Strive to Win or Not to Lose? Age-Related Differences in Framing Effects on Effort-Based Decision-Making

Abstract

Objectives This study sought to assess how framing effects modulate age-related differences in effort-based decision-making. Consistent with the Selection, Optimization, and Compensation (SOC) model’s loss prevention account of aging, we predicted that older adults would be more willing to select high-effort options in loss contexts than gain contexts. Method Older and younger adults completed the Effort Expenditure for Rewards Task (EEfRT) in either a gain or loss context. The EEfRT is an effort-based decision-making paradigm in which participants choose between a low-effort, ‘easy’ option and a high-effort, ‘hard’ option for several trials. The probability and value of an outcome varies on a trial-by-trial basis. Results The results supported our prediction and the SOC model. Older adults chose more high-effort, difficult options in loss frames than gain frames. Older adults also chose more low-effort, easy options than younger adults in gain contexts, but did not differ from younger adults in loss contexts. Discussion These findings demonstrate that framing effects impact older adults’ effort-based decisions. Older adults appear willing to incur a greater ‘cost’ in the form of effort to prevent a loss than to attain a reward.

Losses Motivate Cognitive Effort More Than Gains in Effort-Based Decision Making and Performance

“…One study found that, in agreement with the current findings, people were more willing to invest the physical effort to avoid losses, compared to pursuing gains (Chen et al, 2020 ). Other studies, however, did not find such asymmetry (Nishiyama, 2016 ; Lockwood et al, 2017 ) or only in some populations (i.e., elderly, Byrne and Ghaiumy Anaraky, 2019 ). Importantly, the current effects were not confounded by delay or probability discounting, as these factors were strictly controlled.…”

“…Very little research has been done on how losses affect the willingness to exert effort. The few studies exploring loss aversion in effort-based decision making have yielded inconclusive findings (Nishiyama, 2016 ; Lockwood et al, 2017 ; Byrne and Ghaiumy Anaraky, 2019 ; O’Brien and Ahmed, 2019 ; Chen et al, 2020 ). Similarly, studies examining cognitive performance under gain and loss incentives have not consistently found evidence for loss aversion (i.e., better performance and/or higher effort in loss incentive conditions compared to gains; Yechiam and Hochman, 2013 ; Belayachi et al, 2015 ; Paschke et al, 2015 ; Carsten et al, 2019 ).…”

Risk-taking unmasked: Using risky choice and temporal discounting to explain COVID-19 preventative behaviors

“…The average proportion of risky gambles across all gambling types was computed for regression analyses and used as the primary analysis variable for this task. Additionally, following previous research using the Cups Task and similar risky choice paradigms [8,[63][64][65][66][67][68][69][70], the proportion of risky choices for each gamble type (risky advantageous, risky equal, and risky disadvantageous) was computed and used in follow-up analyses; this provides further information about whether sensitivity to expected values, as reflected by differential risk-taking in advantageous compared to disadvantageous decision contexts, influences the outcome variables.…”

Opposite reactions to loss incentive by young and older adults: Insights from diffusion modeling

“…Thus, motivation-shift theory proposes that while young adults are more motivated to achieve gains, older adults are more motivated to avoid losses (Best & Freund, 2018;Freund & Ebner, 2005). However, while motivation-shift theory may help explain older adults' preferences and choices in some situations (Byrne & Ghaiumy Anaraky, 2020;Ebner et al, 2006;Frank & Kong, 2008), there is little evidence that loss incentives differentially improve older adults' performance.…”