Friedrich, M. J. Depression is the leading cause of disability around the world. JAMA 317, 1517 (2017).
Veal, C. et al. Heterogeneity of outcome measures in depression trials and the relevance of the content of outcome measures to patients: a systematic review. Lancet Psychiatry 11, 285–294 (2024).
Stein, D. J. et al. Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration. World Psychiatry 21, 393–414 (2022).
Winter, N. R. et al. A systematic evaluation of machine learning-based biomarkers for major depressive disorder. JAMA Psychiatry 81, 386–395 (2024).
Moriarty, A. S. et al. Predicting relapse or recurrence of depression: systematic review of prognostic models. Br J Psychiatry 221, 448–458 (2022).
Kennis, M. et al. Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis. Mol. Psychiatry 25, 321–338 (2020).
Leichsenring, F., Steinert, C., Rabung, S. & Ioannidis, J. P. A. The efficacy of psychotherapies and pharmacotherapies for mental disorders in adults: an umbrella review and meta-analytic evaluation of recent meta-analyses. World Psychiatry 21, 133–145 (2022).
Paul, S. M. & Potter, W. Z. Finding new and better treatments for psychiatric disorders. Neuropsychopharmacology 49, 3–9 (2024).
Maj, M. et al. The clinical characterization of the adult patient with depression aimed at personalization of management. World Psychiatry 19, 269–293 (2020).
Marx, W. et al. Major depressive disorder. Nat. Rev. Dis. Primer 9, 44 (2023).
Zimmerman, M., Ellison, W., Young, D., Chelminski, I. & Dalrymple, K. How many different ways do patients meet the diagnostic criteria for major depressive disorder?. Compr. Psychiatry 56, 29–34 (2015).
Fried, E. I., Coomans, F. & Lorenzo-Luaces, L. The 341 737 ways of qualifying for the melancholic specifier. Lancet Psychiatry 7, 479–480 (2020).
Olbert, C. M., Gala, G. J. & Tupler, L. A. Quantifying heterogeneity attributable to polythetic diagnostic criteria: theoretical framework and empirical application. J. Abnorm. Psychol. 123, 452–462 (2014).
International Advisory Group for the Revision of ICD-10 Mental and Behavioural Disorders A conceptual framework for the revision of the ICD-10 classification of mental and behavioural disorders. World Psychiatry 10, 86–92 (2011).
Uher, R., Payne, J. L., Pavlova, B. & Perlis, R. H. Major depressive disorder in DSM-5: implications for clinical practice and research of changes from DSM-IV. Depress. Anxiety 31, 459–471 (2014).
Herrman, H. et al. Time for united action on depression: a Lancet–World Psychiatric Association Commission. Lancet Lond. Engl. 399, 957–1022 (2022).
Kendler, K. S. The phenomenology of major depression and the representativeness and nature of DSM criteria. Am. J. Psychiatry 173, 771–780 (2016).
Chevance, A. et al. Identifying outcomes for depression that matter to patients, informal caregivers, and health-care professionals: qualitative content analysis of a large international online survey. Lancet Psychiatry 7, 692–702 (2020).
Regier, D. A. et al. DSM-5 field trials in the United States and Canada, Part II: test–retest reliability of selected categorical diagnoses. Am. J. Psychiatry 170, 59–70 (2013).
Fried, E. I., Flake, J. K. & Robinaugh, D. J. Revisiting the theoretical and methodological foundations of depression measurement. Nat. Rev. Psychol. 1, 358–368 (2022).
Fried, E. I. The 52 symptoms of major depression: lack of content overlap among seven common depression scales. J. Affect. Disord. 208, 191–197 (2017).
Beck, A. T., Steer, R. A. & Brown, G. K. Beck Depression Inventory Manual (The Psychological Corporation, 1987).
Patalay, P. & Fried, E. I. Editorial perspective: Prescribing measures: unintended negative consequences of mandating standardized mental health measurement. J. Child Psychol. Psychiatry 62, 1032–1036 (2021).
