Current awareness and influencing factors regarding digital out-of-hospital health monitoring among patients after gastrointestinal surgery: A cross-sectional study

Table 1 General characteristics of participants

Item	Category	n	Percentage (%)
Sex	Male	66	52.4
	Female	60	47.6
Age (years)	< 45	47	37.3
	45-60	42	33.3
	> 60	37	29.4
Education level	Primary school or below	7	5.6
	Junior high school	28	22.2
	Senior high school or secondary vocational	34	27.0
	College or above	57	45.2
Marital status	Married	93	73.8
	Unmarried	15	11.9
	Divorced or widowed	18	14.3
Monthly household income (yuan)	< 6000	54	42.9
	> 6000	72	57.1
Primary diagnosis	Colorectal cancer	30	23.8
	Intestinal obstruction	4	3.2
	Appendicitis	30	23.8
	Gallbladder stones/polyps	55	43.7
	Other	7	5.6
Surgical approach	Laparoscopic	92	73.0
	Open	3	2.4
	Other	31	24.6
Postoperative time (weeks)	< 4	22	17.5
	4-12	29	23.0
	> 12	75	59.5
Presence of stoma	Yes	5	4.0
	No	121	96.0
Complications	Yes	9	7.1
	No	117	92.9
Postoperative chemotherapy	Yes	31	24.6
	No	95	75.4
Years of smartphone use	< 3	26	20.6
	3-5	36	28.6
	> 5	64	50.8
Prior use of health-related apps	Yes	57	45.2
	No	69	54.8
Average daily internet use time (hours)	< 3	37	29.4
	3-5	39	31.0
	> 5	50	39.7

Table 2 Scores of each dimension of cognition of digital out-of-hospital health monitoring among postoperative patients in gastrointestinal surgery

Dimension	Number of items	Theoretical score range	Score (mean ± SD)	Item mean score	Actual minimum	Actual maximum	Standardized score rate (%)
Basic cognition	3	3-15	8.67 ± 2.748	2.89	3	15	57.8
Functional cognition	4	4-20	12.00 ± 3.129	3.00	4	19	60.0
Value cognition	5	5-25	15.39 ± 3.075	3.08	9	25	61.6
Concern cognition	3	3-15	9.36 ± 2.515	2.88	4	15	57.6
Total scale	15	15-75	45.41 ± 6.427	3.02	28	61	60.4

Table 3 Top 3 and bottom 3 scoring items

Ranking	Item	Dimension	Score (mean ± SD)
Top 3 items
1	I think digital out-of-hospital health monitoring can help reduce the risk of readmission due to complications	Value cognition	3.14 ± 1.43
2	I know that when uploaded data are abnormal, the system can automatically alert the medical team	Functional cognition	3.12 ± 1.40
3	I think digital out-of-hospital health monitoring can improve communication between me and healthcare staff	Value cognition	3.11 ± 1.49
Bottom 3 items
1	I understand the basic content and procedures of digital out-of-hospital health monitoring	Basic cognition	2.84 ± 1.41
2	I know that I can upload health data such as weight and body temperature to the medical team via mobile phone	Functional cognition	2.87 ± 1.35
3	I have heard of "digital out-of-hospital health monitoring" or similar out-of-hospital health management services	Basic cognition	2.90 ± 1.47

Table 4 Univariate analysis of total cognitive scores among postoperative patients in gastrointestinal surgery by different characteristics

Item	Category	Total cognitive score (mean ± SD)	Statistic	P value
Age (years)			F = 5.304	0.006
	< 45	47.55 ± 6.55
	45-60	45.00 ± 5.25
	> 60	43.16 ± 6.76
Education level			F = 4.472	0.005
	Primary school or below	37.86 ± 7.20
	Junior high school	45.11 ± 6.45
	Senior high school or secondary vocational	44.97 ± 5.18
	College or above	46.75 ± 6.45
Years of smartphone use			F = 4.807	0.010
	< 3	42.50 ± 6.74
	3-5	44.86 ± 5.61
	> 5	46.91 ± 6.36
Prior use of health-related apps			t = 2.818	0.006
	Yes	47.14 ± 5.87
	No	43.99 ± 6.56

Sex, marital status, monthly household income, primary diagnosis, surgical approach, postoperative time, presence of stoma, complications, postoperative chemotherapy, and average daily internet use time showed no statistically significant differences (all P > 0.05) and are not listed in the table.

Table 5 Multiple linear regression analysis of factors influencing cognition

Variable	B	SE	β	t value	P value
Constant	44.713	3.864	-	11.571	< 0.001
Years of smartphone use	1.644	0.684	0.203	2.402	0.018
Prior use of health-related apps	-2.263	1.087	-0.176	-2.082	0.039
Age group	-1.271	0.761	-0.161	-1.670	0.098
Education level	0.917	0.653	0.135	1.404	0.163

Variable assignment: Prior use of health-related apps: Yes = 1, No = 2. Age group: < 45 = 1, 45-60 = 2, > 60 = 3. Education level: Primary school or below = 1, Junior high school = 2, Senior high school or secondary vocational = 3, College or above = 4. Years of smartphone use: < 3 = 1, 3-5 = 2, > 5 = 3. For the variable "prior use of health-related apps" (coded 1 = Yes, 2 = No), the negative β indicates that patients without prior app experience had lower cognitive scores than those with prior experience.