Psychometric properties and measurement invariance of the Beck hopelessness scale (BHS): results from a German representative population sample
TL;DR: The BHS is a valid measure of hopelessness in various subgroups of the general population and a one-dimensional bi-factor model seems appropriate even in a non-clinical population.
Abstract: The Beck Hopelessness Scale (BHS) has been the most frequently used instrument for the measurement of hopelessness in the past 40 years. Only recently has it officially been translated into German. The psychometric properties and factor structure of the BHS have been cause for intensive debate in the past. Based on a representative sample of the German population (N = 2450) item analysis including item sensitivity, item-total correlation and item difficulty was performed. Confirmatory factor analyses (CFA) for several factor solutions from the literature were performed. Multiple group factor analysis was performed to assess measurement invariance. Construct validity was assessed via the replication of well-established correlations with concurrently assessed measures. Most items exhibited adequate properties. Items #4, #8 and #13 exhibited poor item characteristics– each of these items had previously received negative evaluations in international studies. A one-dimensional factor solution, favorable for the calculation and interpretation of a sum score, was regarded as adequate. A bi-factor model with one content factor and two method factors (defined by positive/negative item coding) resulted in an excellent model fit. Cronbach’s alpha in the current sample was .87. Hopelessness, as measured by the BHS, significantly correlated in the expected direction with suicidal ideation (r = .36), depression (r = .53) and life satisfaction (r = −.53). Strict measurement invariance could be established regarding gender and depression status. Due to limited research regarding the interpretation of fit indices with dichotomous data, interpretation of CFA results needs to remain tentative. The BHS is a valid measure of hopelessness in various subgroups of the general population. Future research could aim at replicating these findings using item response theory and cross-cultural samples. A one-dimensional bi-factor model seems appropriate even in a non-clinical population.
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TL;DR: The results of SEM showed that the effect of fear of COVID-19 on hopelessness was partly mediated by mindfulness and humor, and which was supported by bootstrapping, and therefore, higherFear of CO VID-19 was associated with lower mindfulness and Humor, and in turn, lower Mindful Attention Awareness and humor were related with higher hopelessness.
Abstract: Hopelessness is an important vulnerability factor for depressive symptomology and suicidal ideations. It may also play an important role in the fear of coronavirus 2019 (COVID-19). Therefore, the present study tested the mediating role of mindful awareness and humor (both identified as coping strategies for dealing with stressful situations) in the relationship between fear of COVID-19 and hopelessness. Participants comprised 786 Turkish individuals (562 females and 224 males; aged between 18 and 67 years) from 71 of 81 cities in Turkey. An online convenience sampling method was used to recruit participants. Participants completed surveys including the Fear of COVID-19 Scale, Beck Hopelessness Scale, Mindful Attention Awareness Scale, and Coping Humor Scale. The model was tested using structural equation modeling (SEM) and utilizing bootstrapping. The results of SEM showed that the effect of fear of COVID-19 on hopelessness was partly mediated by mindfulness and humor, and which was supported by bootstrapping. Therefore, higher fear of COVID-19 was associated with lower mindfulness and humor. In turn, lower mindfulness and humor were related with higher hopelessness. Findings are discussed in the context of COVID-19 and the hopelessness literature, and practical implications for counselors are also provided.
82 citations
Cites background from "Psychometric properties and measure..."
...Research has shown that hopelessness is a robust risk factor for suicide among clinical samples (Beck et al. 1985, 2006) and for suicidal ideation among non-clinical samples (Kliem et al. 2018)....
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...For instance, hopelessness is negatively associated with life satisfaction (Kliem et al. 2018), is a negative predictor of quality of life among older adults (Scogin et al. 2016), and is a negative predictor of resilience towards stressful events (Hjemdal et al. 2012)....
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TL;DR: In this paper, the structure of hopelessness was investigated in a large community sample (n = 1985) recruited to be highly representative of general population in Germany, and state-of-the-art techniques were adopted to investigate which thoughts and beliefs are the most central ones and to shed light on the specific associations (edges) among them.
Abstract: Hopelessness is a complex phenomenon with important clinical consequences, such as depression and suicidality. Despite its major impact on mental health, little is known about the structure of hopelessness. In this study, hopelessness was investigated in a large community sample (n = 1985), recruited to be highly representative of general population in Germany. In the context of network analysis, state-of-the-art techniques were adopted (i) to investigate which thoughts and beliefs (nodes) are the most central ones and (ii) to shed light on the specific associations (edges) among them. Stability and accuracy were also checked to ensure trustworthiness of the findings. The analyses revealed that expecting more negative than positive future events and having important goals blocked along with feelings of giving-up were the most central elements of hopelessness. Moreover, being unable to imagine the future and perceiving it as vague and uncertain were both coupled with anticipating a dark future. Theoretical and clinical consequences of this study were discussed.