Cronbach, L. J. & Meehl, P. E. Construct validity in psychological tests. Psychol. Bull. 52, 281–302 (1955).
Hamilton, M. in Assessment of Depression (eds Sartorius, N. & Ban, T. A.) 143–152 (Springer, 1986).
Montgomery, S. A. & Asberg, M. A new depression scale designed to be sensitive to change. Br. J. Psychiatry 134, 382–389 (1979).
Martino, D. J., Szmulewicz, A. G., Valerio, M. P. & Parker, G. Melancholia: an attempt at definition based on a review of empirical data. J. Nerv. Ment. Dis. 207, 792–798 (2019).
Arnow, B. A. et al. Depression subtypes in predicting antidepressant response: a report from the iSPOT-D trial. Am. J. Psychiatry 172, 743–750 (2015).
Uher, R. et al. Melancholic, atypical and anxious depression subtypes and outcome of treatment with escitalopram and nortriptyline. J. Affect. Disord. 132, 112–120 (2011).
Oquendo, M. A. et al. Instability of symptoms in recurrent major depression: a prospective study. Am. J. Psychiatry 161, 255–261 (2004).
Veltman, E. M. et al. Melancholia as predictor of electroconvulsive therapy outcome in later life. J. ECT 35, 231–237 (2019).
Milaneschi, Y., Lamers, F., Berk, M. & Penninx, B. W. J. H. Depression heterogeneity and its biological underpinnings: toward immunometabolic depression. Biol. Psychiatry 88, 369–380 (2020).
Penninx, B. W. J. H. et al. Immuno-metabolic depression: from concept to implementation. Lancet Reg. Health Eur. 48, 101166 (2025).
de Kluiver, H. et al. Metabolomics signatures of depression: the role of symptom profiles. Transl. Psychiatry 13, 198 (2023).
Lamers, F. et al. Depression profilers and immuno-metabolic dysregulation: longitudinal results from the NESDA study. Brain Behav. Immun. 88, 174–183 (2020).
Vreijling, S. R. et al. Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials. Br. J. Psychiatry 224, 89–97 (2024).
Shafer, A. B. Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung. J. Clin. Psychol. 62, 123–146 (2006).
Fried, E. I. et al. Measuring depression over time… Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression. Psychol. Assess. 28, 1354–1367 (2016).
Nguyen, H. T., Kitner-Triolo, M., Evans, M. K. & Zonderman, A. B. Factorial invariance of the CES-D in low socioeconomic status African Americans compared with a nationally representative sample. Psychiatry Res. 126, 177–187 (2004).
Crockett, L. J., Randall, B. A., Shen, Y.-L., Russell, S. T. & Driscoll, A. K. Measurement equivalence of the center for epidemiological studies depression scale for Latino and Anglo adolescents: a national study. J. Consult. Clin. Psychol. 73, 47–58 (2005).
van Loo, H. M., de Jonge, P., Romeijn, J.-W., Kessler, R. C. & Schoevers, R. A. Data-driven subtypes of major depressive disorder: a systematic review. BMC Med. 10, 156 (2012).
Kotov, R. et al. The Hierarchical Taxonomy of Psychopathology (HiTOP): a dimensional alternative to traditional nosologies. J. Abnorm. Psychol. 126, 454–477 (2017).
Forbes, M. K. et al. Reconstructing psychopathology: a data-driven reorganization of the symptoms in the Diagnostic and Statistical Manual of Mental Disorders. Clin. Psychol. Sci. 13, 462–488 (2025).
Schramm, E., Klein, D. N., Elsaesser, M., Furukawa, T. A. & Domschke, K. Review of dysthymia and persistent depressive disorder: history, correlates, and clinical implications. Lancet Psychiatry 7, 801–812 (2020).
Eaton, W. W. et al. Population-based study of first onset and chronicity in major depressive disorder. Arch. Gen. Psychiatry 65, 513–520 (2008).
Semkovska, M. et al. Cognitive function following a major depressive episode: a systematic review and meta-analysis. Lancet Psychiatry 6, 851–861 (2019).
