine self-concepts precede spatial skills, or whether the reverse is true. In order to provide novel insights into the individualized nature of these relations, a person-specific network approach devised by Peter Molenaar and the first author – group iterative multiple model estimation for multiple solutions (GIMME-MS) – was applied to 75-day intensive longitudinal data on gender self-concept (i.e., femininity-masculinity, instrumentality, and expressivity) and cognition (i.e., mental rotations and verbal recall) from 103 young adults. GIMME-MS estimates individualized networks that contain same-day and next-day directed relations, prioritizing relations common across participants. It is ideal for analyzing behavioral time series with unclear directionality, as it generates multiple solutions from which an optimal one is selected. GIMME-MS revealed notable heterogeneity in the presence, direction, and nature of relations from gender self-concept to cognition (∼26% of participants) and vice versa (∼21% of participants). Findings are wholly novel in revealing the person-specific nature of gender and its cognitive dynamics, yet somehow, unsurprising given the revolutionary corpus of Peter Molenaar. [ABSTRACT FROM AUTHOR]

With the increased use of time series data in human research, ranging from ecological momentary assessments to data passively obtained, researchers can explore dynamic processes more than ever before. An important question researchers must ask themselves is, do I think all individuals have similar processes? If not, how different, and in what ways? Dr. Peter Molenaar's work set the foundation to answer these questions by providing insight into individual-level analysis for processes that are assumed to differ across individuals in at least some aspects. Currently, such assumptions do not have a clear taxonomy regarding the degree of homogeneity in the patterns of relations among variables and the corresponding parameter values. This paper provides the language with which researchers can discuss assumptions inherent in their analyses. We define strict homogeneity as the assumption that all individuals have an identical pattern of relations as well as parameter values; pattern homogeneity assumes the same pattern of relations but parameter values can differ; weak homogeneity assumes there are some (but not all) generalizable aspects of the process; and no homogeneity explicitly assumes no population-level similarities in dynamic processes across individuals. We demonstrate these assumptions with an empirical data set of daily emotions in couples. [ABSTRACT FROM AUTHOR]

Evidence suggests that complex micro‐dynamics occurring in daily life underly the development of mental distress. We aimed to (1) study the cross‐lagged association between stressful events and negative affect (NA), (2) show that there is substantial between‐person variability in idiographic associations and (3) show that idiographic associations are indicative of mental health. Experience sampling study assessing perceived stressfulness of events (PSE) and NA four times per day for 2 weeks in a non‐clinical convenience sample (N = 70, mean age = 22.9, 61% female, 69% German). Bivariate vector autoregressive model implemented in dynamic structural equation modelling to model the associations between stressful events and NA and obtain idiographic associations. Stressfulness of events and NA were significantly reciprocally associated. Autocorrelations and cross‐lagged associations from PSE to NA showed substantial variability and were significantly related with trait measures of depression, anxiety, well‐being, and perceived stress. Contrary to expectations, cross‐lagged associations from NA to stressfulness of events were not related to trait mental health. The approach outlined in this article is useful for studying idiographic dynamics in daily life. The findings increase our understanding of micro‐dynamics underlying mental health and individual differences in these processes. [ABSTRACT FROM AUTHOR]

AbstractIdiographic measurement models such as p-technique and dynamic factor analysis (DFA) assess latent constructs at the individual level. These person-specific methods may provide more accurate models than models obtained from aggregated data when individuals are heterogeneous in their processes. Developing clustering methods for the grouping of individuals with similar measurement models would enable researchers to identify if measurement model subtypes exist across individuals as well as assess if the different models correspond to the same latent concept or not. In this paper, methods for clustering individuals based on similarity in measurement model loadings obtained from time series data are proposed. We review literature on idiographic factor modeling and measurement invariance, as well as clustering for time series analysis. Through two studies, we explore the utility and effectiveness of these measures. In Study 1, a simulation study is conducted, demonstrating the recovery of groups generated to have differing factor loadings using the proposed clustering method. In Study 2, an extension of Study 1 to DFA is presented with a simulation study. Overall, we found good recovery of simulated clusters and provide an example demonstrating the method with empirical data. [ABSTRACT FROM AUTHOR]

Complex dynamic systems offer a rich platform for understanding the individual or the person‐specific mechanisms. Yet, in learning analytics research and education at large, a complex dynamic system has rarely been framed, developed, or used to understand the individual student where the learning process takes place. Individual (or person‐specific) methods can accurately and precisely model the individual person, create person‐specific models, and devise unique parameters for each individual. Our study used the latest advances in complex systems dynamics to study the differences between group‐based and individual self‐regulated learning (SRL) dynamics. The findings show that SRL is a complex, dynamic system where different sub‐processes influence each other resulting in the emergence of non‐trivial patterns that vary across individuals and time scales, and as such far from the uniform picture commonly theorized. We found that the average SRL process does not reflect the individual SRL processes of different people. Therefore, interventions derived from the group‐based SRL insights are unlikely to be effective in personalization. We posit that, if personalized interventions are needed, modelling the person with person‐specific methods should be the guiding principle. Our study offered a reliable solution to model the person‐specific self‐regulation processes which can serve as a ground for understanding and improving individual learning and open the door for precision education. Practitioner notesWhat is already known about this topic Self‐regulation is a catalyst for effective learning and achievement.Our understanding of SRL personalization comes from insights based on aggregate group‐based data.What this paper adds Every student has their own unique SRL process that varies from the average in non‐trivial ways.We offer a credible method for mapping the individualized SRL process.SRL dynamics vary across time scales. That is, the trait dynamics are different from the state dynamics, and they should be supported differently.Implications for practice and/or policy Personalization can best be achieved if based on unique person‐specific idiographic methods.Supporting learning and SRL in particular can be more efficient when we understand the differences across time scales and persons and apply insights accordingly.The general SRL average should not be expected to work for everyone. [ABSTRACT FROM AUTHOR]

