A cross-sectional study on exploring the antecedents of patient’s revisit intention: Mediating role of trust in the hospital among patients in India

Nahima Akthar; Smitha Nayak; Yogesh Pai P

doi:10.12688/f1000research.128220.2

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Research Article

Revised

A cross-sectional study on exploring the antecedents of patient’s revisit intention: Mediating role of trust in the hospital among patients in India

[version 2; peer review: 2 approved]

Nahima Akthar¹, Smitha Nayak ², Yogesh Pai P³

PUBLISHED 10 Aug 2023

Author details Author details

¹ Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India
² Additional Professor, Department of Humanities and Management, Manipal Institute of Technology, Manipal Academy of Higehr Education, Manipal, India
³ Professor - Senior Scale and Head of the Department, Department of Humanities and Management, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

Nahima Akthar
Roles: Conceptualization, Data Curation, Investigation, Methodology, Project Administration, Resources, Writing – Original Draft Preparation, Writing – Review & Editing

Smitha Nayak
Roles: Conceptualization, Formal Analysis, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Yogesh Pai P
Roles: Conceptualization, Methodology, Supervision, Visualization, Writing – Review & Editing

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This article is included in the Health Services gateway.

Abstract

Background: In the healthcare domain, patients’ trust in the hospital plays an instrumental role in determining the behavioral intention of the patient. This article attempts to investigate the impact of service quality perception on behavioral intention with the mediating effect of trust in the hospital and patient satisfaction.
Methods: This research was carried out in multispecialty hospitals located in Bangalore Urban and Mysore districts of Karnataka during August 2021. This was a questionnaire-based study and the sample size was 242. Statistical Package for the Social Science (SPSS) 27.0 and SmartPLS 3.0 software was used to analyze the data.
Results: The findings revealed that perceived service quality significantly influences trust through patient satisfaction (observed partial mediation) and patient satisfaction significantly impacts behavioral intention through trust (observed partial mediation).
Conclusion: This study empowers hospital managers to understand the factors influencing behavioral intention. Healthcare professionals must ensure that good quality service is delivered to enhance patient satisfaction and trust in adverse services, which influence behavioral intention among the patients.

Keywords

Healthcare, service quality, satisfaction, trust, revisit intention, structural equation modeling, adverse services

Corresponding author: Smitha Nayak

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2023 Akthar N et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Akthar N, Nayak S and Pai P Y. A cross-sectional study on exploring the antecedents of patient’s revisit intention: Mediating role of trust in the hospital among patients in India [version 2; peer review: 2 approved]. F1000Research 2023, 12:75 (https://doi.org/10.12688/f1000research.128220.2) First published: 19 Jan 2023, 12:75 (https://doi.org/10.12688/f1000research.128220.1) Latest published: 18 Mar 2024, 12:75 (https://doi.org/10.12688/f1000research.128220.3)

Revised Amendments from Version 1

The following changes are incorporated in the manuscript:
1. reference quoted for sample size determination
2. mentioned limitations as directed by reviewer
3. strengthened the implications in the discussion section

See the authors' detailed response to the review by Satyanarayana Rentala
See the authors' detailed response to the review by Prof. (Adj.) Dr. Supaprawat Siripipatthanakul

Introduction

The service sector has a substantial influence on a country’s development and is increasingly driving economic transformation. The service sector accounted for approximately 55% of the gross domestic product (GDP) and 45% of employment in developing economies in 2019.¹ The service sector constitutes diverse services like healthcare, banking, hospitality, consultancy, and entertainment, to name a few. In services like healthcare, customer undergoes stressful situation, in terms of treatment process etc., hence create an unpleasant experience for the customer.²^,³ Healthcare service providers are leaving no stone unturned to create a positive servicescape to nurture an enabling environment for patients. Hence, service quality has attracted significant research and academic interest. Patient expectations for increasing levels of healthcare service quality are primarily triggered by rising healthcare demand and informed consumer decision-making.⁴^–⁶

Researchers have shown that healthcare services are evaluated based on service quality and medical efficacy.⁷^–¹⁰ Service quality (SQ) is termed as the process of meeting consumers’ expectations by providing excellent services.¹¹ Service quality evaluation helps to identify the unmet needs of the patients during the service encounter. In the healthcare landscape, SQ is crucial and it has a meaningful effect on patient satisfaction (PS).¹²^–¹⁶

Patients evaluate healthcare service quality based on their personal experiences, therefore a user-centered approach to healthcare delivery is critical for increasing overall patient satisfaction.⁴^,¹⁷ Patients believe that the Health Care Organization (HCO) meets their expectations when they receive essential healthcare services, which results in a strong bond between the patients and the HCO.¹⁸ Patients’ perceptions of medical staff’s trustworthiness and the degree of satisfaction with the care they receive are directly related to each other. As a result, when patients require healthcare services again, they will seek the same facility and physician. Researchers have discovered that SQ is a precursor to PS, and satisfaction is an antecedent to trust.¹²^,¹⁹

When patients receive satisfactory medical care, they trust the hospital and return for future medical treatment.²⁰^–²² Patients shift to another hospital if the SQ of the hospital declines.⁴ Patients’ willingness to visit the hospital again for their treatment is referred to as “intent to revisit”.²³ The effect of hospital SQ on PS and intent to return has been investigated by the researchers.²⁴^,²⁵ Patients’ revisit intent and the services rendered by healthcare professionals are also studied in the past.¹⁶ This is in line with the service marketing literature, which reiterates the importance of trust in the service provider and trust in the brand of the service provider.²⁶ The “Commitment-Trust Theory (CTT)” proposed by Morgan and Hunt (1994) has shown the relevance of trust and commitment in developing effective long-term partnerships in the service industry.²⁷^,²⁸ Relationships are established on the foundation of mutual commitment in the services relationship marketing area.²⁹ Customer commitment is defined as the customer’s long-term aim to create and maintain a connection with the supplier.³⁰ Furthermore, commitment is a feature that has been widely identified in earlier studies as a key predictor of sustained usage. In addition, it was found that dedication had a considerable beneficial impact on consumers’ recommendations. Loyal consumers assume the role of company advocates by spreading favorable word of mouth and recommending the service to others.³¹

In the Jordanian setting, researchers have explored the association between perceived service quality (PSQ), PS, and trust in the service provider.¹² They opined that trust in the service provider played an instrumental role in determining perceived service quality and patient satisfaction. The association of patients’ revisit intention has been researched with constructs like satisfaction, medical SQ, hospital brand image, assurance, and word-of-mouth.²⁴^,²⁵^,³² Researchers have explored the constructs such as PSQ, customer satisfaction, perceived value, brand trust, loyalty, and behavioral intention (BI) in various service sectors.³³^–³⁶ However, literature on influencing BI through PSQ, PS, and trust in the hospital in the Indian context has received less attention. Therefore, this study proposes a conceptual framework and tests the relationship between the constructs in an attempt to bridge the gap. The objectives of the study are:

• To investigate the mediating effect of patient satisfaction between perceived service quality and trust in the hospital
• To examine the role of trust in mediating the relationship between patient satisfaction and behavioral intention

This research paper is structured as follows: First, a review of the literature and hypothesis development is explained. Secondly, the methodology adopted and results are presented. The report concludes with a discussion of the results, limitations, and useful implications, as well as recommendations for additional research.

Review of literature

Perceived service quality (PSQ)

Service quality (SQ) is regarded as a vital aspect of modern service firms.³⁷ “SQ is the delivery of excellent or superior service relative to customer expectations”.¹¹ “PSQ is defined as the consumer’s judgment about a product’s overall excellence or superiority”.³⁸ In hospitals, SQ is appraised based on care provided by healthcare personnel, not only the technical aspect.⁶ Researchers have proposed that healthcare SQ acts as a mirror of PS.¹³ Also, SQ and consumer loyalty are strongly associated with each other.³⁹^,⁴⁰ In addition, SQ is a key element to an effective consumer relationship.¹⁸^,⁴¹

Patient satisfaction (PS)

“Satisfaction is defined as the consumer’s fulfillment response, a post-consumption judgment by the consumer that a service provides a pleasing level of consumption-related fulfillment including under or over fulfillment”.⁴² Like other services, customer or patient satisfaction is also considered to be a significant service outcome. PS is deliberated as one of the fundamental parameters of healthcare quality. Satisfaction among patients is a multi-dimensional concept.¹⁷ “PS is a patient’s sensation of joy or disappointment as a result of comparing a perceived service performance to his or her expectations”.⁴³

PS is a result of a patient’s experience of receiving medical services, and it displays a variety of functions concerning consumer relationships.¹⁷ Researchers have suggested that satisfaction is known as a global consumer response since it results from consumers’ pleasure levels.⁴³ Healthcare professionals must ensure that they provide good quality services to meet patients’ anticipations thereby improving satisfaction. Therefore, hospitals must work consistently to meet their patient’s expectations.¹²^,⁴⁴

Trust

“Trust is the client’s confidence that the service provider will fulfill his/her expectations by delivering what was promised explicitly and implicitly”.⁴⁵ An organization must maintain customers’ trust, which will enhance competition and accomplishment of goals.⁴⁶ A service provider is expected to work in favor of the patient when there is trust between them.⁴⁷ “Trust is defined as a willingness to rely on an exchange partner in whom one has confidence”.⁴⁸ Trust arises from faith and reliability. Hence, good relationships are developed and maintained.²⁶ Positive behavioral intents are developed as a result of mutual trust among the partners. Trust inspires both parties to maintain the relationships.¹⁶^,⁴⁹ Through repeated encounters, trust is gradually created, and these interactions influence customers’ revisit intention.⁵⁰

“Patient trust is defined as patient’s belief that their doctors would act in their best interests and offer proper treatment and medical care”.⁵¹ Researchers have suggested that trust is essential since it serves as a foundation for upcoming associations. Patients usually evaluate the services provided by the healthcare professionals which leads to trust in the hospital brand.³⁰^,⁵² Customers revisit the service entity when they trust that service brand, which results in increasing the profit.⁵² Researchers have observed that building trust in the healthcare brand is very essential for selecting a hospital for treatment and continuing the treatment with the same hospital.¹⁶^,⁵³

Behavioral Intention (BI)

“BI can be defined as the likelihood that an individual will take part in a particular behavior and represents the level of effort that an individual is willing to make to secure a specific behavior”.⁵⁴ BI concerns the hospital talks about the preparedness of patients to come back to the same hospital for their treatment. Retaining a client is very essential for the long-standing achievement of any service provider.²⁵ Researchers have proposed that if a service is evaluated positively, then the desired BI of the client build up liaison with the provider. BI is divided into desirable and undesirable intentions. Clients with desirable BI think optimistically about the provider and recommend it to others.⁵⁵

The key elements of BI are “SQ”, “customer satisfaction”, “perceived value”, and “customer loyalty”.⁵⁶ Past research shows that client behavior is critical to the profitability and long-term viability of any service business.⁵⁷ Customer satisfaction results from service contact having a direct impact on consumer behavior. Satisfied customers are more likely to experience positive behavior and stick to the same service provider. Client pleasure not only increases the company’s relationship with its customers but also aids in customer retention.⁵⁸^,⁵⁹

Perceived service quality and patient satisfaction

“Satisfaction is defined as an assessment of service experience, either specific or global, influenced by SQ among other factors”.⁶⁰ The relationship between SQ and customer satisfaction (CS) is well-established by researchers from various sectors.²⁴^,⁶¹^,⁶² Researchers view SQ as a precursor of CS.³⁷^,⁶²^,⁶³ In HCO, the relationship between healthcare quality and PS is significant.²⁵^,⁴³^,⁶³ When patients’ necessities and anticipations are equal to the quality services of the hospital, the patient will be satisfied.⁶⁴^,⁶⁵ A linear liaison between SQ and PS (increased satisfaction level) is observed when the SQ is at a higher level.¹³^,²⁵ Hence, it is expected that there is a significant association between PSQ and PS.

