"How Nuts Are The Dutch" is an online research platform that became established on 13 December 2013 in the Netherlands.[1] HowNutsAreTheDutch has been designed by researchers from the University of Groningen to support self-measurement of mental health for the entire population of The Netherlands. The project shows how crowdsourcing can be used for studying mental health in the general population. HowNutsAreTheDutch (HoeGekIsNL in Dutch) provides automatic personalized feedback on filled-out questionnaires to provide participants with more basic insight in their mental health, including a comparison with the scores of other participants. HowNutsAreTheDutch is meant to reduce mental health stigma and to promote a discrete categorization of mental health, by showing that all people have both personal strengths and weaknesses, and that most psychological characteristics are distributed continuously in the population.[2][3] A background goal is to develop and evaluate personalized interventions to improve mood-related problems and social-emotional functioning.[4] In the first year 13000 inhabitants of the Netherlands and Belgium participated.[3]

Available inDutch
OwnerUniversity of Groningen
Created byHowNutsAreTheDutch
LaunchedDecember 13, 2013
Current status14000 members


The HowNutsAreTheDutch name has been reported to be inspired by the Pandora foundation.[1] The Pandora foundation was a Dutch patient organization for people with mental health problems, which used posters with tongue-in-cheek sayings to inform the public and reduce mental health stigma.[5] The HowNutsAreTheDutch project was created by scientists from different fields, including computer sciences, psychiatric epidemiology, psychology, and mathematics.[6]

Diary StudyEdit

Since the summer of 2014 HowNutsAreTheDutch provides an automated electronic diary study. This is also known as the ecological momentary assessment methodology.[7] With this diary study participants can monitor their emotions, behaviour, somatic symptoms, and well-being over 30 days (3 times a day), which results in a personal network model.[8] There is no financial compensation for taking part in the research; instead, if participants fill in the diary often enough they get a personal, automatically generated report in return.[6] The web-platform uses automated vector autoregression models to determine cause-effect relationships between the measured features in the time series data.[9] Results evidence substantial between-person variability in within-person associations.[8] The diary study featured in the Dutch magazine "Psychologie" as a Quantified Self tool.[10] Some researchers coupled data from commercially available sensors (i.e., their Apple Watch, Google Fit, Jawbone, NikeFuel, or Misfit) to their HowNutsAreTheDutch diary data to study the interaction between their physical and psychological processes.[11]

One study showed that positive affect and prosocial actions reinforce each other; Thus when an individual was feeling good in one six-hour period, they were more likely to do something prosocial in the next six hours, and vice versa, in line with the mood maintenance theory.[12] Another study showed that negative affect predicted most differences in somatic symptoms between subjects, whereas positive affect predicted most variations in symptom levels within subjects.[13] An increase in positive affect was followed by a decrease in somatic symptoms in the following 24 hours.


Psychological problems like major depression can be seen as complex dynamic systems in which symptom activation patterns can change suddenly (phase transitions).[14] Researchers showed that people from the general Dutch population were not susceptible to these transitions whereas someone who had experienced a depression was, using mean field approximation.[15]


  1. ^ a b "HowNutsAreTheDutch". HoeGekIsNL. 13 December 2013. Retrieved 28 November 2014.
  2. ^ Pol, Margot (May 2014). "Allemaal gaga". Margot C Pol. De Volkskrant (a Dutch newspaper). Retrieved 21 December 2014.
  3. ^ a b Pepping, Anita (15 November 2014). "Iedereen is een beetje gek". Dagblad van het Noorden. Retrieved 21 December 2014.
  4. ^ "The Interdisciplinary Center Psychopathology and Emotion regulation (ICPE)". August 2013. Retrieved 28 November 2014.
  5. ^ Gemma Blok (2004). Baas in eigen brein, Antipsychiatrie in Nederland, 1965-1985. Nieuwezijds. ISBN 978-90-5712-173-9.
  6. ^ a b Sarampalis, Tassos (June 2016). "HoeGekIs.NL – How Nuts Are The Dutch?". Mindwise. University of Groningen. Retrieved 4 October 2016.
  7. ^ Csikszentmihalyi, M. (July 2014). Validity and Reliability of the Experience-Sampling Method. New York: Springer. p. 322. ISBN 978-94-017-9087-1.
  8. ^ a b van der Krieke, L; Blaauw, FJ; Emerencia, AC; Schenk, HM; Slaets, JP; Bos, EH; de Jonge, P; Jeronimus, BF (2016). "Temporal Dynamics of Health and Well-Being: A Crowdsourcing Approach to Momentary Assessments and Automated Generation of Personalized Feedback (2016)". Psychosomatic Medicine. 79 (2): 213–223. doi:10.1097/PSY.0000000000000378. PMID 27551988.
  9. ^ Emerencia, Ando Celino; Van Der Krieke, Lian; Bos, Elisabeth H.; De Jonge, Peter; Petkov, Nicolai; Aiello, Marco (2016). "Automating Vector Autoregression on Electronic Patient Diary Data (2016)". IEEE Journal of Biomedical and Health Informatics. 20 (2): 631–643. doi:10.1109/JBHI.2015.2402280. PMID 25680221.
  10. ^ van der Neut, Dagmar (1 June 2014). "Meten is Weten". Psychologie Magazine. Retrieved 28 November 2014.
  11. ^ Blaauw, FJ; Schenk, HM; Jeronimus, BF; van der Krieke, L; de Jonge, P; Aiello, M; Emerencia, AC (2016). "Let's get Physiqual - an intuitive and generic method to combine sensor technology with ecological momentary assessments". Journal of Biomedical Informatics. 63: 141–149. doi:10.1016/j.jbi.2016.08.001. PMID 27498066.
  12. ^ Baer, Drake (Jan 2017). "Neurotics Get an Extra Benefit From Being Extra Nice". Science of Us. New York Magazine. Retrieved 28 January 2017.
  13. ^ Schenk, H.M.; et al. (2017). "Differential association between affect and somatic symptoms at the between- and within-individual level". British Journal of Health Psychology. 22 (2): 270–280. doi:10.1111/bjhp.12229. PMID 28083924.
  14. ^ Wichers; et al. (2016). "Critical Slowing Down as a Personalized Early Warning Signal for Depression". Psychotherapy and Psychosomatics. 85 (2): 114–116. doi:10.1159/000441458. PMID 26821231.
  15. ^ Jolanda J Kossakowski; Marijke CM Gordijn; Riese, Harriette; Lourens J Waldorp (2016). "Mean Field Dynamics of Graphs II: Assessing the Risk for the Development of Phase Transitions in Empirical Data". arXiv:1610.05046 [stat.AP].

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