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Structural validation of the Self-Compassion Scale with a German general population sample.

Adina CoroiuLinda KwakkenbosChelsea MoranBrett ThombsCornelia AlbaniSophia BourkasMarkus ZengerElmar BrahlerAnnett Körner
Published in: PloS one (2018)
The main results of this study are that, among the German general population, six SCS factors and two SCS factors fit the data reasonably well. While six factors can be modelled, the three negative factors and the three positive factors, respectively, did not reflect reliable or meaningful variance beyond the two summative positive and negative item factors. As such, we recommend the use of two subscale scores to capture a positive factor and a negative factor when administering the German SCS to general population samples and we strongly advise against the use of a total score across all SCS items.
Keyphrases
  • machine learning
  • electronic health record
  • big data