HI: PSQ is significantly related to PS.

Patient satisfaction and trust

Patient satisfaction serves as a key factor when evaluating the quality of healthcare services.⁷^,²⁵^,⁴⁴ Based on an assessment of their impression and service outcome expectations, customers are either satisfied or dissatisfied.⁶⁶ PS is a multi-faceted aspect of the healthcare industry that has an impact on patient trust.¹²^,⁴³ Trust is denoted as a key factor in any relationship. It is crucial since it is the most important part of any exchange connection.⁵³^,⁶⁷

According to past research, CS is critical for building customer trust and loyalty.⁴⁵^,⁶⁸ Researchers have witnessed that satisfaction is a precursor of trust.⁶⁹^,⁷⁰ Scholars have revealed that CS and trust play a crucial role in service sectors like tourism,⁴⁵ retail,⁷¹ and public services.⁶⁶ Trust can be developed over some time, based on CS.¹⁹^,⁷² Customer trust is regarded as a crucial construct concerning satisfaction in marketing and consumer behavior research.²¹ Therefore, we propose that PS has a significant positive influence on trust in the hospital.

H2: PS is positively related to trust in the hospital.

The mediating role of PS

PS results from healthcare SQ which leads to trust in the hospital. PS is a processing feature of trust.¹² Perceived quality has a large and beneficial effect on consumer trust. SQ is a key precursor to customer trust.²⁸^,⁷² CS is a mediator in the relationship between SQ and consumer trust.¹²^,¹⁹ Hence, we tend to establish that the liaison between PSQ and trust in the hospital is mediated by PS.

H3: The link between PSQ and trust in the hospital is mediated by PS.

Trust and BI

The effect of trust on BI has been exhaustively studied in the marketing literature.³⁰^,³²^,⁴⁹^,⁷³ Customers’ BI can be developed and maintained with the use of trust.⁶⁷^,⁷⁴ Trust and commitment are the main drivers of intent to return. Customers’ intentions to recommend the brand and make repeat purchases are also influenced by their degree of trust in the company.²³

In service sectors, the association between brand trust and revisit intention is studied previously.⁷⁵^,⁷⁶ Maintaining customer-provider relationships requires a high level of trust.¹⁶^,⁴⁹^,⁷⁴ Overall, past empirical research supports the idea that trust is important in the establishment of BI. The trust–BI relationship has received a lot of attention and support, especially in the context of the service sector.⁴⁰^,⁴⁶ Hence, we propose that trust in the hospital significantly contributes to BI of the customer.

H4: Trust in the hospital is positively related to BI.

The mediating role of trust

The first research on healthcare trust concentrated on the interpersonal trust of the patient in their doctors.⁵¹ Scholars have investigated the impact of trust and assurance on “relationship marketing performance”.²⁶ Trust has been studied as a mediator in other business entities.⁵⁰^,⁷⁷^,⁷⁸ In a hospital, trust is important in the interaction between healthcare personnel and patients.¹⁶^,⁷⁹^,⁸⁰

Scholars have observed that a positive service evaluation (cognition response) has a favorable impact on patients’ trust in healthcare interactions.⁸¹ Trust has been established as a strong mediator among PSQ and intent to return to avail medical care.¹⁶ Patients’ perceptions of medical staff’s trustworthiness have an impact on their satisfaction level through the care they received. Studies have found that customers develop trust in the organization only if they are satisfied with the service provider.²¹^,⁶⁷ Hence, we tend to establish that the liaison between PS and BI is mediated by trust in the hospital.

H5: The association between PS and BI is mediated by trust in the hospital.

The proposed conceptual framework (Figure 1) suggests that PSQ influences BI through PS and trust in the hospital.

Figure 1. Proposed conceptual framework.

Methods

Study design

This research endeavor is quantitative by nature and has adopted a “cross-sectional research design”. The research philosophy deliberated in this study is “post-positivism”, which deals with the development of empirical approaches to interpret and study the behavior of people. This study explores the association between the independent, dependent, and mediating variables as proposed in the conceptual framework.

Study setting

There is significant research evidence to indicate a strong relationship between human development index (HDI) and life satisfaction.⁸²^,⁸³ Districts were ranked based on the HDI report of Karnataka state.⁸⁴: 4 districts ranked high as per the HDI report namely, Bangalore Urban, Dakshina Kannada, Udupi, and Mysore. For this study, Bangalore Urban and Mysore Districts were selected through a simple random sampling approach. This research was undertaken in three multispecialty hospitals located in Bangalore Urban and one located in Mysore during 4^th August 2021 to 26^th August 2021.

Eligibility criteria

The study comprised of patients within the 18-65 years of age group, who knew English or Kannada, and consulted the outpatient department at least two times. Medicine and medical specializations, as well as surgery and surgical specialties, were the outpatient departments (OPDs) studied. Pediatric and psychiatric OPDs were not included in the study.

Data Sources/Measurements

A structured questionnaire was used to gather the data. A copy of the questionnaire can be found in the Extended data.⁸⁵ The survey included scales for assessing SQ perceptions,⁸⁶^,⁸⁷ PS,⁴²^,⁸⁸ trust,⁴⁷ and BI.⁵⁶ All the scales were scored on a “five-point Likert scale”. The questionnaire featured a total of 27 questions, 6 of which were about the participants’ demographics and 21 of which were about the study’s constructs. The questionnaire was developed in English and translated into the Kannada language in Microsoft Word 2013. The printed version of the questionnaire was utilized for data collection. Participation in the study was voluntary. The respondents were given a participant information sheet that explained the study’s purpose and procedures. After obtaining written agreement from the subjects, the investigator handed over the questionnaire to them. The research subjects were directed by the researcher to mark the right point on the questionnaire. The questionnaire was completed by all 242 participants; no partially completed questionnaires were acquired. The data were collected during 4^th August 2021 to 26^th August 2021.

Study size

This study adopted the purposive sampling method. A total of 242 respondents participated in this study. Respondents were contacted at the pharmacy, which was their last point of contact with the hospital for outpatient services.

The sample size was generated by multiplying the number of elements on the rating scale by ten⁸⁹ i.e. 21*10 = 210. Considering 10% of the unanswered sample (i.e. 21) gave rise to 231 (210+21=231). Finally, the researcher approached 242 participants to collect the data.⁹⁰

Statistical methods

The preliminary analysis was performed using IBM SPSS statistics 27 (IBM SPSS Statistics, RRID: SCR_016479; Armonk, NY: IBM Corp). The frequency distribution of the demographic variables has been presented in the result section. SmartPLS 3 (smartPLS, RRID: SCR_022040) was used to test the proposed hypotheses and perform the mediation analysis. Partial least squares-structural equation modeling (PLS-SEM) was used to test linear and additive models. PLS-SEM is becoming more popular in healthcare research, as it is a suitable and reliable tool for analyzing composite models in empirical studies.⁹⁰ In the following sections, the results are presented in the form of figures and tables.

Ethical considerations

The ethical approval (IEC: 868/2020) was granted by “The Institutional Ethics Committee (IEC) of Kasturba Medical College and Kasturba Hospital, Manipal”. The data were kept completely undisclosed and no participant identifiers are used.

Pilot testing

Finally, a pretest of the questionnaire was conducted on a sample of 47 outpatients in the Udupi area before the actual survey. There were no reported misconceptions or difficulties with the questions. The constructs had Cronbach’s alpha values of >0.7, specifying good levels of internal consistency such as BI (0.891), trust (0.875), PS (0.862), and PSQ (0.756). A main components analysis of the data was used to get a preliminary indication of construct validity. All factor loadings and communalities were considerably over 0.50, and “Kaiser–Meyer–Olkin and Bartlett’s test” was significant and >0.80.

Results

The frequencies and percentages of the demographic variables were estimated using the software SPSS version 27 and the output is presented in Tables 1 & 2. The complete dataset is found in the Underlying data.⁸⁵

Table 1. Demographic characteristics (N=242).

Demographics	Components	N	%
Gender	Male	133	55.0
Gender	Female	109	45.0
Age	18—25	38	15.7
	26—40	132	54.5
	41—55	54	22.3
	56—65	18	7.4
Education	Up to 12th	95	39.3
	Graduate	103	42.6
	Postgraduate	44	18.2
Occupation	Unemployed	93	38.4
	Employed	75	31.0
	Professional	47	19.4
	Business	27	11.2
Monthly Income	25000 and below	162	66.9
	25001-75000	64	26.4
	75001-125000	9	3.7
	125001-200000	5	2.1
	Above 200000	2	.8

Table 2. Outpatient Departments involved in the study.

Category	Departments	N	%
Medicine	Medicine	69	28.5
Medical Specialty	Cardiology	14	5.8
	Dental	4	1.7
	Dermatology	12	5.0
	Endocrinology	9	3.7
	ENT	14	5.8
	Gastroenterology	2	.8
	Nephrology	17	7.0
	Neurology	13	5.4
	OBG	24	9.9
	Oncology	14	5.8
	Ophthalmology	9	3.7
	Ortho	16	6.6
	Pulmonology	2	.8
	Urology	15	6.2
Surgery	Surgery	7	2.9
Surgical specialty	Neurosurgery	1	.4

Structural model

The structural model evaluation is represented below (Figure 2).

Figure 2. Structural model evaluation.

The reliability and validity of constructs were investigated using outer loadings, composite reliability, average variance extracted (AVE), and variance inflated factor (VIF).⁸⁹ The output is presented in the table below (Table 3). Composite reliability was used to examine the internal consistency reliability of constructs.⁹¹ The composite reliability of all the constructs is above the threshold value. In PLS, the indicators were placed in order based on their reliability. Cronbach’s alpha implies that all indications are equally reliable. Cronbach’s alpha value of all the constructs was above 0.7.⁹² AVE numbers were used to quantify convergent validity, which is the ability of a latent concept to elucidate a large portion of the variance in its indicators. The constructs’ AVEs were well above the threshold value of 0.5.⁹³

Table 3. Evaluation of the structural model.

Construct	Indicators	Outer loadings	Composite Reliability	AVE	Cronbach’s Alpha	Outer weights	VIF
Perceived Service Quality	PSQ1	0.860***	0.901	0.695	0.854	0.303***	2.194
	PSQ2	0.842***				0.317***	1.961
	PSQ3	0.818***				0.295***	1.837
	PSQ4	0.814***				0.284***	1.843
Patient Satisfaction	PS1	0.790***	0.905	0.655	0.868	0.225***	2.025
	PS2	0.826***				0.245***	2.107
	PS3	0.816***				0.269***	2.041
	PS4	0.788***				0.232***	1.915
	PS5	0.825***				0.264***	2.140
Trust	T1	0.861***	0.919	0.694	0.889	0.252***	2.620
	T2	0.746***				0.233***	1.635
	T3	0.842***				0.247***	2.226
	T4	0.870***				0.235***	2.808
	T5	0.841***				0.234***	2.375
Behavioral Intentions	BI1	0.837***	0.911	0.672	0.877	0.255***	2.197
	BI2	0.808***				0.236***	1.984
	BI3	0.830***				0.246***	2.177
	BI4	0.852***				0.250***	2.343
	BI5	0.767***				0.232***	1.728

*** p<0.01,

** <0.05,

* p<0.1.

