Use of best–worst scaling to estimate the magnitude of stressful life events in older adults

Ganchimeg Zorigt, Nomin Enkh-Amgalan, Tsung Yu

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Aim: The magnitude of stressful life events can be measured by using rating scales such as the Social Readjustment Rating Scale. This study aimed to estimate the magnitude of stressful life events by using a best–worst scaling approach in a sample of community-dwelling older persons in Taiwan. Methods: Participants aged 55 years or older were asked to rate the stressfulness of 11 life events on a scale from 0 to 10 and the best–worst scaling. We used the case one (object case) best–worst scaling design: each task on a list of events was presented to participants, and they were asked to indicate the events that they considered most and least stressful. Results: A total of 61 persons (66% women) provided valid responses for analysis; the mean age was 64.8 ± 8.6 years. For best–worst scaling, ‘major illness of family member’ (mean best-minus-worst score = 128) was rated the most stressful, and ‘sexual difficulties’ was rated the least stressful (mean best-minus-worst score = −153). For the rating scale, ‘major personal illness’ was rated the most stressful (mean rating = 6.95), and ‘sexual difficulties’ was again the least stressful (mean rating = 2.05). Rankings of events based on both methods were similar but were different from ratings based on the Social Readjustment Rating Scale. Conclusion: The current study explored using BWS to estimate the magnitude of stressful life events. The magnitude of events estimated in our study was found to differ from the magnitude estimated previously by some common scales for assessing stressful life events.

Original languageEnglish
Pages (from-to)212-218
Number of pages7
JournalPsychogeriatrics
Volume19
Issue number3
DOIs
Publication statusPublished - 2019 May

All Science Journal Classification (ASJC) codes

  • Gerontology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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