Eiko I Fried
Biographic Data
| ID | 148303 |
|---|---|
| NAME | Eiko I Fried |
| GIVEN NAMES | Eiko I |
| FAMILY NAME | Fried |
| SIGNATURE | FRIED E I |
| AFFILIATIONS | Leiden University |
| ORCID | 0000-0001-7469-594X |
| VERIFIED | Yes |
| TOTAL WORKS | 26 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 26 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Causal beliefs about social determinants of depression, poverty, and mortality
Social determinants influence multiple life outcomes including depression, poverty, and mortality. While causal beliefs shape public views on these issues, studies have remained siloed across disciplines. We surveyed 1000 UK adults on 43 social and non‐social risk factors for these outcomes, using a broader set of social factors than previous work. We ask which social determinants are perceived to be causally important, how these are weighted rel…
Anxiety, Worry, and Difficulty Concentrating: A Longitudinal Examination of Concurrent and Prospective Symptom Relationships
Worry was associated with difficulty concentrating across three pandemic timepoints. • Anxiety predicted worry three months later, controlling for concurrent worry. • Worry partially mediated the path from T1 anxiety to T3 difficulty concentrating. • Mediation was not robust to controlling for outcomes at previous timepoints. Difficulty concentrating is an understudied cognitive phenomenon, despite its status as a diagnostic criterion for general…
A Network Study of Family Affect Systems in Daily Life
Adolescence is a time period characterized by extremes in affect and increasing prevalence of mental health problems. Prior studies have illustrated how affect states of adolescents are related to interactions with parents. However, it remains unclear how affect states among family triads, that is adolescents and their parents, are related in daily life. This study investigated affect state dynamics (happy, sad, relaxed, and irritated) of 60 fami…
Reporting standards for psychological network analyses in cross-sectional data.
in a scientific report. A lack of such reporting standards may foster researcher degrees of freedom and could provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific…
Investigating the DSM–5 and the ICD-11 PTSD symptoms using network analysis across two distinct samples
The results underline that a combination of five symptoms representing both diagnostic systems may hold central positions and potentially be important for treatment. However, the implications depend on if the different diagnostic descriptions can be reconciled in an indexical rather than constitutive perspective. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
Network analysis of multivariate data in psychological science
In recent years, network analysis has been applied to identify and analyse patterns of statistical association in multivariate psychological data. In these approaches, network nodes represent variables in a data set, and edges represent pairwise conditional associations between variables in the data, while conditioning on the remaining variables. This Primer provides an anatomy of these techniques, describes the current state of the art and discu…
Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction
In recent years, a growing chorus of researchers has argued that psychological theory is in a state of crisis: Theories are rarely developed in a way that indicates an accumulation of knowledge. Paul Meehl raised this very concern more than 40 years ago. Yet in the ensuing decades, little has improved. We aim to chart a better path forward for psychological theory by revisiting Meehl’s criticisms, his proposed solution, and the reasons his soluti…
Investigating the Utility of Fixed-margin Sampling in Network Psychometrics
Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. W…
On the Importance of Estimating Parameter Uncertainty in Network Psychometrics: A Response to Forbes et al. (2019)
In their recent paper, Forbes et al. (2019; FWMK) evaluate the replicability of network models in two studies. They identify considerable replicability issues, concluding that "current 'state-of-the-art' methods in the psychopathology network literature [...] are not well-suited to analyzing the structure of the relationships between individual symptoms". Such strong claims require strong evidence, which the authors do not provide. FWMK identify …
Lack of Theory Building and Testing Impedes Progress in The Factor and Network Literature
The applied social science literature using factor and network models continues to grow rapidly. Most work reads like an exercise in model fitting, and falls short of theory building and testing in three ways. First, statistical and theoretical models are conflated, leading to invalid inferences such as the existence of psychological constructs based on factor models, or recommendations for clinical interventions based on network models. I demons…
Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them
In this article, we define questionable measurement practices (QMPs) as decisions researchers make that raise doubts about the validity of the measures, and ultimately the validity of study conclusions. Doubts arise for a host of reasons, including a lack of transparency, ignorance, negligence, or misrepresentation of the evidence. We describe the scope of the problem and focus on how transparency is a part of the solution. A lack of measurement …
Social media and depression symptoms: A network perspective.
