Gender Impacts the Relationship between Mood Disorder Symptoms and Effortful Avoidance Performance

Brandon J. Forys; Ryan J. Tomm; Dayana Stamboliyska; Alex R. Terpstra; Luke Clark; Trisha Chakrabarty; Stan B. Floresco; Rebecca M. Todd

doi:10.1523/ENEURO.0239-22.2023

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Figure 1.
Trial layout diagram. A diagram of the active and inhibitory avoidance and reward-seeking tasks. In the avoidance task (A), after an interstimulus interval (ISI) with a fixation cross onscreen, participants were presented with a cue associated with active or inhibitory avoidance. For the active avoidance cue, participants had to respond with repeated spacebar presses to avoid hearing an aversive sound. For the inhibitory avoidance cue, participants had to withhold responding to avoid hearing an aversive sound. In the reward-seeking task (B), after the ISI, participants were presented with a cue associated with active or inhibitory reward-seeking. For the active reward-seeking cue, participants had to respond with repeated spacebar presses to obtain points toward a monetary reward. For the inhibitory reward-seeking cue, participants had to withhold responding to obtain points toward a monetary reward. ms = milliseconds.
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Figure 2.
Avoidance demographics. Distribution of anxiety (BAI) and depression (BDI) scores by gender and sample. Proportion scores are scores divided by total possible score. BAI = Beck Anxiety Inventory, BDI = Beck Depression Inventory II.
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Figure 3.
Linear model significant effects for sensitivity in avoidance. A, Gender interacted with anxiety scores (BAI proportion scores) to explain sensitivity (d′ ) in the avoidance task. B, Gender interacted with depression scores (BDI proportion scores) to explain sensitivity (d′ ) in the avoidance task. BAI = Beck Anxiety Inventory. BDI = Beck Depression Inventory II. Proportion scores are scores divided by total possible score.
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Figure 4.
Avoidance effort deployment. A, Multilevel model significant effects and interactions for effort in avoidance. Effort decreased relative to criterion as the avoidance task progressed, an effect that (B) interacted with anxiety scores (BAI) and gender. Proportion scores are scores divided by total possible score.
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Figure 5.
Reward-seeking demographics. Distribution of anxiety (BAI) and depressive (BDI) scores by gender and sample. Proportion scores are scores divided by total possible score. BAI = Beck Anxiety Inventory, BDI = Beck Depression Inventory II.
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Figure 6.
Linear model significant effects for sensitivity in reward-seeking. Gender explained sensitivity (d′ ) in the reward-seeking task. BAI = Beck Anxiety Inventory. Proportion scores are scores divided by total possible score.
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Figure 7.
Reward-seeking effort deployment. A, Multilevel model significant effects and interactions for effort in reward-seeking. Effort decreased relative to criterion as the reward-seeking task progressed, an effect that (B) interacted with anxiety scores (BAI) and gender. Proportion scores are scores divided by total possible score.

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Table 1

Demographic information for all participants

Study	N recruited	N analyzed	N female	N male	N other	M age	Range age
1A (avoidance, undergraduate)	357	272	174	86	12	20.42	17–32
1B (avoidance, paid global)	310	272	87	176	9	24.06	18–57
2A (reward-seeking, undergraduate)	114	36	28	8	0	20.67	18–26
2B (reward-seeking, paid global)	309	274	78	180	16	25.18	18–62

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Table 2
Mean and SD Beck Depression Inventory II (BDI) and Beck Anxiety Inventory (BAI) proportion scores (score divided by total possible score)
Task Gender M BDIprop SD BDIprop M BAIprop SD BAIprop
Avoidance Female 0.30 0.19 0.29 0.22
Male 0.23 0.16 0.23 0.19
Reward-seeking Female 0.29 0.19 0.28 0.21
Male 0.26 0.17 0.22 0.17

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Table 3

Linear model analysis coefficients and SEs for sensitivity (d ′) in avoidance

	Linear model: BAI pred. sensitivity (d′)
(Intercept)	2.46*** (0.09)
BAI (prop. score)	−0.94 *** (0.23)
Gender	−0.07 1 (0.11)
Sample	−0.17 (0.11)
BAI (prop. score) × Gender	0.74* (0.31)
BAI (prop. score) × Sample	0.73* (0.29)
Gender × Sample	0.06 (0.15)
BAI (prop. score) × Gender × Sample	−0.69 (0.46)
Num. obs.	523
R²	0.050
R² adj.	0.037
AIC	769.8
BIC	808.2
Log. Lik.	−375.910
F	3.893
RMSE	0.50

BAI (prop. score) = anxiety score on the Beck Anxiety Inventory. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
*p < 0.05, ***p < 0.001.

