Publications

You can find other overviews of my work in my CV or on Google Scholar.

SM = Supplementary Materials; * = shared first authorship.

Several articles contain open data, which you can find here.


Selected preprints

  • Teague, Robinaugh & Fried (2020). On the control of psychological networks. Under revision at Psychometrika. PDF.
  • Robinaugh et al. (2019). Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder. Submitted to Psychological Review. PDF.

Peer-reviewed publications

First author

  • Fried, Papanikolaou & Epskamp (2020). Mental Health and Social Contact During the COVID-19 Pandemic: An Ecological Momentary Assessment Study. Submitted to Clinical Psychological Science. PDF, SM.
  • Fried (2021). Lack of theory building and testing impedes progress in the factor and network literature. Psychological Inquiry. PDF.
  • Fried (2021). Theories and Models: What They Are, What They Are for, and What They Are About. Psychological Inquiry. PDF.
  • Fried*, Greene* & Eaton (2021). The p factor is the sum of its parts, for now. World Psychiatry. PDF.
  • Flake & Fried* (2020). Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them. Advances in Methods and Practices in Psychological Science. PDF.
  • Fried & Robinaugh (2020). Systems all the way down: embracing complexity in mental health research. BMC Medicine. PDF.
  • Patalay & Fried* (2020). Prescribing measures: Unintended negative consequences of mandating standardized mental health measurement. Submitted to Journal of Child Psychology and Psychiatry. PDF.
  • Fried, Coomans & Lorenzo-Luaces (2020). The 341737 ways of qualifying for the melancholic specifier. Lancet Psychiatry. PDF, SM. [Feyaerts & Thornton wrote a commentary on our piece; here is our rejoinder]
  • Fried, van Borkulo & Epskamp (2020). On the Importance of Estimating Parameter Uncertainty in Network Psychometrics: A Response to Forbes et al. (2019). Multivariate Behavioral Research. PDF.
  • Fried et al. (2019). Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates. Psychological Medicine. PDF, SM.
  • Fried et al. (2018). Replicability and generalizability of PTSD networks: A cross-cultural multisite study of PTSD symptoms in four trauma patient samples. Clinical Psychological Science. PDF, SM.
  • Fried & Cramer (2017). Moving forward: challenges and directions for psychopathological network theory and methodology. Perspectives on Psychological Science. PDF, SM.
  • Fried (2017). The 52 symptoms of major depression: lack of content overlap among seven common depression scales. Journal of Affective Disorders. PDF, SM, Correction.
  • Fried (2017). What are psychological constructs? On the nature and statistical modelling of emotions, intelligence, personality traits and mental disorders. Health Psychology Review. PDF, SM.
  • Fried (2017). Moving forward: how depression heterogeneity hinders progress in treatment and research. Expert Review of Neurotherapeutics. PDF.
  • Fried, van Borkulo*, et al. (2017). Mental disorders as networks of problems: a review of recent insights. Social Psychiatry and Psychiatric Epidemiology. PDF, SM.
  • Armour, Fried* et al. (2017). A Network Analysis of DSM-5 posttraumatic stress disorder symptoms and correlates in U.S. military veterans. Journal of Anxiety Disorders. PDF, SM.
  • Armour, Fried*, & Olff (2017). PTSD symptomics: network analyses in the field of psychotraumatology. European Journal of Psychotraumatology, PDF.
  • Fried (2016). Are more responsive depression scales really superior depression scales? Journal of Clinical Epidemiology. PDF.
  • Fried et al. (2016). Measuring Depression over Time … or not? Lack of Unidimensionality and Longitudinal Measurement Invariance in Four Common Rating Scales of Depression. Psychological Assessment. PDF, SM.
  • Fried et al. (2016). What are ‘good’ depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. Journal of Affective Disorders. PDF, SM, Syntax.
  • Fried & Kievit (2016). The volumes of subcortical regions in depressed and healthy individuals are strikingly similar: A reinterpretation of the results by Schmaal et al. Molecular Psychiatry. PDF, SM.
  • Rhemtulla, Fried* et al. (2016). Network analysis of substance abuse and dependence symptoms. Drug and Alcohol Dependence. PDF, SM1, SM2.
  • Fried (2015). Problematic assumptions have slowed down depression research: why symptoms, not syndromes are the way forward. Frontiers in Psychology. PDF.
  • Fried & Nesse (2015). Depression sum-scores don’t add up: Why analyzing specific depression symptoms is essential. BMC Medicine. PDF.
  • Fried & Nesse (2015). Depression is not a consistent syndrome: an investigation of unique symptom patterns in the STAR*D study. Journal of Affective Disorders. PDF.
  • Fried et al. (2015). The differential influence of life stress on individual symptoms of depression. Acta Psychiatrica Scandinavica. PDF.
  • Fried et al. (2015). From Loss to Loneliness: The Relationship Between Bereavement and Depressive Symptoms. Journal of Abnormal Psychology. PDF, SM.
  • Fried et al. (2015). Symptomics as a new research paradigm in psychiatry. Frontiers in Psychiatry. PDF, SM.
  • Fried, Tuerlinckx & Borsboom, D. (2014). Mental health: more than neurobiology. Nature. PDF.
  • Fried & Nesse (2014). The Impact of Individual Depressive Symptoms on Impairment of Psychosocial Functioning. PLoS ONE. PDF.
  • Fried et al. (2014). Depression is more than the sum score of its parts: individual DSM symptoms have different risk factors. Psychological Medicine. PDF.