Cosci, F. & Fava, G. A. Staging of unipolar depression: systematic review and discussion of clinical implications. Psychol. Med. 52, 1621–1628 (2022).
McIntyre, R. S. et al. Treatment-resistant depression: definition, prevalence, detection, management, and investigational interventions. World Psychiatry 22, 394–412 (2023).
Ruhé, H. G., van Rooijen, G., Spijker, J., Peeters, F. P. M. L. & Schene, A. H. Staging methods for treatment resistant depression. A systematic review. J. Affect. Disord. 137, 35–45 (2012).
McAllister-Williams, R. H. et al. The identification, assessment and management of difficult-to-treat depression: An international consensus statement. J. Affect. Disord. 267, 264–282 (2020).
Ebrahimi, O. V. et al. Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder. Br. J. Psychiatry 224, 157–163 (2024).
Nemesure, M. D. et al. Depressive symptoms as a heterogeneous and constantly evolving dynamical system: idiographic depressive symptom networks of rapid symptom changes among persons with major depressive disorder. J. Psychopathol. Clin. Sci. 133, 155–166 (2024).
Davis, S. et al. Reporting lived experience work. Lancet Psychiatry 11, 8–9 (2024).
Fusar-Poli, P. et al. The lived experience of depression: a bottom-up review co-written by experts by experience and academics. World Psychiatry 22, 352–365 (2023).
Kendler, K. S. The dappled nature of causes of psychiatric illness: replacing the organic-functional/hardware–software dichotomy with empirically based pluralism. Mol. Psychiatry 17, 377–388 (2012).
Wittenborn, A. K., Rahmandad, H., Rick, J. & Hosseinichimeh, N. Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder. Psychol. Med. 46, 551–562 (2016).
Fried, E. I. Studying mental health problems as systems, not syndromes. Curr. Dir. Psychol. Sci. 31, 500–508 (2022).
Fried, E. I. & Nesse, R. M. Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential. BMC Med. 13, 72 (2015).
Gururajan, A., Reif, A., Cryan, J. F. & Slattery, D. A. The future of rodent models in depression research. Nat Rev Neurosci 20, 686–701 (2019).
Hasler, G., Drevets, W. C., Manji, H. K. & Charney, D. S. Discovering endophenotypes for major depression. Neuropsychopharmacology 29, 1765–1781 (2004).
Insel, T. et al. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167, 748–751 (2010).
Dell’Acqua, C., Palomba, D., Patron, E. & Messerotti Benvenuti, S. Rethinking the risk for depression using the RDoC: a psychophysiological perspective. Front. Psychol. 14, 1108275 (2023).
Ahmed, A. T. et al. Mapping depression rating scale phenotypes onto research domain criteria (RDoC) to inform biological research in mood disorders. J. Affect. Disord. 238, 1–7 (2018).
Tao, Y. et al. Comparing the centrality symptoms of major depressive disorder samples across junior high school students, senior high school students, college students and elderly adults during city lockdown of COVID-19 pandemic—a network analysis. J. Affect. Disord. 324, 190–198 (2023).
Moradi, S. et al. Network modeling of major depressive disorder symptoms in adult women. Psychol. Med. 53, 5449–5458 (2023).
Malgaroli, M., Calderon, A. & Bonanno, G. A. Networks of major depressive disorder: a systematic review. Clin. Psychol. Rev. 85, 102000 (2021).
Fried, E. I. & Nesse, R. M. The impact of individual depressive symptoms on impairment of psychosocial functioning. PLoS ONE 9, e90311 (2014).
McGlinchey, J. B., Zimmerman, M., Young, D. & Chelminski, I. Diagnosing major depressive disorder VIII: are some symptoms better than others? J. Nerv. Ment. Dis. 194, 785 (2006).
Mitchell, A. J., McGlinchey, J. B., Young, D., Chelminski, I. & Zimmerman, M. Accuracy of specific symptoms in the diagnosis of major depressive disorder in psychiatric out-patients: data from the MIDAS project. Psychol. Med. 39, 1107–1116 (2009).