This study uses time-intensive, item-level assessment to examine individual depressive and co-occurring symptom dynamics. Participants experiencing moderate-severe depression (N = 31) completed ecological momentary assessment (EMA) four times per day for 20 days (total observations = 2480). We estimated idiographic networks using MDD, anxiety, and ED items. ED items were most frequently included in individual networks relative to depression and anxiety items. We built ridge and logistic regression ensembles to explore how idiographic network centrality metrics performed at predicting between-subject depression outcomes (PHQ-9 change score and clinical deterioration, respectively) at 6-months follow-up. For predicting PHQ-9 change score, R 2 ranged between 0.13 and 0.28. Models predicting clinical deterioration ranged from no better than chance to 80 % accuracy. This pilot study shows how co-occurring anxiety and ED symptoms may contribute to the maintenance of depressive symptoms. Future work should assess the predictive utility of psychological networks to develop understanding of how idiographic models may inform clinical decisions. • Eating disorder, anxiety, and depressive symptoms were central in depressed sample. • Each participant had a unique network structure. • Central symptoms accounted for change in depressive symptoms at 6-months follow-up. • Central symptoms with high means and variability predicted clinical deterioration. • The structure of co-occurring psychopathology may relate to depression outcomes. [ABSTRACT FROM AUTHOR]

Idiographic measures, such as the Top Problems Assessment (TPA), offer great utility over nomothetic measures as they can be used to characterize participants in a person-centered manner. Despite such utility, idiographic measures rely on heuristic coding systems, which limit their applicability as a research tool. To address such concerns, the present study utilized Latent Dirichlet Allocation (LDA) to model the latent topics in youth- and parent-reported concerns identified by the TPA in a sample of 172 treatment-seeking youth. Clinical and demographic correlates associated with the identified topics were assessed using general linear models. Topic modeling identified four latent topics in youth-reported concerns that were characterized by Emotional Reactivity, Worry, Avoidance, and Contexts and six latent topics in the parent-reported concerns, Worry, Avoidance, Emotional Reactivity, Negative-Valenced Emotions, Parent–Child Interactions, and Other Maladaptive Behavioral Response. Certain latent topics were significantly associated with standardized measures of anxiety, avoidance, age and reported sex. Results serve as a proof of concept for applying topic modeling to the TPA and further contribute to efforts that characterize domains of impairment in youth with psychopathology. Results of the present study and subsequent discussion of important methodological and conceptual considerations may guide the use of similar research in leveraging data-driven modeling to elucidate latent topics underlying qualitative clinical data. [ABSTRACT FROM AUTHOR]

Background: Challenging behaviors like aggression and self-injury are dangerous for clients and staff in residential care. These behaviors are not well understood and therefore often labeled as "complex". Yet it remains vague what this supposed complexity entails at the individual level. This case-study used a three-step mixed-methods analytical strategy, inspired by complex systems theory. First, we construed a holistic summary of relevant factors in her daily life. Second, we described her challenging behavioral trajectory by identifying stable phases. Third, instability and extraordinary events in her environment were evaluated as potential change-inducing mechanisms between different phases. Case presentation: A woman, living at a residential facility, diagnosed with mild intellectual disability and borderline personality disorder, who shows a chronic pattern of aggressive and self-injurious incidents. She used ecological momentary assessments to self-rate challenging behaviors daily for 560 days. Conclusions: A qualitative summary of caretaker records revealed many internal and environmental factors relevant to her daily life. Her clinician narrowed these down to 11 staff hypothesized risk- and protective factors, such as reliving trauma, experiencing pain, receiving medical care or compliments. Coercive measures increased the chance of challenging behavior the day after and psychological therapy sessions decreased the chance of self-injury the day after. The majority of contemporaneous and lagged associations between these 11 factors and self-reported challenging behaviors were non-significant, indicating that challenging behaviors are not governed by mono-causal if-then relations, speaking to its complex nature. Despite this complexity there were patterns in the temporal ordering of incidents. Aggression and self-injury occurred on respectively 13% and 50% of the 560 days. On this timeline 11 distinct stable phases were identified that alternated between four unique states: high levels of aggression and self-injury, average aggression and self-injury, low aggression and self-injury, and low aggression with high self-injury. Eight out of ten transitions between phases were triggered by extraordinary events in her environment, or preceded by increased fluctuations in her self-ratings, or a combination of these two. Desirable patterns emerged more often and were less easily malleable, indicating that when she experiences bad times, keeping in mind that better times lie ahead is hopeful and realistic. [ABSTRACT FROM AUTHOR]

Numerous theories suggest that parents and adolescents influence each other in diverse ways; however, whether these influences differ between subgroups or are unique to each family remains uncertain. Therefore, this study explored whether data-driven subgroups of families emerged that exhibited a similar daily interplay between parenting and adolescent affective well-being. To do so, Subgrouping Group Iterative Multiple Model Estimation (S-GIMME) was used to estimate family-specific dynamic network models, containing same- and next-day associations among five parenting practices (i.e., warmth, autonomy support, psychological control, strictness, monitoring) and adolescent positive and negative affect. These family-specific networks were estimated for 129 adolescents (Mage = 13.3, SDage = 1.2, 64% female, 87% Dutch), who reported each day on parenting and their affect for 100 consecutive days. The findings of S-GIMME did not identify data-driven subgroups sharing similar parenting-affect associations. Instead, each family displayed a unique pattern of temporal associations between the different practices and adolescent affect. Thus, the ways in which parenting practices were related to adolescents' affect in everyday life were family specific. [ABSTRACT FROM AUTHOR]

Windelband ([1894]1980) advocated that two approaches are used for accumulating scientific knowledge. The first is the idiographic approach that derives knowledge from a single unit, and the second is the nomothetic approach that accumulates knowledge of a group. Given these two approaches, the former matches case studies while the latter is more appropriate with experimental group studies. Scientists have criticized both methodologies for their various limitations. Later, the single-case methodology emerged as an alternative that potentially allays these limitations. In this context, this narrative review aims to describe the historical roots of single-case experimental designs (SCEDs) that have emerged to eliminate the tension of nomothetic and idiographic approaches over time. First, the review focuses on the emergence of SCEDs. Second, the strengths and challenges of SCEDs are reviewed, including those to address the limitations of group experimental and case studies. Third, the use and analyses of SCEDs are outlined, considering their current status. Fourth, this narrative review continues to delineate the dissemination of SCEDs in the modern scientific world. As a result, SCEDs can be evaluated as a method that has the potential to overcome the issues encountered in case description and group experimental research. Thus, that helps accumulate nomothetic and idiographic knowledge in determining evidence-based practices. [ABSTRACT FROM AUTHOR]