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Table 4

Linear model analysis coefficients and SEs for sensitivity (d ′) in avoidance

	Linear model: BDI pred. sensitivity (d′)
(Intercept)	2.52*** (0.11)
BDI (prop. score)	−1.09 *** (0.29)
Gender	−0.13 1 (0.13)
Sample	−0.29 * (0.13)
BDI (prop. score) × Gender	0.88* (0.38)
BDI (prop. score) × Sample	1.11** (0.35)
Gender × Sample	0.16 (0.17)
BDI (prop. score) × Gender × Sample	−0.93 + (0.53)
Num. obs.	523
R²	0.042
R² adj.	0.029
AIC	774.1
BIC	812.4
Log. Lik.	−378.038
F	3.265
RMSE	0.50

BDI (prop. score) = depression score on the Beck Depression Inventory II. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
+p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001.

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Table 5

Multilevel model analysis coefficients and SEs for effort in avoidance

	Multilevel model: BAI pred. effort
(Intercept)	5.74*** (0.26)
BAI (prop. score)	−0.63 (0.68)
Block	−0.91 ***
	1 (0.02)
Gender	0.29 (0.32)
Sample	−0.42 (0.33)
BAI (prop. score) × Block	0.16*** (0.05)
BAI (prop. score) × Gender	0.97 (0.92)
Block × Gender	0.04* (0.02)
BAI (prop. score) × Sample	−0.65 (0.87)
Block × Sample	−0.01 (0.03)
Gender × Sample	−0.19 (0.44)
BAI (prop. score) × Block × Gender	−0.19 ** (0.06)
BAI (prop. score) × Block × Sample	−0.06 (0.07)
BAI (prop. score) × Gender × Sample	0.94 (1.36)
Block × Gender × Sample	0.04 (0.04)
BAI (prop. score) × Block × Gender × Sample	−0.08 (0.11)
SD (intercept participant)	1.42
SD (observations)	1.91
Num. obs.	52,261
R² marg.	0.289
R² cond.	0.542
AIC	218,248.5
BIC	218,408.1
ICC	0.4
RMSE	1.90

BAI (prop. score) = anxiety score on the Beck Anxiety Inventory. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, ICC = intraclass correlation, RMSE = root mean squared error.
*p < 0.05, **p < 0.01, ***p < 0.001.

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Table 6

Multilevel model analysis coefficients and SEs for effort in avoidance

	Multilevel model: BDI pred. effort
(Intercept)	5.67*** (0.32)
BDI (prop. score)	−0.41 (0.86)
Block	−0.92 *** (0.02)
Gender	0.24
	1 (0.38)
Sample	−0.40 (0.38)
BDI (prop. score) × Block	0.19** (0.06)
BDI (prop. score) × Gender	1.21 (1.11)
Block × Gender	0.08**
	1 (0.03)
BDI (prop. score) × Sample	−0.70 (1.04)
Block × Sample	0.01 (0.03)
Gender × Sample	−0.31 (0.50)
BDI (prop. score) × Block × Gender	−0.34 ***
	1 (0.08)
BDI (prop. score) × Block × Sample	−0.12 (0.08)
BDI (prop. score) × Gender × Sample	1.54 (1.59)
Block × Gender × Sample	−0.01 (0.04)
BDI (prop. score) × Block × Gender × Sample	0.12 (0.13)
SD (intercept participant)	1.42
SD (observations)	1.91
Num. obs.	52,261
R² marg.	0.289
R² cond.	0.542
AIC	218,241.9
BIC	218,401.4
ICC	0.4
RMSE	1.90

BDI (prop. score) = depression score on the Beck Depression Inventory II. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, ICC = intraclass correlation, RMSE = root mean squared error.
**p < 0.01, ***p < 0.001.