Assessment of collinearity

The guiding principle of VIF is considered to test the collinearity among the constructs.⁸⁹ All the constructs exhibited VIF lesser than 5. This explains that there is no problem with collinearity in the structural model. Table 4, given below, demonstrates the VIF values that this study obtained while we tested the collinearity among independent variables against their respective endogenous constructs. The VIF values of this study were obtained when the collinearity was tested among all the constructs of the inner model of this study. The process of data analysis began with the objective to find out the probability of the presence of collinearity among exogenous constructs. No collinearity was found among the exogenous constructs of this study.

Table 4. Evaluating collinearity for exogenous constructs through VIF inner model.

Constructs	BI	PS	Trust
PS	3.917	NA	3.375
PSQ	NA	1.000	3.375
Trust	3.917	NA	NA

Table 5 given below shows the VIF values of this study obtained when the collinearity was tested among all the indicators of the outer model of this study.

Table 5. Evaluating collinearity for indicators through VIF outer model.

Indicators	VIF	Indicators	VIF	Indicators	VIF	Indicators	VIF
BI1	2.197	PS1	2.025	PSQ1	2.194	T1	2.620
BI2	1.984	PS2	2.107	PSQ2	1.961	T2	1.635
BI3	2.177	PS3	2.041	PSQ3	1.837	T3	2.226
BI4	2.343	PS4	1.915	PSQ4	1.843	T4	2.808
BI5	1.728	PS5	2.140	NA	-------	T5	2.375

As the above tables demonstrate, there are no collinearity issues in the structural model of this research endeavor. Thus, there is no multicollinearity among either the constructs of the study (inner model) or indicators of the study (outer model). Multicollinearity is not an issue by the criterion VIF < 5.⁸⁹

Discriminant validity among latent constructs: Cross-loading method

Cross-loadings (CL) of indicators constitute an additional method of assessing discriminant validity (DV). The outer loadings of indicators are expected to be greater than their CL on other constructs.⁸⁹ The below-mentioned table (Table 6) demonstrates the presence of DV in the constructs of the study.

Table 6. Discriminant validity by the cross-loading method.

	BI	PS	PSQ	Trust
BI1	0.837	0.759	0.649	0.756
BI2	0.808	0.698	0.608	0.702
BI3	0.830	0.750	0.682	0.713
BI4	0.852	0.746	0.670	0.742
BI5	0.767	0.672	0.649	0.707
PS1	0.653	0.790	0.625	0.620
PS2	0.748	0.826	0.641	0.681
PS3	0.748	0.816	0.801	0.728
PS4	0.658	0.788	0.605	0.691
PS5	0.764	0.825	0.704	0.760
PSQ1	0.663	0.688	0.860	0.710
PSQ2	0.711	0.728	0.842	0.731
PSQ3	0.614	0.716	0.818	0.643
PSQ4	0.662	0.664	0.814	0.644
T1	0.790	0.739	0.693	0.861
T2	0.691	0.735	0.647	0.746
T3	0.751	0.732	0.726	0.842
T4	0.738	0.684	0.642	0.870
T5	0.704	0.700	0.699	0.841

Hypotheses testing

All exogenous latent variables’ effect sizes, f², were estimated (Table 7). The magnitude of the variables’ influence is reflected by f², regardless of the sample size.⁹⁴ A strong effect is reported when the effect size exceeds 0.35; a moderate effect is given when the effect size is between 0.15 and 0.35, and a small influence is recorded when the effect size is less than 0.15 stated as a low effect. PSQ on PS (f²=2.375), PS on trust (f²=0.464), trust on BI (f²=0.352), and PS on BI (f²=0.368) are assessed to have substantial effect sizes in this study. The value of the standard root mean square residual (SRMR) is used to measure model fitness. The threshold value of SRMR is <0.8.⁹⁵ This model’s SRMR rating is 0.066, indicating that it fits the data well.

Table 7. Hypothesis testing (f²) and Predictive relevance test (q²).

Relationship	Path Coefficient	t-Value	Bias Corrected 95% Confidence Interval	f²	q²
PSQ -> PS	0.839***	34.906	(0.781 0.878)	2.375	Not Defined
PS -> Trust	0.593***	7.458	(0.433, 0.748)	0.464	0.451
PSQ -> Trust	0.322***	3.703	(0.153, 0.493)	0.137	Not Defined
Trust -> BI	0.469***	6.480	(0.330, 0.493)	0.352	0.528
PS -> BI	0.480***	6.655	(0.333, 0.617)	0.368	0.556

*** p<0.01,

** <0.05,

* p<0.1.

Predictive relevance test (Q²)

Blindfolding is a technique for reusing samples. It allows you to calculate the Q² value,⁹⁶^,⁹⁷ which is an evaluation criterion for the PLS path model’s cross-validated predictive significance. Q² values greater than zero suggest that your data is well rebuilt and the model is predictive. The Q² values of the dependent and mediating variables are presented in the table below (Table 7).

Mediation analysis

This research endeavor includes two mediations. First, the latent variable PS is a mediator amongst the latent variables PSQ and trust in the hospital (Figure 3). A partial mediation has been observed and it is presented in the table below (Table 8). Second, the latent variable ‘trust in hospital’ is a mediating variable between the latent variables PS and BI (Figure 4). A partial mediation has been observed and it is presented below (Table 9).

Figure 3. The mediating role of patient satisfaction.

Table 8. The mediating role of patient satisfaction.

	Direct Effect	Indirect Effect	VAF	Mediation
Figure 3	0.320***	0.501***	61%	Partial

*** p<0.01,

** <0.05,

* p<0.1.

Figure 4. The mediating role of trust in the hospital.

Table 9. The mediating role of trust.

	Direct Effect	Indirect Effect	VAF	Mediation
Figure 4	0.479***	0.406***	46%	Partial

*** p<0.01,

** <0.05,

* p<0.1.

Importance performance matrix analysis (IPMA)

IPMA allows investigators to look at an item’s importance as well as its performance. The goal of this analysis is to determine the overall influence of the preceding constructs (PSQ, PS, and trust) in predicting the endogenous construct (BI).⁸⁹ The total effect determines the construct’s relevance, while the performance is determined by the mean value of their score (from 0 to 100).⁹⁸^,⁹⁹

IPMA’s findings are shown in Figure 5 and Table 10. PS outperforms the other exogenous constructs in terms of performance (80.815), according to analyses. Furthermore, PS has a total effect on BI of 0.759, which is quite strong. As a result, a unit increase in PS performance from 80.815 to 81.815 results in a performance gain in BI from 80.046 to 80.805. The exogenous construct PSQ has a total effect of 0.787 and a performance of 79.916. As a result, a one-unit improvement in PSQ from 79.916 to 80.916 would boost BI’s performance from 80.046 to 80.833. Similarly, the exogenous construct trust has a total effect of 0.469 and a performance of 78.581. As a result, a one-unit increase in trust from 78.581 to 79.581 would result in an increase in BI to 80.515. PS has a robust and significant influence on BI, followed by PSQ and trust. This has significant implications for healthcare practitioners.

Figure 5. Importance performance matrix analysis.

Table 10. IPMA of Institutional Efficacy.

	Behavioral Intention (BI)
Latent Constructs	Importance (Total Effects)	Performance (Index Values)
Patient satisfaction (PS)	0.759	80.815
Perceived service quality (PSQ)	0.787	79.916
Trust	0.469	78.581

Importance performance map

Figure 6 shows the performance of the exogenous constructs. PS is high on performance whereas trust in the hospital is low on performance.

Figure 6. Importance performance map.

Discussion

In this research endeavor, the researchers observed that PS and trust in the hospital play a vital role in developing BI. In adverse services, PSQ and PS support building trust in the hospital. When a patient trusts the hospital, he/she intends to visit the hospital again for their treatment. PSQ, PS, and trust in the hospital are explored as an antecedent to BI. This study concludes that patient who is satisfied with the healthcare services received will develop trust in that hospital and continues to visit the hospital for treatment in the future.

In this study, a partial mediation relationship is observed between PSQ and trust in the hospital. Also, there is a partial mediating relationship between PS and BI. This study consists of a conceptual framework; the hypotheses were proposed based on the literature review explaining the association between the constructs. The proposed model is empirically tested, and validity and reliability of the constructs were estimated. Hypotheses testing and mediation analysis were done. IPMA was done to estimate the performance of endogenous variables through the exogenous variables.

The objective of this paper is to investigate the influence of PSQ on BI through PS and trust in the hospital. This paper includes a conceptual framework and hypotheses. The first hypothesis was that PSQ and PS are significantly related to each other. This hypothesis is in line with the literature that shows a significant relationship between healthcare quality and PS.⁴³ Secondly, researchers hypothesized that PS is positively related to trust. It was shown by researchers in the past that PS is a multi-dimensional element of the healthcare sector that influences patient trust.¹²^,⁴³ Past literature has shown that satisfaction is an antecedent of trust.⁷⁰ Further, it was hypothesized that the association between PSQ and trust in the hospital is mediated by PS. PS results from healthcare SQ which in turn leads to trust. PS is a processing feature of trust.¹² In the service sector, the influence of SQ on building trust will be through consumers’ satisfaction.⁷²

The next hypothesis states that trust in the hospital is significantly associated with BI. Past studies have explored the relationship between trust and BI in the marketing domain.²⁶^,³⁰^,⁴⁹^,⁷³ Past empirical research recommended that trust is essential to establish BI, especially in service sectors.⁴⁶^,⁷⁵^,⁷⁶ Scholars have suggested that building trust in any institution results in repeat business.²⁹ Last, the researchers hypothesized that trust in the hospital acts as a mediator between PS and BI. Scholars have observed that trust plays a mediating role in service entities.⁵⁰^,⁷⁷^,⁷⁸ Trust is exhibited as a mediator between perceived quality and intent to visit for medical treatment.¹⁶ IPMA determines that the performance of the construct PS is higher than the other exogenous constructs concerning BI. Trust in the hospital is low on performance. Therefore, it is important to build trust in the hospital and enhance behavioral intent.

The findings of the study imply a few managerial implications that are mentioned here. This study suggests that service providers should obtain customer input on the services received. Service providers should deliver error-free services to ensure satisfaction. It also aids in matching and comprehending customer expectations. The staff’s readiness to serve the patients is demonstrated by their willingness to provide service without being asked. Measurement of healthcare service quality should include factors such as personnel technical experience, availability of additional amenities such as medical equipment, and availability of various types of drugs. Hospitals should give effective training to all employees including nurses, doctors, and general staff to improve their communication so that they can deliver excellent service to patients. In a hospital, it is important to deliver the services to the best, which improves PS. Medical professionals should be consumer-oriented and deliver high-quality services with a human touch. Along with the quality of services, maintaining a patient-provider relationship is also very essential. This relationship becomes the base of developing trust in the hospital. This trust then influences repeat visits which aid in profitability. Therefore, trust in the hospital plays a vital role in enhancing the BI of a patient.

