Status and influencing factors of medication adherence among elderly tuberculosis patients based on digital technologies

doi:10.19982/j.issn.1000-6621.20250405

Abstract

Abstract:

Objective: To explore the status and influencing factors of medication adherence in elderly patients with tuberculosis based on digital technology management. Methods: With the convenience sampling method, 220 elderly tuberculosis patients who were hospitalized at the Tuberculosis Diagnosis and Treatment Center of Hangzhou Red Cross Hospital from August 2024 to August 2025 and who received digital technology for medication adherence management after discharge were selected as the study participants. Data on demographic characteristics and disease-related variables were collected through medical record review. Medication adherence, activities of daily living, and family support were assessed via structured questionnaires. Univariate analysis and binary logistic regression were performed to explore the associations between these variables and medication adherence. Results: A total of 205 elderly tuberculosis patients were included, with 139 (67.8%) in the medication compliance group and 66 (32.2%) in the medication non-compliance group. Multivariate logistic analysis showed that skin allergic reactions caused by anti-tuberculosis drugs (OR=16.357, 95%CI:1.683-158.968), gastrointestinal adverse reactions induced by anti-tuberculosis drugs (OR=3.804, 95%CI:1.318-10.978), history of allergy to other medications (OR=10.782, 95%CI:1.714-67.828), good follow-up response to digital technology (OR=0.317, 95%CI:0.128-0.790), high family support (OR=0.085, 95%CI:0.017-0.414), mild dependence on activities of daily living (OR=0.083, 95%CI:0.008-0.901), and non-dependence on activities of daily living (OR=0.029, 95%CI:0.001-0.675) were independent factors associated with medication adherence among elderly tuberculosis patients managed via digital technology (P<0.05). Conclusion: The medication adherence of elderly patients with tuberculosis based on digital technology management is affected by the skin allergic reactions and gastrointestinal adverse reactions caused by anti-tuberculosis drugs, history of allergy to other medications, follow-up response to digital technology, daily living ability and family support level. The nursing staff should implement tailored interventions based on the influencing factors to improve the medication adherence under the digital health management model.

Key words: Digital adherence technology, Tuberculosis, Medication compliance, Influencing factors

CLC Number:

Zhang Yue, Huang Jinpeng, Gao Dan, Ling Lin. Status and influencing factors of medication adherence among elderly tuberculosis patients based on digital technologies[J]. Chinese Journal of Antituberculosis, 2026, 48(6): 813-820. doi: 10.19982/j.issn.1000-6621.20250405

Figures/Tables 3

项目		服药依从组(139例)	服药不依从组(66例)		统计检验值	P值
性别					χ²=0.621	0.431
男性		88(63.3)	38(57.6)
女性		51(36.7)	28(42.4)
医保类别					χ²=4.942	0.084
医保		82(59.0)	38(57.6)
农保		50(36.0)	19(28.8)
自费		7(5.0)	9(13.6)
文化程度					χ²=4.098	0.129
初中及以下		78(56.1)	45(68.2)
中专及高中		31(22.3)	14(21.2)
大专及以上		30(21.6)	7(10.6)
吸烟				χ²=4.709		0.030
否	125(89.9)		52(78.8)
是	14(10.1)		14(21.2)
饮酒				χ²=4.001		0.045
否	124(89.2)		52(78.8)
是	15(10.8)		14(21.2)
婚姻状态				χ²=0.984		0.321
有配偶	102(73.4)		44(66.7)
无配偶	37(26.6)		22(33.3)
并发高血压				χ²=0.739		0.390
否	111(79.9)		56(84.8)
是	28(20.1)		10(15.2)
并发糖尿病				χ²=0.184		0.668
否	121(87.1)		56(84.8)
是	18(12.9)		10(15.2)
血型				χ²=5.035		0.169
A	47(33.8)		13(19.7)
B	22(15.8)		16(24.2)
AB	53(38.1)		28(42.4)
O	17(12.2)		9(13.6)
治疗分类				χ²=1.985		0.159
初治	127(91.4)		56(84.8)
复治	12(8.6)		10(15.2)
诊断分类				χ²=1.048		0.306
肺结核	78(56.1)		32(48.5)
肺外结核	61(43.9)		34(51.5)
其他药物过敏史				χ²=23.639		<0.001
否	136(97.8)		51(77.3)
是	3(2.2)		15(22.7)
皮肤过敏反应				χ²=6.987		0.008
否	137(98.6)		57(86.4)
是	2(1.4)		9(13.6)
胃肠道反应				χ²=5.504		0.019
否	126(90.6)		52(78.8)
是	13(9.4)		14(21.2)
数字技术随访应答				χ²=5.965		0.015
不佳	25(18.0)		22(33.3)
良好	114(82.0)		44(66.7)
家庭支持				χ²=7.504		0.023
低家庭支持	16(11.5)		13(19.7)
中家庭支持	84(60.4)		45(68.2)
高家庭支持	39(28.1)		8(12.1)
日常生活能力				-^a		<0.001
不依赖	1(0.7)		2(9.1)
轻度依赖	4(2.9)		14(31.8)
中度依赖	122(87.8)		49(57.6)
重度依赖	12(8.6)		1(1.5)
BMI[kg/m²,M(Q₁,Q₃)]	20.3(18.4,22.7)		20.1(17.6,22.1)	Z=-1.115		0.265
ALT[U/L,M(Q₁,Q₃)]	16(10,25)		16(10,29)	Z=-0.130		0.897
AST[U/L,M(Q₁,Q₃)]	19(16,28)		23(16,35)	Z=-1.168		0.243
BUN[mmol/L,M(Q₁,Q₃)]	4.6(3.5,5.9)		4.4(3.3,6.8)	Z=-0.219		0.826
SCr[umol/L,M(Q₁,Q₃)]	68.5(59.3,79.2)		66.9(54.5,79.9)	Z=-0.746		0.456

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自变量	赋值方式
家庭支持	低家庭支持=(0,0);中家庭支持=(1,0);高家庭支持=(0,1)
日常生活能力	不依赖=(0,0,0);轻度依赖=(1,0,0);中度依赖=(0,1,0);重度依赖=(0,0,1)
吸烟	否=0;是=1
饮酒	否=0;是=1
皮肤过敏反应	否=0;是=1
胃肠道反应	否=0;是=1
其他药物过敏史	否=0;是=1
数字技术随访应答	不佳=0;良好=1

项目	β值	s${}_{\overline{x}}$值		P值		OR (95%CI)值
吸烟
否						1
是	0.224	0.751		0.766		1.251(0.287~5.456)
饮酒
否						1
是	-0.17	0.761		0.824		0.844(0.190~3.753)
皮肤过敏反应
否						1
是	2.795	1.160		0.016		16.357(1.683~158.968)
胃肠道反应
否						1
是	1.336	0.541		0.013		3.804(1.318~10.978)
其他药物过敏史
否							1
是	2.378		0.938		0.011		10.782(1.714~67.828)
数字技术随访应答
不佳							1
良好	-1.147		0.465		0.014		0.317(0.128~0.790)
家庭支持
低							1
中	-0.54		0.523		0.302		0.583(0.209~1.624)
高	-2.469		0.810		0.002		0.085(0.017~0.414)
日常生活能力
重度依赖							1
中度依赖	1.353		1.417		0.340		3.869(0.241~62.163)
轻度依赖	-2.485		1.215		0.041		0.083(0.008~0.901)
不依赖	-3.529		1.600		0.027		0.029(0.001~0.675)