58 citations
TL;DR: Brief cognitive behavioral therapy significantly reduces sleep disturbance and suicide risk and changes in cognitive flexibility, in part, explain change in sleep disturbance across both treatments.
28 citations
Journal Article•
TL;DR: In this paper, a factor analytic approach for testing the level of measurement based on measurement models for ordered-categorical indicators is presented. But the authors focus on questionnaires items.
Abstract: In the social and behavioral sciences, self-report measures administered as questionnaires are commonly used to measure psychological constructs. Data resulting from these measurements are subjected to statistical methods to describe characteristics of the sample (i.e., descriptive statistics) and to draw conclusions about the population (i.e., inferential statistics). Thus, appropriate statistical methods need to be selected based on research hypotheses and in accordance with the data at hand. One of the fundamental deciding factors for choosing appropriate statistical methods is the level of measurement of data (Pett, 2015). However, researchers rarely bother about the level of measurement and oftentimes apply statistical tests for metric dependent variables (e.g., two-sample t-test or ANOVA) instead of statistical tests commonly used for ordered-categorical dependent variables (e.g., Mann-Whitney U test or Kruskal-Wallis test). One reason for simply assuming metric-level data is that there is no appropriate statistical method available to test this assumption.In the present study, we introduce a factor analytic approach for testing the level of measurement based on measurement models for ordered-categorical indicators. In the following, we present a commonly used item format for questionnaires and discuss the concept of level of measurement. Next, we discuss two approaches for analyzing measurement models for ordered-categorical indicators. Last, we describe the analytical steps for testing the level of measurement.Note that the present paper focuses on questionnaires items. As for items in achievement or intelligence tests, the dichotomous Rasch model and the uni- or multidimensional polytomous Rasch model (Rasch, 1960/1980; see also Fischer, 1974) can be used to test hypotheses about the properties of the items (see Hohensinn & Kubinger, 2017).Questionnaire itemsA questionnaire item consists of an item stem, which contains the stimulus material to which respondents have to respond, and a system of response options (McDonald, 1999). There are numerous item types from which rating scale items are most frequently used in the social and behavior sciences. In a rating scale item, respondents are asked to answer a specific question (e.g., How much do you enjoy scientific writing?) by selecting an option out of a set of ordered categories (e.g., not at all - very little - somewhat - to a great extent). Numerical values are assigned to the item responses in accordance to the selected response options. The amount of information within the numbers assigned to the item responses is described in the level of measurement.Level of measurementAccording to Stevens (1960), four levels of measurement are distinguished: (1) nominal, (2) ordinal, (3) interval, and (4) ratio. The former two are labeled categorical and the latter two metric. More specifically, a categorical variable (see Agresti, 2002) comprises a set of categories which can be either unordered (i.e., numbers represent a qualitative distinction, e.g., girls and boys) or ordered (i.e., numbers represent some natural order, e.g., school grades). A metric variable, on the other hand, not only represents a meaningful order of numbers, but also meaningful intervals between numbers (i.e., number represent equal differences in the underlying variable, e.g., temperature in degrees Fahrenheit). In theory, the distinction between ordered-categorical and metric variables is clear. In practice, however, it is not clear if data resulting from scale items of a questionnaire are ordered-categorical or metric. As for rating scale items, it seems clear that the resulting data is ordered-categorical and not metric given ordered categories of response options. Nevertheless, scores on rating scale items are typically summed to derive a composite index of the construct of interest used in subsequent statistical analyses. The implicit assumption of this approach is that respondents perceive differences between adjacent levels of response categories as equidistant. …
20 citations
TL;DR: An inverse correlation between the hopelessness score and dopamine transporter availability in all basal ganglia was bilaterally found and a positive correlation was also found between hopelessness and dissociative symptoms.
Abstract: Background: Major depressive disorder (MDD) has different clinical presentations and is associated with neurobiological alterations. Hopelessness, anhedonia, and dissociation represent some of the most pervasive psychopathological symptoms that often lead to suicidal thoughts, attempts, and actions. To further research on the concept of depression endophenotypes, this study aimed to assess the possible relationships between hopelessness and other clinical and biological correlates (i.e., striatal dopaminergic dysfunction) in depressed patients. Methods: We recruited 51 subjects with MDD. All subjects underwent 123I-FP-CIT SPECT to assess striatal dopamine transporter (DAT) availability and a psychometric evaluation using the psychometric scale to assess depressive, anxious, dissociative, and hopelessness symptoms aside from suicidal ideation. Result: An inverse correlation between the hopelessness score and dopamine transporter availability in all basal ganglia was bilaterally found. (Right Putamen, r = -0.445, p < 0.01; Left Putamen, r = -0.454, p < 0.01; Right Caudate, r = -0.398, p < 0.01; Left Caudate, r = -0.467, p < 0.01) Moreover, a positive correlation was also found between hopelessness and dissociative symptoms. Conclusions: These results provide important evidence on the neurobiological and clinical correlates of different psychopathological symptoms of depression with potential implications in terms of devising more effective treatment programs.