Last author

  • Kendler, Aggen, Werner & Fried (2020). A topography of 21 phobic fears: network analysis in an epidemiological sample of adult twins. Psychological Medicine. PDF, SM.
  • Cai, Choi & Fried (2020). Reviewing the genetics of heterogeneity in depression: Operationalizations, manifestations, and etiologies. Human molecular genetics. PDF.
  • Burger et al. (2020). Bereavement or Breakup: Differences in Networks of Depression. Journal of Affective Disorders. URL.
  • Aristodemou & Fried (2020). Common Factors and Interpretation of the p Factor of Psychopathology. Journal of the American Academy of Child & Adolescent Psychiatry. PDF.
  • McWilliams & Fried (2019). Reconceptualizing adult attachment relationships: A network perspective. Personal Relationships. PDF, SM.
  • Adolf & Fried (2019). Ergodicity is sufficient but not necessary for group-to-individual generalizability. PNAS. PDF.
  • Epskamp & Fried (2018). A Tutorial on Regularized Partial Correlation Networks. Psychological Methods. PDF.
  • Mottus & Fried (2018). Same Processes, Different Outcomes. European Journal of Personality. PDF.
  • Aalbers et al. (2018). Social Media and Depression Symptoms: A Network Perspective. Journal of Experimental Psychology: General. PDF.
  • Santos et al. (2018). Network Structure of Perinatal Depressive Symptoms in Latinas: Relationship to Stress-Related and Reproductive Biomarkers. Research in Nursing & Health. PDF.
  • Greene et al. (2018). Dynamic networks of PTSD symptoms during conflict. Psychological Medicine. PDF.
  • Fonseca-Pedrero et al. (2018). The network structure of schizotypal personality traits. Schizophrenia Bulletin. PDF, SM.
  • Kendler et al. (2018). The Centrality of DSM and non-DSM Depressive Symptoms in Han Chinese Women with Major Depression. Journal of Affective Disorders. PDF.
  • Epskamp, Borsboom & Fried (2018). Estimating psychological networks and their accuracy: a tutorial paper. Behavioral Research Methods. PDF, SM.
  • Santos et al. (2018). Longitudinal network structure of depression symptoms and self-efficacy in low- income mothers. PLoS ONE. PDF.
  • Mottus & Fried (2018). Same Processes, Different Outcomes. European Journal of Personality. PDF.
  • Miloyan & Fried (2017). A reassessment of the relationship between depression and all-cause mortality in 3,604,005 participants from 293 studies. World Psychiatry. PDF, SM.
  • Haslbeck & Fried (2017). How Predictable are Symptoms in Psychopathological Networks? A Reanalysis of 18 Published Datasets. Psychological Medicine. PDF, SM.
  • van Loo et al. (2016). Problems with latent class analysis to detect data-driven subtypes of depression. Molecular Psychiatry. PDF.