A longstanding goal of psychology is to predict the things that people do and feel, but tools to accurately predict future behaviors and experiences remain elusive. In the present study, we used intensive longitudinal data (N = 104 college-age adults at a midwestern university; total assessments = 5,971) and three machine-learning approaches to investigate the degree to which three future behaviors and experiences-loneliness, procrastination, and studying-could be predicted from past psychological (i.e., personality and affective states), situational (i.e., objective situations and psychological situation cues), and time (i.e., trends, diurnal cycles, time of day, and day of the week) phenomena from an idiographic, person-specific perspective. Rather than pitting persons against situations, such an approach allows psychological phenomena, situations, and time to jointly predict future behaviors and experiences. We found (a) a striking degree of prediction accuracy across participants, (b) that a majority of participants future behaviors are predicted by both person and situation features, and (c) that the most important features vary greatly across people.

Maintenance of brain structure is essential for neurocognitive health. Precision medicine has interests in understanding how maintenance of an individual person's brain, including cerebral cortical structure, interacts with lifestyle factors like physical activity. Cortical structure, including cortical thickness, has recognized relationships with physical activity, but concepts of these relationships come from group, not individual, focused findings. Whether or how group-focused concepts apply to an individual person is fundamental to precision medicine interests but remains unclear. This issue was studied in a healthy man using concurrent micro-longitudinal tracking of magnetic resonance imaging-defined cortical thickness and accelerometer-defined steps/day over six months. These data permitted detailed examination of temporal relationships between thickness maintenance and physical activity at an individual level. Regression analyses revealed graded significant and trend-level temporal interactions between preceding activity vs. subsequent thickness maintenance and between preceding thickness maintenance vs. subsequent activity. Interactions were bidirectional, delayed/prolonged over days/weeks, positive, bilateral, directionally asymmetric, and limited in strength. These novel individual-focused findings in some ways are predicted, but in other ways remain unaddressed or undetected, by group-focused work. We suggest that individual-focused concepts of temporal interactions between maintenance of cortical structure and activity can provide needed new insight for personalized tailoring of physical activity, cortical, and neurocognitive health. [ABSTRACT FROM AUTHOR]

Background: Despite public knowledge of the adverse health effects of tobacco use, cigarettes remain widely used due to the addictive nature of nicotine. Physiologic adaptation to the presence of nicotine over time leads to unpleasant effects during withdrawal periods. Alongside these physiological effects, tobacco users often report changes in their consumption of tobacco in response to their emotional state. Objectives: We hypothesized that idiographic, or person-specific level, increases in participants' negative affect (NA) and positive affect (PA) ratings at a given time point would be associated with higher and lower craving and smoking over the following several hours, respectively. Fifty-two participants completed block randomized ecological momentary assessment surveys on their smartphones 4 times per day for 30 days, reporting from 0-100 their level of seven discrete emotions, stress, current craving, and smoking behavior. We analyzed the relationships between affect and smoking and craving using idiographic generalized linear models. Results: While some participants exhibited the hypothesized relationships, each participant varied in the strength and direction of the relationships between affect and craving/smoking. These outcomes were partially moderated at the group level by anxiety/depression at baseline, but not by level of nicotine dependence or sex. Conclusions: This suggests that the factors driving cigarette use vary significantly between individuals. [ABSTRACT FROM AUTHOR]

Power analysis informs a priori planning of behavioral and medical research, including for randomized clinical trials that are nomothetic (i.e., studies designed to infer results to the general population based on interindividual variabilities). Far fewer investigations and resources are available for power analysis of clinical trials that follow an idiographic approach, which emphasizes intraindividual variabilities between baseline (control) phase versus one or more treatment phases. We tested the impact on statistical power to detect treatment outcomes of four idiographic trial design factors that are under researchers' control, assuming a multiple baseline design: sample size, number of observations per participant, proportion of observations in the baseline phase, and competing statistical models (i.e., hierarchical modeling versus piecewise regression). We also tested the impact of four factors that are largely outside of researchers' control: population size, proportion of intraindividual variability due to residual error, treatment effect size, and form of outcomes during the treatment phase (phase jump versus gradual change). Monte Carlo simulations using all combinations of the factors were sampled with replacement from finite populations of 200, 1750, and 3500 participants. Analyses characterized the unique relative impact of each factor individually and all two-factor combinations, holding all others constant. Each factor impacted power, with the greatest impact being from larger treatment effect sizes, followed respectively by more observations per participant, larger samples, less residual variance, and the unexpected improvement in power associated with assigning closer to 50% of observations to the baseline phase. This study's techniques and R package better enable a priori rigorous design of idiographic clinical trials for rare diseases, precision medicine, and other small-sample studies. [ABSTRACT FROM AUTHOR]

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A complex systems approach to psychopathology proposes that general principles lie in the dynamic patterns of psychopathology, which are not restricted to specific psychological processes like symptoms or affect. Hence, it must be possible to find general change profiles in time series data of fully personalized questionnaires. In the current study, we examined general change profiles in personalized self-ratings and related these to four measures of treatment outcome (International Symptom Rating, 21-item Depression Anxiety and Stress Scale, daily symptom severity, and self-reflective capacity). We analyzed data of 404 patients with mood and/or anxiety disorders who completed daily self-ratings on personalized questionnaires during psychotherapy. For each patient, a principal component analysis was applied to the multivariate time series in order to retrieve an univariate person-specific time series. Then, using classification and regression methods, we examined these time series for the presence of general change profiles. The change profile classification yielded the following distribution of patients: no-shift (n = 55; 14%), gradual-change (n = 52; 13%), one-shift (n = 233; 58%), reversed-shift (n = 39; 10%) and multiple-shifts (n = 25; 6%). The multiple-shift group had better treatment outcome than the no-shift group on all outcome measures. The one-shift and gradual-change groups had better treatment outcome than the no-shift group on two and three outcome measures, respectively. Overall, this study illustrates that person-specific (idiographic) and general (nomothetic) aspects of psychopathology can be integrated in a complex systems approach to psychopathology, which may combine "the best of both worlds." General Scientific Summary: Personalized questionnaires have clinical and intuitive appeal, but the question rises how to generalize if questionnaires measure different constructs in different patients. In this article, we develop a novel method to abstract general change profiles from personalized daily questionnaire data collected during psychotherapy. We find that the way in which patients change on their personalized questionnaire over the course of treatment is related to treatment outcome as predicted by the complexity theory of psychopathology. [ABSTRACT FROM AUTHOR]