Conclusion

This study provides several insights for healthcare organizations to develop BI by enhancing trust in the hospital. A hospital can assure the satisfaction of patients when good quality services are rendered by healthcare professionals. Satisfied patients form the bedrock of trust in any hospital, and this trust, in turn, plays a pivotal role in influencing their intention to revisit the facility for future medical needs. Patient satisfaction (PS) serves as a crucial mediator between the perceived service quality and the establishment of trust in the hospital. To enhance trust among patients, healthcare providers must focus on several key aspects. First and foremost, the hospital should consistently deliver high-quality and compassionate care across all departments. Effective communication, empathy, and respect for patients’ privacy and confidentiality are also essential in fostering trust. Educating patients about their health conditions and involving them in their care decisions can further strengthen the bond of trust. Regular follow-up care, transparent feedback mechanisms, and community engagement initiatives can also contribute to building a strong foundation of trust with patients. By emphasizing patient-centred care and continually striving to improve services, hospitals can enhance trust among patients, leading to improved satisfaction and increased revisit intentions. Trust in the hospital has a significant mediating effect between PS and BI. Thus, we can conclude that improving PS and trust in the hospital is essential to having a positive intention to revisit the healthcare organization.

Unlike other studies, this study also has a few limitations which pave the way for future researchers. First, this study was conducted in outpatient departments of multispecialty hospitals in 2021. Future researchers would do a comparative study including both inpatients and outpatients in the present context. Second, the hospitals were situated in higher HDI districts. Future researchers would consider lower as well as higher HDI districts and carry out a comparative study.

Data availability

Underlying data

Figshare: Underlying data: A Cross-sectional study on Exploring the Antecedents of Patient’s Revisit Intention: Mediating role of Trust in the Hospital among Patients in India https://doi.org/10.6084/m9.figshare.21505641.⁸⁵

This project contains the following underlying data:

• Dataset.csv

Extended data

This project contains the following extended data:

• Questionnaire.docx

References

1. Noland M, Park D, Estrada GB: Developing the service sector as engine of growth for Asia: an overview. Asian Development Bank Economics Working Paper Series. 2012 Nov; (320). Publisher Full Text
2. Berry LL, Bendapudi N: Health care: a fertile field for service research. Journal of service research. 2007 Nov; 10(2): 111–122. Publisher Full Text
3. Hellén K, Sääksjärvi M: Happy people manage better in adverse services. International Journal of Quality and Service Sciences. 2011 Oct 18; 3: 319–336. Publisher Full Text
4. Amin M, Nasharuddin SZ: Hospital service quality and its effects on patient satisfaction and behavioural intention. Clinical Governance: An International Journal. 2013 Jul 19; 18: 238–254. Publisher Full Text
5. Tang C, Luo Z, Fang P, et al.: Do patients choose community health services (CHS) for first treatment in China? Results from a community health survey in urban areas. Journal of community health. 2013 Oct; 38(5): 864–872. PubMed Abstract | Publisher Full Text
6. Piña IL, Cohen PD, Larson DB, et al.: A framework for describing health care delivery organizations and systems. American journal of public health. 2015 Apr; 105(4): 670–679. PubMed Abstract | Publisher Full Text
7. Mohammed P, Mercy M: Understanding service quality and patient satisfaction in private medical practice: A case study. African Journal of Business Management. 2011 May 4; 5(9): 3690–3698. Publisher Full Text
8. Carlucci D, Renna P, Schiuma G: Evaluating service quality dimensions as antecedents to outpatient satisfaction using back propagation neural network. Health care management science. 2013 Mar; 16(1): 37–44. PubMed Abstract | Publisher Full Text
9. Bjertnaes OA, Sjetne IS, Iversen HH: Overall patient satisfaction with hospitals: effects of patient-reported experiences and fulfilment of expectations. BMJ quality & safety. 2012 Jan 1; 21(1): 39–46. PubMed Abstract | Publisher Full Text
10. Gonzalez ME: Improving customer satisfaction of a healthcare facility: reading the customers’ needs. Benchmarking: An International Journal. 2019 Jan 28; 26: 854–870. Publisher Full Text
11. Zeithaml V, Bitner M: Service Marketing. New York, NY: The McGrow–Hill Companies. Inc; 1996.
12. Alrubaiee L, Alkaa’ida F: The Mediating Effect of Patient Satisfaction in the Patients’ Perceptions of Healthcare Quality–Patient Trust Relationship. Int J Mark Stud. 2011; 3(1): 103–127. Publisher Full Text
13. Zarei E, Daneshkohan A, Pouragha B, et al.: An empirical study of the impact of service quality on patient satisfaction in private hospitals, Iran. Global journal of health science. 2015 Jan; 7(1): 1–9. PubMed Abstract | Publisher Full Text
14. Zarei E: Service quality of hospital outpatient departments: patients’ perspective. International journal of health care quality assurance. 2015 Oct 12; 28: 778–790. PubMed Abstract | Publisher Full Text
15. Hu HH, Kandampully, Juwaheer J, et al.: Relationships and impacts of service quality, perceived value, customer satisfaction, and image: an empirical study. The service industries journal. 2009; 29(2): 111–125. Publisher Full Text
16. Han H, Hyun SS: Customer retention in the medical tourism industry: Impact of quality, satisfaction, trust, and price reasonableness. Tourism management. 2015 Feb 1; 46: 20–29. Publisher Full Text
17. Pakdil F, Harwood TN: Patient satisfaction in a preoperative assessment clinic: an analysis using SERVQUAL dimensions. Total Quality Management & Business Excellence. 2005 Jan 1; 16(1): 15–30. Publisher Full Text
18. Alshurideh M: The factors predicting students’ satisfaction with universities’ healthcare clinics’ services. Dirasat. Administrative Sciences. 2014; 41(2): 451–464. Publisher Full Text
19. Setiawan E, Wati S, Wardana A, et al.: Building trust through customer satisfaction in the airline industry in Indonesia: Service quality and price fairness contribution. Management Science Letters. 2020; 10(5): 1095–1102. Publisher Full Text
20. Pai YP, Chary ST: Dimensions of hospital service quality: A critical review: Perspective of patients from global studies. International journal of health care quality assurance. 2013 May 3; 26: 308–340. PubMed Abstract | Publisher Full Text
21. Martínez P, Del Bosque IR: CSR and customer loyalty: The roles of trust, customer identification with the company and satisfaction. International Journal of Hospitality Management. 2013 Dec 1; 35: 89–99. Publisher Full Text
22. Chang KC: Examining the effect of tour guide performance, tourist trust, tourist satisfaction, and flow experience on tourists’ shopping behavior. Asia Pacific Journal of Tourism Research. 2014 Feb 1; 19(2): 219–247. Publisher Full Text
23. Isa SM, Lim GS, Chin PN: Patients’ intent to revisit with trust as the mediating role: lessons from Penang Malaysia. International journal of pharmaceutical and healthcare marketing. 2019 Jun 7; 13: 140–159. Publisher Full Text
24. Al-Refaie A: Factors affect companies’ safety performance in Jordan using structural equation modeling. Safety science. 2013 Aug 1; 57: 169–178. Publisher Full Text
25. Lee S, Kim EK: The effects of Korean medical service quality and satisfaction on revisit intention of the United Arab Emirates government sponsored patients. Asian nursing research. 2017; 11(2): 142–149. PubMed Abstract | Publisher Full Text
26. Morgan RM, Hunt SD: The commitment-trust theory of relationship marketing. Journal of marketing. 1994 Jul; 58(3): 20–38. Publisher Full Text
27. Mukherjee A, Nath P: Role of electronic trust in online retailing: A re-examination of the commitment-trust theory. European journal of marketing. 2007 Sep 25; 41: 1173–1202. Publisher Full Text
28. Vatanasombut B, Igbaria M, Stylianou AC, et al.: Information systems continuance intention of web-based applications customers: The case of online banking. Information & management. 2008 Nov 1; 45(7): 419–428. Publisher Full Text
29. Berry LL, Parasuraman A: MARKETING SERVICESCOMPETING THROUGH QUALITY. New York: The Free Press.
30. Ryssel R, Ritter T, Gemünden HG: The impact of information technology deployment on trust, commitment and value creation in business relationships. Journal of business & industrial marketing. 2004 May 1; 19: 197–207. Publisher Full Text
31. Ghorban ZS, Tahernejad H: A study on effect of brand credibility on word of mouth: With reference to internet service providers in Malaysia. International Journal of Marketing Studies. 2012 Feb 1; 4(1): 26. Publisher Full Text
32. Abubakar AM, Ilkan M, Al-Tal RM, et al.: eWOM, revisit intention, destination trust and gender. Journal of Hospitality and Tourism Management. 2017 Jun 1; 31: 220–227. Publisher Full Text
33. Cuong DT, Long NT: The impact of service quality and brand image on customer satisfaction and behavioral intention in Vietnam Fashion market. Test Engineering and Management. 2020 Mar; 83(389): 389–398.
34. Sultan P, Wong HY: How service quality affects university brand performance, university brand image and behavioural intention: The mediating effects of satisfaction and trust and moderating roles of gender and study mode. Journal of Brand Management. 2019 May; 26(3): 332–347. Publisher Full Text
35. Sharma JK, Kumar N: Service quality, satisfaction and behavioural intention: Mediation and interaction analysis in electronic food ordering services. Academy of Marketing Studies Journal. 2019; 23(3): 1–5.
36. Cham TH, Lim YM, Sigala M: Marketing and social influences, hospital branding, and medical tourists’ behavioural intention: Before-and after-service consumption perspective. International Journal of Tourism Research. 2022 Jan; 24(1): 140–157. Publisher Full Text
37. Al-dweeri RM, Obeidat ZM, Al-dwiry MA, et al.: The impact of e-service quality and e-loyalty on online shopping: moderating effect of e-satisfaction and e-trust. International Journal of Marketing Studies. 2017 Mar; 9(2): 92–103. Publisher Full Text
38. Zeithaml VA: Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of marketing. 1988 Jul; 52(3): 2–2, 22. Publisher Full Text
39. Bostanji GM: The impact of service quality on customers loyalty: A study on five stars hotel’s customers in Riyadh, KSA. European Journal of Business and Management. 2013; 5(31): 230–240.
40. Lie D, Sudirman A, Efendi E, et al.: Analysis of mediation effect of consumer satisfaction on the effect of service quality, price and consumer trust on consumer loyalty. International Journal of Scientific and Technology Research. 2019; 8(8): 421–428.
41. Alshurideh M, Alsharari NM, Al KB: Supply chain integration and customer relationship management in the airline logistics. Theoretical Economics Letters. 2019 Feb 27; 09(02): 392–414. Publisher Full Text
42. Oliver RL: Satisfaction: A behavioral perspective on the consumer. New Yorkˈ NY: Irwin-McGraw-Hill; 1997.
43. Naidu A: Factors affecting patient satisfaction and healthcare quality. International journal of health care quality assurance. 2009 Jun 12; 22: 366–381. Publisher Full Text
44. Ahmad I, Nawaz A, ud Din S.: Dynamics of patient satisfaction from health care services. Gomal. Journal of Medical Sciences. 2011; 9(1).
45. Osman Z, Sentosa I: Influence of customer satisfaction on service quality and trust relationship in Malaysian rural tourism. Business and Management Quarterly Review. 2013 Apr 20; 4(2): 12–25.
46. Kim RB, Chao Y: Effects of brand experience, brand image and brand trust on brand building process: The case of Chinese millennial generation consumers. Journal of International Studies. 2019; 12(3): 9–21. Publisher Full Text
47. Hall MA, Zheng B, Dugan E, et al.: Measuring patients’ trust in their primary care providers. Medical care research and review. 2002 Sep; 59(3): 293–318. PubMed Abstract | Publisher Full Text
48. Moorman C, Zaltman G, Deshpande R: Relationships between providers and users of market research: The dynamics of trust within and between organizations. Journal of marketing research. 1992 Aug; 29(3): 314–328. Publisher Full Text
49. Chiu CM, Hsu MH, Lai H, et al.: Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems. 2012 Nov 1; 53(4): 835–845. Publisher Full Text
50. Wang SW, Ngamsiriudom W, Hsieh CH: Trust disposition, trust antecedents, trust, and behavioral intention. The Service Industries Journal. 2015 Jul 27; 35(10): 555–572. Publisher Full Text
51. Thom DH, Hall MA, Pawlson LG: Measuring patients’ trust in physicians when assessing quality of care. Health affairs. 2004 Jul; 23(4): 124–132. PubMed Abstract | Publisher Full Text
52. Hosseini SH, Behboudi L: Brand trust and image: effects on customer satisfaction. International journal of health care quality assurance. 2017 Aug 14; 30: 580–590. PubMed Abstract | Publisher Full Text
53. Hyder AS, Rydback M, Borg E, et al.: Medical tourism in emerging markets: The role of trust, networks, and word-of-mouth. Health marketing quarterly. 2019 Jul 3; 36(3): 203–219. PubMed Abstract | Publisher Full Text
54. Ajzen I: The theory of planned behavior. Organizational behavior and human decision processes. 1991 Dec 1; 50(2): 179–211. Publisher Full Text
55. Zeithaml VA, Berry LL, Parasuraman A: The behavioral consequences of service quality. Journal of marketing. 1996 Apr; 60(2): 31–46. Publisher Full Text
56. Ryu K, Lee HR, Kim WG: The influence of the quality of the physical environment, food, and service on restaurant image, customer perceived value, customer satisfaction, and behavioral intentions. International journal of contemporary hospitality management. 2012 Mar 2; 24: 200–223. Publisher Full Text
57. Ladhari R: Service quality, emotional satisfaction, and behavioural intentions: A study in the hotel industry. Managing Service Quality: An International Journal. 2009 May 15; 19: 308–331. Publisher Full Text
58. Dolnicar S, Coltman T, Sharma R: Do satisfied tourists really intend to come back? Three concerns with empirical studies of the link between satisfaction and behavioral intention. Journal of Travel Research. 2015 Mar; 54(2): 152–178. Publisher Full Text
59. Loureiro SM, Kastenholz E: Corporate reputation, satisfaction, delight, and loyalty towards rural lodging units in Portugal. International Journal of Hospitality Management. 2011 Sep 1; 30(3): 575–583. Publisher Full Text
60. Lee WI, Chen CW, Chen TH, et al.: The relationship between consumer orientation, service value, medical care service quality and patient satisfaction: The case of a medical center in Southern Taiwan. African Journal of Business Management. 2010 Apr 30; 4(4): 448–458.
61. Panjaitan H, Djunaedi D: Product advantage, customer relationship marketing, and service quality on customer satisfaction of Bank Syariah Mandiri in Surabaya. International Review of Management and Marketing. 2017; 7(4): 122.
62. Suhartanto D, Helmi Ali M, Tan KH, et al.: Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of foodservice business research. 2019 Jan 2; 22(1): 81–97. Publisher Full Text
63. Srivastava S, Prakash G: Internal Service Quality: Insights from Healthcare Sector. Journal of Health Management. 2019 Jun; 21(2): 294–312. Publisher Full Text
64. Chahal H, Kumari N: Development of multidimensional scale for healthcare service quality (HCSQ) in Indian context. Journal of Indian Business Research. 2010 Oct 12; 2: 230–255. Publisher Full Text
65. Melián-Alzola L, Martín-Santana JD: Service quality in blood donation: satisfaction, trust and loyalty. Service Business. 2020 Mar; 14(1): 101–129. Publisher Full Text
66. Badri M, Al Khaili M, Al Mansoori RL: Quality of service, expectation, satisfaction and trust in public institutions: the Abu Dhabi citizen satisfaction survey. Asian Journal of Political Science. 2015 Sep 2; 23(3): 420–447. Publisher Full Text
67. Chang CS, Chen SY, Lan YT: Service quality, trust, and patient satisfaction in interpersonal-based medical service encounters. BMC health services research. 2013 Dec; 13(1): 1–1. Publisher Full Text
68. Kantsperger R, Kunz WH: Consumer trust in service companies: a multiple mediating analysis. Managing Service Quality: An International Journal. 2010 Jan 26; 20: 4–25. Publisher Full Text
69. Rasheed FA, Abadi MF: Impact of service quality, trust and perceived value on customer loyalty in Malaysia services industries. Procedia-Social and Behavioral Sciences. 2014 Dec 31; 164: 298–304. Publisher Full Text
70. Moreira AC, Silva PM: The trust-commitment challenge in service quality-loyalty relationships. International Journal of Health Care Quality Assurance. 2015 Apr 20; 28: 253–266. PubMed Abstract | Publisher Full Text
71. Fernández-Sabiote E, Román S: The multichannel customer’s service experience: building satisfaction and trust. Service Business. 2016 Jun; 10(2): 423–445. Publisher Full Text
72. Prameka AS, Do BR, Rofiq A: How brand trust is influenced by perceived value and service quality: mediated by hotel customer satisfaction. APMBA (Asia Pacific Management and Business Application). 2017 Apr 3; 5(2): 73–88. Publisher Full Text
73. Zboja JJ, Voorhees CM: The impact of brand trust and satisfaction on retailer repurchase intentions. Journal of services marketing. 2006 Oct 1; 20: 381–390. Publisher Full Text
74. Chiu JL, Bool NC, Chiu CL: Challenges and factors influencing initial trust and behavioral intention to use mobile banking services in the Philippines. Asia Pacific Journal of Innovation and Entrepreneurship. 2017 Aug 7; 11: 246–278. Publisher Full Text
75. Limbu YB, Wolf M, Lunsford D: Perceived ethics of online retailers and consumer behavioral intentions: The mediating roles of trust and attitude. Journal of Research in Interactive Marketing. 2012 Jun 1; 6: 133–154. Publisher Full Text
76. Jung NY, Kim S, Kim S: Influence of consumer attitude toward online brand community on revisit intention and brand trust. Journal of Retailing and Consumer Services. 2014 Jul 1; 21(4): 581–589. Publisher Full Text
77. Vedel B, Gabarret I: The role of trust as mediator between contract, information and knowledge within business incubators. International Journal of Entrepreneurship and Small Business. 2014; 23(4).
78. Yu Y, Choi Y: Corporate social responsibility and firm performance through the mediating effect of organizational trust in Chinese firms. Chinese Management Studies. 2014 Oct 28; 8: 577–592. Publisher Full Text
79. Jambulingam T, Kathuria R, Nevin JR: How fairness garners loyalty in the pharmaceutical supply chain: Role of trust in the wholesaler-pharmacy relationship. International journal of pharmaceutical and healthcare marketing. 2009 Nov 20; 3: 305–322. Publisher Full Text
80. Moliner MA: Loyalty, perceived value and relationship quality in healthcare services. Journal of service management. 2009 Mar 13; 20: 76–97. Publisher Full Text
81. da Silva TM , dos Santos CP : Consumer trust in high-consequence decisions: a study of medical services. International Journal of Pharmaceutical and Healthcare Marketing. 2013 Jun 21. Publisher Full Text
82. Leigh A, Wolfers J: Happiness and the human development index: Australia is not a paradox. Australian Economic Review. 2006 Jun; 39(2): 176–184. Publisher Full Text
83. Hall J, Helliwell JF, Helliwell JF: Happiness and human development. Occasional Paper, Human Development Report Office.2014.a
84. Karnataka Human Development Index Report - 2015 (English).Pdf.
85. Akthar N, Nayak S, Pai PY: Figshare: Underlying data: A Cross-sectional study on Exploring the Antecedents of Patient’s Revisit Intention: Mediating role of Trust in the Hospital among Patients in India. F1000Res. 2022 Nov. Publisher Full Text
86. Parasuraman A, Zeithaml VA, Berry L: SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality.1988; 64(1): 12–40.
87. Brady MK, Cronin JJ Jr: Some new thoughts on conceptualizing perceived service quality: a hierarchical approach. Journal of marketing. 2001 Jul; 65(3): 34–49. Publisher Full Text
88. Greenfield TK, Attkisson CC: Steps toward a multifactorial satisfaction scale for primary care and mental health services. Evaluation and Program Planning. 1989 Jan 1; 12(3): 271–278. Publisher Full Text
89. Hair JF Jr, Hult GT, Ringle CM, et al.: A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications; 2nd ed2017.
90. Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep; 21(3): 401–408. PubMed Abstract | Publisher Full Text
91. Werts CE, Linn RL, Jöreskog KG: Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological measurement. 1974 Apr; 34(1): 25–33. Publisher Full Text
92. Wong KK: Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin. 2013 Jan 1; 24(1): 1–32.
93. Bagozzi RP, Yi Y: On the evaluation of structural equation models. Journal of the academy of marketing science. 1988 Mar; 16(1): 74–94. Publisher Full Text
94. Cohen J: Set correlation and contingency tables. Applied psychological measurement. 1988 Dec; 12(4): 425–434. Publisher Full Text
95. Hu LT, Bentler PM: Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods. 1998 Dec; 3(4): 424–453. Publisher Full Text
96. Stone M: Cross-validatory choice and assessment of statistical predictions. Journal of the royal statistical society: Series B (Methodological). 1974 Jan; 36(2): 111–133.
97. Geisser S: A predictive approach to the random effect model. Biometrika. 1974 Apr 1; 61(1): 101–107. Publisher Full Text
98. Hock C, Ringle CM, Sarstedt M: Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. International journal of services technology and management. 2010 Jan 1; 14(2-3): 188–207. Publisher Full Text
99. Hair JF Jr, Sarstedt M, Ringle CM, et al.: Advanced issues in partial least squares structural equation modeling. Sage Publications; 2017.

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Nahima Akthar
Roles: Conceptualization, Data Curation, Investigation, Methodology, Project Administration, Resources, Writing – Original Draft Preparation, Writing – Review & Editing

Yogesh Pai P
Roles: Conceptualization, Methodology, Supervision, Visualization, Writing – Review & Editing

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Akthar N, Nayak S and Pai P Y. A cross-sectional study on exploring the antecedents of patient’s revisit intention: Mediating role of trust in the hospital among patients in India [version 2; peer review: 2 approved] F1000Research 2023, 12:75 (https://doi.org/10.12688/f1000research.128220.2)

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The revised manuscript addresses all the issues highlighted by the earlier reviewers. The manuscript may now be considered. The research design and methodology are adequate. The results of the research model have been explained well. The literature review covers the important, and recent research studies. The data set had been provided by the authors to check for replicability and other analytical aspects of the research.

