Reassessing the impact of social media on healthcare delivery: insights from a less digitalized economy

Figures & data

Figure 1. Author proposed conceptual framework.

Table 1. Background information of respondents.

Details	Groups	Frequency (N = 457)	Percentage 100%
Age	Below 30 years	121	26.48
	31–40years	145	31.73
	41–50years	105	22.97
	51 above	86	18.82
Gender	Male	278	60.83
	Female	179	39.17
Level of education	Cert/Diploma	205	44.86
	Degree	115	25.16
	Doctorate	90	19.69
	Others	47	10.28
Work experience	1–3 years	97	21.22
	4–6 years	162	35.45
	Above 7 years	198	43.33
Respondents categories	Doctors	89	19.47
	Nurses	172	37.64
	Physician Assistants	98	21.44
	Pharmacists	32	7.00
	Others	66	14.44

Table 2. Test of validity and reliability of research construct.

Constructs	Dijkstra-Henseler’s rho (ρA)	Jöreskog’s rho (ρc)	Cronbach’s alpha (α)	The average variance extracted (AVE)
Crisis Mgt	0.762	0.861	0.759	0.674
Pat-Doc Comm.	0.768	0.851	0.767	0.589
Healthcare Deliv.	0.802	0.871	0.801	0.627
Info. and Guid. patient	0.823	0.881	0.820	0.650
Public relations	0.797	0.865	0.793	0.616

Source: Author’s processing from PLS-SEM version 4.0.

Table 3. Construct items, loading, and variance inflation factor (VIF).

Construct	Indicator/measurement of operationalization	Loading	VIF
Crisis management	CM1: It helps in information dissemination	0.825	1.495
	CM2: An avenue for public participation to provide timely responses	0.819	1.630
	CM3: Gauge the overall health of the public, and spread messages and awareness	0.819	1.501
Patience-doctor communication	PDC1: Social media communicates more effectively.	0.757	1.486
	PDC2: It improves patient education	0.746	1.421
	PDC3: Enables medical professionals to manage more patients	0.769	1.520
	PDC4: Aids in keeping track of patient’s health and enhancing treatment compliance	0.796	1.597
Healthcare delivery	HCD1: Social media helps in quality health care via its platforms	0.748	1.450
	HCD2: It helps in emergency management & and preparedness.	0.822	1.772
	HCD3: Enhancement in participatory medicine	0.812	1.811
	HCD4: Allows physicians to handle a larger number of patients	0.785	1.450
Information and guidance to patients	IGP1: In my view, social media has created a platform for information sharing and assistance to patients	0.823	1.862
	IGP2: Information shared is confidential between patient-health care professionals.	0.808	1.777
	IGP3: Doctor-patients use social media as a channel to get feedback.	0.820	1.707
	IGP4: It serves as a means of advice	0.772	1.575
Public relations	BD1: There are opportunities to interact with healthcare professionals on various SM platforms	0.798	2.9831
	BD2: Awareness can be created through Social media	0.784	2.5374
	BD3: It serves as a medium for public education.	0.792	2.6430
	BD4: Reassures patient about the disease	0.765	3.2220

Source: Author’s processing from PLS-SEM version 4.0 software.

Table 4. Discriminant validity using Fornell Larcker.

Constructs	CM	PDC	HDC	IGP	PC
Crisis management	0.821
Patience-doctor communication	0.694	0.767
Healthcare delivery	0.730	0.709	0.792
Information and guidance to patients	0.769	0.763	0.720	0.806
Public relations	0.762	0.723	0.699	0.793	0.785

Source: Author’s processing from PLS-SEM version 4.0.

Note: The diagonal bold values are the square root of the average variance extracted.

Figure 2. Estimated research model.

Source: Authors’ processing form PSL-SEM software.

Table 5. Hypothesis testing.

Effect	Beta (β)	Standard bootstrap results
		Mean value	Standard error	t-Value	p-Value (2-sided)	Decision
Direct effect
H1: CM->HDC	0.312	0.309	0.069	4.517	0.000	Agreed
H2:PDC->HDC	0.264	0.265	0.072	3.680	0.000	Agreed
H3: IGP->HDC	0.174	0.174	0.074	2.355	0.019	Agreed
H4: PR->HDC	0.133	0.135	0.080	1.666	0.096	Not Agreed
Construct	Coefficients of determination (R^2)			Adjusted R^2
Healthcare delivery	0.632			0.628

Source: Author’s processing from PLS-SEM version 4.0 software.

Data availability statement

The data will be made available upon the request of the editor subject to the approval of the research respondents.