Emotional differences based on comments on doctor-patient disputes with varying levels of severity

Table 1 Examples of collected comments on incidents of doctor-patient disputes

Serial number	Comments
1	Doctor-patient conflicts are not without cause
2	Not all people are good, and not all doctors are good
3	There are problems on both sides
4	Do the right thing. If the doctor doesn’t do a good job, complain to him
5	I think the doctor’s attitude is very bad now
6	Medical ethics are important
7	Where there is a cause, there is an effect. In particular, some patients are already suffering from illnesses, coupled with the irresponsibility of doctors, so it is only right that some doctors have been killed because of doctor-patient disputes
8	Are patients the only ones to blame for doctor-patient conflicts?

Table 2 Examples of basic emotion lexicons

Word	Lexical category	Intensity	Polarity	Weight
Dependency	Verb	1	0	0
Careful	Adjective	3	1	3
Eccentric	Adjective	1	-1	-1
Guffaw	Verb	5	-1	-5

Table 3 Negative lexicon examples

Word	Weight	Quantity
Didn’t, no, not, couldn’t, rarely, never, terminated, missing, never	-1	71

Table 4 Example of partial results of Python extracting the number of emotion words corresponding to the matrix data

Serial number	Comments	Length	Positive	Negative	Anger	Disgust	Fear	Sadness	Surprise	Good	Happy
1	It ends 80% of the time with an apology, the nurse showing under-standing, and ending up at home for the rest of the year	14	1	0	0	0	0	0	0	1	0
2	If they can’t be punished severely; similar things will keep happening	10	0	0	0	0	0	0	0	0	0
3	Looking at the injuries, it feels like they may not be able to return home next New Year’s Eve, either	10	0	1	0	1	0	0	0	0	0
4	Why? I wouldn’t accept an apology if I were you	10	1	0	0	0	0	0	0	1	0

Table 5 Example of partial results for the corresponding matrix data after commenting on the manual assignment

Serial number	Comments	Length	Positive	Negative	Anger	Disgust	Fear	Sadness	Surprise	Good	Happy	Comment score
1	Excessive people are inexplicable	5	0	2	0	2	0	0	0	0	0	-8
2	The point is, you can’t leave an emergency room unattended	7	0	0	0	0	0	0	0	0	0	0
3	What is an emergency? What is an urgent case? The family’s in a hurry, the doctor doesn’t panic	12	1	1	0	1	0	0	0	0	1	-3
4	A few doctors have some really bad attitudes	6	0	1	0	1	0	0	0	0	0	-3
5	Doctor, you have to know what an emergency is. Every second counts, understand?	14	1	0	0	0	0	0	0	1	0	5

Table 6 Kruskal-Wallis H test

Variable	Comparison of incident levels		SE	P value
Positive	Group differences	14.822		0.002
	2 vs 1	113.738	48.270	0.018
	2 vs 4	-177.112	56.576	0.002
	3 vs 1	83.643	38.222	0.029
	3 vs 4	-147.016	48.289	0.002
Negative	Group differences	35.397		0
	2 vs 1	218.660	50.200	0
	2 vs 4	-281.295	58.838	0
	3 vs 1	140.349	39.750	0
	3 vs 4	-202.985	50.219	0
Anger	Group differences	1.779		0.619
Disgust	Group differences	27.043		0
	2 vs 4	-165.943	56.332	0.003
	2 vs 1	182.248	48.062	0
	3 vs 4	-143.057	48.080	0.003
	3 vs 1	159.362	38.057	0
Fear	Group differences	21.502		0
	2 vs 4	-78.824	25.924	0.002
	2 vs 1	84.332	22.118	0
	3 vs 4	-51.862	22.127	0.019
	3 vs 1	57.370	17.514	0.001
Sadness	Group differences	44.747		0
	2 vs 3	-81.824	31.089	0.008
	2 vs 4	-187.128	33.791	0
	1 vs 3	-55.240	22.829	0.016
	1 vs 4	-160.543	26.391	0
	3 vs 4	-105.304	28.841	0
Surprise	Group differences	5.539		0.136
Good	Group differences	14.396		0.002
	3 vs 1	98.017	37.044	0.008
	3 vs 4	-147.035	46.800	0.002
	2 vs 1	95.630	46.782	0.041
	2 vs 4	-144.648	54.831	0.008
Happy	Group differences	9.647		0.022
	2 vs 3	-57.709	28.480	0.043
	2 vs 4	-94.158	30.956	0.002
	1 vs 4	-49.162	24.176	0.042
Comment score	Group differences	14.206		0.003
	1 vs 3	-81.270	40.833	0.047
	1 vs 4	-104.633	47.204	0.027
	1 vs 2	-177.166	51.567	0.001

1: Level 1 incidents (verbal conflicts); 2: Level 2 incidents (physical conflicts); 3: Level 3 incidents (injuries); 4: Level 4 incidents (fatalities).

Table 7 Spearman’s correlation analyses between incident levels, number of words for each sentiment and comment scores

Variable	Incident level	Positive	Negative	Anger	Disgust	Fear	Sadness	Surprise	Good	Happy	Comment score
Incident level	1.000
Positive	0	1.000
Negative	-0.010	0.101b	1.000
Anger	0	0.028	0.197b	1.000
Disgust	-0.0340a	0.104b	0.842b	0.058b	1.000
Fear	-0.027	0.025	0.262b	-0.020	0.048b	1.000
Sadness	0.086b	0.047b	0.366b	0.046b	0.072b	0.023	1.000
Surprise	-0.008	0.122b	0.015	0.020	0.021	-0.023	-0.003	1.000
Good	-0.007	0.905b	0.094b	0.026	0.094b	0.027	0.047b	0.039a	1.000
Happy	0.027	0.390b	0.069b	0.026	0.073b	0.009	0.042a	0.036a	0.092b	1.000
Comment score	0.036b	0.223b	-0.470b	-0.070b	-0.488b	-0.064b	-0.099b	0.014	0.228b	0.041b	1.000

^aP < 0.05 (two-tailed).

^bP < 0.05 (two-tailed).

Table 8 Linear regression analysis

Variable	Step 1		Step 2
	β	SE	β	SE
Incident level	0.020	0.059
Positive	0.452	2.372
Negative	-1.084c	0.648	-1.009c	0.730
Anger	0.136c	0.743	0.131c	0.838
Disgust	0.304b	0.644	0.302b	0.725
Fear	0.193c	0.667	0.189c	0.750
Sadness	0.295c	0.632	0.300c	0.713
Surprise	-0.035	2.475
Good	-0.017	2.371
Happy	-0.094	2.366
Adjusted R2	0.460		0.309
F	312.274c		327.572c

^bP < 0.01.

^cP < 0.001.