The article is a critical analysis of selected issues examined in Wprowadzenie do metodologii historii (Introduction to the Methodology of History), edited by Ewa Domańska and Jan Pomorski, Warsaw 2022. The reviewer focuses on general methodological and epistemological issues, believing that the authors of the various chapters pay too little attention, for the most part, to the relation between the methodology of history and general methodology. The discussion concerns the history of historiography, the role of history in the emergence of the humanities, the dispute over the status of history in the nineteenth century, particularly nomothetism and idiographism in the light of Auguste Comte's classification of sciences compiled in France and their division as seen by Wilhelm Windelband and Heinrich Rickert, proposed in Germany, as well as explanation in historiography. With regard to that last point, deductive-nomological and genetic explanations are considered. Attention is drawn to the problematic nature of the application of the classic pattern of deductive-nomological explanation in connection with the problem of universal laws and historical theories (more generally - concerning the social sciences), as well as to the differences in the understanding of causality in historiography and theoretical natural sciences, which is relevant to the analysis of the genetic explanation. In the final section of the article the author points to the link between the approach to historical cognition and general problems of epistemology. [ABSTRACT FROM AUTHOR]

AbstractIntroduction: Idiographic, or individual-level, methodology has been touted for its potential clinical utility. Empirically modeling relationships between symptoms for a single individual may offer both the client and therapist information that is useful for case conceptualization and treatment planning. However, few studies have investigated the feasibility and utility of integrating idiographic models in a clinical setting.Methods: Clients (n = 12) completed ecological momentary assessment regarding psychological symptoms five times per day for three weeks. Clients also generated predictions about the associative and directed relationships in their networks. Graphical vector autoregression was used to generate contemporaneous and directed networks from each client's data, and both clients and therapists completed self-report questionnaires regarding the feasibility and utility of these methods.Results: Results indicated that the idiographic model structures varied widely across participants and differed markedly from the client's own predictions. Clients found the models useful, whereas their therapists demonstrated a more tempered response.Discussion: These results echo previous findings suggesting that clients are willing to complete intensive data collection and are interested in the output, whereas therapists may be less open to idiographic methods. We provide recommendations for future implementation of personalized models in clinical settings.

Learning analytics is a fast‐growing discipline. Institutions and countries alike are racing to harness the power of using data to support students, teachers and stakeholders. Research in the field has proven that predicting and supporting underachieving students is worthwhile. Nonetheless, challenges remain unresolved, for example, lack of generalizability, portability and failure to advance our understanding of students' behaviour. Recently, interest has grown in modelling individual or within‐person behaviour, that is, understanding the person‐specific changes. This study applies a novel method that combines within‐person with between‐person variance to better understand how changes unfolding at the individual level can explain students' final grades. By modelling the within‐person variance, we directly model where the process takes place, that is the student. Our study finds that combining within‐ and between‐person variance offers a better explanatory power and a better guidance of the variables that could be targeted for intervention at the personal and group levels. Furthermore, using within‐person variance opens the door for person‐specific idiographic models that work on individual student data and offer students support based on their own insights. Practitioner notesWhat is already known about this topicPredicting students' performance has commonly been implemented using cross‐sectional data at the group level.Predictive models help predict and explain student performance in individual courses but are hard to generalize.Heterogeneity has been a major factor in hindering cross‐course or context generalization.What this paper addsIntra‐individual (within‐person) variations can be modelled using repeated measures data.Hybrid between–within‐person models offer more explanatory and predictive power of students' performance.Intra‐individual variations do not mirror interindividual variations, and thus, generalization is not warranted.Regularity is a robust predictor of student performance at both the individual and the group levels.Implications for practiceThe study offers a method for teachers to better understand and predict students' performance.The study offers a method of identifying what works on a group or personal level.Intervention at the personal level can be more effective when using within‐person predictors and at the group level when using between‐person predictors. [ABSTRACT FROM AUTHOR]

This study aims to highlight the theory-method relationship, as well as some problems strongly intertwined with the methodological. It is also intended to show how conceptualizations inspired by Piagetian and dynamic systems, for example, go hand in hand with methodologies that are close to them and from which they can be approached. Methodologically, a microgenetic approach is chosen in a singular version, which recovers the spirit conceived in the Geneva School from a cultural and idiographic perspective. Assuming development as change implies taking into account the temporality of the processes, for which we will rely on treatments, some already known (MIN-MAX) and others relatively new (Phase Spaces), which allow us to represent and understand in a more detailed way how change occurs in time, in this case, in the process of understanding the visual metaphor in children from 3 to 4 years of age. [ABSTRACT FROM AUTHOR]

To evaluate the feasibility, usability and clinical value of daily diary assessments combined with actigraphy in older persons with cognitive impairment. For 63 days, patients ≥60 years with cognitive impairments filled out a daily diary (including standardized questionnaires and cognitive test battery), and wore an actiwatch (sleep). After the study, participants and clinicians received personal feedback about patterns and daily triggers of depressive symptoms, sleep and cognitive performance. We assessed feasibility (participation rate, compliance and subjective burden), usability (variability and floor- or ceiling effects) and clinical value for patients and their clinicians (questionnaires). Of 96 eligible patients, 13 agreed to participate (13.5%). One patient dropped out after 2 days, another after 37 days, and another did not complete the cognitive test battery. Compliance rate was high (6.7-10% missing values). Subjective burden was relatively low. Time-series data showed sufficient variability and no floor- or ceiling effects, except for one relevant ceiling effect on the One Back task. The personal feedback report was considered insightful by 4 out of 11 participants and 5 out of 7 clinicians. Daily assessments are suitable for a minority of cognitively impaired older persons, but is helpful to increase insight into their symptoms. [ABSTRACT FROM AUTHOR]

