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Article

Examining the Effects of Media-Generated Stereotypes on Receivers’ Trust and Attitude in Pakistan. Moderating Influence of Ethnicity and Gender

by
Syed Hassan Raza
1,
Umer Zaman
2,* and
Moneeba Iftikhar
3
1
Department of Communication Studies, Bahauddin Zakariya University, Multan 66000, Pakistan
2
Endicott College of International Studies, Woosong University, Daejeon 34606, Korea
3
Department of Mass Communication, Lahore College for Women University, Lahore 54000, Pakistan
*
Author to whom correspondence should be addressed.
Information 2021, 12(1), 35; https://0-doi-org.brum.beds.ac.uk/10.3390/info12010035
Submission received: 23 December 2020 / Revised: 12 January 2021 / Accepted: 13 January 2021 / Published: 16 January 2021
(This article belongs to the Special Issue Information Technology and Consumer Behavior: Challenges and Opportunities)
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Abstract

:
There is a long-standing debate about the effects of media-generated stereotypes on receivers’ trust and attitude. However, there is insufficient consensus about their influence on the media receiver’s ecological perspective in determining their extent of trust and attitudes. Drawing an analogy from Differential Susceptibility to Media Effect Model (hereafter DSMM) notion that media effects are conditional and are contingent on differential-susceptibility, this study examines the influence of dispositional and social susceptibility to media. To do so, the study validates the influence of media user’s gender (dispositional susceptibility) and ethnicity (social susceptibility) in determining the outcomes of media-generated stereotypes, media trust (MT), and attitude towards media organization (AO). The survey method has been employed to collect data through a self-administered questionnaire from 1061 university students in public sector institutions in Pakistan. The results provide empirical evidence that media-generated stereotypes are a substantially negative predictor of media trust and attitudes towards the media organization. The results also validate that the influence of the stereotyping manifested by the receiver’s ecological perspective such as ethnicity and gender are crucial determinants of the receiver’s trust and attitudes. Managerially, the study urges that journalistic practices must be more ethnoculturally inclusive, to cope with the contemporary media landscape.

1. Introduction

In recent decades, media access has been improved due to technological advancements [1]. Additionally, the freedom of the news media enables the dissemination of informational contents of societal issues [2]. This growing access to a diverse audience has dramatically evolved the contemporary media landscape. Consequently, the media-generated content needs more pluralistic and deliberative coverage to epitomize the numerous ethnic and cultural entities [2,3]. Considering such diverse media receivers, certain challenges for the media have been posed, e.g., to sketch out more ethnoculturally inclusive policies to overcome possible media-generated stereotypes [4]. To put it simply, media reach and freedom to cover certain societal issues may trigger ethnocultural sensitivities among the media receivers [5]. In this scenario, media receivers may perceive the media channel as a source of promoting stereotypes about an individual’s sub-group [6].
To comprehend media-generated stereotypes’ latent effects, scholars must recognize the understated groups, which tend to be depicted in numerous stereotypical ways within the media landscape [7]. Past research mostly endeavored to comprehend the stereotypical depiction of a specific group such as women [8], race [9], religion [10], and ethnicity [11]. Albeit, these previous studies have provided substantial evidence regarding underrepresentation and stereotyping of groups, but researchers undertook lesser investigations to unfold the potential effect of such media-generated content. Similarly, in Pakistan, there is no substantial work that has been conducted to measure the potential effects and outcomes of the media-generated stereotypes in the context of the receivers’ ethnicity and gender.
It is well-known that the media can apply its judgments on assembling media content in several ways. As such, media-generated contents sometimes emphasize certain aspects, e.g., racial or ethnic [7,10]. Rhetorically, individuals or groups can be depicted with certain labels [6,9]. For example, western media portrayed Muslims as terrorists and also coined terms like radical Islamism groups. Therefore, the phenomena of stereotyping can be the outcome of the media-generated content such as news. These stereotypical media-generated contents negatively depict certain groups (e.g., minority or race) [12]. Scholars have identified several outcomes of stereotypical representations of racial, ethnic, and gender in the media [8,9,13]. Such media-generated content is evaluated by the groups in question with their understanding and perspectives [14]. However, the past research remains inconclusive in stating a clear dispositional and social perspective of media receivers’ behavioral outcomes.
Among these perspectives, ethnicity is of overriding eminence [7], specifically in Asian developing nations such as Pakistan, wherein group fidelities are valued by individuals [15]. Ethnicity is the state of fitting into a social group that has always been a contributing factor in the media literature [16]. Eventually, this sense of belongingness and group fidelities can serve as a substantial effective factor to determine the attitude of the receivers of media commodities [17]. Earlier investigations also found the interplay between ethnicity and certain media commodities, e.g., news, and advertisement [18,19]. The literature is replete with evidence that ethnicity plausibly influences the media receivers’ attitude as the result of the media-generated ethnic stereotypes [20].
Researchers [21] noted that stereotyping on the issue of gender is also critical and can affect the trust of the media. Furthermore, research [22] indicated that media trust is also assessed by individuals based on the extent to which an individual relies on ethnocentric information. Therefore, the media’s trust is closely associated with ethnic and gender stereotyping in the news. To illustrate, individuals evaluate the news stories in the given context of ethnicity and gender, which may directly affect their media trust. Similarly, the audience attitude towards the media organization is also a dependable factor indicated in the literature [23]. However, in the context of differential susceptibility to media effect (DSSM), media trust and attitude towards media organizations have remained unaddressed; that is how the news media’s depiction of one’s ethnic group may affect the possible outcomes of the trust on media and attitude towards the media organizations [24].
In a nutshell, the present study aims to unfold three inherent objectives: firstly, it contributes by answering the queries and research gaps indicated in extant literature [7,23,24]. In doing so, the current study unfolds the interaction effect of the media user’s gender (i.e., dispositional susceptibility) and ethnicity (i.e., social susceptibility) with the media-generated stereotypes. Secondly, the selection of these two understudied outcomes, i.e., media trust and attitudes toward media organizations, are in line with the research directions given in the differential susceptibility media theory (DSSM) [24]. The DSSM suggests an examination of the theoretical relevance of the variables of gender (i.e., dispositional susceptibility) and ethnicity (i.e., social susceptibility) to measure their media effects. However, this study advances the body of knowledge by providing evidence that how dispositional and social susceptibility of the media receivers intensify or diminish the media trust and attitudes of the receiver. This would enrich understanding about the understudied phenomenon of how individuals’ evaluations based on their dispositional and social susceptibility factors determine the media trust [7,24]. Lastly, the investigation of the attitude towards the media channel in the context of Pakistan can also provide useful information about how they evaluate the media-generated stereotypes using their ecological perspectives of ethnicity and gender [11,23].

