Aging Increases Prosocial Motivation for Effort

Lockwood, Patricia L.; Abdurahman, Ayat; Gabay, Anthony S.; Drew, Daniel; Tamm, Marin; Husain, Masud; Apps, Matthew A. J.

doi:10.1177/0956797620975781

Cited by 61 publications

(88 citation statements)

References 50 publications

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“…To derive the best estimates of each individual’s willingness to invest effort, we fit participants’ choices to three functions that are commonly used to model effort discounting—linear, parabolic, and hyperbolic. These model comparisons revealed that participants’ choices were best fit by a parabolic pattern of effort discounting (AIC: parabolic = 4544, linear = 4787, hyperbolic = 5329; BIC: parabolic = 5042, linear = 5285, hyperbolic = 5826), which is consistent with previous work 36 , 52 , 53 , 64 , 69 , 70 . We then extracted the k -values for each participant from the winning model, and correlated them with ratings on the apathy and fatigue inventories.…”

Section: Resultssupporting

confidence: 88%

Heightened effort discounting is a common feature of both apathy and fatigue

Jurgelis

Chong

Atkins

et al. 2021

Sci Rep

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Apathy and fatigue have distinct aetiologies, yet can manifest in phenotypically similar ways. In particular, each can give rise to diminished goal-directed behaviour, which is often cited as a key characteristic of both traits. An important issue therefore is whether currently available approaches are capable of distinguishing between them. Here, we examined the relationship between commonly administered inventories of apathy and fatigue, and a measure of goal-directed activity that assesses the motivation to engage in effortful behaviour. 103 healthy adults completed self-report inventories on apathy (the Dimensional Apathy Scale), and fatigue (the Multidimensional Fatigue Inventory, and/or Modified Fatigue Impact Scale). In addition, all participants performed an effort discounting task, in which they made choices about their willingness to engage in physically effortful activity. Importantly, self-report ratings of apathy and fatigue were strongly correlated, suggesting that these inventories were insensitive to the fundamental differences between the two traits. Furthermore, greater effort discounting was strongly associated with higher ratings across all inventories, suggesting that a common feature of both traits is a lower motivation to engage in effortful behaviour. These results have significant implications for the assessment of both apathy and fatigue, particularly in clinical groups in which they commonly co-exist.

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Section: Resultssupporting

confidence: 88%

Heightened effort discounting is a common feature of both apathy and fatigue

Jurgelis

Chong

Atkins

et al. 2021

Sci Rep

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“…Do older people exert more prosocial effort than younger people (Lockwood et al, 2021)? Does high talker variability in training examples make it easier for non-native speakers to learn Mandarin tones (Dong et al, 2019)?…”

Section: Introductionmentioning

confidence: 99%

Bayes factors for logistic (mixed effect) models

Silvey¹,

Dienes²,

Wonnacott³

2021

Preprint

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In psychology, we often want to know whether or not an effect exists. The traditional way of answering this question is to use frequentist statistics. However, a significance test against a null hypothesis of no effect cannot distinguish between two states of affairs: evidence of absence of an effect, and absence of evidence for or against an effect. Bayes factors can make this distinction; however, uptake of Bayes factors in psychology has so far been low for two reasons. Firstly, they require researchers to specify the range of effect sizes their theory predicts. Researchers are often unsure about how to do this, leading to the use of inappropriate default values which may give misleading results. Secondly, many implementations of Bayes factors have a substantial technical learning curve. We present a case study and simulations demonstrating a simple method for generating a range of plausible effect sizes based on the output from frequentist mixed-effects models. Bayes factors calculated using these estimates provide intuitively reasonable results across a range of real effect sizes. The approach provides a solution to the problem of how to come up with principled estimates of effect size, and produces comparable results to a state-of-the-art method without requiring researchers to learn novel statistical software.

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“…After a literature study regarding several variables considered rational to be used as determining factors in prosocial action, model specifications were adopted in several studies. Some of the variables adopted are gender (Kamas & Preston, 2021;Rietveld et al, 2013), Age (Lockwood et al, 2021), Education (Umar et al, 2021;Smith, 2016;Rietveld et al, 2013, Employment (Smith, 2016, length of stay (Allen, 2018), and expenses (Clotfelter & Steuerle, 1981;James & Sharpe, 2007). This study includes the variable of family size that explains the number of dependents.…”

Section: Discussionmentioning

confidence: 99%

“…Someone with older age will have a higher prosocial value (Jin et al, 2021). Compared to younger people, older people are more willing to help others and exert the same power on themselves and others (Lockwood et al, 2021). This is based on the premise that older people become more prosocially motivated.…”

Section: Individual Factors In Prosocial Behaviormentioning

confidence: 99%

Charitable Behavior of Muslim in Indonesia during the COVID-19 Pandemic: A Tobit Model Analysis

Awirya

Piliyanti

Novita

2021

Shirkah

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The COVID-19 pandemic has caused a decline in social welfare. In such a situation, community philanthropy, including from the Muslim community, becomes critical. This study aims to explore the charitable behavior of Muslims in Indonesia during the COVID-19 pandemic. The Tobit regression was used to analyze data from online surveys to determine the pattern changes of donations during the pandemic as well as the factors affecting the amount of donation. This study uncovered that Zakat Management Organizations (BAZNAS and LAZ) were some of the main choices for distributing zakat and alms (sedekah) during the pandemic. It was found that the factors with a positive and significant effect on the probability of increasing the percentage of donations were education, length of stay, and expenses. The results of this study contribute to the policy of developing the Zakat Management Organization as institutions trusted by the community in distributing zakat funds. This study supports the fundraising of the zakat organizations in terms of offering valuable insights and clear description about the Indonesian people’s charitable behavior. More importantly, this study suggests that improving the quality of education is crucial to increase community awareness in performing Islamic philanthropy such as giving zakat, sedekah, and waqf.

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Aging Increases Prosocial Motivation for Effort

Cited by 61 publications

References 50 publications

Heightened effort discounting is a common feature of both apathy and fatigue

Heightened effort discounting is a common feature of both apathy and fatigue

Bayes factors for logistic (mixed effect) models

Charitable Behavior of Muslim in Indonesia during the COVID-19 Pandemic: A Tobit Model Analysis

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