Research and practice in clinical neurosciences often involve cognitive assessment. However, this has traditionally used a nomothetic approach, comparing the performance of patients to normative samples. This method of defining abnormality places the average test performance of neurologically healthy individuals at its center. However, evidence suggests that neurological 'abnormalities' are very common, as is the diversity of cognitive abilities. The veneration of central tendency in cognitive assessment, i.e., equating typicality with healthy or ideal, is, I argue, misguided on neurodiversity, bio-evolutionary, and cognitive neuroscientific grounds. Furthermore, the use of average performance as an anchor point for normal performance is unreliable in practice and frequently leads to the mischaracterization of cognitive impairments. Examples are explored of how individuals who are already vulnerable for socioeconomic reasons can easily be over-pathologized. At a practical level, by valuing diversity rather than typicality, cognitive assessments can become more idiographic and focused on change at the level of the individual. The use of existing methods that approach cognitive assessment ideographically is briefly discussed, including premorbid estimation methods and informant reports. Moving the focus away from averageness to valuing diversity for both clinical cognitive assessments and inclusion of diverse groups in research is, I argue, a more just and effective way forward for clinical neurosciences. [ABSTRACT FROM AUTHOR]

Significant heterogeneity in network structures reflecting individuals' dynamic processes can exist within subgroups of people (e.g., diagnostic category, gender). This makes it difficult to make inferences regarding these predefined subgroups. For this reason, researchers sometimes wish to identify subsets of individuals who have similarities in their dynamic processes regardless of any predefined category. This requires unsupervised classification of individuals based on similarities in their dynamic processes, or equivalently, in this case, similarities in their network structures of edges. The present paper tests a recently developed algorithm, S-GIMME, that takes into account heterogeneity across individuals with the aim of providing subgroup membership and precise information about the specific network structures that differentiate subgroups. The algorithm has previously provided robust and accurate classification when evaluated with large-scale simulation studies but has not yet been validated on empirical data. Here, we investigate S-GIMME's ability to differentiate, in a purely data-driven manner, between brain states explicitly induced through different tasks in a new fMRI dataset. The results provide new evidence that the algorithm was able to resolve, in an unsupervised data-driven manner, the differences between different active brain states in empirical fMRI data to segregate individuals and arrive at subgroup-specific network structures of edges. The ability to arrive at subgroups that correspond to empirically designed fMRI task conditions, with no biasing or priors, suggests this data-driven approach can be a powerful addition to existing methods for unsupervised classification of individuals based on their dynamic processes. [ABSTRACT FROM AUTHOR]

Ethical treatment of animals is the keystone of livestock production. Assessment of welfare is integral to assurance that animals experience a good life. Underpinning assurance are concepts of what constitutes good welfare, a good life and wellbeing. This review examines the concepts of welfare and wellbeing and the frameworks that have been developed for describing their scope. Historically, the tripartite model of welfare (feeling well, functioning well, leading a natural life) has been translated into the Five Freedoms (FF), Five Domains (FD), Good Life (GL), Welfare through Competence (WtC) and OIE World Organisation for Animal Health Welfare Principles frameworks. These frameworks provide scaffolds for numerous welfare assessment schemes. However, the three-part model of wellbeing (eudaimonia, hedonia, social interaction) lacks an explicit assessment framework, although FD, GL and WtC implicitly address aspects of wellbeing. Whereas positive affective (hedonic) experiences are considered to constitute positive welfare, positive aspects of eudaimonic function and social interaction are considered to be aspects of wellbeing above and beyond any indirect contribution they make to positive affective experiences (i.e. positive welfare). In this view, positive health is more than the absence of ill-health and positive social interactions are more than freedom from social isolation. New phenotypes in farm animals identified through analysis of sensor data are providing new perspectives on the functional integrity of biological processes that align well with concepts of wellbeing. These analyses draw on methods in resilience theory to examine stability in complex dynamic systems, specifically, uniformity of trajectories, periodicity of biorhythms and complexity of networks. A framework is proposed that loosely partitions FF, FD, GL and WtC into inputs, opportunities, and outcomes. The framework positions the outcome of biological integrity within the context of input constraints that can generate harms and deficiencies, and environmental opportunities that can foster acquisition of competencies and flourishing. It combines the eudaimonic, hedonic and social aspects of wellbeing within the tripartite terminology of welfare. It is hoped that the framework can help orientate new descriptions of biological function in farm animals derived from sensor data within the broader literature on welfare and wellbeing. Welfare and wellbeing are evolving concepts. Interest in assessing positive welfare has focussed on positive mental experiences. In contrast, wellbeing recognises fulfilment of the individual's potential to express positive health, positive social interactions, and a thriving physical constitution as additional positive attributes an animal can attain. New methods for analysis of sensor data are revealing integrity of biological function as an indicator of wellbeing. A framework is proposed that orientates biological integrity within an integrated description of welfare and wellbeing. [ABSTRACT FROM AUTHOR]

The aim of this paper is to report our notes from the field on using movement toward goals at an aggregate level as an inference of service effectiveness. Analysis of routinely collected data from UK youth mental health services was conducted (N = 8,172, age M = 13.8, 67% female, 32% male) to explore the impact of including goal‐based outcome data in combined calculations of standardized measures based on the principles of reliable change ("measurable change"). Due to the broad nature of standardized measures, inferred validity becomes diluted in any team or service level aggregate analysis. To make inferences that are closer to the person's interpretation of their difficulties, we argue that Idiographic Patient Reported Outcome Measures (I‐PROMs) counterbalance these limitations. This is supported by our findings. The measurable change metric is the first step towards enabling national analysis of aggregated I‐PROMs. I‐PROMs, supplemented by standardized measures should be used to consider service evaluation. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess the reliability, validity, and clinical utility of an idiographic, goal‐focused patient‐reported outcome measure: The Goals Form. Methods: Data were analyzed from 88 participants, across three samples, who had participated in collaborative–integrative psychotherapy at university‐based clinics in the UK. The samples were approximately 70% female with mean age of 30 years old. Results: The psychometric properties of the Goals Form were generally good. Noncompletion of individual items was low, temporal stability tended to be at target levels, and mean change scores showed moderate to good convergent validity against measures of psychological distress. The measure appeared sensitive to change in psychotherapy and was experienced by most patients as helpful. Conclusions: The Goals Form shows acceptable psychometric and clinical properties for routine outcome monitoring in psychotherapy. [ABSTRACT FROM AUTHOR]

