AN ANALYSIS OF DETERMINANTS OF THE ADOPTION OF MOBILE HEALTH (MHEALTH)

Martins, Nayra Leandro Miguel; Duarte, Paulo; Pinho, José Carlos M. R.

doi:10.1590/S0034-759020210403x

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ARTICLES • Rev. adm. empres. 61 (4) • 2021 • https://doi.org/10.1590/S0034-759020210403x copy

AN ANALYSIS OF DETERMINANTS OF THE ADOPTION OF MOBILE HEALTH (MHEALTH)

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Given the increasing use of the Internet and mobile technologies, this study is pertinent as it seeks to analyze the factors that determine the adoption of Mobile Health (mHealth). To that end, the proposed conceptual model integrates the Unified Theory of Acceptance and Use of Technology (UTAUT2), Perceived Health Condition, eHealth Literacy and Perceived Health Competence as determinants of the adoption of mHealth. To answer the research questions, we used an online questionnaire administered to a non-probabilistic sample of Brazilian and Portuguese individuals who have or have not used mHealth. Data were analyzed using SPSS and SmartPLS3 software. The results indicate that adoption of mHealth is heavily impacted only by some UTAUT2 variables. The 'Performance Expectancy' dimension was found to heavily impact the adoption of mHealth among both users and non-users.

KEYWORDS:
Perceived health condition; eHealth literacy; perceived health competence; mHealth; UTAUT2

Grupo 1	CFacil	EDesem	EEsforço	Hábito	ISocial	Ineficiência em Saúde	Motiv_Hed	Condição de Saúde	Competência em Saúde	Preço	Adoção mHealth	e-literacia
CFacil	0.754
EDesem	0.520	0.875
EEsforço	0.675	0.361	0.842
Hábito	0.227	0.381	0.150	0.803
ISocial	0.274	0.218	0.151	0.280	0.931
Ineficiência em Saúde	0.161	-0.064	0.206	-0.074	-0.107	0.782
Motiv_Hed	0.179	0.230	0.240	0.309	0.201	-0.004	0.823
Condição de Saúde	0.198	0.192	0.276	-0.016	-0.072	0.520	0.148	0.784
Competência em Saúde	0.178	0.114	0.177	0.196	0.006	0.375	0.241	0.536	0.747
Preço	0.189	0.042	0.310	0.103	0.235	0.073	0.279	0.155	0.156	0.702
Adoção mHealth	0.437	0.705	0.328	0.505	0.298	-0.138	0.437	0.047	0.153	0.137	0.819
e-literacia	0.392	0.250	0.423	0.163	0.026	0.219	0.118	0.369	0.434	0.046	0.217	0.829

Grupo 2	Cond_Facil	Exp_Esfor	Exp_desemp_	Ineficiencia_	Infl_soc	Motiv_Hed	PHC	PHCs	Preço	eHealth	hábito	mAdopt
Cond_Facil	0.728
Exp_Esfor	0.457	0.914
Exp_desemp_	0.415	0.305	0.929
Ineficiencia_	0.066	0.114	-0.061	0.740
Infl_soc	0.324	0.410	0.320	-0.051	0.961
Motiv_Hed	0.284	0.537	0.246	0.040	0.455	0.950
PHC	0.095	0.070	0.055	0.461	-0.071	0.019	0.809
PHCs	0.135	0.125	0.112	0.135	0.045	0.156	0.412	0.804
Preço	0.117	0.304	0.179	-0.038	0.408	0.556	0.010	0.151	0.803
eHealth	0.251	0.300	0.109	0.109	0.021	0.106	0.165	0.132	0.046	0.831
hábito	0.255	0.114	0.299	-0.111	0.234	0.169	-0.027	0.112	-0.012	0.067	0.935
mAdopt	0.368	0.231	0.717	-0.155	0.376	0.265	-0.014	0.162	0.161	0.003	0.353	0.852

	Experienced mHealth (group 1)			Did not experience mHealth (group 2)
Paths	Direct Effects	t-Value (bootstrap)	Supported	Direct Effects	t-Value (bootstrap)	Supported
H1: CSP→ e-Literacia	0.36^* ***** p <0.001 (3,092); unilateral.	5.34	Yes	0.16^* * p <0.05 (1,645);	2.10	Yes
H2: CSP → ad_mHealth	0.10	1.35	No	-0.02	0.40	No
H3a: COMP_S → ad_mHealth	0.06	0.68	No	0.10	1.16	No
H3b: Inefic_S → ad_mHealth	0.07	0.85	No	0.10^* * p <0.05 (1,645);	1.65	Yes
H4: e-Literacia → ad_mHealth	0.02	0.23	No	-0.07	1.16	No
H5a: ED→ ad_mHealth	0.54^* ***** p <0.001 (3,092); unilateral.	6.56	Yes	0.61^* ***** p <0.001 (3,092); unilateral.	11.3	Yes
H5b: EE→ ad_mHealth	0.02	0.36	No	-0.05	0.80	No
H5c: IS→ ad_mHealth	0.04	0.61	No	0.13^* * p <0.05 (1,645);	1.96	Yes
H5d: CF→ ad_mHealth	0.05	0.61	No	0.07	1.15	No
H5e: MH→ ad_mHealth	0.22^* ***** p <0.001 (3,092); unilateral.	3.35	Yes	0.07	0.94	No
H5f: VP→ ad_mHealth	0.01	0.12	No	-0.05	0.47	No
H5g: Hab→ ad_mHealth	0.18^* * p <0.05 (1,645);	2.16	Yes	0.09^* * p <0.05 (1,645);	1.70	Yes

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[1] nayra.martins@islagaia.pt