Passive social media use (PSMU)-for example, scrolling through social media news feeds-has been associated with depression symptoms. It is unclear, however, if PSMU causes depression symptoms or vice versa. In this study, 125 students reported PSMU, depression symptoms, and stress 7 times daily for 14 days. We used multilevel vector autoregressive time-series models to estimate (a) contemporaneous, (b) temporal, and (c) between-subjects associati…
Reconceptualizing adult attachment relationships: A network perspective
This article explores attachment relationships from a network theory perspective: Correlations among behaviors, beliefs, and feelings related to attachment are hypothesized to stem from causal relations. The authors used two data sets that assessed relationships with four attachment figures (mother, father, romantic partner, and best friend) using the Relationship Structures Questionnaire. Separate networks (Gaussian Graphical Models) were estima…
Replicability and Generalizability of Posttraumatic Stress Disorder (PTSD) Networks: A Cross-Cultural Multisite Study of PTSD Symptoms in Four Trauma Patient Samples
The growing literature conceptualizing mental disorders like posttraumatic stress disorder (PTSD) as networks of interacting symptoms faces three key challenges. Prior studies predominantly used (a) small samples with low power for precise estimation, (b) nonclinical samples, and (c) single samples. This renders network structures in clinical data, and the extent to which networks replicate across data sets, unknown. To overcome these limitations…
Estimating psychological networks and their accuracy: A tutorial paper
The usage of psychological networks that conceptualize behavior as a complex interplay of psychological and other components has gained increasing popularity in various research fields. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar wit…
A tutorial on regularized partial correlation networks.
Recent years have seen an emergence of network modeling applied to moods, attitudes, and problems in the realm of psychology. In this framework, psychological variables are understood to directly affect each other rather than being caused by an unobserved latent entity. In this tutorial, we introduce the reader to estimating the most popular network model for psychological data: the partial correlation network. We describe how regularization tech…
The 52 symptoms of major depression: Lack of content overlap among seven common depression scales
Mental disorders as networks of problems: A review of recent insights
PURPOSE: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years. METHODS: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three m…
Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology
Since the introduction of mental disorders as networks of causally interacting symptoms, this novel framework has received considerable attention. The past years have resulted in over 40 scientific publications and numerous conference symposia and workshops. Now is an excellent moment to take stock of the network approach: What are its most fundamental challenges, and what are potential ways forward in addressing them? After a brief conceptual in…
How predictable are symptoms in psychopathological networks? A reanalysis of 18 published datasets
Background Network analyses on psychopathological data focus on the network structure and its derivatives such as node centrality. One conclusion one can draw from centrality measures is that the node with the highest centrality is likely to be the node that is determined most by its neighboring nodes. However, centrality is a relative measure: knowing that a node is highly central gives no information about the extent to which it is determined b…
What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis
Network analysis of depression and anxiety symptom relationships in a psychiatric sample
Background Researchers have studied psychological disorders extensively from a common cause perspective, in which symptoms are treated as independent indicators of an underlying disease. In contrast, the causal systems perspective seeks to understand the importance of individual symptoms and symptom-to-symptom relationships. In the current study, we used network analysis to examine the relationships between and among depression and anxiety sympto…
From loss to loneliness: The relationship between bereavement and depressive symptoms.
Spousal bereavement can cause a rise in depressive symptoms. This study empirically evaluates 2 competing explanations concerning how this causal effect is brought about: (a) a traditional latent variable explanation, in which loss triggers depression which then leads to symptoms; and (b) a novel network explanation, in which bereavement directly affects particular depression symptoms which then activate other symptoms. We used data from the Chan…
Depression is not a consistent syndrome: An investigation of unique symptom patterns in the STAR*D study
Depression sum-scores don’t add up: Why analyzing specific depression symptoms is essential
Most measures of depression severity are based on the number of reported symptoms, and threshold scores are often used to classify individuals as healthy or depressed. This method--and research results based on it--are valid if depression is a single condition, and all symptoms are equally good severity indicators. Here, we review a host of studies documenting that specific depressive symptoms like sad mood, insomnia, concentration problems, and …
Anxiety, Worry, and Difficulty Concentrating: A Longitudinal Examination of Concurrent and Prospective Symptom Relationships
Worry was associated with difficulty concentrating across three pandemic timepoints. • Anxiety predicted worry three months later, controlling for concurrent worry. • Worry partially mediated the path from T1 anxiety to T3 difficulty concentrating. • Mediation was not robust to controlling for outcomes at previous timepoints. Difficulty concentrating is an understudied cognitive phenomenon, despite its status as a diagnostic criterion for general…
From loss to loneliness: The relationship between bereavement and depressive symptoms.
