COVID-19 preventive behaviors and digital health communication media usage model

Figures & data

Figure 1. The conceptual model.

Table 1. Variables and indicators

Variables	Indicators	Adapted from:
Digital Health Communication Media Platforms (USE)	Information on COVID-19 preventive behaviors is searched by using …	(Al-Dmour et al., 2020; Choi & Noh, 2020)
	Website (USE1)
	YouTube (USE2)
	Instagram (USE3)
	Facebook (USE4)
	Twitter (USE5)
	Titkok (USE6)
	WhatsApp (USE7)
	Health applications (USE8)
Message Characteristics (MSG)	The contents of information on COVID-19 preventive behaviors found in digital media are	(Deng et al., 2015; Sumaedi et al., 2021b; Zhou, 2013)
	Easy to understand (MSG1)
	Accurately true (MSG2)
	In line with my needs (MSG3)
	Current/up-to-date (MSG4)
	Delivered in detail (MSG5)
Source Credibility (SRC)	The sources of information on COVID-19 preventive behaviors found in digital media are:	(Nguyen & Le, 2021; Sumaedi et al., 2021b; Wiedmann & von Mettenheim, 2020)
	Trustworthy (SRC1)
	Interesting (SRC2)
	Competent (SRC3)
Communication Exposure (EXP)	Frequency of acquiring information about the call to:	(Boyle et al., 2016; Fenitra et al., 2021; Xin et al., 2021)
	Wear face masks (EXP1)
	Keep social distance (EXP2)
	Wash hands with soap (EXP3)
	Avoid crowds (EXP4)
	Limit mobility (EXP5)
	Get vaccinated (EXP6)
Perceived Threat of COVID-19 (TRH)	I have a chance of getting COVID-19 (TRH1)	(Hong et al., 2021; Nguyen & Le, 2021; Sumaedi et al., 2020, 2021; Twum et al., 2021)
	I feel worried about COVID-19 (TRH2)
	I am at risk of getting COVID-19 (TRH3)
	I am afraid of getting COVID-19 (TRH4).
	Getting COVID-19 causes severe health problems (TRH5)
Subjective Norm (SNM)	People who are important to me think that I should practice COVID-19 preventive behaviors COVID-19 (SNM1)	(Astrini et al., 2021; Bronfman et al., 2021; ; Sumaedi et al., 2020; 2021a)
	People who are influential in my life think that I should practice COVID-19 preventive behaviors (SNM2).
	People whose opinions matter to me think that I should practice COVID-19 preventive behaviors (SNM3).
Perceived Behavior Control (PBC)	Financial wise, I am able to practice various COVID-19 preventive behaviors (PBC1)	(Bronfman et al., 2021; Sumaedi et al., 2020; 2021a)
	I have the facilities for practicing COVID-19 preventive behaviors (PBC2)
	Generally speaking, I am able to practice COVID-19 preventive behaviors (PBC3)
Awareness (AWR)	To avoid getting COVID-19, I am aware that it is important for me to … .	(Al-Dmour et al., 2020; Mohiuddin et al., 2018)
	Wear face masks (AWR1)
	Keep social distance (AWR2)
	Wash hands with soap (AWR3)
	Avoid crowds (AWR4)
	Limit mobility (AWR5)
	Get vaccinated (AWR6)
Knowledge (KNW)	I have knowledge about COVID-19 preventive behaviors (KNW1)	(Lee et al., 2018; Wang et al., 2020; Xin & Seo, 2020)
	My knowledge about COVID-19 preventive behaviors is better than my friends’ (KNW2)
	I know what behaviors need to be practiced to prevent COVID-19 (KNW3)
Attitude (ATT)	I think that COVID-19 preventive behaviors are:	(Sumaedi et al., 2020; 2021a; Twum et al., 2021; Wang et al., 2020)
	useful (ATT1)
	meaningful (ATT2)
	good (ATT3)
	behaviors I like (ATT4)
	positive (ATT5)
Behavioral Intention (INT)	In the next several days and onwards, … …	(SumaediSumaedi et al., 2020; 2021a; Twum et al., 2021; Wang et al., 2020)
	I intend to practice COVID-19 preventive behaviors (INT1)
	I will try to practice COVID-19 preventive behaviors (INT2)
	I plan to practice COVID-19 preventive behaviors (INT3)
COVID-19 Preventive Behaviour (BHV)	Frequency of practicing several COVID-19 preventive activities by … .	(Chen & Chen, 2020; WHO, 2020)
	Wearing face masks (BHV1)
	Keeping social distance (BHV2)
	Washing hands with soap (BHV3)
	Avoiding crowds (BHV4)
	Limiting mobility (BHV5)
	Getting vaccinated (BHV6)