Leverich, G. S. & Post, R. M. Life charting of affective disorders. CNS Spectr. 3, 21–37 (1998).
Keller, M. B. et al. The Longitudinal Interval Follow-up Evaluation. A comprehensive method for assessing outcome in prospective longitudinal studies. Arch. Gen. Psychiatry 44, 540–548 (1987).
Schramm, E. et al. Two-year follow-up after treatment with the cognitive behavioral analysis system of psychotherapy versus supportive psychotherapy for early-onset chronic depression. Psychother. Psychosom. 88, 154–164 (2019).
Elsaesser, M. et al. Longitudinal clusters of long-term trajectories in patients with early-onset chronic depression: 2 years of naturalistic follow-up after extensive psychological treatment. Psychother. Psychosom. 93, 65–74 (2024).
Kendler, K. S., Thornton, L. M. & Gardner, C. O. Stressful life events and previous episodes in the etiology of major depression in women: an evaluation of the ‘kindling’ hypothesis. Am. J. Psychiatry 157, 1243–1251 (2000).
Piccinelli, M. & Wilkinson, G. Gender differences in depression: critical review. Br. J. Psychiatry 177, 486–492 (2000).
Trull, T. J. & Ebner-Priemer, U. W. Ambulatory assessment in psychopathology research: a review of recommended reporting guidelines and current practices. J. Abnorm. Psychol. 129, 56–63 (2020).
Insel, T. R. Digital phenotyping: technology for a new science of behavior. JAMA 318, 1215–1216 (2017).
Winter, N. R. et al. From multivariate methods to an AI ecosystem. Mol. Psychiatry 26, 6116–6120 (2021).
Wichers, M., Riese, H., Hodges, T. M., Snippe, E. & Bos, F. M. A narrative review of network studies in depression: what different methodological approaches tell us about depression. Front. Psychiatry 12, 719490 (2021).
Huang, D., Susser, E., Rudolph, K. E. & Keyes, K. M. Depression networks: a systematic review of the network paradigm causal assumptions. Psychol. Med. 53, 1665–1680 (2023).
Scheffer, M. et al. A dynamical systems view of psychiatric disorders—practical implications: a review. JAMA Psychiatry 81, 624–630 (2024).
Hofmann, S. G. A network control theory of dynamic systems approach to personalize therapy. Behav. Ther. 56, 199–212 (2025).
Stocker, J. E. et al. Formalizing psychological interventions through network control theory. Sci. Rep. 13, 13830 (2023).
van der Wal, J. M. et al. Advancing urban mental health research: from complexity science to actionable targets for intervention. Lancet Psychiatry 8, 991–1000 (2021).
Schumacher, L. et al. Predicting the outcome of psychotherapy for chronic depression by person-specific symptom networks. World Psychiatry 23, 411–420 (2024).
Robberegt, S. J. et al. Personalised app-based relapse prevention of depressive and anxiety disorders in remitted adolescents and young adults: a protocol of the StayFine RCT. BMJ Open 12, e058560 (2022).
Kooiman, B. E. A. M. et al. Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people. Front. Psychiatry 14, 1229713 (2023).
Leaning, I. E. et al. From smartphone data to clinically relevant predictions: a systematic review of digital phenotyping methods in depression. Neurosci. Biobehav. Rev. 158, 105541 (2024).
Jim, J. R. et al. Recent advancements and challenges of NLP-based sentiment analysis: a state-of-the-art review. Nat. Lang. Process J. 6, 100059 (2024).
Hossain, M. M., Hossain, M. S., Mridha, M. F., Safran, M. & Alfarhood, S. Multi task opinion enhanced hybrid BERT model for mental health analysis. Sci. Rep. 15, 3332 (2025).
Acheampong, F. A., Nunoo-Mensah, H. & Chen, W. Transformer models for text-based emotion detection: a review of BERT-based approaches. Artif. Intell. Rev. 54, 5789–5829 (2021).
Chalmers, I. et al. How to increase value and reduce waste when research priorities are set. Lancet Lond. Engl. 383, 156–165 (2014).