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Nahima Akthar, Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India

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Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers ... Continue reading Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers data availability has been ensured by the authors.
Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers data availability has been ensured by the authors.
Competing Interests: No Competing interests were disclosed. Close
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Author Response 04 Apr 2024

Nahima Akthar, Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India

04 Apr 2024

Author Response

Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers ... Continue reading Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers data availability has been ensured by the authors.
Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers data availability has been ensured by the authors.
Competing Interests: No Competing interests were disclosed. Close
Report a concern

Views

Reviewer Report 31 Aug 2023

Prof. (Adj.) Dr. Supaprawat Siripipatthanakul, Manipal GlobalNxt University, Nilai, Negeri Sembilan, Malaysia; Bangkokthonburi University, Bangkok, Bangkok, Thailand

Approved

https://doi.org/10.5256/f1000research.153946.r195437

Summary of revisions:

The following changes are incorporated in the manuscript:

1. reference quoted for sample size determination

Reviewer's Feedback: Acceptable

2. mentioned limitations as directed by reviewer

Reviewer's Feedback: Acceptable

3. strengthened the implications in the discussion section

Reviewer's Feedback: Acceptable

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Management (Business, Education, Healthcare) & Behavioural Analytics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Version 1

VERSION 1

PUBLISHED 19 Jan 2023

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Reviewer Report 20 Jul 2023

Prof. (Adj.) Dr. Supaprawat Siripipatthanakul, Manipal GlobalNxt University, Nilai, Negeri Sembilan, Malaysia; Bangkokthonburi University, Bangkok, Bangkok, Thailand

Approved with Reservations

https://doi.org/10.5256/f1000research.140789.r176087

The topic should include patient satisfaction as another mediator. Please consider adding new citations and references because all previous studies are from 1974–1998 and 2006–2019. There are no recent studies for the years 2020–2023. It is hard to say that sufficient details of methods are provided due to the research design, which is necessary to be more straightforward for sample size determination. It is better to explain a definite or indefinite population of hospital outpatients. The data is from three multispecialty hospitals in Bangalore Urban and one in Mysore from August 4th, 2021, to August 26th, 2021. It means that it is a definite population, and it is necessary to calculate it from a known population of three hospitals. However, the sample size was 242; still, previous studies must support this number. In this case, the researchers did not use sample size determination calculations from a definite population. The statistical analysis and its interpretation are acceptable. The conclusion should summarize how a strategic planner could improve each variable, especially perceived service quality, because the researchers do not show the questions. The limitations could not be explained in the present because the data was collected in 2021, but now it is 2023 as current, and the data was explained in 2021, not now. It is necessary to mention this in the limitations section.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Management (Business, Education, Healthcare) & Behavioural Analytics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 29 Nov 2023

Nahima Akthar, Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India

29 Nov 2023

Author Response
Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.
- Patient Satisfaction as a mediator: The mediating role of “patient satisfaction”
... Continue reading
Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.

Patient Satisfaction as a mediator: The mediating role of “patient satisfaction” as a construct is explored and presented in the manuscript. PLS SEM software is used to assess the mediating effect and the output is presented in Figure 3 and Table 8.

References: This manuscript was conceptualized, and data collection was completed in 2021. Data cleaning, analysis, and drafting of the manuscript were undertaken in 2022 and the final version was submitted to the journal on November 5^th, 2022. Hence, we have relied on the published literature until 2021.

Sample size determination: we have incorporated this in our manuscript. The reference was not presented, which had been incorporated now. The explanation for the same is presented below:

PLS-SEM is the software adopted to undertake the analysis. This investigation used a purposive sampling approach (non-probability by nature), which was adopted due to the absence of a sampling frame. Data was collected from 231 respondents. When the PLS-SEM is used for data analysis, Avkiran (2018) suggests that the sample size is determined by multiplying the number of items on the rating scale by 10. Hence 21 ( number of items) * 10 = 210. In addition 10% error of margin therefore 231.

Ref: Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep;21(3):401–408. 28181112 10.1007/s10729-017-9393-7

Implications: emphasized in the manuscript

Limitation: change incorporated in the manuscript

Regards,
Authors
Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.

Patient Satisfaction as a mediator: The mediating role of “patient satisfaction” as a construct is explored and presented in the manuscript. PLS SEM software is used to assess the mediating effect and the output is presented in Figure 3 and Table 8.

References: This manuscript was conceptualized, and data collection was completed in 2021. Data cleaning, analysis, and drafting of the manuscript were undertaken in 2022 and the final version was submitted to the journal on November 5^th, 2022. Hence, we have relied on the published literature until 2021.

Sample size determination: we have incorporated this in our manuscript. The reference was not presented, which had been incorporated now. The explanation for the same is presented below:

PLS-SEM is the software adopted to undertake the analysis. This investigation used a purposive sampling approach (non-probability by nature), which was adopted due to the absence of a sampling frame. Data was collected from 231 respondents. When the PLS-SEM is used for data analysis, Avkiran (2018) suggests that the sample size is determined by multiplying the number of items on the rating scale by 10. Hence 21 ( number of items) * 10 = 210. In addition 10% error of margin therefore 231.

Ref: Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep;21(3):401–408. 28181112 10.1007/s10729-017-9393-7

Implications: emphasized in the manuscript

Limitation: change incorporated in the manuscript

Regards,
Authors
Competing Interests: No competing interests. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 29 Nov 2023

Nahima Akthar, Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India

29 Nov 2023

Author Response
Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.
- Patient Satisfaction as a mediator: The mediating role of “patient satisfaction”
... Continue reading
Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.

Patient Satisfaction as a mediator: The mediating role of “patient satisfaction” as a construct is explored and presented in the manuscript. PLS SEM software is used to assess the mediating effect and the output is presented in Figure 3 and Table 8.

References: This manuscript was conceptualized, and data collection was completed in 2021. Data cleaning, analysis, and drafting of the manuscript were undertaken in 2022 and the final version was submitted to the journal on November 5^th, 2022. Hence, we have relied on the published literature until 2021.

Sample size determination: we have incorporated this in our manuscript. The reference was not presented, which had been incorporated now. The explanation for the same is presented below:

PLS-SEM is the software adopted to undertake the analysis. This investigation used a purposive sampling approach (non-probability by nature), which was adopted due to the absence of a sampling frame. Data was collected from 231 respondents. When the PLS-SEM is used for data analysis, Avkiran (2018) suggests that the sample size is determined by multiplying the number of items on the rating scale by 10. Hence 21 ( number of items) * 10 = 210. In addition 10% error of margin therefore 231.

Ref: Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep;21(3):401–408. 28181112 10.1007/s10729-017-9393-7

Implications: emphasized in the manuscript

Limitation: change incorporated in the manuscript

Regards,
Authors
Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.

Patient Satisfaction as a mediator: The mediating role of “patient satisfaction” as a construct is explored and presented in the manuscript. PLS SEM software is used to assess the mediating effect and the output is presented in Figure 3 and Table 8.

References: This manuscript was conceptualized, and data collection was completed in 2021. Data cleaning, analysis, and drafting of the manuscript were undertaken in 2022 and the final version was submitted to the journal on November 5^th, 2022. Hence, we have relied on the published literature until 2021.

Sample size determination: we have incorporated this in our manuscript. The reference was not presented, which had been incorporated now. The explanation for the same is presented below:

PLS-SEM is the software adopted to undertake the analysis. This investigation used a purposive sampling approach (non-probability by nature), which was adopted due to the absence of a sampling frame. Data was collected from 231 respondents. When the PLS-SEM is used for data analysis, Avkiran (2018) suggests that the sample size is determined by multiplying the number of items on the rating scale by 10. Hence 21 ( number of items) * 10 = 210. In addition 10% error of margin therefore 231.

Ref: Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep;21(3):401–408. 28181112 10.1007/s10729-017-9393-7

Implications: emphasized in the manuscript

Limitation: change incorporated in the manuscript

Regards,
Authors
Competing Interests: No competing interests. Close
Report a concern

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VERSION 3 PUBLISHED 19 Jan 2023

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Version 3 (revision) 18 Mar 24
Version 2 (revision) 10 Aug 23	read	read
Version 1 19 Jan 23	read

Prof. (Adj.) Dr. Supaprawat Siripipatthanakul, Manipal GlobalNxt University, Nilai, Malaysia; Bangkokthonburi University, Bangkok, Thailand
Satyanarayana Rentala, Bharathidasan Institute of Management, Tiruchirappalli, India

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5 Views

11 Mar 2024 | for Version 2

Satyanarayana Rentala, Bharathidasan Institute of Management, Tiruchirappalli, Tamil Nadu, India

5 Views Cite this report Responses(1)

Approved

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Export performance of Indian pharmaceutical industry; Service quality in Indian healthcare (hospital industry); Financial inclusion; Sustainable Development Goals; Sustainable and Responsible Marketing

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Author Response

04 Apr 2024

Nahima Akthar, Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India

Dear Sir,
We thank you for the feedback on our manuscript. The manuscript upholds the rigor expected in all stages of the research process. As indicated by both the reviewers data availability has been ensured by the authors.

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Competing Interests

No Competing interests were disclosed.

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31 Aug 2023 | for Version 2

Prof. (Adj.) Dr. Supaprawat Siripipatthanakul, Manipal GlobalNxt University, Nilai, Negeri Sembilan, Malaysia; Bangkokthonburi University, Bangkok, Bangkok, Thailand

5 Views Cite this report Responses(0)

Approved

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Management (Business, Education, Healthcare) & Behavioural Analytics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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18 Views

20 Jul 2023 | for Version 1

Prof. (Adj.) Dr. Supaprawat Siripipatthanakul, Manipal GlobalNxt University, Nilai, Negeri Sembilan, Malaysia; Bangkokthonburi University, Bangkok, Bangkok, Thailand

18 Views Cite this report Responses(1)

Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Management (Business, Education, Healthcare) & Behavioural Analytics

Respond to this report

Responses (1)

Author Response

29 Nov 2023

Nahima Akthar, Ph.D. Scholar, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India

Dear Sir,

Many thanks for the review. We are hereby enclosing our response to your queries.

Patient Satisfaction as a mediator: The mediating role of “patient satisfaction” as a construct is explored and presented in the manuscript. PLS SEM software is used to assess the mediating effect and the output is presented in Figure 3 and Table 8.
References: This manuscript was conceptualized, and data collection was completed in 2021. Data cleaning, analysis, and drafting of the manuscript were undertaken in 2022 and the final version was submitted to the journal on November 5^th, 2022. Hence, we have relied on the published literature until 2021.
Sample size determination: we have incorporated this in our manuscript. The reference was not presented, which had been incorporated now. The explanation for the same is presented below:

PLS-SEM is the software adopted to undertake the analysis. This investigation used a purposive sampling approach (non-probability by nature), which was adopted due to the absence of a sampling frame. Data was collected from 231 respondents. When the PLS-SEM is used for data analysis, Avkiran (2018) suggests that the sample size is determined by multiplying the number of items on the rating scale by 10. Hence 21 ( number of items) * 10 = 210. In addition 10% error of margin therefore 231.

