Measuring depression over time . . . Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression.

Abstract

In depression research, symptoms are routinely assessed via rating scales and added to construct sum-scores. These scores are used as a proxy for depression severity in cross-sectional research, and differences in sum-scores over time are taken to reflect changes in an underlying depression construct. To allow for such interpretations, rating scales must (a) measure a single construct, and (b) measure that construct in the same way across time. These requirements are referred to as unidimensionality and measurement invariance. We investigated these 2 requirements in 2 large prospective studies (combined n = 3,509) in which overall depression levels decrease, examining 4 common depression rating scales (1 self-report, 3 clinician-report) with different time intervals between assessments (between 6 weeks and 2 years). A consistent pattern of results emerged. For all instruments, neither unidimensionality nor measurement invariance appeared remotely tenable. At least 3 factors were required to describe each scale, and the factor structure changed over time. Typically, the structure became less multifactorial as depression severity decreased (without however reaching unidimensionality). The decrease in the sum-scores was accompanied by an increase in the variances of the sum-scores, and increases in internal consistency. These findings challenge the common interpretation of sum-scores and their changes as reflecting 1 underlying construct. The violations of common measurement requirements are sufficiently severe to suggest alternative interpretations of depression sum-scores as formative instead of reflective measures. We discuss the possible causes of these violations such as response shift bias, restriction of range, and regression to the mean.

Factors Influencing the Evolution of Vocational Teachers’ Beliefs and Practices Related to Classroom Management during Teacher Education

“…In order to solve the problem of high kurtosis in a sample of 71 teachers, we added more participants from a broader and less specific sample (total participants in this combined sample N = 410), following Fried, van Borkulo, Epskamp, Schoevers, and Tuerlinckx (2016). Indeed, in the specific sample consisting of 71 teachers, participants' answers were very consensual: many teachers gave the exact same scores, which led participants deviating from this consensus to be considered as outliers.…”

The 52 different symptoms of major depression: lack of content overlap among seven common depression scales

“…The evidence for convergent validity of depression instruments is mixed, and correlations ranging from 0 to virtually 1 have been reported in prior investigations (Fried et al, 2016b;Polaino and Senra, 1991). But even if the convergent validity were high -assume a correlation of 0.7 between the 20-item CES-D and 20-item SDS sumscores -this does not imply that scales measure the same construct.…”

“…Second, psychometric analyses have documented that most scales are multidimensional, meaning they assess several constructs (Fried et al, 2016b); these factor structures, however, do not generalize across scales (Shafer, 2006;van Loo et al, 2012). Since scales measure different constructs, using different instruments may lead to different results; this is more likely to be problematic the more severe the heterogeneity of depression symptoms across different rating scales is.…”

“…Not only do symptoms differ from each other in important dimensions (Fried and Nesse, 2015b), scales also encompass many different types of symptoms (Snaith, 1993). On top of that, common rating scales are multidimensional, meaning they do not capture one underlying construct (Fried et al, 2016b;van Loo et al, 2012), making the routine use of one sum-score to reflect depression severity highly problematic. A way forward for now is the assessment of a broad range of symptoms; the 44-item Symptoms of Depression Questionnaire provides a good example and aims to capture the full range of clinical presentations of depression (Pedrelli et al, 2014).…”

Análisis De Redes en Psicología

“…Las temáticas de estudio bajo el modelo de redes se encuentran en clara ebullición y expansión. Sirva como muestra los trabajos que han analizado la sintomatología depresiva (Bringmann, Lemmens, Huibers, Borsboom, y Tuerlinckx, 2015;Cramer et al, 2016;Fried, van Borkulo, Epskamp, et al, 2016), la psicosis y su relación con experiencias traumáticas o impactos ambientales (Isvoranu, Borsboom, van Os, y Guloksuz, 2016;Isvoranu et al, 2017), los síntomas psicóticos negativos (Levine y Leucht, 2016), los síntomas psicóticos atenuados (Fonseca-Pedrero, 2018), el abuso de sustancias (Rhemtulla et al, 2016), la calidad de vida (Kossakowski et al, 2016), los sínto-mas de estrés post-traumático (McNally et al, 2014), la comorbilidad (Cramer, Waldorp, van der Maas, y Borsboom, 2010), la relación entre síntomas y trastornos desde los sistemas taxonómicos (Boschloo et al, 2015;Tio, Epskamp, Noordhof, y Borsboom, 2016), los problemas emocionales y comportamentales en adolescentes (Boschloo, Schoevers, van Borkulo, Borsboom, y Oldehinkel, 2016;Fonseca-Pedrero, 2017) o la inteligencia (Maas, Kan, Marsman, y Stevenson, 2017), por citar algunos. Borsboom (2017) ha propuesto un modelo teórico de redes para la comprensión de los trastornos mentales.…”