Crowe, S., Fenton, M., Hall, M., Cowan, K. & Chalmers, I. Patients’, clinicians’ and the research communities’ priorities for treatment research: there is an important mismatch. Res. Involv. Engagem. 1, 2 (2015).
Mokkink, L. B., Herbelet, S., Tuinman, P. R. & Terwee, C. B. Content validity: judging the relevance, comprehensiveness, and comprehensibility of an outcome measurement instrument—a COSMIN perspective. J. Clin. Epidemiol. 185, 111879 (2025).
Alexandrova, A. & Haybron, D. M. Is construct validation valid? Philos. Sci. 83, 1098–1109 (2016).
Charvet, C. et al. How to measure mental pain: a systematic review assessing measures of mental pain. Evid. Based Ment. Health 25, e4–e4 (2022).
Williamson, P., Altman, D., Blazeby, J., Clarke, M. & Gargon, E. Driving up the quality and relevance of research through the use of agreed core outcomes. J. Health Serv. Res. Policy 17, 1–2 (2012).
Veal, C. et al. A protocol for the development of a core outcome set for adults with depression. J. Clin. Epidemiol. 191, 112119 (2026).
Tunis, S. R. et al. Improving the relevance and consistency of outcomes in comparative effectiveness research. J. Comp. Eff. Res. 5, 193–205 (2016).
Kirkham, J. J., Boers, M., Tugwell, P., Clarke, M. & Williamson, P. R. Outcome measures in rheumatoid arthritis randomised trials over the last 50 years. Trials 14, 324 (2013).
Spitzer, R. L. Validation and utility of a self-report version of PRIME-MD. The PHQ Primary Care Study. JAMA 282, 1737 (1999).
Kroenke, K., Spitzer, R. L. & Williams, J. B. W. The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 16, 606–613 (2001).
Zimmerman, M., Morgan, T. A. & Stanton, K. The severity of psychiatric disorders. World Psychiatry 17, 258–275 (2018).
Farber, G. K., Gage, S., Kemmer, D. & White, R. Common measures in mental health: a joint initiative by funders and journals. Lancet Psychiatry 10, 465–470 (2023).
Hamilton, M. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56–62 (1960).
Williams, J. B. W. Standardizing the Hamilton Depression Rating Scale: past, present, and future. Eur. Arch. Psychiatry Clin. Neurosci. 251, 6–12 (2001).
Montgomery, S. A. & Åsberg, M. A new depression scale designed to be sensitive to change. Br. J. Psychiatry 134, 382–389 (1979).
Beck, A. T., Steer, R. A., Ball, R. & Ranieri, W. F. Comparison of Beck Depression Inventories-IA and -II in psychiatric outpatients. J. Pers. Assess. 67, 588–597 (1996).
Storch, E. A., Roberti, J. W. & Roth, D. A. Factor structure, concurrent validity, and internal consistency of the Beck Depression Inventory? Second edition in a sample of college students. Depress. Anxiety 19, 187–189 (2004).
Busner, J. & Targum, S. D. The clinical global impressions scale: applying a research tool in clinical practice. Psychiatry 4, 28–37 (2007).
Rush, A. J., Gullion, C. M., Basco, M. R., Jarrett, R. B. & Trivedi, M. H. The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychol. Med. 26, 477–486 (1996).
Rush, A. J. et al. The 16-item Quick Inventory of Depressive Symptomatology (QIDS), Clinician Rating (QIDS-C), and Self-Report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol. Psychiatry 54, 573–583 (2003).
Trivedi, M. H. et al. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation. Psychol. Med. 34, 73–82 (2004).
Roberts, R. E. & Vernon, S. W. The Center for Epidemiologic Studies Depression Scale: its use in a community sample. Am. J. Psychiatry 140, 41–46 (1983).
Osório, F. L. et al. Clinical validity and intrarater and test–retest reliability of the Structured Clinical Interview for DSM-5 – Clinician Version (SCID-5-CV). Psychiatry Clin. Neurosci. 73, 754–760 (2019).
