Ryerson Project Ryerson Project

Ryerson Project Item 143

I trust AI to give me advice on my mental health.

American adults' average (mean) response was 3.43 on a scale of 0 (Disagree) to 10 (Agree). 383 responses have been collected (so far) from 2026-07-01 to 2026-08-06.

Descriptive Statistics

Mean3.43
Median3.00
Standard deviation2.92
N383
Standard error0.149

All-Time Distribution

Response 0: 104 Response 1: 27 Response 2: 32 Response 3: 42 Response 4: 28 Response 5: 45 Response 6: 37 Response 7: 33 Response 8: 19 Response 9: 6 Response 10: 10 0 1 2 3 4 5 6 7 8 9 10 0 104 Response value Count

Comparison to Other Items

Based on all-time mean agreement, this item ranks 110 out of 123 qualifying items and is at the 10.7 percentile.

Qualifying items have 100 or more total observations. Higher means indicate more agreement and therefore a higher rank.

Monthly Trend

0 1 2 3 4 5 6 7 8 9 10 0% 50% 100% 0 5 10 2026-07 response 0: 27.3% 2026-07 response 1: 7.1% 2026-07 response 2: 7.1% 2026-07 response 3: 12.2% 2026-07 response 4: 6.8% 2026-07 response 5: 13.2% 2026-07 response 6: 9.6% 2026-07 response 7: 8.4% 2026-07 response 8: 5.1% 2026-07 response 9: 1.3% 2026-07 response 10: 1.9% 2026-08 response 0: 26.4% 2026-08 response 1: 6.9% 2026-08 response 2: 13.9% 2026-08 response 3: 5.6% 2026-08 response 4: 9.7% 2026-08 response 5: 5.6% 2026-08 response 6: 9.7% 2026-08 response 7: 9.7% 2026-08 response 8: 4.2% 2026-08 response 9: 2.8% 2026-08 response 10: 5.6% Jul 2026 Aug 2026 Observation month Percent of responses Monthly mean

Observed Trend

Observations suggest unchanging agreement over the observed period, from 2026-07-01 to 2026-08-06. The estimated change over that period is -0.064 points on a 0 to 10 scale. Regression results place a 95% confidence interval around that observed-period change of [-1.168, 1.039].
Regression table

The daily slope annualized over 365.25 days is -0.652 points per year, with a 95% confidence interval of [-11.848, 10.543]. This short-window annualized number is provided for reference, but the observed-period change above is the primary trend estimate.

Call:
lm(formula = response_value ~ days_since_start, data = model_data)

Residuals:
    Min      1Q  Median      3Q     Max 
-3.4610 -3.4039 -0.4199  2.5631  6.5997 

Coefficients:
                  Estimate Std. Error t value Pr(>|t|)    
(Intercept)       3.464586   0.350947   9.872   <2e-16 ***
days_since_start -0.001786   0.015590  -0.115    0.909    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2.923 on 381 degrees of freedom
Multiple R-squared:  3.446e-05,	Adjusted R-squared:  -0.00259 
F-statistic: 0.01313 on 1 and 381 DF,  p-value: 0.9088