Ref: Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep;21(3):401–408. 28181112 10.1007/s10729-017-9393-7
Implications: emphasized in the manuscript
Limitation: change incorporated in the manuscript

Regards,
Authors

View more View less

Competing Interests

No competing interests.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] 1. Noland M, Park D, Estrada GB: Developing the service sector as engine of growth for Asia: an overview. Asian Development Bank Economics Working Paper Series. 2012 Nov; (320). Publisher Full Text

[2] 2. Berry LL, Bendapudi N: Health care: a fertile field for service research. Journal of service research. 2007 Nov; 10(2): 111–122. Publisher Full Text

[3] 3. Hellén K, Sääksjärvi M: Happy people manage better in adverse services. International Journal of Quality and Service Sciences. 2011 Oct 18; 3: 319–336. Publisher Full Text

[4] 4. Amin M, Nasharuddin SZ: Hospital service quality and its effects on patient satisfaction and behavioural intention. Clinical Governance: An International Journal. 2013 Jul 19; 18: 238–254. Publisher Full Text

[5] 5. Tang C, Luo Z, Fang P, et al.: Do patients choose community health services (CHS) for first treatment in China? Results from a community health survey in urban areas. Journal of community health. 2013 Oct; 38(5): 864–872. PubMed Abstract | Publisher Full Text

[6] 6. Piña IL, Cohen PD, Larson DB, et al.: A framework for describing health care delivery organizations and systems. American journal of public health. 2015 Apr; 105(4): 670–679. PubMed Abstract | Publisher Full Text

[7] 7. Mohammed P, Mercy M: Understanding service quality and patient satisfaction in private medical practice: A case study. African Journal of Business Management. 2011 May 4; 5(9): 3690–3698. Publisher Full Text

[8] 8. Carlucci D, Renna P, Schiuma G: Evaluating service quality dimensions as antecedents to outpatient satisfaction using back propagation neural network. Health care management science. 2013 Mar; 16(1): 37–44. PubMed Abstract | Publisher Full Text

[9] 9. Bjertnaes OA, Sjetne IS, Iversen HH: Overall patient satisfaction with hospitals: effects of patient-reported experiences and fulfilment of expectations. BMJ quality & safety. 2012 Jan 1; 21(1): 39–46. PubMed Abstract | Publisher Full Text

[10] 10. Gonzalez ME: Improving customer satisfaction of a healthcare facility: reading the customers’ needs. Benchmarking: An International Journal. 2019 Jan 28; 26: 854–870. Publisher Full Text

[11] 11. Zeithaml V, Bitner M: Service Marketing. New York, NY: The McGrow–Hill Companies. Inc; 1996.

[12] 12. Alrubaiee L, Alkaa’ida F: The Mediating Effect of Patient Satisfaction in the Patients’ Perceptions of Healthcare Quality–Patient Trust Relationship. Int J Mark Stud. 2011; 3(1): 103–127. Publisher Full Text

[13] 13. Zarei E, Daneshkohan A, Pouragha B, et al.: An empirical study of the impact of service quality on patient satisfaction in private hospitals, Iran. Global journal of health science. 2015 Jan; 7(1): 1–9. PubMed Abstract | Publisher Full Text

[14] 14. Zarei E: Service quality of hospital outpatient departments: patients’ perspective. International journal of health care quality assurance. 2015 Oct 12; 28: 778–790. PubMed Abstract | Publisher Full Text

[15] 15. Hu HH, Kandampully, Juwaheer J, et al.: Relationships and impacts of service quality, perceived value, customer satisfaction, and image: an empirical study. The service industries journal. 2009; 29(2): 111–125. Publisher Full Text

[16] 16. Han H, Hyun SS: Customer retention in the medical tourism industry: Impact of quality, satisfaction, trust, and price reasonableness. Tourism management. 2015 Feb 1; 46: 20–29. Publisher Full Text

[17] 17. Pakdil F, Harwood TN: Patient satisfaction in a preoperative assessment clinic: an analysis using SERVQUAL dimensions. Total Quality Management & Business Excellence. 2005 Jan 1; 16(1): 15–30. Publisher Full Text

[18] 18. Alshurideh M: The factors predicting students’ satisfaction with universities’ healthcare clinics’ services. Dirasat. Administrative Sciences. 2014; 41(2): 451–464. Publisher Full Text

[19] 19. Setiawan E, Wati S, Wardana A, et al.: Building trust through customer satisfaction in the airline industry in Indonesia: Service quality and price fairness contribution. Management Science Letters. 2020; 10(5): 1095–1102. Publisher Full Text

[20] 20. Pai YP, Chary ST: Dimensions of hospital service quality: A critical review: Perspective of patients from global studies. International journal of health care quality assurance. 2013 May 3; 26: 308–340. PubMed Abstract | Publisher Full Text

[21] 21. Martínez P, Del Bosque IR: CSR and customer loyalty: The roles of trust, customer identification with the company and satisfaction. International Journal of Hospitality Management. 2013 Dec 1; 35: 89–99. Publisher Full Text

[22] 22. Chang KC: Examining the effect of tour guide performance, tourist trust, tourist satisfaction, and flow experience on tourists’ shopping behavior. Asia Pacific Journal of Tourism Research. 2014 Feb 1; 19(2): 219–247. Publisher Full Text

[23] 23. Isa SM, Lim GS, Chin PN: Patients’ intent to revisit with trust as the mediating role: lessons from Penang Malaysia. International journal of pharmaceutical and healthcare marketing. 2019 Jun 7; 13: 140–159. Publisher Full Text

[24] 24. Al-Refaie A: Factors affect companies’ safety performance in Jordan using structural equation modeling. Safety science. 2013 Aug 1; 57: 169–178. Publisher Full Text

[25] 25. Lee S, Kim EK: The effects of Korean medical service quality and satisfaction on revisit intention of the United Arab Emirates government sponsored patients. Asian nursing research. 2017; 11(2): 142–149. PubMed Abstract | Publisher Full Text

[26] 26. Morgan RM, Hunt SD: The commitment-trust theory of relationship marketing. Journal of marketing. 1994 Jul; 58(3): 20–38. Publisher Full Text

[27] 27. Mukherjee A, Nath P: Role of electronic trust in online retailing: A re-examination of the commitment-trust theory. European journal of marketing. 2007 Sep 25; 41: 1173–1202. Publisher Full Text

[28] 28. Vatanasombut B, Igbaria M, Stylianou AC, et al.: Information systems continuance intention of web-based applications customers: The case of online banking. Information & management. 2008 Nov 1; 45(7): 419–428. Publisher Full Text

[29] 29. Berry LL, Parasuraman A: MARKETING SERVICESCOMPETING THROUGH QUALITY. New York: The Free Press.

[30] 30. Ryssel R, Ritter T, Gemünden HG: The impact of information technology deployment on trust, commitment and value creation in business relationships. Journal of business & industrial marketing. 2004 May 1; 19: 197–207. Publisher Full Text

[31] 31. Ghorban ZS, Tahernejad H: A study on effect of brand credibility on word of mouth: With reference to internet service providers in Malaysia. International Journal of Marketing Studies. 2012 Feb 1; 4(1): 26. Publisher Full Text

[32] 32. Abubakar AM, Ilkan M, Al-Tal RM, et al.: eWOM, revisit intention, destination trust and gender. Journal of Hospitality and Tourism Management. 2017 Jun 1; 31: 220–227. Publisher Full Text

[33] 33. Cuong DT, Long NT: The impact of service quality and brand image on customer satisfaction and behavioral intention in Vietnam Fashion market. Test Engineering and Management. 2020 Mar; 83(389): 389–398.

[34] 34. Sultan P, Wong HY: How service quality affects university brand performance, university brand image and behavioural intention: The mediating effects of satisfaction and trust and moderating roles of gender and study mode. Journal of Brand Management. 2019 May; 26(3): 332–347. Publisher Full Text

[35] 35. Sharma JK, Kumar N: Service quality, satisfaction and behavioural intention: Mediation and interaction analysis in electronic food ordering services. Academy of Marketing Studies Journal. 2019; 23(3): 1–5.

[36] 36. Cham TH, Lim YM, Sigala M: Marketing and social influences, hospital branding, and medical tourists’ behavioural intention: Before-and after-service consumption perspective. International Journal of Tourism Research. 2022 Jan; 24(1): 140–157. Publisher Full Text

[37] 37. Al-dweeri RM, Obeidat ZM, Al-dwiry MA, et al.: The impact of e-service quality and e-loyalty on online shopping: moderating effect of e-satisfaction and e-trust. International Journal of Marketing Studies. 2017 Mar; 9(2): 92–103. Publisher Full Text

[38] 38. Zeithaml VA: Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of marketing. 1988 Jul; 52(3): 2–2, 22. Publisher Full Text

[39] 39. Bostanji GM: The impact of service quality on customers loyalty: A study on five stars hotel’s customers in Riyadh, KSA. European Journal of Business and Management. 2013; 5(31): 230–240.

[40] 40. Lie D, Sudirman A, Efendi E, et al.: Analysis of mediation effect of consumer satisfaction on the effect of service quality, price and consumer trust on consumer loyalty. International Journal of Scientific and Technology Research. 2019; 8(8): 421–428.

[41] 41. Alshurideh M, Alsharari NM, Al KB: Supply chain integration and customer relationship management in the airline logistics. Theoretical Economics Letters. 2019 Feb 27; 09(02): 392–414. Publisher Full Text

[42] 42. Oliver RL: Satisfaction: A behavioral perspective on the consumer. New Yorkˈ NY: Irwin-McGraw-Hill; 1997.

[43] 43. Naidu A: Factors affecting patient satisfaction and healthcare quality. International journal of health care quality assurance. 2009 Jun 12; 22: 366–381. Publisher Full Text

[44] 44. Ahmad I, Nawaz A, ud Din S.: Dynamics of patient satisfaction from health care services. Gomal. Journal of Medical Sciences. 2011; 9(1).

[45] 45. Osman Z, Sentosa I: Influence of customer satisfaction on service quality and trust relationship in Malaysian rural tourism. Business and Management Quarterly Review. 2013 Apr 20; 4(2): 12–25.