Collaborations

  • Buckman et al. (2021). Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches. Psychological Medicine. PDF.
  • O’Driscoll et al. (2021). The importance of transdiagnostic symptom level assessment to understanding prognosis for depressed adults: analysis of data from six randomized control trials. BMC Medicine. PDF.
  • Specker, Fried, Rosenberg, & Leder (2021). Associating With Art: A Network Model of Aesthetic Effects. Collabra: Psychology. PDF, SM.
  • Robinaugh et al. (2021). Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction. Perspectives on Psychological Science. PDF.
  • Hebbrecht et al. (2020). Understanding personalized dynamics to inform precision medicine : a dynamic time warp analysis of 255 depressed inpatients. BMC Medicine. PDF.
  • Chevance et al. (2020). Identifying outcomes for depression that matter to patients, informal caregivers and healthcare professionals: qualitative content analysis of a large international online survey. Lancet Psychiatry1. PDF.
  • Stochl et al. (2020). On Dimensionality, Measurement Invariance, and Suitability of Sum Scores for the PHQ-9 and the GAD-7. Assessment. PDF.
  • Duek et al. (2020). Network analysis of PTSD and depressive symptoms in 158,139 treatment‐seeking veterans with PTSD. Depression & Anxiety. PDF.
  • Abend et al. (2020). A computational network perspective on pediatric anxiety symptoms. Psychological Medicine. URL.
  • Taquet et al. (2020). Mood Homeostasis Before and During the Coronavirus Disease 2019 (COVID-19) Lockdown Among Students in the Netherlands. JAMA Psychiatry. PDF.
  • Hilland et al. (2020). Exploring the links between specific depression symptoms and brain structure: A network study. Psychiatry and Clinical Neurosciences. PDF.
  • Van Eeden et al. (2020). Basal and LPS-stimulated inflammatory markers and the course of individual symptoms of depression. Translational Psychiatry. PDF.
  • Hakulinen et al. (2020). Network structure of depression symptomology in participants with and without depressive disorder: the population‑based Health 2000–2011 study. Social Psychiatry and Psychiatric Epidemiology. PDF.
  • Vervaet et al. (2020). Transdiagnostic vulnerability factors in eating disorders: A network analysis. European Eating Disorder Review. PDF.
  • Morvan, Fried, & Chevance (2020). Network modeling in psychopathology: hopes and challenges. Encéphale. PDF.
  • De Ron, Fried, & Epskamp (2019). Psychological networks in clinical populations: investigating the consequences of Berkson’s bias. Psychological Medicine. PDF.
  • Jongeneel et al. (2019). A time-series network approach to auditory verbal hallucinations: Examining dynamic interactions using experience sampling methodology. Schizophrenia Research. PDF.
  • Waszczuk et al. (2019). Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology. Journal of Abnormal Psychology. PDF.
  • Lin, Fried, & Eaton (2019). The association of life stress with substance use symptoms: A network analysis and replication. Journal of Abnormal Psychology. PDF.
  • Conway et al. (2019). A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research. Perspectives on Psychological Science. PDF.
  • Greene et al. (2019). Are Fit Indices Used to Test Psychopathology Structure Biased? A Simulation Study. Journal of Abnormal Psychology. PDF.
  • Fritz et al. (2019). Unravelling the Complex Nature of Resilience Factors and their Changes between Early and Later Adolescence. BMC Medicine. PDF.
  • Greene et al. (2019). Dynamic Network Analysis of Negative Emotions and DSM‐5 Posttraumatic Stress Disorder Symptom Clusters During Conflict. Journal of Traumatic Stress. PDF.
  • De Beurs et al. (2019). Exploring the psychology of suicidal ideation: A theory driven network analysis. Behaviour Research and Therapy. PDF.
  • Heino et al. (2019). Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the let’s move it trial. Health Psychology and Behavioral Medicine . PDF.
  • Hartung et al. (2019). Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population. Journal of Affective Disorders. PDF.
  • De Haan et al. (2019). Dysfunctional posttraumatic cognitions, posttraumatic stress, and depression in children and adolescents exposed to trauma: A network analysis. Journal of Child Psychology and Psychiatry. PDF.
  • Faelens et al. (2019). Negative influences of Facebook use through the lens of network analysis. Computers in Human Behavior. PDF.
  • Molendijk, Fried & van der Does (2018). The SMILES trial: do undisclosed recruitment practices explain the remarkably large effect? BMC Medicine. PDF.
  • Briganti, Fried & Linkowski (2018). Network analysis of Contingencies of Self-Worth Scale in 680 university students. Psychiatry Research. PDF.
  • Epskamp et al. (2018). Investigating the Utility of Fixed-Margin Sampling in Network Psychometrics. Multivariate Behavioral Research. PDF.
  • Fritz et al. (2018). A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity. Scientific Reports. PDF.
  • Rodebaugh et al. (2018). Does centrality in a cross-sectional network suggest intervention targets for social anxiety disorder? Journal of Consulting and Clinical Psychology. PDF.
  • Rouquette et al. (2018). Emotional and Behavioral Symptom Network Structure in Elementary School Girls and Association With Anxiety Disorders and Depression in Adolescence and Early Adulthood — A Network Analysis. JAMA Psychiatry. PDF.
  • Borsboom et al. (2018). Robustness and replicability of psychopathology networks. World Psychiatry. PDF.
  • Briganti et al. (2018). Network analysis of empathy items from the Interpersonal Reactivity Index in 1973 young adults. Psychiatry Research. PDF.
  • Bos et al. (2018). Cross-sectional networks of depressive symptoms before and after antidepressant medication treatment. Social Psychiatry and Psychiatric Epidemiology. PDF.
  • von Stockert et al. (2018). Evaluating the stability of DSM-5 PTSD symptom network structure in a national sample of U.S. military veterans. Journal of Affective Disorders. PDF, SM.
  • van Loo et al. (2018). Robust symptom networks in recurrent major depression across different levels of genetic and environmental risk. Journal of Affective Disorders. PDF.
  • Borsboom et al. (2017). False alarm? A comprehensive reanalysis of “Evidence that psychopathology symptom networks have limited replicability” by Forbes, Wright, Markon, and Krueger (2017). Journal of Abnormal Psychology. URL.
  • Schweren et al. (2017). Assessment of Symptom Network Density as a Prognostic Marker of Treatment Response in Adolescent Depression. JAMA Psychiatry. PDF.
  • Murphy et al. (2017). Distress, impairment and the extended psychosis phenotype: A network analysis of psychotic experiences in a US general population sample. Schizophrenia Bulletin. PDF.
  • Dejonckheere et al. (2017). Perceiving social pressure not to feel negative predicts depressive symptoms in daily life. Depression and Anxiety. PDF.
  • Heino, Fried & LeBel, E. P. (2017). Commentary: Reproducibility in Psychological Science:When Do Psychological Phenomena Exist? Frontiers in Psychology, 8(1004). PDF.
  • Beard et al. (2016). Network Analysis of Depression and Anxiety Symptom Relations in a Psychiatric Sample. Psychological Medicine. PDF.
  • Heylen et al. (2016). Two-mode K-Spectral Centroid analysis for studying multivariate time profiles. Chemometrics and Intelligent Laboratory Systems. PDF.
  • Costantini et al. (2015). Development of Indirect Measures of Conscientiousness: Combining a Facets Approach and Network Analysis. European Journal of Personality. PDF.

