Ryerson Project Ryerson Project

Ryerson Project Item 142

I would not want therapists to use AI to help them care for me.

American adults' average (mean) response was 6.93 on a scale of 0 (Disagree) to 10 (Agree). 290 responses have been collected (so far) from 2026-07-01 to 2026-08-28.

Descriptive Statistics

Mean6.93
Median7.50
Standard deviation2.92
N290
Standard error0.171

All-Time Distribution

Response 0: 7 Response 1: 9 Response 2: 13 Response 3: 11 Response 4: 19 Response 5: 41 Response 6: 16 Response 7: 29 Response 8: 34 Response 9: 19 Response 10: 92 0 1 2 3 4 5 6 7 8 9 10 0 92 Response value Count

Comparison to Other Items

Based on all-time mean agreement, this item ranks 49 out of 134 qualifying items and is at the 63.9 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: 2.6% 2026-07 response 1: 2.6% 2026-07 response 2: 3.5% 2026-07 response 3: 2.6% 2026-07 response 4: 7.9% 2026-07 response 5: 14.9% 2026-07 response 6: 7.0% 2026-07 response 7: 8.8% 2026-07 response 8: 14.9% 2026-07 response 9: 5.3% 2026-07 response 10: 29.8% 2026-08 response 0: 2.3% 2026-08 response 1: 3.4% 2026-08 response 2: 5.1% 2026-08 response 3: 4.5% 2026-08 response 4: 5.7% 2026-08 response 5: 13.6% 2026-08 response 6: 4.5% 2026-08 response 7: 10.8% 2026-08 response 8: 9.7% 2026-08 response 9: 7.4% 2026-08 response 10: 33.0% 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 2026-08-28. The estimated change over that period is -0.625 points on a 0 to 10 scale. Regression results place a 95% confidence interval around that observed-period change of [-1.937, 0.688].
Regression table

The daily slope annualized over 365.25 days is -3.933 points per year, with a 95% confidence interval of [-12.196, 4.330]. 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 
-7.0734 -2.0276  0.5451  2.9239  3.3143 

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)       7.31029    0.43615  16.761   <2e-16 ***
days_since_start -0.01077    0.01149  -0.937     0.35    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2.916 on 288 degrees of freedom
Multiple R-squared:  0.003038,	Adjusted R-squared:  -0.0004234 
F-statistic: 0.8777 on 1 and 288 DF,  p-value: 0.3496