To have a very rough overview and a comparison of the sample size Walitt uses to that of other studies, below is some very brief information of the various publications (HCs=Healthy Controls).
The original study:
Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia
Sample size: 61 HCs
Analysing the EEfRT:
Examining the reliability and validity of two versions of the Effort-Expenditure for Rewards Task (EEfRT) (Ohmann et al, 2022)
Sample size: 120 HCs for one experiment, 394 HCs for one experiment
“In Study 1, we tested 120 healthy participants to directly compare two versions of the EEfRT. In Study 2, we tested a larger sample of 394 healthy participants to further examine the original EEfRT…Our results indicate complex and sometimes inconsistent relations between different personality traits, task properties, and reward attributes.”
General studies:
Parabolic discounting of monetary rewards by physical effort (Hartmann et al, 2013) (uses a modified approach)
Sample size: 24 HCs
"Three different models in a binary choice task in which human participants had to squeeze a handgrip to earn monetary rewards: a linear, a hyperbolic, and a parabolic model. Participants repeatedly chose between a
no effort/low reward and a
high effort/high reward option. Consider the example of adding weight during a weight-lifting competition: The hyperbolic model predicts that adding 1 kg has a stronger impact on subjective experience at the beginning of the competition, when the lifters are well below their individual maximum. By contrast, the parabolic model predicts that the impact of adding 1 kg is larger toward the end of the competition, when lifters are close to their individual maximum and the linear model predicts the impact to be the same in both cases."
“The parabolic model clearly outperformed the other models on both the group and the individual level.”
This discussion might be of interest to people with ME/CFS and it isn’t a priori clear to me which model would be best suited for a fatiguing disease in which people pace. Other
studies have suggested that “Hand fatigue is suggested to occur across the 20-min EEfRT, as HE choice selection statistically decreases with trial number across the session (Hughes et al.,
2015; Ohmann et al.,
2018; Treadway et al.,
2009).”
Effect of failure/success feedback and the moderating influence of personality on reward motivation (Treadway et al, 2014)
Sample size: 131 HCs
“Results indicate that participants who received failure feedback relied more strongly on the reward magnitude when choosing whether to exert greater effort to obtain larger rewards, though this effect only held under conditions of significant uncertainty about whether the effort would be rewarded.”
In the intramural study more pwME receive failure feedback on the hard task. It might be worth looking at the above study.
Asymmetric frontal cortical activity predicts effort expenditure for reward (Hughes et al, 2014)
Sample size: 55 HCs
Interestingly the equipment failed here for one participant and they still included this person “The task ran for 20 min in which participants completed as many trials as possible, and the minimum number of trials completed by all participants during this time (46) was included in analyses. One participant completed only 23 trials due to equipment failure; however, their data were included in final analyses because preliminary investigation revealed that it did not significantly impact results.”
In this study gender didn’t affect results “Gender, age and experimenter were all non-significant predictors of task choice.” The also used a GEE model “A preliminary GEE model examined the effects of reward magnitude, reward probability, expected value (the magnitude × probability interaction), trial number (i.e. position of the trial in the sequence of 46 trials), gender, age and experimenter on task difficulty choice (see Model 1 in Table 1). Experimenter was included as a covariate because data collection was split between three researchers. Reward magnitude was converted to a categorical variable with three levels: low (<$2.30), medium ($2.31–$3.29) and high (>$3.30).”
Trait Anticipatory Pleasure Predicts Effort Expenditure for Reward (Treadway et al, 2015)
Sample size: 97 HCs
It seems that in this trial, to reduce the risk of certain strategies participants were given wrong information of the setup before starting to play “During verbal instruction, participants were informed that the EEfRT would run for 20 min and they would be paid 10% of their total winnings at the end of the experiment (
M = $5.86,
SD = 0.47). We modeled the likelihood of choosing the hard-task (vs. the easy-task) using generalized estimating equations (GEE) [55].”
They also performed an “EEfRT—manipulation check.”
Three people had invalid data “Valid EEfRT data were not obtained from three participants due to two instances of computer failure and one of noncompliance.” I’m not sure what noncompliance means but they do specify that “All remaining participants (
n = 94) chose a mixture of easy- and hard-tasks throughout the EEfRT (hard-task proportion
M = .53,
SD = .14), at a high completion rate (
M = 99.4%).”
Another thing that was done was “The total number of completed trials varied because participants performed the EEfRT for the same length of time (20 min) but differed in their profile of choices (range = 43 to 68,
M = 54.79). For consistency, we analyzed only the first 43 trials completed by all participants.”
They clearly state “There was also a significant negative effect of trial number, which is routinely observed in studies using the EEfRT [47,48], potentially reflecting a fatigue effect.”
Effort valuation and psychopathology in children and adults (Nguyen et al, 2019)
Sample size: 1215 children, 1044 adults (their parents)
“In children, significant interactions between reward sensitivity and sex were observed in association with anxiety and thought problems, specifically at low reward sensitivity levels. In adults, main effects of effort expenditure were seen in drug and alcohol abuse, where higher effort was associated with higher degrees of abuse.”
Since this is a large trial the population level averages might be more accurate.
“For the adult participant population, average proportion of hard task choices was 36.76%, and the average reward sensitivity beta- weight was 0.765. Mean percent completion rate among adults was 93.47%. On average, adult participants timed out in their choice of the hard v. easy task in 5.90% of trials. For the child participant population, average proportion of hard task choices was 58.34%, and the average reward sensitivity betaweight was 0.118. Mean percent completion rate among children was 87.27%. On average, child participants timed out in their choice of the hard v. easy task in 1.38% of trials.”
“For the adult participant population, average proportion of hard task choices was 36.76%, and the average reward sensitivity beta- weight was 0.765. Mean percent completion rate among adults was 93.47%. On average, adult participants timed out in their choice of the hard v. easy task in 5.90% of trials. For the child participant population, average proportion of hard task choices was 58.34%, and the average reward sensitivity betaweight was 0.118. Mean percent completion rate among children was 87.27%. On average, child participants timed out in their choice of the hard v. easy task in 1.38% of trials. “
“These results suggest that dysfunction in effort valuation may be a contributing factor rather than a driving force for a range of psychopathology and impairment in children and adults.”
They also have data on “Somatic Problems” if this is what Walitt proposes one may want to look into this data.
Exploring approach motivation: Correlating self-report, frontal asymmetry, and performance in the Effort Expenditure for Rewards Task (Hillmann et al, 2020)
Sample size: 49 HCs
This study tries to build upon the earlier study
Asymmetric frontal cortical activity predicts effort expenditure for reward (Hughes et al, 2014) et al from this list. They seem to not be able to reproduce those results from what I’ve gathered which once again shows the fragility of this method “Our third prediction was that higher LFA would correlate to higher trial completion rates and higher % HE trial selection in the EEfRT. As shown in Table
5, resting-state LFA did not correlate to performance variables in the 20-min EEfRT. There were, however, significant correlations between task-state LFA and EEfRT performance.”
