The Psychological Impact of Cancer (PIC) Scale: development and comparative psychometric testing against the Mini-MAC Scale in UK and Australian cancer survivors

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Abstract

Background: Clinicians and researchers make considerable use of both the Mental Adjustment to Cancer (MAC) Scale, and the shorter Mini-MAC, to measure psychological adjustment in cancer patients. The length of the scale is problematic when used clinically, and its psychometric properties have been criticized. This article presents two studies leading to the development of a novel scale, the Psychological Impact of Cancer (PIC) Scale, using items drawn from the MAC. Methods: Study 1 used standard item-reduction techniques to shorten the Mini-MAC in a sample of 160 cancer patients of mixed diagnosis, recruited an average 46 days post-diagnosis. This resulted in a 12-item scale with a 4-factor structure, similar to that derived from a 2012 re-analysis of the Mini-MAC. Study 2 presents confirmatory factor analysis (CFA) of this new measure and tests its construct validity and test–retest reliability in a sample of 183 mixed cancer survivors. Results: This study indicated that the shorter scale performed well on CFA indicators (RMSEA = .083; ECVI = .923; PNFI = .604; AGFI = .857) and tests of internal consistency (all >.623), and comparable concurrent validity with longer versions. The 4 factors were labeled cognitive distress, cognitive avoidance, emotional distress, and fighting spirit. Conclusions: Given its shorter length and acceptable psychometrics, the PIC offers a useful clinical and research tool to assess the psychological impact of cancer. Psychometric properties of one subscale (fighting spirit) remain poor, but no worse than in the original scale; directions for further development of the scale are described.

Original languageEnglish
Pages (from-to)1-7
JournalJournal of Psychosocial Oncology Research & Practice
Volume12
Issue number2
DOIs
Publication statusPublished - 30 Sept 2019

Keywords

  • Adjustment
  • Cancer
  • Distress
  • Factor Structure
  • Measurement
  • Psychometric Validation
  • Quality of Life
  • Reliability

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