Sheehan, D. V. et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 59, 22–33 (1998).
Lin, C.-H., Lu, M.-J., Wong, J. & Chen, C.-C. Comparison of physician-rating and self-rating scales for patients with major depressive disorder. J. Clin. Psychopharmacol 34, 716–721 (2014).
Ma, S. et al. Discrepancies between self-rated depression and observed depression severity: The effects of personality and dysfunctional attitudes. Gen. Hosp. Psychiatry 70, 25–30 (2021).
Cuijpers, P., Li, J., Hofmann, S. G. & Andersson, G. Self-reported versus clinician-rated symptoms of depression as outcome measures in psychotherapy research on depression: a meta-analysis. Clin. Psychol. Rev. 30, 768–778 (2010).
Goodmann, D. R. et al. Factor analysis of depression symptoms across five broad cultural groups. J. Affect. Disord. 282, 227–235 (2021).
Maj, M. Understanding depression beyond the ‘mind–body’ dichotomy. World Psychiatry 22, 349–350 (2023).
Morriss, R., Leese, M., Chatwin, J. & Baldwin, D. Inter-rater reliability of the Hamilton Depression Rating Scale as a diagnostic and outcome measure of depression in primary care. J. Affect. Disord. 111, 204–213 (2008).
Corruble, E., Purper, D., Payan, C. & Guelfi, J. Inter-rater reliability of two depression rating scales, MADRS and DRRS, based on videotape records of structured interviews. Eur. Psychiatry 13, 264–266 (1998).
Schramm, E., Elsaesser, M., Jenkner, C., Hautzinger, M. & Herpertz, S. C. Algorithm-based modular psychotherapy vs. cognitive-behavioral therapy for patients with depression, psychiatric comorbidities and early trauma: a proof-of-concept randomized controlled trial. World Psychiatry 23, 257–266 (2024).
Elsaesser, M. et al. Modular-based psychotherapy (MoBa) versus cognitive-behavioural therapy (CBT) for patients with depression, comorbidities and a history of childhood maltreatment: study protocol for a randomised controlled feasibility trial. BMJ Open 12, e057672 (2022).
Watson, D. & Clark, L. A. Mood and Anxiety Symptom Questionnaire (APA PsycNet, 1991); https://doi.org/10.1037/t13679-000.
Steitz, T. & Weeß, H.-G. in Enzyklopädie der Schlafmedizin (eds Peter, H. et al.) 1–2 (Springer, 2020).
Watson, D., Clark, L. A. & Tellegen, A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 54, 1063–1070 (1988).
Huang, Z., Kohler, I. V. & Kämpfen, F. A single-item Visual Analogue Scale (VAS) measure for assessing depression among college students. Commun. Ment. Health J 56, 355–367 (2020).
Snaith, R. P. et al. A scale for the assessment of hedonic tone – the Snaith–Hamilton Pleasure Scale. Br. J. Psychiatry 167, 99–103 (1995).
Fawcett, J., Clark, D. C., Scheftner, W. A. & Gibbons, R. A. Assessing anhedonia in psychiatric patients: the pleasure scale. Arch. Gen. Psychiatry 40, 79 (1983).
Chapman, L. J., Chapman, J. P. & Raulin, M. L. Scales for physical and social anhedonia. J. Abnorm. Psychol. 85, 374–382 (1976).
Gard, D. E., Gard, M. G., Kring, A. M. & John, O. P. Anticipatory and consummatory components of the experience of pleasure: a scale development study. J. Res. Personal. 40, 1086–1102 (2006).
Rizvi, S. J. et al. Dimensional Anhedonia Rating Scale (APA PsycNet, 2015); https://doi.org/10.1037/t46939-000
Mathey, M. F. Assessing appetite in Dutch elderly with the Appetite, Hunger and Sensory Perception (AHSP) questionnaire. J. Nutr. Health Aging 5, 22–28 (2001).