Table 2. Characteristics of respondents

Characteristics	Criteria	%
Sex	Man (Male)	49.7
	Woman (Female)	50.3
Age	17–20 years old	43
	21–30 years old	23.7
	31–40 years old	14.8
	>40 years old	18.5
Main occupation	Student	60.1
	Private employee	11.7
	Civil servant/military/police	17.6
	Others	10.6
Last education level	Junior high school/equivalent graduate	0.3
	High school/equivalent graduate	61.7
	Diploma graduate (D1, D2, D3)	2.8
	Bachelor’s degree graduate (D4, S1)	15.1
	Master’s/doctoral degree graduate (S2/S3)	20.1
Monthly income	None/No income	47,1
	≤ IDR 3,000,000	18.6
	IDR 3,000,001–6,000,000	8.7
	IDR 6,000,001–10,000,000	12
	≥ IDR 10,000,001	13.4

Table 3. Result of model constructs reliability and convergent validity Testing

Construct	Loading	Outer loading	Cronbach’s alpha	Composite reliability	AVE
Digital Health Communication Media Platforms	USE2 <- USE	0.717	0.714	0.717	0.464
	USE3 <- USE	0.713
	USE5 <- USE	0.650
	USE6 <- USE	0.688
	USE7 <- USE	0.633
Message Characteristics	MSG1 <- MSG	0.734	0.866	0.871	0.653
	MSG2 <- MSG	0.771
	MSG3 <- MSG	0.859
	MSG4 <- MSG	0.828
	MSG5 <- MSG	0.843
Source Credibility	SRC1 <- SRC	0.898	0.819	0.840	0.734
	SRC2 <- SRC	0.778
	SRC3 <- SRC	0.890
Communication Exposure	EXP1 <- EXP	0.861	0.937	0.938	0.761
	EXP2 <- EXP	0.905
	EXP3 <- EXP	0.887
	EXP4 <- EXP	0.914
	EXP5 <- EXP	0.824
	EXP6 <- EXP	0.841
Awareness	AWR1 <- AWR	0.796	0.890	0.898	0.650
	AWR2 <- AWR	0.864
	AWR3 <- AWR	0.846
	AWR4 <- AWR	0.878
	AWR5 <- AWR	0.752
	AWR6 <- AWR	0.682
Knowledge	KNW1 <- KNW	0.880	0.782	0.827	0.694
	KNW2 <- KNW	0.726
	KNW3 <- KNW	0.883
Attitude	ATT1 <- ATT	0.909	0.908	0.919	0.737
	ATT2 <- ATT	0.903
	ATT3 <- ATT	0.901
	ATT4 <- ATT	0.684
	ATT5 <- ATT	0.874
Intention	INT1 <- INT	0.914	0.915	0.917	0.854
	INT2 <- INT	0.942
	INT3 <- INT	0.916
Behavior	BHV1 <- BHV	0.807	0.888	0.893	0.645
	BHV2 <- BHV	0.887
	BHV3 <- BHV	0.801
	BHV4 <- BHV	0.835
	BHV5 <- BHV	0.793
	BHV6 <- BHV	0.683
Perceived Threat of Covid-19	TRH2 <- TRH	0.848	0.768	0.775	0.682
	TRH4 <- TRH	0.843
	TRH5 <- TRH	0.785
Subjective Norm	SNM1 <- SNM	0.932	0.937	0.938	0.888
	SNM2 <- SNM	0.957
	SNM3 <- SNM	0.939
Perceived Behavior Control	PBC1 <- PBC	0.884	0.871	0.874	0.795
	PBC2 <- PBC	0.903
	PBC3 <- PBC	0.886

