Factors influencing physician's behavioral intention to use Traditional Chinese Medicine to treat coronavirus disease 2019 based on the theory of planned behavior

doi:10.19852/j.cnki.jtcm.20220607.001

Abstract

Abstract:

OBJECTIVE: To explore the factors influencing physicians' intentions to use Traditional Chinese Medicine (TCM) to treat coronavirus disease 2019 (COVID-19). METHODS: A cross-sectional, self-report online survey was conducted from March 16, 2020, to April 2, 2020, in China. Participants were recruited through convenience and snowball sampling. Data were collected by using a self-designed questionnaire based on the Theory of Planned Behavior. Structural equation modeling was used for data analysis. RESULTS: A total of 494 physicians were enrolled in this study. Overall, the model explained 75.4% and 75.5% of the total variance in intention and attitude, respectively. Specifically, attitudes (β = 0.467, P < 0.001), past behavior (β = 0.384, P < 0.05), subjective norms (SN) (β = 0.177, P < 0.001), and perceived behavioral control (PBC) (β = 0.133, P < 0.05) significantly affected physicians' intention to use TCM. Cognition (β = 0.606, P < 0.001) and PBC (β = 0.569, P < 0.01) significantly influenced physicians' attitudes toward using TCM. SN (β = 0.064, P = 0.263) was not a factor affecting attitude. CONCLUSION: Physicians’ intention to use TCM was significantly associated with attitude, past behavior, PBC, and SN. The findings may not only be useful for understanding the influencing factors and paths of physicians’ intention to use TCM to treat COVID-19 but also provide a reference for health authorities and policymakers to promote physicians to utilize TCM.

Key words: COVID-19, Medicine, Chinese Traditional, physicians, intention, behavior control

CHEN Huang, SHI Lushaobo, SHI Zengping, XIA Yi, WANG Dong. Factors influencing physician's behavioral intention to use Traditional Chinese Medicine to treat coronavirus disease 2019 based on the theory of planned behavior[J]. Journal of Traditional Chinese Medicine, 2022, 42(4): 633-6400.

Figures/Tables 9

References 42

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Variable	Categories	Case	Percentage (%)
Gender	Female	212	42.91
	Male	282	57.09
Age	30 or below	62	12.55
	31-45	288	58.30
	46-60	134	27.13
	60 or above	10	2.02
Marital status	Unmarried	44	8.91
	Married	450	91.09
Family register	Rural	28	5.67
	Urban	466	94.33
Educational level	Secondary or below	22	4.45
	Tertiary or above	472	95.55
Family annual income (RMB)	50 000 or below	52	10.53
	50 000-200 000	348	70.45
	200 000 or above	94	19.02
Occupational background	Western Medicine	246	49.80
	Traditional Chinese Medicine	248	50.20

Variable	Categories	Case	Percentage (%)
Gender	Female	212	42.91
	Male	282	57.09
Age	30 or below	62	12.55
	31-45	288	58.30
	46-60	134	27.13
	60 or above	10	2.02
Marital status	Unmarried	44	8.91
	Married	450	91.09
Family register	Rural	28	5.67
	Urban	466	94.33
Educational level	Secondary or below	22	4.45
	Tertiary or above	472	95.55
Family annual income (RMB)	50 000 or below	52	10.53
	50 000-200 000	348	70.45
	200 000 or above	94	19.02
Occupational background	Western Medicine	246	49.80
	Traditional Chinese Medicine	248	50.20

Parameter	Item	Standard loading	AVE	CR	Cronbach’s α	Bartlett Test of Sphericity	KMO Measure	Square root of AVE
Cognition (C)	C1	0.735	0.583	0.906	0.915	2607.352	0.858	0.764
	C2	0.735
	C3	0.874
	C4	0.890
	C5	0.695
	C6	0.622
	C7	0.760
Attitude (ATT)	ATT1	0.886	0.764	0.907	0.911	1228.996	0.767	0.874
	ATT2	0.888
	ATT3	0.848
Subjective norms (SN)	SN1	0.951	0.871	0.964	0.960	2508.428	0.860	0.933
	SN2	0.965
	SN3	0.936
	SN4	0.878
Perceived behavioral control (PBC)	PBC1	0.824	0.727	0.941	0.936	2647.807	0.906	0.853
	PBC2	0.768
	PBC3	0.897
	PBC4	0.827
	PBC5	0.884
	PBC6	0.907
Past behavior (PB)	PB1	0.925	0.789	0.918	0.859	1068.051	0.755	0.888
	PB2	0.868
	PB3	0.870
Behavioral intention (BI)	BI1	0.944	0.872	0.932	0.948	879.793	0.500		0.934
Behavioral intention (BI)	BI2	0.924	0.872	0.932	0.948	879.793	0.500		0.934

Parameter	Item	Standard loading	AVE	CR	Cronbach’s α	Bartlett Test of Sphericity	KMO Measure	Square root of AVE
Cognition (C)	C1	0.735	0.583	0.906	0.915	2607.352	0.858	0.764
	C2	0.735
	C3	0.874
	C4	0.890
	C5	0.695
	C6	0.622
	C7	0.760
Attitude (ATT)	ATT1	0.886	0.764	0.907	0.911	1228.996	0.767	0.874
	ATT2	0.888
	ATT3	0.848
Subjective norms (SN)	SN1	0.951	0.871	0.964	0.960	2508.428	0.860	0.933
	SN2	0.965
	SN3	0.936
	SN4	0.878
Perceived behavioral control (PBC)	PBC1	0.824	0.727	0.941	0.936	2647.807	0.906	0.853
	PBC2	0.768
	PBC3	0.897
	PBC4	0.827
	PBC5	0.884
	PBC6	0.907
Past behavior (PB)	PB1	0.925	0.789	0.918	0.859	1068.051	0.755	0.888
	PB2	0.868
	PB3	0.870
Behavioral intention (BI)	BI1	0.944	0.872	0.932	0.948	879.793	0.500		0.934
Behavioral intention (BI)	BI2	0.924	0.872	0.932	0.948	879.793	0.500		0.934

	Mean ± SD	ATT	BI	SN	PB	PBC	C
ATT	4.3±0.8	0.874
BI	4.2±0.9	0.824^a	0.934
SN	4.0±0.9	0.712^a	0.753^a	0.933
PB	4.0±1.1	0.725^a	0.782^a	0.692^a	0.888
PBC	4.1±0.8	0.756^a	0.772^a	0.795^a	0.723^a	0.853
C	3.8±0.7	0.748^a	0.682^a	0.606^a	0.567^a	0.567^a	0.764

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