2. Literature Review

2.1. The Differential Susceptibility to Media Effects Model

Though previous studies used the Elaboration Likelihood Model (hereafter ELM) and priming theory frameworks to analyze the media’s effects [24], some researchers [25] stated that the results based on the Elaboration Likelihood Model and priming theory were inconsistent and contradictory in some cases while measuring the media effects [24]. The literature stated that inconsistency in media effects reporting is owing to the dearth of non-media constructs in past media theories. In other words, these models were not compiled to find out the exclusive role of non-media constructs in describing the media effects [26]. Additionally, [27] also explained the importance of investigating the indirect media effects and highlighted those previous theories of media effects such as priming theory, which represent the slight or an invalid illustration of the fundamental media effect sizes.
Therefore, critics [28] explained that the media effects theories remain inconsistent in addressing the true effect size of the media and indicated that this is because of the conceptual and methodological indistinctness. Likewise, usage of invalid media effect measures is another reason for small or moderate effect size reporting and flawed the actual media effect [29]. The conceptualization of media effects was also based on the less exclusive constructs; therefore, the media effects can also not be analyzed optimally [30]. The present study is using the differential susceptibility to media effect DSSM model, as it systematizes the media effect previous works to attain further theoretical rationality about the role of media effects and related constructs like media usage and media indulgence [24]. The DSMM underpinned critical questions: “(a) why few people are greatly susceptible to media effects than others, (b) how and why media influence those individuals, and (c) how media effects can be enhanced or counteracted” ([24], p. 221).
The DSMM originally conceived from the previous models such as Social Cognitive Theory [31], Media Priming [32], Selective Exposure [33], Communication Mediation Model [34], Neo-associationist Model [34], ELM [35], and micro-level variants of cultivation [36]. These models have acknowledged individual differences and the role of the non-media variables in defining the media effects [23]. Building an analogy from these well-cited media effects theories, DSMM postulated that the media effects are conditional and reliant on the deliberated and non-deliberate individual-level variations in perceptions, e.g., feelings, predispositions, views, and actions that result from media usage [24]. Precisely, DSMM differentiates three kinds of susceptibility to media effects namely: dispositional, social, and developmental susceptibility [37]. Dispositional susceptibility has been conceived as the stable and transient individual dimensions that possibly influence the choice of and receptiveness to media-generated content, such as gender, impetuses, and beliefs [24,38]. Further, social susceptibility has been described as the influence of social and contextual factors on one’s choice of and receptiveness to media-generated content [24]. The DSSM assumed that the social factors may act on an interpersonal level (e.g., peers), institutional (e.g., University), and societal contexts (e.g., ethnicity) [24,39]. These ecological elements could confine or encourage one’s exposure to media-generated content. Finally, developmental susceptibility has been described as the choice of and receptiveness to media-generated content on account of perceptive, affective, and societal growth [40,41]. The developmental susceptibility affects media usage patterns throughout all developmental phases of the lifecycle [38,42]. Though, the impact of these developmental dimensions becomes minute in the middle or older age [28,38]. In older age, developmental dimensions are certainly confounded with situational variables (e.g., profession) that could influence more intensely to regulate media usage [39].
In reality, the differential susceptibility DSSM model also facilitates the use of other non-media constructs like the individual difference construct and use of the social perspective in analyzing the media influences [28]. Though the previous models like the Elaboration Likelihood Model are based on the media effects notion, characteristically they only comprise of the media constructs and some process variables like the attitude [43]. The differential susceptibility DSSM used the non-media constructs with more adequate articulations of the media usage due to the effect of non-media constructs. Moreover, the DSMM addresses the implication of the individual’s level of media usage pattern [38,44]. It refers to the media-effects as the result of the influence of the several micro-, meso-, and macro-level antecedents of one’s susceptibility towards media-generated content. Drawing the media effect study based on other factors like ethnicity and group affiliation may give a better understanding of the media effects. Based on a review presented above, prevailing media affect models and theories, the differential susceptibility DSMM introduced a novel and integrated model to improve the understanding of the media effects and used as a theoretical framework in the current study.

2.2. Media Generated Stereotypes and Attitude Towards Media

The quality of the media informational content such as news is dependent on factual representation in its coverage. However, occasionally media has been criticized owing to its coverage based on the biased facts or negative depiction of certain groups [7]. The reason for such stereotyping is rooted in the news media policy in framing the social issues related to certain communities [12]. This kind of bias could be observed in the journalistic practices owing to the media landscape [45]. Literature suggested that biased reporting may lead to a negative evaluation of the news media and results in negative attitudes towards the media organization [46]. Prior investigations tapping media effects considered the stereotyping perspective as the framework to evaluate the outcomes of media effects [47]. Findings of prior research suggest that negative predispositions about specific media organizations can be triggered when media content receivers’ sense of stereotypical depiction [45]. In this standard, the responses of the media receivers depend on their prior ecological perspective [41].
Indeed, such media generated stereotypes can provoke ethnocentric or racial centered evaluations that may influence one’s attitude [48]. One of the main reasons for such consequences is stereotypical portrayals of ethnic groups in media reporting [49]. Scholars noted that the postulation of the media-generated content containing suspicious facts towards a specific group may actuate the racial/ethnic attitudes [7]. Previous literature indicates that stereotypical coverage of a specific group may automatically activate a negative evaluation of the given media organization [50]. Thereby, individuals’ response to stereotype media-generated content can directly influence their attitudes [13] and it is hypothesized that:
Hypothesis 1 (H1):
There is a negative influence of the media-generated stereotypes on attitude towards the media organization.

2.3. Media Generated Stereotypes and Media Trust

The advent of information technology has drastically improved the access of individuals to information [51]. This extensive access to diverse informational sources has led to a growing more analytical approach owing to media receivers usage of modern information technologies [50,52]. In this manner, now media receivers are becoming quite aware of fact-checking of the media-generated content [53]. This phenomenon is now posing threats and challenges to media credibility [54]. Similarly, technology has evolved the journalistic practices that have simplified the creation of new media outlets such as web-based channels [55]. The information technology usage made media consumers more equipped to cross-check the facts using more sources of information [54]. Thereby, sustaining the numbers and trust of media receivers is another sensitive issue for the existing media organizations [56]. Therefore, media organizations are now more conscious of reporting facts to sustain media trust [57,58]. To exemplify, in the case of fake or biased factual representations in media-generated content, individuals may rely on the other available alternative information sources to verify, which can diminish the media trust. Hence, diverse informational sources have enabled individuals to evaluate the facts [49]. For that reason, exposure to the group-biased coverage may activate the fact-checking phenomenon amongst its receiver [43]. In this scenario, the credibility of the news media is more at stake than ever [45]. As an illustration, if the individuals find biased facts in a story associated with their ethnic/racial group, they probably rely on other sources to double-check the facts. Undeniably, the use of social media can provide its user with alternative standpoints on that specific issue, and the credibility of the media organization would become ambiguous [53]. Therefore, the media trust is directly related to the media-generated stereotypes, and it is hypothesized that:
Hypothesis 2 (H2):
There is a negative influence of the media-generated stereotypes on media trust.