Table 4. Fornell-Larcker criterion analysis result

	ATT	AWR	BHV	EXP	INT	KNW	MSG	PBC	SNM	SRC	TRH	USE
ATT	0,858
AWR	0,625	0,806
BHV	0,596	0,818	0,803
EXP	0,421	0,458	0,410	0,873
INT	0,638	0,641	0,715	0,393	0,924
KNW	0,564	0,456	0,470	0,370	0,547	0,833
MSG	0,461	0,365	0,317	0,457	0,421	0,467	0,808
PBC	0,404	0,366	0,361	0,459	0,469	0,510	0,526	0,891
SNM	0,486	0,482	0,482	0,460	0,524	0,428	0,406	0,554	0,942
SRC	0,357	0,365	0,320	0,326	0,369	0,345	0,713	0,422	0,345	0,857
TRH	0,316	0,382	0,349	0,273	0,377	0,291	0,219	0,340	0,446	0,256	0,826
USE	0,147	0,254	0,262	0,127	0,199	0,153	0,283	0,120	0,175	0,313	0,239	0,681

Table 5. Cross loading analysis result

	ATT	AWR	BHV	EXP	INT	KNW	MSG	PBC	SNM	SRC	TRH	USE
ATT1	0.909	0.547	0.531	0.418	0.564	0.507	0.425	0.392	0.435	0.334	0.261	0.076
ATT2	0.903	0.555	0.515	0.356	0.550	0.498	0.383	0.347	0.408	0.311	0.314	0.117
ATT3	0.901	0.549	0.512	0.406	0.568	0.490	0.419	0.375	0.443	0.290	0.264	0.082
ATT4	0.684	0.407	0.420	0.155	0.468	0.400	0.275	0.207	0.305	0.255	0.247	0.229
ATT5	0.874	0.604	0.566	0.428	0.583	0.518	0.454	0.384	0.476	0.338	0.273	0.154
AWR1	0.574	0.796	0.624	0.418	0.543	0.411	0.346	0.344	0.381	0.336	0.297	0.179
AWR2	0.515	0.864	0.701	0.384	0.543	0.367	0.305	0.295	0.394	0.304	0.334	0.252
AWR3	0.534	0.846	0.650	0.423	0.506	0.377	0.338	0.351	0.413	0.317	0.295	0.181
AWR4	0.547	0.878	0.739	0.407	0.580	0.397	0.318	0.273	0.434	0.305	0.344	0.194
AWR5	0.364	0.752	0.630	0.255	0.447	0.332	0.202	0.200	0.330	0.248	0.332	0.244
AWR6	0.466	0.682	0.614	0.304	0.467	0.311	0.235	0.300	0.373	0.242	0.243	0.189
BHV1	0.561	0.694	0.807	0.389	0.611	0.431	0.297	0.372	0.437	0.268	0.284	0.154
BHV2	0.493	0.694	0.887	0.363	0.612	0.399	0.279	0.310	0.443	0.277	0.321	0.251
BHV3	0.496	0.651	0.801	0.364	0.556	0.391	0.287	0.321	0.374	0.279	0.230	0.197
BHV4	0.407	0.646	0.835	0.292	0.583	0.363	0.241	0.244	0.380	0.284	0.293	0.274
BHV5	0.418	0.647	0.793	0.274	0.551	0.365	0.197	0.235	0.377	0.220	0.355	0.257
BHV6	0.499	0.607	0.683	0.285	0.529	0.309	0.219	0.249	0.299	0.210	0.189	0.116
EXP1	0.392	0.380	0.339	0.861	0.333	0.327	0.385	0.389	0.358	0.315	0.168	0.078
EXP2	0.363	0.390	0.362	0.905	0.365	0.300	0.404	0.449	0.418	0.300	0.220	0.091
EXP3	0.332	0.363	0.332	0.887	0.322	0.296	0.383	0.413	0.393	0.289	0.229	0.111
EXP4	0.365	0.429	0.374	0.914	0.350	0.328	0.413	0.396	0.425	0.298	0.268	0.145