Objective: Few studies report the psychometric properties of individualized patient‐reported outcome measures (I‐PROMs) combining traditional analysis and Item Response Theory (IRT). Methods: Pre‐ and posttreatment PSYCHLOPS data derived from six clinical samples (n = 939) were analyzed for validity, reliability, and responsiveness; caseness cutoffs and reliable change index were calculated. Exploratory and confirmatory factor analyses were used to determine whether items represented a unidimensional construct; IRT examined item properties of this construct. Results: Values for internal consistency, construct validity, convergent and discriminant validity, and structural validity were satisfactory. Responsiveness was high: Cohen's d, 1.48. Caseness cutoff and reliable clinical change scores were 6.41 and 4.63, respectively. IRT analysis confirmed that item scores possess strong properties in assessing the underlying trait measured by PSYCHLOPS. Conclusion: PSYCHLOPS met the criteria for norm‐referenced measurement of patient psychological distress. PSYCHLOPS functioned as a measure of a single latent trait, which we describe as "personal distress." [ABSTRACT FROM AUTHOR]

Background: There have been two kinds of methods for assessing individuals' motivation and their goal‐striving behavior. The idiographic method obtains respondents' individual descriptions of their behavior or inner experiences. The nomothetic approach uses a standardized questionnaire in which respondents select from a set of alternatives. Idiographic responses provide rich, individualized information, but they make comparisons across different individuals difficult. By contrast, the nomothetic approach loses valuable individualized information, but it readily lends itself to cross‐individual comparisons. Objective: The present authors have developed a family of motivational assessment instruments within the framework of the Goal Theory of Current Concerns and individuals' goal pursuits. Each of these instruments is a hybrid version of the idiographic and nomothetic methods. Each one obtains individualized information about each respondent at the start of the assessment, but it then utilizes rating scales that allow comparisons across different individuals to be made. The objective of the present article is to present this family of hybridized instruments for potential use in routine outcome monitoring. Method: The method used in this article was to review the development of this family of hybrid assessments instruments over the preceding decades and the research on their psychometric properties and clinical applications. These hybrid tools include the Interview Questionnaire, Work Concerns Inventory, Motivational Structure Questionnaire, and Personal Concerns Inventory and their variants. The review includes only the idiographic‐nomothetic approaches that are based on the Goal Theory of Current Concerns. Results: The review reveals that for each instrument, motivational indices are calculated, which have been shown to be valid and reliable. Analyses have also revealed adaptive and maladaptive motivational factors. Conclusions: The measures discussed here have proven useful in clinical applications, when, for example, they are used as components of Systematic Motivational Counseling and the Life Enhancement and Advancement Programme for helping individuals improve their motivational structure. Similarly, the measures hold promise for use in routine outcome monitoring. [ABSTRACT FROM AUTHOR]

Detecting early signs of recurrence of psychopathology is key for prevention and treatment. Personalized risk assessment is especially relevant for formerly depressed patients, for whom recurrence is common. We aimed to examine whether recurrence of depression can be accurately foreseen by applying Exponentially Weighted Moving Average (EWMA) statistical process control charts to Ecological Momentary Assessment (EMA) data. Participants were formerly depressed patients (n = 41) in remission who (gradually) discontinued antidepressants. Participants completed five smartphone-based EMA questionnaires a day for 4 months. EWMA control charts were used to prospectively detect structural mean shifts in high and low arousal negative affect (NA), high and low arousal positive affect (PA), and repetitive negative thinking in each individual. A significant increase in repetitive negative thinking (worry, negative thoughts about the self) was the most sensitive early sign of recurrence: this was detected in 18 out of 22 patients (82%) before recurrence and in 8 out of 19 patients (42%) who stayed in remission. A significant increase in NA high arousal (stress, irritation, restlessness) was the most specific early sign of recurrence: this was detected in 10 out of 22 patients (45%) before recurrence and in 2 out of 19 patients (11%) who stayed in remission. These mean changes were detected at least a month before recurrence in the majority of the participants. The outcomes were robust across EWMA parameter choices, but not when using fewer observations per day. The findings demonstrate the value of monitoring EMA data with EWMA charts for detecting prodromal symptoms of depression in real-time. General Scientific Summary: The findings of this study suggest that significant rises in repetitive negative thinking and high arousal negative emotions are early signs of recurrence of depression. Such increases can be detected reliably in real-time using person-specific statistical process control charts in formerly depressed patients. [ABSTRACT FROM AUTHOR]

Historically, evidence-based treatment has followed the latent disease model, which emphasizes using specific protocols tied to diagnoses. Today, the field continues to move towards an individual approach with models of treatment based on change processes. Here, we describe Process-Based Therapy (PBT), a new way of thinking that is moving away from nomothetic studies of diagnosis-driven interventions toward an individual approach to treatment that recognizes the complexity of human suffering. In PBT, therapists select from a wide range of evidence-based interventions, tailoring treatment to meet a person's needs at a given point in time. PBT is used to analyze intra-individual changes at the level of complex networks of biopsychosocial events, then gathering these into subpopulation and overall population parameters using theory and experimental analysis. PBT emphasizes tracking patient progress over time and treating symptoms based on current experiences, as well as understanding a patient's past and predicting future experiences. Through specific analyses that aid in this process, therapists can use PBT to create a network with clients to visualize symptoms over time and areas of change. [ABSTRACT FROM AUTHOR]