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Table 7

Linear model analysis coefficients and SEs for break point in avoidance

	Linear model: BAI pred. sensitivity (d′)
(Intercept)	133.41*** (7.78)
BAI (prop. score)	−18.55 (20.00)
Gender	12.52 (9.52)
Sample	−5.39 (9.53)
BAI (prop. score) × Gender	42.11 (27.05)
BAI (prop. score) × Sample	−12.37 (25.25)
Gender × Sample	5.42 (12.91)
BAI (prop. score) × Gender × Sample	−30.85 (39.58)
Num. obs.	523
R²	0.105
R² adj.	0.093
AIC	5440.4
BIC	5478.7
Log. Lik.	−2711.198
F	8.668
RMSE	43.16

BAI (prop. score) = anxiety score on the Beck Anxiety Inventory. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
***p < 0.001.

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Table 8

Linear model analysis coefficients and SEs for break point in avoidance

	Linear model: BDI pred. Sensitivity (d′)
(Intercept)	136.99*** (9.46)
BDI (prop. score)	−28.79 (25.30)
Gender	11.13 (11.28)
Sample	−10.46 (11.10)
BDI (prop. score) × Gender	42.87 (32.83)
BDI (prop. score) × Sample	2.96 (30.35)
Gender × Sample	0.59 (14.72)
BDI (prop. score) × Gender × Sample	1.39 (46.40)
Num. obs.	523
R²	0.101
R² adj.	0.089
AIC	5443.1
BIC	5481.4
Log. Lik.	−2712.530
F	8.250
RMSE	43.27

BDI (prop. score) = depression score on the Beck Depression Inventory II. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
***p < 0.001.

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Table 9

Linear model analysis coefficients and SEs for sensitivity (d ′) in reward-seeking

	Linear model: BAI pred. sensitivity (d′)
(Intercept)	3.12*** (0.15)
BAI (prop. score)	−0.16 (0.40)
Gender	0.34* (0.17)
Sample	0.15 (0.27)
BAI (prop. score) × Gender	−0.75 (0.52)
BAI (prop. score) × Sample	−0.48 (0.84)
Gender × Sample	−0.53 (0.42)
BAI (prop. score) × Gender × Sample	3.16 (2.69)
Num. obs.	294
R²	0.041
R² adj.	0.017
AIC	686.9
BIC	720.1
Log. Lik.	−334.458
F	1.739
RMSE	0.75

BAI (prop. score) = anxiety score on the Beck Anxiety Inventory. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
*p < 0.05, ***p < 0.001.

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Table 10

Linear model analysis coefficients and SEs for sensitivity (d ′) in reward-seeking

	Linear model: BDI pred. sensitivity (d′)
(Intercept)	3.09*** (0.16)
BDI (prop. score)	−0.05 (0.46)
Gender	0.26 (0.20)
Sample	0.07 (0.30)
BDI (prop. score) × Gender	−0.28 (0.58)
BDI (prop. score) × Sample	−0.15 (0.92)
Gender × Sample	−0.35 (0.50)
BDI (prop. score) × Gender × Sample	1.27 (2.13)
Num. obs.	294
R²	0.016
R² adj.	−0.008
AIC	694.5
BIC	727.6
Log. Lik.	−338.246
F	0.655
RMSE	0.76

BDI (prop. score) = depression score on the Beck Depression Inventory II. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
***p < 0.001.