2.4. Moderating Role of Non-Media Susceptibility Variables

Numerous content analysis studies have offered evidence in backing the notion that media stereotypically represent certain groups (e.g., race, gender, etc.) [59,60]. Conversely, the effects of media stereotypes also remained a topic pursued by researchers for eras [13,47]. However, only some researches focus on measuring the effects of the media-generated stereotypes or advanced theoretical outline to clarify the effects of such depictions on media receivers belonging to the stereotyped group [61]. Perhaps, these fewer studies indicated that biased factual representations of minority groups influence them negatively and develop negative feelings about the source. According to a study [62], media viewers may already have the feeling of the stereotype-based on their affiliation with ethnic groups and automatically activate the cognitive process towards a negative evaluation of the media. Such cognitive systems are described in previous theories like media priming but remained marginally rationalized [24]. Recent studies also suggest that future investigations should endeavor to extricate the role of social and dispositional factors in determining the effects of media-generated stereotypes [63].
Past theoretical rationalizations described that exposure to media stereotypes serve as cognitive provocations for the negatively depicted audience members [8,20]. Subsequently, these cognitive provocations can activate negative feelings that lead to negative attitudes. The extent of such negative outcomes would be reliant on the extent of audience members’ ethnocultural manifested sensitivity [64,65]. For instance, if a person watches a news story narrating a feeble fact about a criminal who belongs to ones’ similar racial group, this might have a negative consequence and lessen the trust in that media outlet [5]. Similarly, exposure to a joke about women or viewing a newscaster that lacks warmth while reading a story related to one’s group are some illustrations of potential perception of media-generated stereotypes [41].
This study is contingent on the view posited in DSSM that consideration of non-media constructs, e.g., social (ethnicity) or dispositional (gender) can describe the theoretical rationalization of the media effects [24,66]. Certainly, it will reinforce the notion that media effects are conditional and reliant on an individual’s level of susceptibility that is manifested as their frame of reference. Thereby the theoretical model (see Figure 1) of this study would provide evidence in support of DSMM notions: (1) individuals are considerably susceptible to media effects and (2) contextual and social factors regulated the media effects [66]. Hence, we assumed moderating implications of the dispositional (gender) and social (ethnicity) factors that would certainly predict the strength of the relationship of media-generated stereotypes with an attitude towards media organization and media trust. This would clarify that how media generated stereotypes effects are dependent on ones’ cognitive and affective response state and it is hypothesized that:
Hypothesis 3 (H3a):
Individual’s gender moderates the relationship of the media-generated stereotypes with an attitude towards media organization trust such that it would strengthen the negative influence of media-generated stereotypes.
Hypothesis 3 (H3b):
Individual’s gender moderates the relationship of the media-generated stereotypes with media trust such that it would strengthen the negative influence of media-generated stereotypes.
Hypothesis 4 (H4a):
Individual’s ethnicity moderates the relationship of the media-generated stereotypes with an attitude towards media organization such that it would strengthen the negative influence of media-generated stereotypes.
Hypothesis 4 (H4b):
Individual’s ethnicity moderates the relationship of the media-generated stereotypes with media trust such that it would strengthen the negative influence of media-generated stereotypes.

3. Materials and Methods

Drawing from the positivistic epistemological approach, this study examined the predictiveness of the (DSMM) model. Hence, the survey technique has been employed to validate the proposed hypotheses. For that reason, a self-administrated questionnaire has been adopted from the previous literature. The participants (N = 1061) were selected students from the three public sector universities located in the different cities of Pakistan. The selection of the students from these three universities justifies the purpose of the study based on three reasons: (a) In these three universities, a large number of students of all ethnic groups in Pakistan are enrolled and (b) among them, to balance the gender, which is also a moderating variable in this study, a women’s university is selected. Therefore, this sample is based on ethnic and gender diversity. Additionally, moral assurance was made that their details would be kept confidential. The students who agreed to participate were asked to fill the survey questionnaire to submit their responses. We approached the students of three universities with the support of the faculty, students, and volunteers. Eventually, 1061 students participated in the survey.

Instrumentation

The media-generated stereotypes (MGS) were measured with a 16-item scale on a seven-point Likert scale adopted from the previous literature [65] that showed reliability with Cronbach alpha of 0.708. This scale [61] is considered more diverse and designed to tap stereotyping in terms of the depiction of facts and accuracy in reporting. For measuring the trust on media MT, five items in a seven-point Likert scale adopted for the study [66] designed to tap the media credibility with the dimension of the trust. Media trust items showed reliability with a Cronbach alpha of 0.867, Whereas attitude towards the media organization was measured AO with four items in a seven-point Likert scale adopted from the prior study [67]. Media trust items showed reliability with a Cronbach alpha of 0.814.

4. Results

After receiving the responses, the normality of the data was observed by employing the skewness/kurtosis test and visual inspection for the outliers. After deleting the outliers cases, the data of (n = 1043), which meet the criteria of normality, were retained for further analysis. There were 593 (56.9%) males and 450 (43.1%) females in the sample. In terms of the ethnic group’s representation, results matched substantially: 628 (60.2%) Punjabi, 136 (13%) Sindhi, 148 (14.2%) Kpk, 105 (10.1%) Balochistan, and 26 (2.5%) with other ethnic backgrounds), with Pakistan’s national population data, like study 2. Therefore, the student sample reflected the actual ethnic composition of Pakistan to a rational extent. Furthermore, correlation analysis was carried out that revealed correlation between the constructs of this study (see Table 1).

4.1. Exploratory Factor Analysis

We used the principal component factor PCF analysis with Promax rotation on a segregated data of 531. It is recommended to use segregated data to validate the factor structure [68]. The selection of the extraction and rotation for this study is based on past recommendations [69] to attain meaningful factors. The criteria for the decision about the scale’s factor solution involved (a) the eigenvalues of 1.0 or above for all the extracted factors, (b) variance exceeds 60%, and (c) the loading of 0.70 or above with at least three items alongside the secondary loadings less than 0.40. Based on the criteria findings for the stereotyping in news, the 16-items factor revealed adequacy, as KMO was 0.652 above the cutoff with explained 63.12% variance. Similarly, regarding attitude towards media organization, the four-item factor revealed adequacy, as KMO was also 0.643 above the cutoff with explained 51.39% variance which is acceptable. The media trust five-item factor also revealed adequacy with KMO 0.728 with explained 57.47% variance. However, the study used the confirmatory factor analysis on AMOS 23.0; therefore, exploratory factor analysis was conducted only as part of the preliminary normality checks and to inspect the structure of the factor as recommended by [64].

