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Original Articles

Using warnings to reduce categorical false memories in younger and older adults

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Pages 853-863 | Received 14 Jan 2015, Accepted 01 Jun 2015, Published online: 14 Aug 2015
 

Abstract

Warnings about memory errors can reduce their incidence, although past work has largely focused on associative memory errors. The current study sought to explore whether warnings could be tailored to specifically reduce false recall of categorical information in both younger and older populations. Before encoding word pairs designed to induce categorical false memories, half of the younger and older participants were warned to avoid committing these types of memory errors. Older adults who received a warning committed fewer categorical memory errors, as well as other types of semantic memory errors, than those who did not receive a warning. In contrast, young adults' memory errors did not differ for the warning versus no-warning groups. Our findings provide evidence for the effectiveness of warnings at reducing categorical memory errors in older adults, perhaps by supporting source monitoring, reduction in reliance on gist traces, or through effective metacognitive strategies.

ACKNOWLEDGEMENTS

The authors thank Pete Millar, Lauryn Garner and Ryn Flaherty for research assistance.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

ORCID

Angela H. Gutchess http://orcid.org/0000-0003-3047-5907

Notes

1Two additional participants (one from each warning condition) were not included in the analyses because they did not commit any memory errors. Data obtained from younger adult participants in no-warning condition have been published by Schwartz et al. (Citation2014). Instructions to participants were identical to the prior study, with the warning added for participants in that condition. The raw data were rescored for the current study to ensure consistency in coding across conditions.

Additional information

Funding

Portions of this research were supported by NSF [grant number BCS-1,147,707] and Brandeis University.

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