Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model
The current study presents a reliability generalization of the Problem-Solving Inventory (PSI), utilizing the comprehensive Reliability Generalization Meta-Analysis (REGEMA) checklist to ensure a thorough and methodical approach. The PSI, a tool designed to assess individuals’ perceptions of their p...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-08-01
|
| Series: | SAGE Open |
| Online Access: | https://doi.org/10.1177/21582440251361978 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849330545998168064 |
|---|---|
| author | Tyrone B. Pretorius Anita Padmanabhanunni |
| author_facet | Tyrone B. Pretorius Anita Padmanabhanunni |
| author_sort | Tyrone B. Pretorius |
| collection | DOAJ |
| description | The current study presents a reliability generalization of the Problem-Solving Inventory (PSI), utilizing the comprehensive Reliability Generalization Meta-Analysis (REGEMA) checklist to ensure a thorough and methodical approach. The PSI, a tool designed to assess individuals’ perceptions of their problem-solving abilities, consists of a total scale and three subscales: problem-solving confidence (PSC), approach-avoidance style (AAS), and personal control (PC). Each subscale evaluates distinct facets of problem-solving appraisal. From an initial pool of 2,196 articles, 123 met the inclusion criteria and were analyzed using a varying-coefficient model to account for the dynamic nature of reliability coefficients across studies. The meta-analysis revealed that the PSI total scores consistently demonstrated excellent reliability, as did the PSC and AAS subscales. Key predictors of reliability for the PSI and PSC included standard deviation, mean age of the sample, and sample type, whereas mean age and the language of inventory administration were key predictors for the PC subscale. The AAS scale’s reliability was notably influenced by the standard deviation of the scores, sample size, and proportion of women in the sample. These insights underscore the critical role of demographic and methodological variables in evaluating an instrument’s reliability across varied contexts. The study findings reinforce the importance of a nuanced approach to psychological measurement with an awareness of how demographic, sample, and cultural factors influence the reliability of psychometric tools. |
| format | Article |
| id | doaj-art-affd5350552d472abd4f0f5063f0df55 |
| institution | Kabale University |
| issn | 2158-2440 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | SAGE Open |
| spelling | doaj-art-affd5350552d472abd4f0f5063f0df552025-08-20T03:46:53ZengSAGE PublishingSAGE Open2158-24402025-08-011510.1177/21582440251361978Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient ModelTyrone B. Pretorius0Anita Padmanabhanunni1University of the Western Cape, Cape Town, South AfricaUniversity of the Western Cape, Cape Town, South AfricaThe current study presents a reliability generalization of the Problem-Solving Inventory (PSI), utilizing the comprehensive Reliability Generalization Meta-Analysis (REGEMA) checklist to ensure a thorough and methodical approach. The PSI, a tool designed to assess individuals’ perceptions of their problem-solving abilities, consists of a total scale and three subscales: problem-solving confidence (PSC), approach-avoidance style (AAS), and personal control (PC). Each subscale evaluates distinct facets of problem-solving appraisal. From an initial pool of 2,196 articles, 123 met the inclusion criteria and were analyzed using a varying-coefficient model to account for the dynamic nature of reliability coefficients across studies. The meta-analysis revealed that the PSI total scores consistently demonstrated excellent reliability, as did the PSC and AAS subscales. Key predictors of reliability for the PSI and PSC included standard deviation, mean age of the sample, and sample type, whereas mean age and the language of inventory administration were key predictors for the PC subscale. The AAS scale’s reliability was notably influenced by the standard deviation of the scores, sample size, and proportion of women in the sample. These insights underscore the critical role of demographic and methodological variables in evaluating an instrument’s reliability across varied contexts. The study findings reinforce the importance of a nuanced approach to psychological measurement with an awareness of how demographic, sample, and cultural factors influence the reliability of psychometric tools.https://doi.org/10.1177/21582440251361978 |
| spellingShingle | Tyrone B. Pretorius Anita Padmanabhanunni Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model SAGE Open |
| title | Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model |
| title_full | Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model |
| title_fullStr | Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model |
| title_full_unstemmed | Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model |
| title_short | Reliability Generalization of the Problem Solving Inventory: A Meta-Analysis of Cronbach’s Alpha With a Varying-Coefficient Model |
| title_sort | reliability generalization of the problem solving inventory a meta analysis of cronbach s alpha with a varying coefficient model |
| url | https://doi.org/10.1177/21582440251361978 |
| work_keys_str_mv | AT tyronebpretorius reliabilitygeneralizationoftheproblemsolvinginventoryametaanalysisofcronbachsalphawithavaryingcoefficientmodel AT anitapadmanabhanunni reliabilitygeneralizationoftheproblemsolvinginventoryametaanalysisofcronbachsalphawithavaryingcoefficientmodel |