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Table 11

Multilevel model analysis coefficients and SEs for effort in reward-seeking

	Multilevel model: BAI pred. effort
(Intercept)	5.27*** (0.26)
BAI (prop. score)	1.44* (0.71)
Block	−0.87 ***
	1 (0.02)
Gender	1.30*** (0.31)
Sample	1.08* (0.49)
BAI (prop. score) × Block	0.00 (0.05)
BAI (prop. score) × Gender	−3.35 *** (0.93)
Block × Gender	−0.03 (0.02)
BAI (prop. score) × Sample	−2.92 + (1.52)
Block × Sample	−0.12 ** (0.04)
Gender × Sample	−2.05 ** (0.76)
BAI (prop. score) × Block × Gender	0.15* (0.07)
BAI (prop. score) × Block × Sample	0.39** (0.13)
BAI (prop. score) × Gender × Sample	3.62 (4.81)
Block × Gender × Sample	0.22*** (0.06)
BAI (prop. score) × Block × Gender × Sample	−0.79 + (0.42)
SD (intercept participant)	1.30
SD (observations)	1.98
Num. obs.	37,677
R² marg.	0.282
R² cond.	0.498
AIC	159,770.0
BIC	159,923.7
ICC	0.3
RMSE	1.98

BAI (prop. score) = anxiety score on the Beck Anxiety Inventory. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, ICC = intraclass correlation, RMSE = root mean squared error.
+p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001.

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Table 12

Multilevel model analysis coefficients and SEs for effort in reward-seeking

	Multilevel model: BDI pred. effort
(Intercept)	5.64*** (0.29)
BDI (prop. score)	0.15 (0.82)
Block	−0.88 *** (0.02)
Gender	0.73* (0.35)
Sample	0.44 (0.53)
BDI (prop. score) × Block	0.03 (0.06)
BDI (prop. score) × Gender	−1.01 (1.03)
Block × Gender	0.01 (0.03)
BDI (prop. score) × Sample	−0.51 (1.64)
Block × Sample	−0.07 (0.04)
Gender × Sample	−1.29 (0.89)
BDI (prop. score) × Block × Gender	0.00 (0.08)
BDI (prop. score) × Block × Sample	0.17 (0.13)
BDI (prop. score) × Gender × Sample	1.45 (3.81)
Block × Gender × Sample	0.14+ (0.07)
BDI (prop. score) × Block × Gender × Sample	−0.25 (0.32)
SD (intercept participant)	1.32
SD (observations)	1.98
Num. obs.	37,677
R² marg.	0.276
R² cond.	0.499
AIC	159,796.9
BIC	159,950.6
ICC	0.3
RMSE	1.98

BDI (prop. score) = depression score on the Beck Depression Inventory II. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, ICC = intraclass correlation, RMSE = root mean squared error.
+p < 0.1, *p < 0.05, ***p < 0.001.

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Table 13

Linear model analysis coefficients and SEs for break point in reward-seeking

	Linear model: BAI pred. sensitivity (d′)
(Intercept)	113.69*** (3.21)
BAI (prop. score)	7.21 (8.83)
Gender	6.73+ (3.84)
Sample	−2.79 (6.05)
BAI (prop. score) × Gender	−13.91 (11.57)
BAI (prop. score) × Sample	9.61 (18.66)
Gender × Sample	3.79 (9.34)
BAI (prop. score) × Gender × Sample	−3.59 (59.57)
Num. obs.	294
R²	0.019
R² adj.	−0.005
AIC	2507.8
BIC	2540.9
Log. Lik.	−1244.881
F	0.786
RMSE	16.70

BAI (prop. score) = anxiety score on the Beck Anxiety Inventory. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
+p < 0.1, ***p < 0.001.

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Table 14

Linear model analysis coefficients and SEs for break point in reward-seeking

	Linear model: BDI pred. sensitivity (d′)
(Intercept)	114.96*** (3.56)
BDI (prop. score)	2.79 (10.06)
Gender	6.66 (4.30)
Sample	−3.31 (6.45)
BDI (prop. score) × Gender	−12.94 (12.64)
BDI (prop. score) × Sample	10.64 (20.01)
Gender × Sample	3.16 (10.88)
BDI (prop. score) × Gender × Sample	−1.17 (46.44)
Num. obs.	294
R²	0.019
R² adj.	−0.005
AIC	2507.8
BIC	2541.0
Log. Lik.	−1244.920
F	0.775
RMSE	16.70

BDI (prop. score) = depression score on the Beck Depression Inventory II. Proportion scores are scores divided by total possible score. AIC = Akaike information criterion, BIC = Bayesian information criterion, Log. Lik. = log likelihood, RMSE = root mean squared error.
***p < 0.001.