Automated Author ProfileGlaesmer, Heide
Glaesmer, Heide
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.5 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Childhood maltreatment has diverse, lifelong impact on morbidity and mortality. The Childhood Trauma Questionnaire (CTQ) is one of the most commonly used scales to assess and quantify these experiences and their impact. Curiously, despite very widespread use of the CTQ, scores on its Minimization-Denial (MD) subscale—originally designed to assess a positive response bias—are rarely reported. Hence, little is known about this measure. If response biases are either common or consequential, current practices of ignoring the MD scale deserve revision. Therewith, we designed a study to investigate 3 aspects of minimization, as defined by the CTQ’s MD scale: 1) its prevalence; 2) its latent structure; and finally 3) whether minimization moderates the CTQ’s discriminative validity in terms of distinguishing between psychiatric patients and community volunteers. Archival, item-level CTQ data from 24 multinational samples were combined for a total of 19,652 participants. Analyses indicated: 1) minimization is common; 2) minimization functions as a continuous construct; and 3) high MD scores attenuate the ability of the CTQ to distinguish between psychiatric patients and community volunteers. Overall, results suggest that a minimizing response bias—as detected by the MD subscale—has a small but significant moderating effect on the CTQ’s discriminative validity. Results also may suggest that some prior analyses of maltreatment rates or the effects of early maltreatment that have used the CTQ may have underestimated its incidence and impact. We caution researchers and clinicians about the widespread practice of using the CTQ without the MD or collecting MD data but failing to assess and control for its effects on outcomes or dependent variables.
Authors
- MacDonald, Kai ;
- L. Thomas, Michael ;
- F. Sciolla, Andres ;
- Schneider, Beacher ;
- Pappas, Katherine ;
- Bleijenberg, Gijs ;
- Bohus, Martin ;
- Bekh, Bradley ;
- Carpenter, Linda ;
- Carr, Alan ;
- Dannlowski, Udo ;
- Dorahy, Martin ;
- Fahlke, Claudia ;
- Finzi-Dottan, Ricky ;
- Karu, Tobi ;
- Gerdner, Arne ;
- Glaesmer, Heide ;
- Grabe, Hans Jörgen ;
- Heins, Marianne ;
- T Kenny, Dianna ;
- Kim, Daeho ;
- Knoop, Hans ;
- Lobbestael, Jill ;
- Lochner, Christine ;
- Lauritzen, Grethe ;
- Ravndal, Edle ;
- Riggs, Shelley ;
- Sar, Vedat ;
- Schäfer, Ingo ;
- Schlosser, Nicole ;
- L Schwandt, Melanie ;
- B Stein, Murray ;
- Subic-Wrana, Claudia ;
- Vogel, Mark ;
- Wingenfeld, Katja
Childhood maltreatment has diverse, lifelong impact on morbidity and mortality. The Childhood Trauma Questionnaire (CTQ) is one of the most commonly used scales to assess and quantify these experiences and their impact. Curiously, despite very widespread use of the CTQ, scores on its Minimization-Denial (MD) subscale—originally designed to assess a positive response bias—are rarely reported. Hence, little is known about this measure. If response biases are either common or consequential, current practices of ignoring the MD scale deserve revision. Therewith, we designed a study to investigate 3 aspects of minimization, as defined by the CTQ’s MD scale: 1) its prevalence; 2) its latent structure; and finally 3) whether minimization moderates the CTQ’s discriminative validity in terms of distinguishing between psychiatric patients and community volunteers. Archival, item-level CTQ data from 24 multinational samples were combined for a total of 19,652 participants. Analyses indicated: 1) minimization is common; 2) minimization functions as a continuous construct; and 3) high MD scores attenuate the ability of the CTQ to distinguish between psychiatric patients and community volunteers. Overall, results suggest that a minimizing response bias—as detected by the MD subscale—has a small but significant moderating effect on the CTQ’s discriminative validity. Results also may suggest that some prior analyses of maltreatment rates or the effects of early maltreatment that have used the CTQ may have underestimated its incidence and impact. We caution researchers and clinicians about the widespread practice of using the CTQ without the MD or collecting MD data but failing to assess and control for its effects on outcomes or dependent variables.