4.2. Confirmatory Factor Analysis: Common Method Biasness, Convergent and Discriminant Validity

With the purpose of the checking the common method biasness, all twenty-four items of all variables in study were loaded on a single factor in first confirmatory test conducted on AMOS 23.0. The result clarified a better fit model with data of 1043 by deleting three items. Initial, results observed that χ2(37) = 146.11, p < 0.001, GFI = 0.98, AGFI = 0.94, NFI = 0.93, TLI = 0.87, IFI = 0.95, CFI = 0.94, RMSEA = 0.05, and SRMR = 0.03. After adjusting the recommended covariance amongst error terms, the further best fit model was attained as χ2(25) = 30.58, p < 0.231, GFI = 0.99, AGFI = 0.98, NFI = 0.98, TLI = 0.99, IFI = 0.97, CFI = 0.99, RMSEA = 0.02, and SRMR = 0.016.
As the results in Table 2 indicated, after the adjustments, p < 0.231 and was not significant, and it was desired to attain model fitness. The attained values indicated an acceptable fitness of the proposed one-factor twenty-two item model, as it is within range of the recommended cutoffs.
Further, for the convergent and discriminant validity assessment and measurement model fitness, all items of MT, AO, and MGS were loaded on their parent factor (see Figure 1 for item loadings) to run the CFA again to observe the model fitness. The result clarified a better fit model with data of 1043. Initial results observed that χ2(78) = 158.03, p < 0.001, GFI = 0.98, AGFI = 0.96, NFI = 0.94, TLI = 0.94, IFI = 0.96, CFI = 0.97, RMSEA = 0.03, and SRMR = 0.027. Afterward, the convergent and divergent validities were measured as composite reliability (CR), average variance extracted (AVE), and maximum shared variance (MSV), given in Table 3 and within the acceptable range of the recommended cutoffs [68].

4.3. Hypothesis Testing and Criterion-Related Validity

For the hypothesis testing and the criterion-related validation of the model in terms of its degree to forecast the outcomes of media trust and attitude towards media organizations, the study also selected two possible moderating variables, gender and ethnicity. For each hypothesis, testing the relationship of constructs of MGS, MT, and AO, three models were tested using Structural Equational Modeling (hereafter SEM). The first model was run without the moderating variable, the second model was based on one moderating variable of gender and its interaction, and the third model with a moderating variable of ethnicity as an interaction.
At the first stage, path analysis was conducted to observe the proposed MGS as the predictor of the attitude towards media organizations AO without any moderating variable to test the hypothesis 1, which postulated about the negative influence of the MGS on AO, and results suggested good fitness as χ2(93) = 278.34, p < 0.0001, GFI = 0.97, AGFI = 0.95, NFI = 0.93, TLI = 0.92, IFI = 0.95, CFI = 0.95, RMSEA = 0.04, and SRMR = 0.047. Reasonable extent of variance change observed as (β = −0.21, ΔR2 = 0.15, p < 0.001), which suggested to accept the H1 (see Table 4).
In model two with one moderating variable (see Figure 2) of gender, MGS remains a significant predictor attitude towards media organizations AO; interaction was (β = 0.28, ΔR2 = 0.26, p < 0.001), and model fitness also revealed good fit as χ2(107) = 397.91, p < 0.0001, GFI = 0.96, AGFI = 0.93, NFI = 0.91, TLI = 0.89, IFI = 0.93, CFI = 0.93, RMSEA = 0.05, and SRMR = 0.051, see Table 5. It is suggested that H3a, which postulated that there is a moderating role of gender in the relationship of MGS and AO, was also supported.
In the third model with the moderating variable (see Figure 3) of ethnicity, MGS remains a significant predictor of AO, and interaction was (β = 0.22, ΔR2 = 0.08, p < 0.001), and model fitness also revealed good fit as χ2(121) = 368.53, p < 0.0001, GFI = 0.97, AGFI = 0.94, NFI = 0.92, TLI = 0.91, IFI = 0.94, CFI = 0.94, RMSEA = 0.04, and SRMR = 0.047. However, regarding prediction of AO, with ethnic background as the moderating variables, the R2 change decreases but is not insignificant; therefore, H4a which postulated that there is moderating a role of gender in the relationship of MGS and MT, was also supported.
At the second stage, path analysis was conducted to observe the proposed MGS as the negative predictor of the media trust MT in absence of any moderating variable to test the hypothesis 2. H2 postulated the negative influence of the MGS on MT, and results suggested good fitness, as χ2(94) = 166.14, p < 0.001, GFI = 0.98, AGFI = 0.97, NFI = 0.93, TLI = 0.95, IFI = 0.97, CFI = 0.97, RMSEA = 0.02, and SRMR = 0.025 and accounted for an acceptable extent of variance change (β = −0.27, ΔR2 = 0.17, p < 0.001). H2 was supported.
In model two with one moderating variable (see Figure 4) of gender, MGS remains a significant predictor of MT, and interaction was (β = 0.24, ΔR2 = 0.32, p < 0.001), and model fitness also revealed good fit, as χ2(94) = 261.03, p < 0.0001, GFI = 0.97, AGFI = 0.95, NFI = 0.93, TLI = 0.93, IFI = 0.96, CFI = 0.96, RMSEA = 0.04, and SRMR = 0.038. It is suggested that H3b, which postulated that there is a moderating role of gender in the relationship of MGS and MT, was also supported.
In the third model with moderating variables of ethnicity (see Figure 5), MGS remains a significant predictor of MT, and interaction was (β = 0.17, ΔR2 = 0.40, p < 0.001), and model fitness also revealed good fit, as χ2(126) = 294.87, p < 0.0001, GFI = 0.97, AGFI = 0.95, NFI = 0.95, TLI = 0.97, IFI = 0.95, CFI = 0.97, RMSEA = 0.03, and SRMR = 0.036.
Hence, it suggested that H4b, which postulated that there is a moderating role of gender in the relationship of MGS and MT, was also supported. It can be also concluded that the proposed MGS model attained criterion-related validity by significantly predicting the trust in media MT and attitude towards media organizations AO.