EXP5	0.339	0.389	0.341	0.824	0.317	0.331	0.368	0.351	0.413	0.232	0.315	0.141
EXP6	0.403	0.438	0.389	0.841	0.366	0.347	0.430	0.404	0.396	0.270	0.232	0.098
INT1	0.613	0.621	0.662	0.357	0.914	0.552	0.436	0.426	0.512	0.346	0.359	0.199
INT2	0.627	0.621	0.681	0.390	0.942	0.511	0.393	0.462	0.497	0.359	0.340	0.191
INT3	0.525	0.529	0.639	0.342	0.916	0.448	0.335	0.412	0.439	0.316	0.347	0.158
KNW1	0.533	0.443	0.450	0.355	0.519	0.880	0.412	0.477	0.413	0.285	0.256	0.094
KNW2	0.320	0.263	0.321	0.182	0.353	0.726	0.241	0.249	0.264	0.213	0.319	0.240
KNW3	0.517	0.403	0.390	0.349	0.471	0.883	0.472	0.497	0.370	0.346	0.192	0.097
MSG1	0.407	0.302	0.268	0.410	0.323	0.383	0.734	0.420	0.355	0.499	0.122	0.195
MSG2	0.286	0.249	0.202	0.248	0.278	0.325	0.771	0.336	0.241	0.605	0.163	0.222
MSG3	0.374	0.343	0.278	0.397	0.364	0.385	0.859	0.481	0.328	0.631	0.177	0.231
MSG4	0.396	0.259	0.266	0.421	0.393	0.378	0.828	0.446	0.346	0.560	0.165	0.253
MSG5	0.383	0.314	0.254	0.344	0.333	0.406	0.843	0.426	0.355	0.593	0.257	0.242
PBC1	0.352	0.325	0.305	0.371	0.412	0.482	0.470	0.884	0.508	0.378	0.352	0.094
PBC2	0.316	0.273	0.306	0.346	0.391	0.418	0.430	0.903	0.459	0.371	0.264	0.094
PBC3	0.405	0.375	0.349	0.500	0.448	0.461	0.502	0.886	0.511	0.378	0.293	0.131
SNM1	0.487	0.454	0.437	0.456	0.481	0.392	0.381	0.517	0.932	0.327	0.410	0.122
SNM2	0.457	0.449	0.455	0.450	0.502	0.425	0.400	0.530	0.957	0.316	0.425	0.149
SNM3	0.432	0.460	0.470	0.394	0.496	0.392	0.368	0.520	0.939	0.331	0.426	0.224
SRC1	0.307	0.357	0.291	0.307	0.368	0.326	0.636	0.387	0.313	0.898	0.247	0.268
SRC2	0.264	0.266	0.241	0.252	0.239	0.223	0.579	0.316	0.269	0.778	0.208	0.311
SRC3	0.343	0.309	0.288	0.276	0.328	0.325	0.620	0.376	0.302	0.890	0.204	0.240
TRH2	0.237	0.349	0.300	0.269	0.346	0.307	0.201	0.340	0.379	0.234	0.848	0.194
TRH4	0.225	0.280	0.233	0.175	0.215	0.171	0.139	0.209	0.313	0.153	0.843	0.094
TRH5	0.311	0.306	0.317	0.218	0.346	0.223	0.192	0.272	0.396	0.231	0.785	0.278
USE2	0.100	0.194	0.243	0.094	0.158	0.132	0.245	0.098	0.142	0.250	0.168	0.717
USE3	0.112	0.152	0.153	0.144	0.122	0.193	0.245	0.166	0.143	0.273	0.163	0.713
USE5	0.084	0.151	0.131	0.056	0.117	0.068	0.139	0.068	0.090	0.093	0.182	0.650
USE6	0.055	0.193	0.173	0.022	0.117	0.014	0.128	−0.01	0.061	0.143	0.147	0.688
USE7	0.141	0.172	0.170	0.100	0.153	0.088	0.177	0.069	0.143	0.267	0.158	0.633