Wilson, M.-M. G. et al. Appetite assessment: simple appetite questionnaire predicts weight loss in community-dwelling adults and nursing home residents. Am. J. Clin. Nutr. 82, 1074–1081 (2005).
Stunkard, A. J. & Messick, S. The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J. Psychosom. Res. 29, 71–83 (1985).
EDI-2 – Eating Disorder Inventory-2 (Testzentrale); https://www.testzentrale.de/shop/eating-disorder-inventory-2.html
Thiel, A. & Paul, T. Test–retest reliability of the Eating Disorder Inventory 2. J. Psychosom. Res. 61, 567–569 (2006).
Shahid, A., Wilkinson, K., Marcu, S. & Shapiro, C. M. in STOP, THAT and One Hundred Other Sleep Scales (eds Shahid, A. et al.) 181–183 (Springer, 2011).
Morin C. M. Insomnia: Psychological Assessment and Management (Guilford Press, 1993).
Soldatos, C. R., Dikeos, D. G. & Paparrigopoulos, T. J. Athens Insomnia Scale: validation of an instrument based on ICD-10 criteria. J. Psychosom. Res. 48, 555–560 (2000).
Urponen, H., Partinen, M., Vuori, I. & Hasan, J. in Sleep and Health Risk (eds Peter, J. H. et al.) 555–558 (Springer, 1991).
Violani, C., Devoto, A., Lucidi, F., Lombardo, C. & Russo, P. M. Validity of a short insomnia questionnaire: the SDQ. Brain Res. Bull. 63, 415–421 (2004).
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. & Kupfer, D. J. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 28, 193–213 (1989).
Hadzi-Pavlovic, D. et al. Inter-rater reliability of a refined index of melancholia: the CORE system. J. Affect. Disord. 27, 155–162 (1993).
Corrigan, J. D. & Bogner, J. A. Factor structure of the agitated behavior scale. J. Clin. Exp. Neuropsychol. 16, 386–392 (1994).
Penner, I. et al. The Fatigue Scale for Motor and Cognitive Functions (FSMC): validation of a new instrument to assess multiple sclerosis-related fatigue. Mult. Scler. J. 15, 1509–1517 (2009).
Shahid, A., Wilkinson, K., Marcu, S. & Shapiro, C. M. in STOP, THAT and One Hundred Other Sleep Scales (eds Shahid, A. et al.) 161–162 (Springer, 2011).
McGahuey, A. et al. The Arizona Sexual Experience Scale (ASEX): reliability and validity. J. Sex Marital Ther. 26, 25–40 (2000).
Roelofs, J., Muris, P., Huibers, M., Peeters, F. & Arntz, A. On the measurement of rumination: a psychometric evaluation of the ruminative response scale and the rumination on sadness scale in undergraduates. J. Behav. Ther. Exp. Psychiatry 37, 299–313 (2006).
Hoppen, T. H. et al. A brief measure of guilt and shame: validation of the Guilt and Shame Questionnaire (GSQ-8). Eur. J. Psychotraumatology 13, 2146720 (2022).
Rosenberg, M. Self-Esteem Scale (Zusammenstellung Sozialwissenschaftlicher Items Skalen ZIS, 2002); https://doi.org/10.6102/ZIS46.
Crocker, J., Luhtanen, R. K., Cooper, M. L. & Bouvrette, A. Contingencies of Self-Worth Scale (APA PsycNet, 2003); https://doi.org/10.1037/t00082-000
Frost, R. O. & Shows, D. L. The nature and measurement of compulsive indecisiveness. Behav. Res. Ther. 31, 683–IN2 (1993).
Rassin, E., Muris, P., Franken, I., Smit, M. & Wong, M. Measuring general indecisiveness. J. Psychopathol. Behav. Assess. 29, 60–67 (2007).
Germeijs, V. & De Boeck, P. A measurement scale for indecisiveness and its relationship to career indecision and other types of indecision. Eur. J. Psychol. Assess. 18, 113–122 (2002).
Sullivan, M. J., Edgley, K. & Dehoux, E. A survey of multiple sclerosis: I. Perceived cognitive problems and compensatory strategy use. Can. J. Rehabil. 4, 99–105 (1990).