19 citations
References
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TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...
76,383 citations
"Psychometric properties and measure..." refers methods in this paper
...In this paper, for the lack of alternatives, we will therefore rely on the Hu and Bentler [30] criteria of a CFI and TLI > ....
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...It is common practice to use the same criteria for evaluating goodness of fit for ordered categorical measures as for continuous ones, with the canonical reference being Hu and Bentler [30]....
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...In this paper, for the lack of alternatives, we will therefore rely on the Hu and Bentler [30] criteria of a CFI and TLI > .95 and a RMSEA .08 indicating good model fit....
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TL;DR: In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity, which makes it a useful clinical and research tool.
Abstract: OBJECTIVE: While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity.
26,004 citations
"Psychometric properties and measure..." refers background in this paper
...It consists of only two items, namely the depression scale of the PHQ-9 [24]....
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TL;DR: The aims behind the development of the lavaan package are explained, an overview of its most important features are given, and some examples to illustrate how lavaan works in practice are provided.
Abstract: Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software packages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the development of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.
14,401 citations
"Psychometric properties and measure..." refers methods in this paper
...Measurement invariance was tested using multiple group factor analysis, which was again performed using the lavaan package [28] for R statistics and WLSMV estimation....
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...CFA was performed using the lavaan package [28] for R statistics....
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TL;DR: In this article, the sensitivity of goodness of fit indexes to lack of measurement invariance at three commonly tested levels: factor loadings, intercepts, and residual variances was examined, and the most intriguing finding was that changes in fit statistics are affected by the interaction between the pattern of invariance and the proportion of invariant items.
Abstract: Two Monte Carlo studies were conducted to examine the sensitivity of goodness of fit indexes to lack of measurement invariance at 3 commonly tested levels: factor loadings, intercepts, and residual variances. Standardized root mean square residual (SRMR) appears to be more sensitive to lack of invariance in factor loadings than in intercepts or residual variances. Comparative fit index (CFI) and root mean square error of approximation (RMSEA) appear to be equally sensitive to all 3 types of lack of invariance. The most intriguing finding is that changes in fit statistics are affected by the interaction between the pattern of invariance and the proportion of invariant items: when the pattern of lack of invariance is uniform, the relation is nonmonotonic, whereas when the pattern of lack of invariance is mixed, the relation is monotonic. Unequal sample sizes affect changes across all 3 levels of invariance: Changes are bigger when sample sizes are equal rather than when they are unequal. Cutoff points for t...
6,202 citations
"Psychometric properties and measure..." refers background or methods in this paper
...The cut-off criteria by Chen [34] are exceeded only in the strict bi-factor model regarding depression status....
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...Chen [34] suggest the following cut-off criteria: a change of ≥ − .01 in CFI in addition to a change of ≥.015 in RMSEA indicates non-invariance....
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...Chen [34] suggest the following cut-off criteria: a change of ≥ − ....
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TL;DR: A scale designed to quantify hopelessness was administered to several diverse samples of patients to assess its psychometric properties and was found to have a high degree of internal consistency and showed a relatively high correlation with the clinical ratings of hopelessness and other self-administered measures of despair.
Abstract: A scale designed to quantify hopelessness was administered to several diverse samples of patients to assess its psychometric properties. This scale was found to have a high degree of internal consistency and showed a relatively high correlation with the clinical ratings of hopelessness and other self-administered measures of hopelessness. Furthermore, the scale was sensitive to changes in the patient's state of depression over time. An affective, a motivational, and a cognitive factor were extracted.
4,754 citations
"Psychometric properties and measure..." refers background or methods or result in this paper
...the model suggested by Beck and colleagues [20]: Feelings, about the future (1,5,6,13,15,19), Loss of motivation (2,3,9, 11,12,16,17,20); Future Expectations (4,7,8,10,14,18), χ(2) = 1499....
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...This could also be an explanation regarding the different explanatory value of the subfactors in the present study compared to the recent study by Boduszek and Dhingra [20] as the BHS mean in their student sample is considerably higher than in the present sample....
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...Table 4 shows the correlations of the three BHS factors as originally suggested by Beck and colleagues [20]....
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...First we analyzed, the original model by Beck and colleagues [20] [a three-factor model: Feelings, about the future (1,5,6,13,15,19), Loss of motivation (2,3,9, 11,12,16,17,20), Future Expectations (4,7,8,10,14,18)] and the one-dimensional model (all items loading on one overall hopelessness factor) as these are the models most discussed in the BHS literature....
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...The BHS [20] is a 20 item self-assessment instrument for the measurement of hopelessness....
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