Authors
- MacDonald, Kai ;
- L. Thomas, Michael ;
- F. Sciolla, Andres ;
- Schneider, Beacher ;
- Pappas, Katherine ;
- Bleijenberg, Gijs ;
- Bohus, Martin ;
- Bekh, Bradley ;
- Carpenter, Linda ;
- Carr, Alan ;
- Dannlowski, Udo ;
- Dorahy, Martin ;
- Fahlke, Claudia ;
- Finzi-Dottan, Ricky ;
- Karu, Tobi ;
- Gerdner, Arne ;
- Glaesmer, Heide ;
- Grabe, Hans Jörgen ;
- Heins, Marianne ;
- T Kenny, Dianna ;
- Kim, Daeho ;
- Knoop, Hans ;
- Lobbestael, Jill ;
- Lochner, Christine ;
- Lauritzen, Grethe ;
- Ravndal, Edle ;
- Riggs, Shelley ;
- Sar, Vedat ;
- Schäfer, Ingo ;
- Schlosser, Nicole ;
- L Schwandt, Melanie ;
- B Stein, Murray ;
- Subic-Wrana, Claudia ;
- Vogel, Mark ;
- Wingenfeld, Katja
Background: There is no universally optimal cutoff score for identifying probable PTSD, which makes reliable PTSD diagnosis challenging not only across different populations but also in different settings. Reliable outcomes require tailoring cutoff scores to the population, intended use (clinical, research, or prevalence estimation), and appropriate statistical methods to ensure their validity. Objective: While previously little emphasis has been placed on thorough methodological evaluation and purpose-driven cutoff selection, this work addresses these gaps by evaluating optimal PCL-5 cutoff scores for clinical use, prevalence estimation, and research in a German-speaking clinical sample. Methods: Previously published data from 443 trauma-exposed individuals in Germany were re-analyzed for this purpose. PTSD was assessed using the PCL-5 and with CAPS-5 clinical interview. Optimal cutoffs were identified using ROC analysis, applying standard estimation methods and prioritising diagnostic utility based on specific objectives. Results: After evaluating various cutoff points for different purposes, we identified the following as most suitable for this sample: a cutoff of 34 for clinical use (sensitivity: 0.892, specificity: 0.645, PPV: 0.824, NPV: 0.763); 38 for prevalence estimation (sensitivity: 0.840, specificity: 0.703, PPV: 0.840, NPV: 0.703); and 42 or 43 for identifying clear-cut cases in research or resource-limited settings (sensitivity: 0.774–0.760, specificity: 0.742–0.761, PPV: 0.848–0.855, NPV: 0.639–0.631). The originally intended cutoffs of 31–33 yielded acceptable to excellent diagnostic utility parameters but were not identified as optimal for any specific purpose. Conclusion: This study highlights the variability in optimal PCL-5 cutoffs, linking selection to specific clinical or research aims. It provides validated cutoffs for PTSD prevalence in a German clinical sample, with limitations regarding generalizability to lower-prevalence populations. Future research should refine cutoffs for diverse populations and improve diagnostic precision. Context matters: PTSD screening requires purpose-specific cutoff scores rather than a universal threshold.Validated cutoffs: this study determines optimal PCL-5 scores for clinical screening, prevalence estimation, and research.Methodological refinement: this study applies a purpose-driven approach to determining PTSD cutoff scores, emphasising statistical rigour and diagnostic utility. Context matters: PTSD screening requires purpose-specific cutoff scores rather than a universal threshold. Validated cutoffs: this study determines optimal PCL-5 scores for clinical screening, prevalence estimation, and research. Methodological refinement: this study applies a purpose-driven approach to determining PTSD cutoff scores, emphasising statistical rigour and diagnostic utility.
Authors
- Pettrich, Amelie ;
- Schellong, Julia ;
- Dyer, Anne ;
- Ehring, Thomas ;
- Knaevelsrud, Christine ;
- Krüger-Gottschalk, Antje ;
- Nesterko, Yuriy ;
- Schäfer, Ingo ;
- Glaesmer, Heide
Background: There is no universally optimal cutoff score for identifying probable PTSD, which makes reliable PTSD diagnosis challenging not only across different populations but also in different settings. Reliable outcomes require tailoring cutoff scores to the population, intended use (clinical, research, or prevalence estimation), and appropriate statistical methods to ensure their validity. Objective: While previously little emphasis has been placed on thorough methodological evaluation and purpose-driven cutoff selection, this work addresses these gaps by evaluating optimal PCL-5 cutoff scores for clinical use, prevalence estimation, and research in a German-speaking clinical sample. Methods: Previously published data from 443 trauma-exposed individuals in Germany were re-analyzed for this purpose. PTSD was assessed using the PCL-5 and with CAPS-5 clinical interview. Optimal cutoffs were identified using ROC analysis, applying standard estimation methods and prioritising diagnostic utility based on specific objectives. Results: After evaluating various cutoff points for different purposes, we identified the following as most suitable for this sample: a cutoff of 34 for clinical use (sensitivity: 0.892, specificity: 0.645, PPV: 0.824, NPV: 0.763); 38 for prevalence estimation (sensitivity: 0.840, specificity: 0.703, PPV: 0.840, NPV: 0.703); and 42 or 43 for identifying clear-cut cases in research or resource-limited settings (sensitivity: 0.774–0.760, specificity: 0.742–0.761, PPV: 0.848–0.855, NPV: 0.639–0.631). The originally intended cutoffs of 31–33 yielded acceptable to excellent diagnostic utility parameters but were not identified as optimal for any specific purpose. Conclusion: This study highlights the variability in optimal PCL-5 cutoffs, linking selection to specific clinical or research aims. It provides validated cutoffs for PTSD prevalence in a German clinical sample, with limitations regarding generalizability to lower-prevalence populations. Future research should refine cutoffs for diverse populations and improve diagnostic precision. Context matters: PTSD screening requires purpose-specific cutoff scores rather than a universal threshold.Validated cutoffs: this study determines optimal PCL-5 scores for clinical screening, prevalence estimation, and research.Methodological refinement: this study applies a purpose-driven approach to determining PTSD cutoff scores, emphasising statistical rigour and diagnostic utility. Context matters: PTSD screening requires purpose-specific cutoff scores rather than a universal threshold. Validated cutoffs: this study determines optimal PCL-5 scores for clinical screening, prevalence estimation, and research. Methodological refinement: this study applies a purpose-driven approach to determining PTSD cutoff scores, emphasising statistical rigour and diagnostic utility.
Authors
- Pettrich, Amelie ;
- Schellong, Julia ;
- Dyer, Anne ;
- Ehring, Thomas ;
- Knaevelsrud, Christine ;
- Krüger-Gottschalk, Antje ;
- Nesterko, Yuriy ;
- Schäfer, Ingo ;
- Glaesmer, Heide