On the factor structure of the Beck Depression Inventory–II: G is the key.

Brouwer, Danny; Meijer, Rob R.; Zevalkink, Jolien

doi:10.1037/a0029228

Cited by 146 publications

(169 citation statements)

References 52 publications

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“…21,58,67,73,87,101,105 Although still scant, the bifactor model (G) was able to identify a non-hierarchical general depression in addition to the traditional two-dimensional structure. 18,34,64,81,84,96,121 These investigations shared the view that much of the variance of the BDI-II items can be accounted for by a hierarchical higher order or a parallel dimension of depression, where much of the common variance can be explained by a general construct. Practitioners should be careful when interpreting subscale scores, which might be greatly related to the heterogeneous characteristics of depressive conditions.…”

Section: Content and Construct Validitymentioning

confidence: 52%

Psychometric properties of the Beck Depression Inventory-II: a comprehensive review

Wang

Gorenstein

2013

Rev. Bras. Psiquiatr.

1,110

765

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Objective: To review the psychometric properties of the Beck Depression Inventory-II (BDI-II) as a self-report measure of depression in a variety of settings and populations. Methods: Relevant studies of the BDI-II were retrieved through a search of electronic databases, a hand search, and contact with authors. Retained studies (k = 118) were allocated into three groups: non-clinical, psychiatric/institutionalized, and medical samples. Results: The internal consistency was described as around 0.9 and the retest reliability ranged from 0.73 to 0.96. The correlation between BDI-II and the Beck Depression Inventory (BDI-I) was high and substantial overlap with measures of depression and anxiety was reported. The criterion-based validity showed good sensitivity and specificity for detecting depression in comparison to the adopted gold standard. However, the cutoff score to screen for depression varied according to the type of sample. Factor analysis showed a robust dimension of general depression composed by two constructs: cognitive-affective and somatic-vegetative. Conclusions: The BDI-II is a relevant psychometric instrument, showing high reliability, capacity to discriminate between depressed and non-depressed subjects, and improved concurrent, content, and structural validity. Based on available psychometric evidence, the BDI-II can be viewed as a costeffective questionnaire for measuring the severity of depression, with broad applicability for research and clinical practice worldwide.

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Section: Content and Construct Validitymentioning

confidence: 52%

Psychometric properties of the Beck Depression Inventory-II: a comprehensive review

Wang

Gorenstein

2013

Rev. Bras. Psiquiatr.

1,110

765

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“…Uniquely, Gustafsson and Balke [24] applied what they termed a nested factor model, which was identical to the bi-factor model of Holzinger and Swineford [1]. Subsequently, the bi-factor model has been recommended by Reise [25] for CFA and successfully employed in the measurement of a variety of constructs, such as cognitive ability [22], health outcomes [26], quality of life [27], psychiatric distress [28], early academic skills [29], personality [30], psychopathology [31], and emotional risk [32].…”

Section: Introductionmentioning

confidence: 99%

Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

et al. 2015

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Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

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“…Kada je reč o specifičnim faktorima, situacija je manje jasna. Ne postoje definitivni kriterijumi koji ukazuju na zaključak o primarnosti G faktora, ali u većini dosadašnjih istraživanja u kojima je donet takav zaključak, G je objašnjavao bar oko 80% zajedničke varijanse (npr., Brouwer, Meijer, & Zevalkink, 2013;Ebesutani et al, 2014;Ghisi et al, 2016;Osman et al, 2010). U ovom istraživanju, taj broj je manji (60.75%).…”

Section: Diskusijaunclassified

Psihometrijska Evaluacija Srpske Adaptacije Indeksa Senzitivnosti Na Simptome Anksioznosti (Asi-3)

Volarov¹,

Oljača²,

Mihić³

et al. 2017

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Osnovni cilj ovog rada je provera validnosti i psihometrijskih karakteristika Indeksa senzitivnosti na simptome anksioznosti (ASI-3), na srpskom uzorku ispitanika iz opšte populacije. Uzorak je činilo 553 ispitanika starosti 18 do 60 godina, pri čemu je bilo više ispitanika ženskog pola (82.1%). Rezultati konfirmativne faktorske analize (CFA) ukazuju da bifaktorski model, sa jednim generalnim faktorom opšte senzitivnosti na simptome anksioznosti i tri specifična faktora -zabrinutost za fizičko funkcionisanje, zabrinutost za kognitivno funkcionisanje i zabrinutost u socijalnim situacijama, ima najbolji fit. Rezultati analiza baziranih na teoriji odgovora na stavke (IRT: 2PL model) ukazuju na to da je ASI-3 relativno težak, odnosno da je prilagođen ispitanicima sa prosečnim i natprosečnim nivoom latentne osobine. Na osnovu rezultata baziranih na korelaciono-regresionim analizama donet je zaključak o dobroj konvergentnoj, divergentnoj i inkrementalnoj validnosti upitnika ASI-3. IRT analizama je identifikovana grupa od pet problematičnih stavki (niski parametri informativnosti i diskriminativnosti kao i visoki parametri težine) i razmotrena je njihova potencijalna primena u kliničkoj praksi. Konačno, generalni faktor opšte senzitivnosti na simptome anksioznosti, a u manjoj meri i specifični faktori imaju potencijal u objašnjavanju dodatne varijanse spoljnih kriterijuma povrh koncepta anksioznosti iz domena revidirane teorije osetljivosti na potkrepljenje, što ukazuje na inkrementalnu validnosti upitnika ASI-3. Ponuđene su kliničke i istraživačke implikacije.Ključne reči: senzitivnost na anksioznost, ASI-3, bifaktorski model, konfirmatorna faktorska analiza (CFA), teorija odgovora na stavke (IRT) 2 Rad je nastao u okviru projekta Ministarstva prosvete, nauke i tehnološkog razvoja (179006).

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On the factor structure of the Beck Depression Inventory–II: G is the key.

Cited by 146 publications

References 52 publications

Psychometric properties of the Beck Depression Inventory-II: a comprehensive review

Psychometric properties of the Beck Depression Inventory-II: a comprehensive review

Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

Psihometrijska Evaluacija Srpske Adaptacije Indeksa Senzitivnosti Na Simptome Anksioznosti (Asi-3)

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