Book chapters & dissertation

  • Fried (2017). Psychopathological Networks. In A. E. Wenzel (Ed.), The SAGE Encyclopedia of Abnormal and Clinical Psychology. New York, NY: SAGE Publications. PDF.
  • Fried (2017). Zung Depression Scale. In A. E. Wenzel (Ed.), The SAGE Encyclopedia of Abnormal and Clinical Psychology. New York, NY: SAGE Publications.
  • Dejonckheere & Fried (2017). Bereavement. In V. Zeigler-Hill & T. Shackelford (Eds.), Encyclopedia of Personality and Individual Differences. Preprint.
  • Fried (2014). Covert Heterogeneity of Major Depressive Disorder: Depression Is More Than the Sum-Score of its Symptoms. Dissertation. PDF.

R-packages

  • Epskamp & Fried (2016). bootnet: Bootstrap Methods for Various Network Estimation Routines. Package for the free statistical environment R (CRAN).

Magazine articles

  • Harris et al. (2019). Hacking APS. The Observer, published by the Association for Psychological Science.
  • Fried & Flake (2018). Measurement Matters. The Observer, published by the Association for Psychological Science.
  • Fried (2016). Depressionsforschung im Stimmungstief – Gründe einer wissenschaftlichen Krise und mögliche Auswege. In-Mind.
  • Fried, Dejonckheere & Tuerlinckx (2016). Welke symptomen zijn het meest belangrijk bij depressie? Een netwerkanalyse van depressie. Neuron, Vol. 21 Nr. 6. (Dutch PDF) (French PDF)
  • Fried (2015). Depression — more than the sum of its symptoms. The Psychologist (British Psychological Society).

Other blog posts


Silly publications

  • Fried (2016). True facts about the giant sequoia, or: what kind of name is sequoiadendron giganteum. Science Creative Quarterly.

Disclaimer: Please note that as a researcher at a Dutch University, I am protected under the Taverne Amendment. This allows me to make my published works available, “regardless of any restrictive publishers’ guidelines, provided that clear reference is made to the source of the first publication of the work”.

  1. Astrid won the European Psychiatric Association 2021 research prize with this paper; congratulations, Astrid!