Spousal bereavement can cause a rise in depressive symptoms. This study empirically evaluates 2 competing explanations concerning how this causal effect is brought about: (a) a traditional latent variable explanation, in which loss triggers depression which then leads to symptoms; and (b) a novel network explanation, in which bereavement directly affects particular depression symptoms which then activate other symptoms. We used data from the Chan…
Depression is not a consistent syndrome: An investigation of unique symptom patterns in the STAR*D study
Depression sum-scores don’t add up: Why analyzing specific depression symptoms is essential
Most measures of depression severity are based on the number of reported symptoms, and threshold scores are often used to classify individuals as healthy or depressed. This method--and research results based on it--are valid if depression is a single condition, and all symptoms are equally good severity indicators. Here, we review a host of studies documenting that specific depressive symptoms like sad mood, insomnia, concentration problems, and …
Commentary: “Consistent Superiority of Selective Serotonin Reuptake Inhibitors Over Placebo in Reducing Depressed Mood in Patients with Major Depression”
In the past decades, almost all research in psychiatry and clinical psychology has been directed at the level of disorders, such as major depressive disorder (MDD) or schizophrenia. As has been argued by many scholars in recent work, this organization of the psychiatric research program has yielded limited insights, which justifies the investigation of psychopathology at a more fine-grained level: the level of symptoms (1, 2). In the present lett…
What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis
Network analysis of depression and anxiety symptom relationships in a psychiatric sample
Background Researchers have studied psychological disorders extensively from a common cause perspective, in which symptoms are treated as independent indicators of an underlying disease. In contrast, the causal systems perspective seeks to understand the importance of individual symptoms and symptom-to-symptom relationships. In the current study, we used network analysis to examine the relationships between and among depression and anxiety sympto…
The 52 symptoms of major depression: Lack of content overlap among seven common depression scales
Mental disorders as networks of problems: A review of recent insights
PURPOSE: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years. METHODS: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three m…
Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology
Since the introduction of mental disorders as networks of causally interacting symptoms, this novel framework has received considerable attention. The past years have resulted in over 40 scientific publications and numerous conference symposia and workshops. Now is an excellent moment to take stock of the network approach: What are its most fundamental challenges, and what are potential ways forward in addressing them? After a brief conceptual in…
How predictable are symptoms in psychopathological networks? A reanalysis of 18 published datasets
Background Network analyses on psychopathological data focus on the network structure and its derivatives such as node centrality. One conclusion one can draw from centrality measures is that the node with the highest centrality is likely to be the node that is determined most by its neighboring nodes. However, centrality is a relative measure: knowing that a node is highly central gives no information about the extent to which it is determined b…
Replicability and Generalizability of Posttraumatic Stress Disorder (PTSD) Networks: A Cross-Cultural Multisite Study of PTSD Symptoms in Four Trauma Patient Samples
The growing literature conceptualizing mental disorders like posttraumatic stress disorder (PTSD) as networks of interacting symptoms faces three key challenges. Prior studies predominantly used (a) small samples with low power for precise estimation, (b) nonclinical samples, and (c) single samples. This renders network structures in clinical data, and the extent to which networks replicate across data sets, unknown. To overcome these limitations…
Estimating psychological networks and their accuracy: A tutorial paper
The usage of psychological networks that conceptualize behavior as a complex interplay of psychological and other components has gained increasing popularity in various research fields. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar wit…
A tutorial on regularized partial correlation networks.
Recent years have seen an emergence of network modeling applied to moods, attitudes, and problems in the realm of psychology. In this framework, psychological variables are understood to directly affect each other rather than being caused by an unobserved latent entity. In this tutorial, we introduce the reader to estimating the most popular network model for psychological data: the partial correlation network. We describe how regularization tech…
Social media and depression symptoms: A network perspective.