\n Research in psychology can have various foci, ranging from the psychological dynamics of single individuals to the generalization across individuals, often termed idiographics and nomothetics, respectively. However, terminological ambiguities have limited communication clarity about idiographics and nomothetics. Importantly, whether studies are suitable for idiographic and/or nomothetic inferences is not categorical but rather a matter of degree. Therefore, we propose a list of concrete, better-defined methodological aspects characterizing individual studies. Specifically, we highlight 16 different decisions researchers have to make pertaining to (1) research question, (2) research design, and (3) analyses and interpretation. These decisions are introduced with a focus on personality psychology but apply to psychological research broadly. We discuss the different decisions with an emphasis on their relation to idiographic and nomothetic inferential goals. Rather than providing specific recommendations, we emphasize the importance of aligning the methodology of a given study with the research question and theory. Overall, this overview seeks to help researchers make relevant decisions more intentionally to help them tailor their studies to their inferential goals.Psychological research can be focused on specific individuals (often termed idiographic) or on generalization across individuals (often termed nomothetic). However, various definitions of these terms exist in the literature. Moreover, multiple different aspects of a study affect whether it allows us to understand a specific person and/or whether it allows generalization across people. To characterize individual psychological studies in a more detailed way, we propose a list of 16 decisions researchers have to make. These decisions include aspects of (1) the research question, (2) the research design, and (3) the analyses and interpretation. We discuss how these decisions are related to idiographics and nomothetics. Moreover, we emphasize the importance of a close match between the questions a study seeks to answer and the methodology used in the study. The proposed list of decisions can be used by other researchers to characterize existing studies as well as to plan new studies. [ABSTRACT FROM AUTHOR]

Abstract Background Comorbidity between depression and cognitive impairment is common in older adults, increases the disease burden disproportionally, and leads to diagnostic uncertainty. Insight into individual daily associations between affect and cognitive performance may help in personalizing diagnosis and treatment decisions. Our objective was to get insight into the daily associations between affect and cognitive performance within individual older adults. Methods In this single-subject study seven older adults with both depression and cognitive impairment filled in electronic diaries daily for 62-93 consecutive days evaluating positive affect (PA), negative affect (NA), working memory (WM) and visual learning (VL). Time-series analyses using vector autoregressive modelling, Granger causality tests and cumulative orthogonalized impulse response function analyses were performed for each individual separately. Results In one patient higher NA was associated with better WM the next day. For another patient days with higher NA and lower PA were days with worse WM. For a third patient better VL was associated with lower NA and higher PA the next day. No associations were found for four patients. Conclusions These results highlight heterogeneity in the daily associations between affect and cognitive performance and stress the relevance of single-subject studies. These studies may be an important step towards personalized diagnosis and treatment in old age psychiatry.

Three overarching principles governing patterns of geographic phenomena have been proposed that have been referred to by some as ‘laws of geography’. The first and the second principles address the spatial proximity and spatial heterogeneity of geographic phenomena. These principles, while powerful, fail to resonate with much geographical inquiry. The more recently proposed third principle concerns geographic similarity. The differences of it from the first two can be perceived in three basic aspects: principle expressed, form of expression and role of geographic examples (samples). The third principle emphasizes the geographic context of geographic variables in the form of geographic configuration, compared to a single spatial dimension that are emphasized in the first two principles. The third principle focuses on the comparative nature in the geographic configuration in terms of similarity, that is, in the form of ‘similar to’, as opposed to the relationships ‘between’ that are key to the first and second principles. The third principle emphasizes the individual representation of geographic examples, as opposed to the global representation of geographic examples. These differences not only distinguish the third principle as an important addition to the other two, but also provide a potentially transformative way to address the rigid requirements on samples in geographic analysis, particularly during this age when the collection and provision of geographic data are crowd-sourced and VGI-based. These differences also point to the potential of the third principle opening up a space of inquiry that would resonate more successfully with place-based approaches in human geography.

In this study, we aimed to examine how moment-to-moment interpersonal behaviors of warmth and dominance in patients and therapists, as well as interpersonal complementarity, are related to withdrawal and confrontation ruptures as sessions unfold. Sixteen psychotherapy sessions from eight independent therapeutic dyads were sampled for the highest level of alliance ruptures from a naturalistic psychotherapy data set featuring evidence-based psychodynamic psychotherapy for patients with interpersonal problems and personality pathology. Interpersonal behaviors, complementarity, and alliance ruptures were generated every 30-s within each session. Subgrouping within group iterative multiple model estimation (S-GIMME) was used to identify an idiographic network structure for each session and examine generalizability at the nomothetic and subgroup levels. Nomothetically, patients' dominance negatively predicted therapists' dominance concurrently, but positively predicted therapists' dominance with a 30-s lag; additionally, therapists' dominance predicted their own concurrent warmth. At the subgroup level, therapists being less dominant than typical predicted more concurrent withdrawal ruptures. Idiographic modeling revealed a high degree of heterogeneity in how interpersonal behaviors are associated with ruptures. More confrontation ruptures concurrently predicted higher dominance complementarity in one subgroup. This study demonstrated the interconnection between patients' and therapists' in-session behaviors as well as the role of therapists' behaviors in momentary rupture development. This study highlights the importance of attuning and responding to individualized, momentary therapeutic contexts in navigating ruptures, and emphasizes the value of idiographic relational network approaches to aid in psychotherapy research and case conceptualization. [ABSTRACT FROM AUTHOR]

A longstanding goal of psychology is to predict the things that people do and feel, but tools to accurately predict future behaviors and experiences remain elusive. In the present study, we used intensive longitudinal data (N = 104 college-age adults at a midwestern university; total assessments = 5,971) and three machine-learning approaches to investigate the degree to which three future behaviors and experiences—loneliness, procrastination, and studying—could be predicted from past psychological (i.e., personality and affective states), situational (i.e., objective situations and psychological situation cues), and time (i.e., trends, diurnal cycles, time of day, and day of the week) phenomena from an idiographic, person-specific perspective. Rather than pitting persons against situations, such an approach allows psychological phenomena, situations, and time to jointly predict future behaviors and experiences. We found (a) a striking degree of prediction accuracy across participants, (b) that a majority of participants' future behaviors are predicted by both person and situation features, and (c) that the most important features vary greatly across people. [ABSTRACT FROM AUTHOR]