5. Discussion

The study has employed the SEM technique to validate the postulations of the study [70]. The H1 posited that media-generated stereotypes can provoke negative attitudes towards the media organization. The findings of analysis (β = −0.21, ΔR2 = 0.15, p < 0.001) revealed that individuals negatively evaluate the source of stereotypes generated content. These results are consistent with the prior studies [23,46], which suggested that stereotyping can be conceived as a negative phenomenon [23]. A similar pattern of results has been observed in findings of the postulation H2 that suggests that stereotyping can diminish the media trust (β = −0.27, ΔR2 = 0.17, p < 0.001), see past studies on stereotyping [21]. To put it simply, stereotyping has negative consequences for media organizations [13,18].
In line with past studies [59,61,71,72], results have validated the involvement of several contextual factors in determining the effects of the media-generated stereotype. The study posed four moderating hypotheses based on dispositional and social factors. The result of moderation analysis has clarified that an individual’s gender and ethnicity moderate the relationship of the media-generated stereotypes with the attitude towards media organization and media trust. Furthermore, the negative influence of media-generated stereotypes has been strengthened owing to these dispositional and social factors. The results underlined past research [73] suggesting stereotypes in media content may activate automatically and impact negatively due to one’s ethnocultural sensitivities [59]. The importance of recognizing this procedure becomes even larger based on the recent progress in explaining the central role of social and ethnicity in the process of stereotyping [4,18]. The results of moderating factors in the study advances the applicability of the differential susceptibility to media effect DSSM. Overall, results are in line with suggestions made in this recent model to examine the contextual factors in the media effects study [5,58]. Scholars have identified several outcomes of stereotypical representations of racial, ethnic, and gender in media [8,9,13].

5.1. Theoretical and Managerial Implications

Although cognitive theories and investigation have shown development in the past, the stereotype is still an area that has the potential for additional progress [28]. Past metanalysis has uncovered that media effects need more theoretical rationality to clarify the role of media constructs variables (e.g., media usage or processing) and non-media constructs (e.g., individual variations or societal perspective) in future investigations. Recent studies also underscore that role of non-media constructs has been undermined in past media effects models [24,74]. For instance, DSMM indicated some reasons for the reduced extent of predictivity of past models in tapping media effects. These reasons were rooted in conceptualizations, roles, and interactions amongst these variables [60,75]. Therefore, this study reinforced the notion of DSMM and determined the role of influential factors to comprehend media effects. However, the study underscored the novel context of media-generated stereotypes and their associations with timely issues such as media trust and attitudes related to media organizations. Furthermore, the role of nonmedia constructs (e.g., gender and ethnicity) in defining receivers’ trust and attitude towards the organization was examined. Practically, the presented study can serve as a useful tool for the media organizations to gauge the current practices of reporting the events about the sub-groups (e.g., gender and ethnic) in the context of Pakistan. Additionally, based on the results, media organizations can deliberate the training to the newsroom executive and field reporters to understand the sensitivity of the ones’ ethnocultural context, which may result in developing the stereotype among the media users.

5.2. Limitations and Directions for Future Research

The emphasis on the ethnic groups existing beliefs in terms of recognizing their group competence and comparing others overlooks the other factors like past experiences, knowledge, and cultural norms in determining the stereotype [5,7]. We recommend that future studies may consider these dimensions as well to present a more detailed instrument. Second, on the methodological side, several other methods can also be used like field observation or interviews. Third, the current study used the ethnicity and local news media context only, although it is useful; however, another context like the nation, culture, and international news media or social media may be considered in the future. Lastly, we also recognize the implicit ethnocultural bias that can be avoided in the future by considering diverse samples and comparing the certain diverse ethnocultural groups from different contexts of developmental susceptibility factors [23,65].

6. Conclusions

Recent studies suggested articulating reasons for the reporting of the inconsistent as well as lesser effects [66,72]. The current study followed the imprints of the DSMM model and advanced the theory by validating the conceptual linkage between the diverse perspective of the media receivers as a determinant of the media effects. However, this study has adopted a unique perspective that is the conceptualization of antecedent as “media generated stereotypes” instead of using the construct of media. Additionally, making our study in line with the current landscape of the media environment, we selected timely outcomes attitude and media trust [47,48]. Additionally, articulations about media trust and stereotypical media remained shallow areas in media effect study [50]. To this point, the findings of the study enlightened that contemporary media practitioners must be more aware of biased representation. As such, research has concluded that stereotyping-generated content is problematic for the reputation and worth of their organizations. Moreover, based on DSMM [23], this study posited that a conceivable justification of the slight media effects is the limitation of non-media variables in past models. The study has analytically assessed the integrated role of theory-driven factors, e.g., gender and ethnicity, to rationalize the effects of the media-generated stereotype [27,60]. Ergo, it can be concluded that stereotypical depiction of groups could harm the reputation of the media organization. Moreover, media has an imperative role to play in promoting a pluralistic society through diversity inclusion in its reporting. In this standard, journalistic practices must be more pluralistic and inclusive to avoid stereotypical representations.