Passive social media use (PSMU)-for example, scrolling through social media news feeds-has been associated with depression symptoms. It is unclear, however, if PSMU causes depression symptoms or vice versa. In this study, 125 students reported PSMU, depression symptoms, and stress 7 times daily for 14 days. We used multilevel vector autoregressive time-series models to estimate (a) contemporaneous, (b) temporal, and (c) between-subjects associati…
Reconceptualizing adult attachment relationships: A network perspective
This article explores attachment relationships from a network theory perspective: Correlations among behaviors, beliefs, and feelings related to attachment are hypothesized to stem from causal relations. The authors used two data sets that assessed relationships with four attachment figures (mother, father, romantic partner, and best friend) using the Relationship Structures Questionnaire. Separate networks (Gaussian Graphical Models) were estima…
Lack of Theory Building and Testing Impedes Progress in The Factor and Network Literature
The applied social science literature using factor and network models continues to grow rapidly. Most work reads like an exercise in model fitting, and falls short of theory building and testing in three ways. First, statistical and theoretical models are conflated, leading to invalid inferences such as the existence of psychological constructs based on factor models, or recommendations for clinical interventions based on network models. I demons…
Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them
In this article, we define questionable measurement practices (QMPs) as decisions researchers make that raise doubts about the validity of the measures, and ultimately the validity of study conclusions. Doubts arise for a host of reasons, including a lack of transparency, ignorance, negligence, or misrepresentation of the evidence. We describe the scope of the problem and focus on how transparency is a part of the solution. A lack of measurement …
Network analysis of multivariate data in psychological science
In recent years, network analysis has been applied to identify and analyse patterns of statistical association in multivariate psychological data. In these approaches, network nodes represent variables in a data set, and edges represent pairwise conditional associations between variables in the data, while conditioning on the remaining variables. This Primer provides an anatomy of these techniques, describes the current state of the art and discu…
Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction
In recent years, a growing chorus of researchers has argued that psychological theory is in a state of crisis: Theories are rarely developed in a way that indicates an accumulation of knowledge. Paul Meehl raised this very concern more than 40 years ago. Yet in the ensuing decades, little has improved. We aim to chart a better path forward for psychological theory by revisiting Meehl’s criticisms, his proposed solution, and the reasons his soluti…
Investigating the Utility of Fixed-margin Sampling in Network Psychometrics
Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. W…
On the Importance of Estimating Parameter Uncertainty in Network Psychometrics: A Response to Forbes et al. (2019)
In their recent paper, Forbes et al. (2019; FWMK) evaluate the replicability of network models in two studies. They identify considerable replicability issues, concluding that "current 'state-of-the-art' methods in the psychopathology network literature [...] are not well-suited to analyzing the structure of the relationships between individual symptoms". Such strong claims require strong evidence, which the authors do not provide. FWMK identify …
Investigating the DSM–5 and the ICD-11 PTSD symptoms using network analysis across two distinct samples
The results underline that a combination of five symptoms representing both diagnostic systems may hold central positions and potentially be important for treatment. However, the implications depend on if the different diagnostic descriptions can be reconciled in an indexical rather than constitutive perspective. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
Reporting standards for psychological network analyses in cross-sectional data.
in a scientific report. A lack of such reporting standards may foster researcher degrees of freedom and could provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific…
A Network Study of Family Affect Systems in Daily Life
Adolescence is a time period characterized by extremes in affect and increasing prevalence of mental health problems. Prior studies have illustrated how affect states of adolescents are related to interactions with parents. However, it remains unclear how affect states among family triads, that is adolescents and their parents, are related in daily life. This study investigated affect state dynamics (happy, sad, relaxed, and irritated) of 60 fami…
Causal beliefs about social determinants of depression, poverty, and mortality
Social determinants influence multiple life outcomes including depression, poverty, and mortality. While causal beliefs shape public views on these issues, studies have remained siloed across disciplines. We surveyed 1000 UK adults on 43 social and non‐social risk factors for these outcomes, using a broader set of social factors than previous work. We ask which social determinants are perceived to be causally important, how these are weighted rel…
Mental Health Research Topics (24 works) · Psychology (23 works) · Functional Brain Connectivity Studies (15 works) · Clinical Psychology (14 works) · Psychiatry (13 works) · Computer Science (10 works) · Social Psychology (9 works) · Depression (economics) (7 works) · Mathematics (7 works) · Artificial Intelligence (6 works)