Table 6. Discriminant validity: heterotrait-monotrait ratio Statistics (HTMT)

	ATT	AWR	BHV	EXP	INT	KNW	MSG	PBC	SNM	SRC	TRH	USE
ATT
AWR	0.690
BHV	0.665	0.925
EXP	0.446	0.496	0.447
INT	0.699	0.707	0.794	0.423
KNW	0.651	0.530	0.556	0.412	0.632
MSG	0.512	0.410	0.358	0.499	0.469	0.544
PBC	0.446	0.412	0.408	0.503	0.523	0.590	0.599
SNM	0.525	0.528	0.526	0.491	0.564	0.488	0.447	0.612
SRC	0.412	0.422	0.374	0.371	0.419	0.416	0.850	0.497	0.393
TRH	0.375	0.457	0.413	0.315	0.436	0.384	0.262	0.405	0.517	0.315
USE	0.187	0.321	0.318	0.149	0.241	0.236	0.348	0.154	0.207	0.400	0.309

Figure 2. Empirical results of the structural path model. Value on path: p-value,R²: coefficient of determination.

Table 7. Hypothesis and path coefficients significance Testing results

Hypothesis	Relationships between variables	β	t-statistics	Test results
H1	INT → BHV	0,638*	10,532	Support
H2	ATT → INT	0,444*	7,696	Support
H3	KNW → ATT	0,385*	6,969	Support
H4	AWR → KNW	0,281*	3,953	Support
H5	PBC → INT	0,133*	2,072	Support
H6	PBC → BHV	−0,016	0,268	Non-support
H7	SNM → INT	0,155*	2,210	Support
H8	TRH → AWR	0,225*	4,586	Support
H9	TRH → KNW	0,109*	2,240	Support
H10	TRH → ATT	0,120*	2,990	Support
H11	TRH → INT	0,090	1,862	Non-support
H12	TRH → BHV	0,048	1,240	Non-support
H13	USE → AWR	0,104*	2,301	Support
H14	USE → KNW	−0,038	0,813	Non-support
H15	USE → ATT	−0,017	0,390	Non-support
H16	USE → INT	0,048	1,194	Non-support
H17	USE → BHV	0,114*	3,037	Support
H18	EXP → AWR	0,319*	4,549	Support
H19	EXP → KNW	0,070	1,106	Non-support
H20	EXP → ATT	0,164*	2,784	Support
H21	EXP → INT	0,026	0,418	Non-support
H22	EXP → BHV	0,167*	3,196	Support
H23	SRC → AWR	0,143	1,569	Non-support
H24	SRC → KNW	−0,049	0,680	Non-support
H25	SRC → ATT	0,029	0,403	Non-support
H26	SRC → INT	0,054	0,789	Non-support
H27	SRC → BHV	0,069	1,107	Non-support
H28	MSG → AWR	0,039	0,425	Non-support
H29	MSG → KNW	0,354*	4,538	Support
H30	MSG → ATT	0,164*	2,231	Support
H31	MSG → INT	0,000	0,000	Non-support
H32	MSG → BHV	−0,113	1,749	Non-support

*p-value <0.05.

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