Author Contributions

Conceptualization: S.H.R., M.I., and U.Z.; methodology: S.H.R. and M.I.; software: S.H.R.; validation: S.H.R.; formal analysis: S.H.R.; investigation: S.H.R., M.I., and U.Z.; resources: S.H.R., M.I., and U.Z.; data curation: S.H.R. and M.I.; writing—original draft preparation: S.H.R., M.I., and U.Z.; writing—review and editing: S.H.R., M.I., and U.Z.; project administration: S.H.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Research Ethical Committee of Bahauddin Zakariya University, Multan 66000, Pakistan and approval Number. TMA/02/2020.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Beyer, J.L. The emergence of a freedom of information movement: Anonymous, WikiLeaks, the Pirate party, and Iceland. J. Comput.-Mediat. Commun. 2014, 19, 141–154. [Google Scholar] [CrossRef] [Green Version]
  2. Ananny, M. Networked Press Freedom and Social Media: Tracing Historical and Contemporary Forces in Press-Public Relations. J. Comput.-Mediat. Commun. 2014, 19, 938–956. [Google Scholar] [CrossRef] [Green Version]
  3. Belair-Gagnon, V.; Nelson, J.L.; Lewis, S.C. Audience engagement, reciprocity, and the pursuit of community connectedness in public media journalism. J. Pract. 2019, 13, 558–575. [Google Scholar] [CrossRef]
  4. Cotter, C. Diversity awareness and the role of language in cultural representations in news stories. J. Pragmat. 2011, 43, 1890–1899. [Google Scholar] [CrossRef]
  5. Panis, K.; Paulussen, S.; Dhoest, A. Managing super-diversity on television: The representation of ethnic minorities in Flemish non-fiction programmes. Media Commun. 2019, 7, 13–21. [Google Scholar] [CrossRef] [Green Version]
  6. Fuochi, G.; Voci, A.; Veneziani, C.A.; Boin, J.; Fell, B.; Hewstone, M. Is negative mass media news always associated with outgroup prejudice? The buffering role of direct contact. Group Process. Intergroup Relat. 2020, 23, 195–213. [Google Scholar] [CrossRef]
  7. Dixon, T. Media stereotypes: Content, effects, and theory. In Media Effects: Advances in Theory and Research, 4th ed.; Oliver, M.B., Raney, A.A., Bryant, J., Eds.; Routledge: New York, NY, USA, 2020; pp. 243–257. [Google Scholar]
  8. Khalil, A.; Dhanesh, G.S. Gender stereotypes in television advertising in the Middle East: Time for marketers and advertisers to step up. Bus. Horiz. 2020, 63, 671–679. [Google Scholar] [CrossRef]
  9. Mortensen, T.M.; Moscowitz, L.; Wan, A.; Yang, A. The marijuana user in US news media: An examination of visual stereotypes of race, culture, criminality and normification. Vis. Commun. 2020, 19, 231–255. [Google Scholar] [CrossRef]
  10. Wigger, I. Anti-Muslim racism and the racialisation of sexual violence:‘intersectional stereotyping’in mass media representations of male Muslim migrants in Germany. Cult. Relig. 2019, 20, 248–271. [Google Scholar] [CrossRef]
  11. Raza, S.H.; Zaheer, L.; Iftikhar, M. Gender stereotype news in context of the ethnicity: Scale development and validation. Pak. J. Psychol. Res. 2019, 34, 79–100. [Google Scholar] [CrossRef]
  12. Legg, A.M.; Sweeny, K. Do you want the good news or the bad news first? The nature and consequences of news order preferences. Personal. Soc. Psychol. Bull. 2014, 40, 279–288. [Google Scholar] [CrossRef] [PubMed]
  13. Spohn, C. Race, ethnicity, and crime. In The Oxford Handbook of Crime and Criminal Justice; Oxford University Press: Oxford, UK, 2012. [Google Scholar]
  14. Tukachinsky, R.; Mastro, D.; Yarchi, M. The effect of prime time television ethnic/racial stereotypes on Latino and Black Americans: A longitudinal national level study. J. Broadcasting Electron. Media 2017, 61, 538–556. [Google Scholar] [CrossRef]
  15. Raza, S.H.; Abu Bakar, H.; Mohamad, B. The effects of advertising appeals on consumers’ behavioural intention towards global brands: The mediating role attitude and the moderating role of uncertainty avoidance. J. Islamic Mark. 2019, 11, 440–460. [Google Scholar] [CrossRef]
  16. Cobley, P.; Schulz, P.J. (Eds.) Theories and Models of Communication; Walter de Gruyter: Berlin, Germany, 2013; Volume 1. [Google Scholar]
  17. Arnett Jensen, L. Coming of age in a multicultural world: Globalization and adolescent cultural identity formation. Appl. Dev. Sci. 2003, 7, 189–196. [Google Scholar] [CrossRef]
  18. Beaudoin, C.E. News effects on bonding and bridging social capital: An empirical study relevant to ethnicity in the United States. Commun. Res. 2011, 38, 155–178. [Google Scholar] [CrossRef]
  19. Kim, S.; Yi Luk, K.; Xia, B.; Xu, N.; Yin, X. Brand name and ethnicity of endorser in luxury goods: Does a glocalization strategy work in China? Int. J. Advert. 2020, 39, 824–842. [Google Scholar] [CrossRef]
  20. Valentino, N.A.; Brader, T.; Jardina, A.E. Immigration opposition among US Whites: General ethnocentrism or media priming of attitudes about Latinos? Political Psychol. 2013, 34, 149–166. [Google Scholar] [CrossRef] [Green Version]
  21. Lee, A.M.; Chyi, H.I. Motivational Consumption Model Exploring the Psychological Structure of News Use. J. Mass Commun. Q. 2014, 91, 706–724. [Google Scholar]
  22. Carlsson, R.; Björklund, F. Implicit stereotype content. Soc. Psychol. 2010, 41, 213–222. [Google Scholar] [CrossRef] [Green Version]
  23. Lee, E.J.; Kim, Y.W. Effects of infographics on news elaboration, acquisition, and evaluation: Prior knowledge and issue involvement as moderators. New Media Soc. 2016, 18, 1579–1598. [Google Scholar] [CrossRef]
  24. Valkenburg, P.M.; Peter, J. The differential susceptibility to media effects model. J. Commun. 2013, 63, 221–243. [Google Scholar] [CrossRef]
  25. Gu, J.; Xu, Y.C.; Xu, H.; Zhang, C.; Ling, H. Privacy concerns for mobile app download: An elaboration likelihood model perspective. Decis. Support Syst. 2017, 94, 19–28. [Google Scholar] [CrossRef]
  26. Anderson, C.A.; Shibuya, A.; Ihori, N.; Swing, E.L.; Bushman, B.J.; Sakamoto, A.; Rothstein, H.R.; Saleem, M. Violent video game effects on aggression, empathy, and prosocial behavior in eastern and western countries: A meta-analytic review. Psychol. Bull. 2010, 136, 151–173. [Google Scholar] [CrossRef] [Green Version]
  27. MacDonald, E.; Milfont, T.; Gavin, M. Applying the Elaboration Likelihood Model to increase recall of conservation messages and elaboration by zoo visitors. J. Sustain. Tour. 2016, 24, 866–881. [Google Scholar] [CrossRef]
