Data from: Psychological Pain in Suicidal and Non-Suicidal Populations: Findings from the Translated German Mee-Bunney Psychological Pain Assessment Scale (Summary and Raw Trial-Level Data)

Published: 17 October 2025| Version 1 | DOI: 10.17632/ht5p2dm3v6.1
Contributors:
Lara Marie Aschenbrenner, Stella Brogna,
, Adriana Frei, Marie-Anna Sedlinská,
,
,
,
,

Description

This repository accompanies the article "Psychological Pain in Suicidal and Non-Suicidal Populations: Findings from the Translated German Mee-Bunney Psychological Pain Assessment Scale": Aschenbrenner, L. M., Brogna, S., Teismann, T., Frei, A., Sedlinská, M. A., Glaesmer, H., Forkmann, T., Walther, S., Ehnvall, A., & Gysin-Maillart, A. (2025). Psychological Pain in Suicidal and Non-Suicidal Populations: Findings from the Translated German Mee-Bunney Psychological Pain Assessment Scale. Archives of suicide research : official journal of the International Academy for Suicide Research, 1–17. Advance online publication. https://doi.org/10.1080/13811118.2025.2573059 The research was designed to test two primary hypotheses: (1) that psychological pain levels differ meaningfully between groups with varying histories of suicidal ideation and behaviour (i.e., attempters, ideators, non-suicidal psychiatric patients, and non-clinical controls), and (2) that the German version of the MBPPAS demonstrates sound psychometric properties, including internal consistency and construct validity. The data were collected as part of a cross-sectional study involving psychiatric inpatients and non-clinical controls. Participants completed a battery of self-report questionnaires, including the German-translated MBPPAS, along with established measures of depression and suicidal ideation. In the dataset, participant IDs were anonymised using randomly generated numbers to ensure privacy. The dataset includes the following anonymised individual-level data on: * Randomised numbers as placeholders for IDs * Demographic variables, i.e., age and gender * Group classification (based on suicidal behaviour and ideation history) * Sample * MBPPAS at item level and its sum score * Sum scores on other relevant psychological scales (SIBS, SBQ-R, BDI-II, BSS, PMH) This dataset is provided to enable replication of the analyses reported in the associated publication. File Included: `rawdata_pp_summarised.sav` – SPSS dataset

Files

Steps to reproduce

1. Data Preparation * Ensure the data file `rawdata_pp_summarised.sav` is saved to your working directory. * Open the file in SPSS (v29.0.1.0 or later), or use a compatible statistical environment (e.g., R with the `haven` package or Python with `pyreadstat`) to load the SPSS file. 2. Group Comparisons (SPSS) * To examine differences across four groups (SUAT, SUID, CLIN, HLTH) in psychological pain: * `Analyze` → `Compare Means` → `One-Way ANOVA` * Dependent variable: `mbppas_sum` * Factor: `group` * Post-hoc: Dunn-Bonferroni (run separately). * Test sample differences (e.g., age, gender) between sample 1 and sample 2 using: * `Analyze` → `Nonparametric Tests` → `Independent Samples` (for continuous variables using Mann-Whitney U) 3. Confirmatory Factor Analysis (R) * Use the `lavaan` package in R (version 0.6-13 or newer). # Load data data <- read_sav("rawdata_pp_summarised.sav") # Specify 1-factor model model <- 'MBPPAS =~ mbppas_1 + mbppas_2 + ... + mbppas_10' # Fit model using Maximum Likelihood Estimation fit <- cfa(model, data = data, missing = "fiml") # Evaluate fit summary(fit, fit.measures = TRUE, standardized = TRUE) # Optional: inspect modification indices to improve model fit modindices(fit, sort = TRUE, minimum.value = 10) 4. Internal Consistency (SPSS or R) * SPSS: `Analyze` → `Scale` → `Reliability Analysis` * Input all 10 MBPPAS items * Check Cronbach’s alpha, "if item deleted", and item-total correlations. * R (optional): * Use the `psych` package. alpha(data[, c("mbppas_1", "mbppas_2", ..., "mbppas_10")]) 5. Convergent Validity (SPSS) * Use Spearman correlations: `Analyze` → `Correlate` → `Bivariate` * Select MBPPAS sum score and scores from BDI-II, PMH, SBQ-R, BSS, and SIBS * Check 'Spearman' option. 6. Regression Analyses (SPSS) * `Analyze` → `Regression` → `Linear` * Dependent: SBQ-R, BSS, or SIBS * Block 1: BDI-II total score * Block 2: MBPPAS total score * Compare AIC values (may need to export models and compute AIC in R for comparison)

Institutions

  • Universitat Duisburg-Essen
  • Lunds Universitet
  • Universitat Leipzig
  • Ruhr-Universitat Bochum
  • Universitat Bern
  • Goteborgs Universitet
  • Universitatsklinikum Wurzburg

Categories

Psychology, Questionnaire, Suicide, Suicide Risk, Psychometrics, Suicidal Behavior, Clinical Pain

Licence