Background: Ecological momentary assessment (EMA) studies have provided conflicting evidence for the mood regulation tenet that people drink in response to positive and negative moods. The current study examined mood‐to‐alcohol relationships idiographically to quantify the prevalence and intensity of relationships between positive and negative moods and drinking across individuals. Method: We used two EMA samples: 96 heavy drinking college students (sample 1) and 19 young adults completing an ecological momentary intervention (EMI) for drinking to cope (sample 2). Mood and alcohol use were measured multiple times per day for 4–6 weeks. Mood–alcohol relationships were examined using three different analytic approaches: standard multilevel modeling, group causal modeling, and idiographic causal modeling. Results: Both multilevel modeling and group causal modeling showed that participants in both samples drank in response to positive moods only. However, idiographic causal analyses revealed that only 63% and 21% of subjects (in samples 1 and 2, respectively) drank following any positive mood. Many subjects (24% and 58%) did not drink in response to either positive or negative mood in their daily lives, and very few (5% and 16%) drank in response to negative moods throughout the EMA protocol, despite sample 2 being selected specifically because they endorse drinking to cope with negative mood. Conclusion: Traditional group‐level analyses and corresponding population‐wide theories assume relative homogeneity within populations in mood–alcohol relationships, but this nomothetic approach failed to characterize accurately the relationship between mood and alcohol use in approximately half of the subjects in two samples that were demographically and clinically homogeneous. Given inconsistent findings in the mood–alcohol relationships to date, we conclude that idiographic causal analyses can provide a foundation for more accurate theories of mood and alcohol use. In addition, idiographic causal models may also help improve psychosocial treatments through direct use in clinical settings. [ABSTRACT FROM AUTHOR]

Objective: Measurement-based care (MBC), which encompasses routine outcome monitoring (ROM) and measurement feedback systems (MFSs), is an evidence-based practice (EBP) supporting treatment personalization and clinical responsiveness. Despite MBC's effectiveness, clinicians report reservations regarding its utility, which may be a function of overreliance on nomothetic (i.e., standardized) measures. Although research suggests that individualized (i.e., idiographic) patient-reported outcome measures (I-PROMs) may have the potential to overcome these obstacles, little is known regarding clinicians' perceptions of different measurement approaches to MBC. Methods: This study examined clinicians' perceptions of the clinical utility, relevance to treatment planning, and practicality of nomothetic, individualized, and combined clinical feedback provided by a simulated MFS. Three hundred and twenty-nine clinicians were randomized to one of three conditions that presented a clinical vignette comprising: (a) nomothetic, (b) individualized, or (c) combined clinical feedback. Results: Participants' perceptions of the clinical feedback were not affected by the measurement approach. However, cognitive behavioral participants reported more positive perceptions of all aspects associated with the clinical feedback. Conclusion: These results were consistent with previous findings, suggesting that clinicians' theoretical orientation may have a significant impact on their perceptions of MBC, and should be considered when designing and implementing these systems. [ABSTRACT FROM AUTHOR]

• Psychotherapy is limited by the latent disease model. • Psychotherapy should be studied idiographically. • Psychotherapy can be viewed as process toward adaptation to context. • Psychotherapy is applied evolutionary science. • Process-based therapy combines evolutionary science and network approaches. Cognitive behavioral therapy (CBT) has been one of the most influential developments in psychiatry ever. Since it was developed and introduced, a vast number of treatment protocols focused on specific psychiatric syndromes have been developed. Although this has benefitted many patients and advanced the field, CBT as a treatment with its focus on alleviating psychiatric syndromes seemed to have reached a plateau and a process-focus approach is now emerging within the family of CBT models. This represents a new form of idiographic functional analysis guided by models that integrate a coherent set of change processes. Here, I describe the foundations of this new approach to mental health, called process-based therapy (PBT) and discuss its scientific and clinical implications. [ABSTRACT FROM AUTHOR]

• The ACBS Task Force recommends promising avenues for research. • Person-level, multivariate, and longitudinal analyses are needed. • Decades of methodological work can be leveraged to actualize recommendations. • Specific analytic methods and considerations for implementation are discussed. • Next steps for person-level and complex systems analysis are highlighted. [ABSTRACT FROM AUTHOR]

Syndromal classification has failed to produce a progressive science of case conceptualization for mental and behavioral health issues. An idiographic application of processes of change can provide a viable empirical functional analytic alternative if it could be linked to an idionomic approach , modeling idiographic effects first, and retaining nomothetic findings if they improve idiographic fit. Method: The present study examined this possibility by using the Process-Based Assessment Tool (PBAT), a new assessment tool linked to the Extended Evolutionary Meta-Model (EEMM) of Process-Based Therapy. The PBAT and items assessing common clinical outcomes were assessed repeatedly in 50 individuals in an experience sampling format over a 35 day period yielding at least 60 measurement occasions per person. These data were then analyzed in an idionomic fashion using Group Iterative Multiple Model Estimation (GIMME). Results: Analyses showed that the PBAT related to common clinical outcomes for virtually all participants in the individual complex networks identified by GIMME. Data showed that relationships had to be studied using an idionomic approach because participants' responses violated the ergodic assumptions underlying classical normative statistics. No overall group patterns were found. Subgroup relations did emerge for three common outcomes (sadness, anxiety, and life satisfaction) but most process to outcome relationships were idiographic. Idiographic networks were interpretable, however, using the broadened psychological flexibility approach of the EEMM. Conclusion: Idionomic network analysis of processes of change may provide a replicable form of empirical functional analysis and process-based case conceptualization. • Empirical forms of functional analysis could lead to effective case conceptualization. • Idionomic networks linked to processes of change represents possible approach. • Processes of change and common outcomes were assessed repeatedly over a month. • 45 individuals were analyzed using idionomic statistical procedures. • Processes of change related to outcomes in a coherent way for most participants. [ABSTRACT FROM AUTHOR]