Broadbent, D. E., Cooper, P. F., FitzGerald, P. & Parkes, K. R. The Cognitive Failures Questionnaire (CFQ) and its correlates. Br. J. Clin. Psychol. 21, 1–16 (1982).
Wechsler, D. Wechsler Adult Intelligence Scale 4th edn (APA PsycNet, 2012); https://doi.org/10.1037/t15169-000
Harrison, J. E. et al. Stability, reliability, and validity of the THINC-it screening tool for cognitive impairment in depression: a psychometric exploration in healthy volunteers. Int. J. Methods Psychiatr. Res. 27, e1736 (2018).
Sahakian, B. J. & Owen, A. M. Computerized assessment in neuropsychiatry using CANTAB: discussion paper. J. R. Soc. Med. 85, 399–402 (1992).
Reynolds, W. M. Psychometric characteristics of the adult suicidal ideation questionnaire in college students. J. Pers. Assess. 56, 289–307 (1991).
Beck, A. T., Kovacs, M. & Weissman, A. Assessment of suicidal intention: the Scale for Suicide Ideation. J. Consult. Clin. Psychol. 47, 343–352 (1979).
Posner, K. et al. The Columbia–Suicide Severity Rating Scale: initial validity and internal consistency findings from three multisite studies with adolescents and adults. Am. J. Psychiatry 168, 1266–1277 (2011).
Osman, A. et al. The Suicidal Behaviors Questionnaire-Revised (SBQ-R): validation with clinical and nonclinical samples. Assessment 8, 443–454 (2001).
Von Glischinski, M., Teismann, T., Prinz, S., Gebauer, J. E. & Hirschfeld, G. Depressive Symptom Inventory Suicidality Subscale: optimal cut points for clinical and non-clinical samples. Clin. Psychol. Psychother. 23, 543–549 (2016).
WHO Disability Assessment Schedule (WHODAS 2.0) (WHO, 2012); https://www.who.int/standards/classifications/international-classification-of-functioning-disability-and-health/who-disability-assessment-schedule
Reisberg, B. Functional assessment staging (FAST). Psychopharmacol. Bull. 24, 653–659 (1988).
Rybarczyk, B. in Encyclopedia of Clinical Neuropsychology (eds Kreutzer, J. S. et al.) 2313 (Springer, 2011).
Sheehan, D. V., Harnett-Sheehan, K. & Raj, B. A. The measurement of disability. Int. Clin. Psychopharmacol. 11, 89 (1996).
Gameroff, M. J., Wickramaratne, P. & Weissman, M. M. Testing the short and screener versions of the Social Adjustment Scale – Self-Report (SAS-SR). Int. J. Methods Psychiatr. Res. 21, 52–65 (2012).
Mundt, J. C., Marks, I. M., Shear, M. K. & Greist, J. M. The Work and Social Adjustment Scale: a simple measure of impairment in functioning. Br. J. Psychiatry 180, 461–464 (2002).
Horowitz, L. M., Rosenberg, S. E., Baer, B. A., Ureño, G. & Villaseñor, V. S. Inventory of interpersonal problems: psychometric properties and clinical applications. J. Consult. Clin. Psychol. 56, 885–892 (1988).
Kiesler, D. J., Schmidt, J. A. & Wagner, C. C. in Circumplex Models of Personality and Emotions (eds Plutchik, R. & Conte, H. R.) 221–244 (American Psychological Association, 1997).
Brennan, K. A., Clark, C. L. & Shaver, P. R. (eds) in Attachment Theory and Close Relationships 46–76 (Guilford Press, 1998).
Downey, G. & Feldman, S. I. Implications of rejection sensitivity for intimate relationships. J. Pers. Soc. Psychol. 70, 1327–1343 (1996).
Benjamin, L. S., Rothweiler, J. C. & Critchfield, K. L. The use of structural analysis of social behavior (SASB) as an assessment tool. Annu. Rev. Clin. Psychol. 2, 83–109 (2006).
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