[46] 46. Kim RB, Chao Y: Effects of brand experience, brand image and brand trust on brand building process: The case of Chinese millennial generation consumers. Journal of International Studies. 2019; 12(3): 9–21. Publisher Full Text

[47] 47. Hall MA, Zheng B, Dugan E, et al.: Measuring patients’ trust in their primary care providers. Medical care research and review. 2002 Sep; 59(3): 293–318. PubMed Abstract | Publisher Full Text

[48] 48. Moorman C, Zaltman G, Deshpande R: Relationships between providers and users of market research: The dynamics of trust within and between organizations. Journal of marketing research. 1992 Aug; 29(3): 314–328. Publisher Full Text

[49] 49. Chiu CM, Hsu MH, Lai H, et al.: Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems. 2012 Nov 1; 53(4): 835–845. Publisher Full Text

[50] 50. Wang SW, Ngamsiriudom W, Hsieh CH: Trust disposition, trust antecedents, trust, and behavioral intention. The Service Industries Journal. 2015 Jul 27; 35(10): 555–572. Publisher Full Text

[51] 51. Thom DH, Hall MA, Pawlson LG: Measuring patients’ trust in physicians when assessing quality of care. Health affairs. 2004 Jul; 23(4): 124–132. PubMed Abstract | Publisher Full Text

[52] 52. Hosseini SH, Behboudi L: Brand trust and image: effects on customer satisfaction. International journal of health care quality assurance. 2017 Aug 14; 30: 580–590. PubMed Abstract | Publisher Full Text

[53] 53. Hyder AS, Rydback M, Borg E, et al.: Medical tourism in emerging markets: The role of trust, networks, and word-of-mouth. Health marketing quarterly. 2019 Jul 3; 36(3): 203–219. PubMed Abstract | Publisher Full Text

[54] 54. Ajzen I: The theory of planned behavior. Organizational behavior and human decision processes. 1991 Dec 1; 50(2): 179–211. Publisher Full Text

[55] 55. Zeithaml VA, Berry LL, Parasuraman A: The behavioral consequences of service quality. Journal of marketing. 1996 Apr; 60(2): 31–46. Publisher Full Text

[56] 56. Ryu K, Lee HR, Kim WG: The influence of the quality of the physical environment, food, and service on restaurant image, customer perceived value, customer satisfaction, and behavioral intentions. International journal of contemporary hospitality management. 2012 Mar 2; 24: 200–223. Publisher Full Text

[57] 57. Ladhari R: Service quality, emotional satisfaction, and behavioural intentions: A study in the hotel industry. Managing Service Quality: An International Journal. 2009 May 15; 19: 308–331. Publisher Full Text

[58] 58. Dolnicar S, Coltman T, Sharma R: Do satisfied tourists really intend to come back? Three concerns with empirical studies of the link between satisfaction and behavioral intention. Journal of Travel Research. 2015 Mar; 54(2): 152–178. Publisher Full Text

[59] 59. Loureiro SM, Kastenholz E: Corporate reputation, satisfaction, delight, and loyalty towards rural lodging units in Portugal. International Journal of Hospitality Management. 2011 Sep 1; 30(3): 575–583. Publisher Full Text

[60] 60. Lee WI, Chen CW, Chen TH, et al.: The relationship between consumer orientation, service value, medical care service quality and patient satisfaction: The case of a medical center in Southern Taiwan. African Journal of Business Management. 2010 Apr 30; 4(4): 448–458.

[61] 61. Panjaitan H, Djunaedi D: Product advantage, customer relationship marketing, and service quality on customer satisfaction of Bank Syariah Mandiri in Surabaya. International Review of Management and Marketing. 2017; 7(4): 122.

[62] 62. Suhartanto D, Helmi Ali M, Tan KH, et al.: Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of foodservice business research. 2019 Jan 2; 22(1): 81–97. Publisher Full Text

[63] 63. Srivastava S, Prakash G: Internal Service Quality: Insights from Healthcare Sector. Journal of Health Management. 2019 Jun; 21(2): 294–312. Publisher Full Text

[64] 64. Chahal H, Kumari N: Development of multidimensional scale for healthcare service quality (HCSQ) in Indian context. Journal of Indian Business Research. 2010 Oct 12; 2: 230–255. Publisher Full Text

[65] 65. Melián-Alzola L, Martín-Santana JD: Service quality in blood donation: satisfaction, trust and loyalty. Service Business. 2020 Mar; 14(1): 101–129. Publisher Full Text

[66] 66. Badri M, Al Khaili M, Al Mansoori RL: Quality of service, expectation, satisfaction and trust in public institutions: the Abu Dhabi citizen satisfaction survey. Asian Journal of Political Science. 2015 Sep 2; 23(3): 420–447. Publisher Full Text

[67] 67. Chang CS, Chen SY, Lan YT: Service quality, trust, and patient satisfaction in interpersonal-based medical service encounters. BMC health services research. 2013 Dec; 13(1): 1–1. Publisher Full Text

[68] 68. Kantsperger R, Kunz WH: Consumer trust in service companies: a multiple mediating analysis. Managing Service Quality: An International Journal. 2010 Jan 26; 20: 4–25. Publisher Full Text

[69] 69. Rasheed FA, Abadi MF: Impact of service quality, trust and perceived value on customer loyalty in Malaysia services industries. Procedia-Social and Behavioral Sciences. 2014 Dec 31; 164: 298–304. Publisher Full Text

[70] 70. Moreira AC, Silva PM: The trust-commitment challenge in service quality-loyalty relationships. International Journal of Health Care Quality Assurance. 2015 Apr 20; 28: 253–266. PubMed Abstract | Publisher Full Text

[71] 71. Fernández-Sabiote E, Román S: The multichannel customer’s service experience: building satisfaction and trust. Service Business. 2016 Jun; 10(2): 423–445. Publisher Full Text

[72] 72. Prameka AS, Do BR, Rofiq A: How brand trust is influenced by perceived value and service quality: mediated by hotel customer satisfaction. APMBA (Asia Pacific Management and Business Application). 2017 Apr 3; 5(2): 73–88. Publisher Full Text

[73] 73. Zboja JJ, Voorhees CM: The impact of brand trust and satisfaction on retailer repurchase intentions. Journal of services marketing. 2006 Oct 1; 20: 381–390. Publisher Full Text

[74] 74. Chiu JL, Bool NC, Chiu CL: Challenges and factors influencing initial trust and behavioral intention to use mobile banking services in the Philippines. Asia Pacific Journal of Innovation and Entrepreneurship. 2017 Aug 7; 11: 246–278. Publisher Full Text

[75] 75. Limbu YB, Wolf M, Lunsford D: Perceived ethics of online retailers and consumer behavioral intentions: The mediating roles of trust and attitude. Journal of Research in Interactive Marketing. 2012 Jun 1; 6: 133–154. Publisher Full Text

[76] 76. Jung NY, Kim S, Kim S: Influence of consumer attitude toward online brand community on revisit intention and brand trust. Journal of Retailing and Consumer Services. 2014 Jul 1; 21(4): 581–589. Publisher Full Text

[77] 77. Vedel B, Gabarret I: The role of trust as mediator between contract, information and knowledge within business incubators. International Journal of Entrepreneurship and Small Business. 2014; 23(4).

[78] 78. Yu Y, Choi Y: Corporate social responsibility and firm performance through the mediating effect of organizational trust in Chinese firms. Chinese Management Studies. 2014 Oct 28; 8: 577–592. Publisher Full Text

[79] 79. Jambulingam T, Kathuria R, Nevin JR: How fairness garners loyalty in the pharmaceutical supply chain: Role of trust in the wholesaler-pharmacy relationship. International journal of pharmaceutical and healthcare marketing. 2009 Nov 20; 3: 305–322. Publisher Full Text

[80] 80. Moliner MA: Loyalty, perceived value and relationship quality in healthcare services. Journal of service management. 2009 Mar 13; 20: 76–97. Publisher Full Text

[81] 81. da Silva TM , dos Santos CP : Consumer trust in high-consequence decisions: a study of medical services. International Journal of Pharmaceutical and Healthcare Marketing. 2013 Jun 21. Publisher Full Text

[82] 82. Leigh A, Wolfers J: Happiness and the human development index: Australia is not a paradox. Australian Economic Review. 2006 Jun; 39(2): 176–184. Publisher Full Text

[83] 83. Hall J, Helliwell JF, Helliwell JF: Happiness and human development. Occasional Paper, Human Development Report Office.2014.a

[84] 84. Karnataka Human Development Index Report - 2015 (English).Pdf.

[85] 85. Akthar N, Nayak S, Pai PY: Figshare: Underlying data: A Cross-sectional study on Exploring the Antecedents of Patient’s Revisit Intention: Mediating role of Trust in the Hospital among Patients in India. F1000Res. 2022 Nov. Publisher Full Text

[86] 86. Parasuraman A, Zeithaml VA, Berry L: SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality.1988; 64(1): 12–40.

[87] 87. Brady MK, Cronin JJ Jr: Some new thoughts on conceptualizing perceived service quality: a hierarchical approach. Journal of marketing. 2001 Jul; 65(3): 34–49. Publisher Full Text

[88] 88. Greenfield TK, Attkisson CC: Steps toward a multifactorial satisfaction scale for primary care and mental health services. Evaluation and Program Planning. 1989 Jan 1; 12(3): 271–278. Publisher Full Text

[89] 89. Hair JF Jr, Hult GT, Ringle CM, et al.: A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications; 2nd ed2017.

[90] 90. Avkiran NK: An in-depth discussion and illustration of partial least squares structural equation modeling in health care. Health care management science. 2018 Sep; 21(3): 401–408. PubMed Abstract | Publisher Full Text

[91] 91. Werts CE, Linn RL, Jöreskog KG: Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological measurement. 1974 Apr; 34(1): 25–33. Publisher Full Text

[92] 92. Wong KK: Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin. 2013 Jan 1; 24(1): 1–32.

[93] 93. Bagozzi RP, Yi Y: On the evaluation of structural equation models. Journal of the academy of marketing science. 1988 Mar; 16(1): 74–94. Publisher Full Text

[94] 94. Cohen J: Set correlation and contingency tables. Applied psychological measurement. 1988 Dec; 12(4): 425–434. Publisher Full Text

[95] 95. Hu LT, Bentler PM: Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods. 1998 Dec; 3(4): 424–453. Publisher Full Text

[96] 96. Stone M: Cross-validatory choice and assessment of statistical predictions. Journal of the royal statistical society: Series B (Methodological). 1974 Jan; 36(2): 111–133.

[97] 97. Geisser S: A predictive approach to the random effect model. Biometrika. 1974 Apr 1; 61(1): 101–107. Publisher Full Text

[98] 98. Hock C, Ringle CM, Sarstedt M: Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. International journal of services technology and management. 2010 Jan 1; 14(2-3): 188–207. Publisher Full Text

[99] 99. Hair JF Jr, Sarstedt M, Ringle CM, et al.: Advanced issues in partial least squares structural equation modeling. Sage Publications; 2017.

A cross-sectional study on exploring the antecedents of patient’s revisit intention: Mediating role of trust in the hospital among patients in India

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Review of literature

Perceived service quality (PSQ)

Patient satisfaction (PS)

Trust

Behavioral Intention (BI)

Perceived service quality and patient satisfaction

Patient satisfaction and trust

The mediating role of PS

Trust and BI

The mediating role of trust

Figure 1. Proposed conceptual framework.

Methods

Study design

Study setting

Eligibility criteria

Data Sources/Measurements

Study size

Statistical methods

Ethical considerations

Pilot testing

Results

Table 1. Demographic characteristics (N=242).

Table 2. Outpatient Departments involved in the study.

Structural model

Figure 2. Structural model evaluation.

Table 3. Evaluation of the structural model.

Assessment of collinearity

Table 4. Evaluating collinearity for exogenous constructs through VIF inner model.

Table 5. Evaluating collinearity for indicators through VIF outer model.

Discriminant validity among latent constructs: Cross-loading method

Table 6. Discriminant validity by the cross-loading method.

Hypotheses testing

Table 7. Hypothesis testing (f2) and Predictive relevance test (q2).

Predictive relevance test (Q2)

Mediation analysis

Figure 3. The mediating role of patient satisfaction.

Table 8. The mediating role of patient satisfaction.

Figure 4. The mediating role of trust in the hospital.

Table 9. The mediating role of trust.

Importance performance matrix analysis (IPMA)

Figure 5. Importance performance matrix analysis.

Table 10. IPMA of Institutional Efficacy.

Importance performance map

Figure 6. Importance performance map.

Discussion

Conclusion

Data availability

Underlying data

Extended data

References

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Table 7. Hypothesis testing (f²) and Predictive relevance test (q²).

Predictive relevance test (Q²)