  28. Slater, M.D. Reinforcing spirals model: Conceptualizing the relationship between media content exposure and the development and maintenance of attitudes. Media Psychol. 2015, 18, 370–395. [Google Scholar] [CrossRef] [PubMed]
  29. Knobloch-Westerwick, S. The selective exposure self-and affect-management (SESAM) model: Applications in the realms of race, politics, and health. Commun. Res. 2015, 42, 959–985. [Google Scholar] [CrossRef]
  30. Bakermans-Kranenburg, M.J.; van Ijzendoorn, M.H. Differential susceptibility to rearing environment depending on dopamine-related genes: New evidence and a meta-analysis. Dev. Psychopathol. 2011, 23, 39–52. [Google Scholar] [CrossRef]
  31. Bandura, A. Social cognitive theory or mass communication. In Media Effects: Advances in Theory and Research; Bryant, J., Oliver, M.B., Eds.; Routledge: New York, NY, USA, 2009; pp. 94–124. [Google Scholar]
  32. Roskos-Ewoldson, D.R.; Roskos-Ewoldson, B. Current research in media priming. In The Sage Handbook of Media Processes and Effects; Nabi, R.L., Oliver, M.B., Eds.; Sage: Los Angeles, CA, USA, 2009; pp. 177–192. [Google Scholar]
  33. Klapper, J.T. The Effects of Mass Communication; Free Press: New York, NY, USA, 1960. [Google Scholar]
  34. McLeod, D.M.; Kosicki, G.M.; McLeod, J.M. Political communication effects. In Media Effects: Advances in Theory and Research; Bryant, J., Oliver, M.B., Eds.; Routledge: New York, NY, USA, 2009; pp. 228–251. [Google Scholar]
  35. Berkowitz, L. Some effects of thoughts on antisocial and prosocial influences of media events: A cognitive-neoassociationistic analysis. Psychol. Bull. 1984, 95, 410–427. [Google Scholar] [CrossRef]
  36. Petty, R.E.; Brinol, P.; Priester, J.R. Mass media attitude change: Implications of the elaboration likelihood model of persuasion. In Media Effects: Advances in Theory and Research; Bryant, J., Oliver, M.B., Eds.; Routledge: New York, NY, USA, 2009; pp. 125–163. [Google Scholar]
  37. Shrum, L.J. Media consumption and perceptions of social reality. In Media Effects: Advances in Theory and Research; Bryant, J., Oliver, M.B., Eds.; Routledge: New York, NY, USA, 2009; pp. 50–73. [Google Scholar]
  38. Houston, J.B.; Spialek, M.L.; First, J. Disaster media effects: A systematic review and synthesis based on the differential susceptibility to media effects model. J. Commun. 2018, 68, 734–757. [Google Scholar] [CrossRef]
  39. Cingel, D.P.; Mann, S. Influence of Social Context on Media Selection and Use. Intern. Encycl. Media Psychol. 2020, 1–8. [Google Scholar] [CrossRef]
  40. Choi, S.; Lee, M. Diversity as an opportunity or a challenge? A cross-national study of ethnic diversity and students’ generalized trust. Int. J. Educ. Dev. 2021, 80, 102301. [Google Scholar] [CrossRef]
  41. Landrum, A.R.; Olshansky, A.; Richards, O. Differential susceptibility to misleading flat earth arguments on youtube. Media Psychol. 2019. [Google Scholar] [CrossRef] [Green Version]
  42. Bazzi, S.; Gudgeon, M. The political boundaries of ethnic divisions. Am. Econ. J. Appl. Econ. 2021, 13, 235–266. [Google Scholar] [CrossRef]
  43. Perloff, R.M. Social media effects on young women’s body image concerns: Theoretical perspectives and an agenda for research. Sex Roles 2014, 71, 363–377. [Google Scholar] [CrossRef]
  44. Entman, R.M. Media framing biases and political power: Explaining slant in news of Campaign 2008. Journalism 2010, 11, 389–408. [Google Scholar] [CrossRef]
  45. Bizer, G.Y.; Larsen, J.T.; Petty, R.E. Exploring the valence-framing effect: Negative framing enhances attitude strength. Political Psychol. 2011, 32, 59–80. [Google Scholar] [CrossRef]
  46. Kroon, A.C.; van Selm, M.; ter Hoeven, C.L.; Vliegenthart, R. Poles apart: The processing and consequences of mixed media stereotypes of older workers. J. Commun. 2016, 66, 811–833. [Google Scholar] [CrossRef]
  47. Metzger, M.J.; Flanagin, A.J.; Medders, R.B. Social and heuristic approaches to credibility evaluation online. J. Commun. 2010, 60, 413–439. [Google Scholar] [CrossRef] [Green Version]
  48. Gajjala, R. Digital media, race, gender, affect, and labor: Introduction to special section. Telev. New Media 2014, 15, 215–222. [Google Scholar] [CrossRef]
  49. Tolsma, J.; van Deurzen, I.; Stark, T.H.; Veenstra, R. Who is bullying whom in ethnically diverse primary schools? Exploring links between bullying, ethnicity, and ethnic diversity in Dutch primary schools. Soc. Netw. 2013, 35, 51–61. [Google Scholar] [CrossRef]
  50. Jamil, S. Ethnic news media in the digital age: The impact of technological convergence in reshaping journalists’ practices in Pakistan. J. Multicult. Discourses 2020, 1–21. [Google Scholar] [CrossRef]
  51. Franceschini, G.; Galli, S.; Chiesi, F.; Primi, C. Implicit gender–math stereotype and women’s susceptibility to stereotype threat and stereotype lift. Learn. Individ. Differ. 2014, 32, 273–277. [Google Scholar] [CrossRef]
  52. Brandtzaeg, P.B.; Følstad, A.; Domínguez, M.Á.C. How journalists and social media users perceive online fact-checking and verification services. J. Pract. 2018, 12, 1109–1129. [Google Scholar] [CrossRef]
  53. Nekmat, E. Nudge Effect of Fact-Check Alerts: Source Influence and Media Skepticism on Sharing of News Misinformation in Social Media. Soc. Media+ Soc. 2020, 6, 2056305119897322. [Google Scholar] [CrossRef]
  54. Bashri, M. Ethnic Media in the Digital Age; Sherry, S.Y., Matsaganis, M.D., Eds.; Routledge: New York, NY, USA, 2019; Volume 1, pp. 123–126. [Google Scholar] [CrossRef]
  55. Usher, N. The appropriation/amplification model of citizen journalism: An account of structural limitations and the political economy of participatory content creation. J. Pract. 2017, 11, 247–265. [Google Scholar] [CrossRef]
  56. Schmidt, T.R.; Heyamoto, L.; Milbourn, T. The social construction of media trust: An exploratory study in underserved communities. J. Appl. J. Media Stud. 2019, 8, 257–271. [Google Scholar] [CrossRef]
  57. Koltay, T. The media and the literacies: Media literacy, information literacy, digital literacy. MediaCult. Soc. 2011, 33, 211–221. [Google Scholar] [CrossRef]
  58. Cox, V.; Ward, L.M. A wholistic view of Black women on scripted TV: A content analysis. J. Black Psychol. 2019, 45, 540–570. [Google Scholar] [CrossRef]
  59. Daalmans, S.; Odink, M. Stereotyped but Liked? A Content Analysis of the Presence and Stereotypical Portrayal of Minority Groups in Award-Winning Commercials. Commun. Res. Rep. 2019, 36, 231–241. [Google Scholar] [CrossRef]
  60. Saleem, M.; Ramasubramanian, S. Muslim Americans’ responses to social identity threats: Effects of media representations and experiences of discrimination. Media Psychol. 2019, 22, 373–393. [Google Scholar] [CrossRef]
  61. Appiah, O.; Knobloch-Westerwick, S.; Alter, S. Ingroup favoritism and outgroup derogation: Effects of news valence, character race, and recipient race on selective news reading. J. Commun. 2013, 63, 517–534. [Google Scholar] [CrossRef]
  62. Figueroa-Caballero, A.; Mastro, D.; Stamps, D. An examination of the effects of mediated intragroup and intergroup interactions among latino/a characters. Commun. Q. 2019, 67, 271–290. [Google Scholar] [CrossRef]
  63. van Oosten, J.M.; Peter, J.; Boot, I. Women’s critical responses to sexually explicit material: The role of hyperfemininity and processing style. J. Sex Res. 2015, 52, 306–316. [Google Scholar] [CrossRef] [PubMed]
  64. Valkenburg, P.M.; Peter, J.; Walther, J.B. Media effects: Theory and research. Annu. Rev. Psychol. 2016, 67, 315–338. [Google Scholar] [CrossRef] [Green Version]
  65. Kohring, M.; Matthes, J. Trust in news media: Development and validation of a multidimensional scale. Commun. Res. 2007, 34, 231–252. [Google Scholar] [CrossRef]
  66. Turcotte, J.; York, C.; Irving, J.; Scholl, R.M.; Pingree, R.J. News recommendations from social media opinion leaders: Effects on media trust and information seeking. J. Comput. Mediat. Commun. 2015, 20, 520–535. [Google Scholar] [CrossRef]
  67. Stark, T.H.; Flache, A.; Veenstra, R. Generalization of positive and negative attitudes toward individuals to outgroup attitudes. Personal. Soc. Psychol. Bull. 2013, 39, 608–622. [Google Scholar] [CrossRef]
  68. Black, W.; Babin, B.J. Multivariate data analysis: Its approach, evolution, and impact. In The Great Facilitator; Springer: Cham, Switzerland, 2019; pp. 121–130. [Google Scholar]
  69. Malhotra, N.K.; Dash, S. Marketing Research an Applied Orientation; Pearson Publishing: London, UK, 2011. [Google Scholar]
  70. Zaman, U. Examining the effect of xenophobia on “transnational” mega construction project (MCP) success. Eng. Constr. Archit. Manag. 2020, 2, 1119–1143. [Google Scholar] [CrossRef]
  71. Zaman, U.; Nawaz, S.; Tariq, S.; Humayoun, A.A. Linking transformational leadership and “multi-dimensions” of project success. Int. J. Manag. Proj. Bus. 2019, 13, 103–127. [Google Scholar] [CrossRef]
  72. Carlson, M. When news sites go native: Redefining the advertising–editorial divide in response to native advertising. Journalism 2015, 16, 849–865. [Google Scholar] [CrossRef]
  73. Andrews, K.T.; Caren, N. Making the news: Movement organizations, media attention, and the public agenda. Am. Sociol. Rev. 2010, 75, 841–866. [Google Scholar] [CrossRef]
  74. Zaman, U.; Jabbar, Z.; Nawaz, S.; Abbas, M. Understanding the soft side of software projects: An empirical study on the interactive effects of social skills and political skills on complexity–performance relationship. Int. J. Proj. Manag. 2019, 37, 444–460. [Google Scholar] [CrossRef]
  75. Ferguson, C.J.; Kilburn, J. The public health risks of media violence: A meta-analytic review. J. Pediatrics 2009, 154, 759–763. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Measurement Model with item-loadings on parent factors of MGS, AO, and MT.
Figure 1. Measurement Model with item-loadings on parent factors of MGS, AO, and MT.
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Figure 2. Structural model with Moderation of Gender in MGS and AO link.
Figure 2. Structural model with Moderation of Gender in MGS and AO link.
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Figure 3. Structural model with Moderation of Ethnicity in MGS and AO link.
Figure 3. Structural model with Moderation of Ethnicity in MGS and AO link.
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Figure 4. Moderation of Gender in MGS and MT link.
Figure 4. Moderation of Gender in MGS and MT link.
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Figure 5. Moderation of Ethnicity in MGS and MT link.
Figure 5. Moderation of Ethnicity in MGS and MT link.
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Table
Table 1. Descriptive Statistics and Bivariate Correlations MGS, AO, and MT variables.
Table 1. Descriptive Statistics and Bivariate Correlations MGS, AO, and MT variables.
VariablesMSDαMGSAOMT
MGS4.470.7210.7081
AO4.391.050.867−0.39 *1
MT4.290.9680.814−0.26 *0.15 *1
* p > 0.01.
Table
Table 2. Confirmatory Factor Analysis; MGS, AO, and MT, Measurement Model.
Table 2. Confirmatory Factor Analysis; MGS, AO, and MT, Measurement Model.
Modelsx2DFx2/DFCFIAGFIGFINFIIFITLIRMSEA
MGS-MT-AO single30.58251.220.990.980.990.980.970.990.02
MGS-MT-AO parent158.03782.030.970.960.980.940.960.940.03
Table
Table 3. Convergent and Discriminant Validity of MGS, AO, and AO model.
Table 3. Convergent and Discriminant Validity of MGS, AO, and AO model.
ConstructsCRAVEMGSAOMT
MGS0.950.63(0.793)
AO0.850.570.19 *(0.755)
MT0.860.540.12 *0.08 *(0.735)
Values in parentheses represent the square root of the AVE and *= p < 0.001.
Table
Table 4. Standardized Regression: MGS direct and moderated relations with AO and MT.
Table 4. Standardized Regression: MGS direct and moderated relations with AO and MT.
Direct RelationshipβΔR2p-ValuesHypothesis
AO<--------MGS−0.210.150.01H1 Supported
MT<--------MGS−0.270.170.01H2 Supported
AO<-GN*--MGS0.280.260.001H3a Supported
MT<-GN*--MGS0.240.320.01H3b Supported
AO<-ET*--MGS0.220.080.01H4a Supported
MT<-ET*--MGS0.170.400.01H4b Supported
MT = Media Trust, AO = Attitude towards media Organizations, GN* = interaction of Gender, ET* = interaction of Gender and Ethnicity.
Table
Table 5. Moderation of Gender and Ethnicity Structural Models.
Table 5. Moderation of Gender and Ethnicity Structural Models.
Modelsx2DFx2/DFCFIAGFIGFINFIIFITLIRMSEA
1.MGS-AO278.34932.990.950.950.970.930.950.920.04
2.MGS-AO Gender397.911073.720.960.930.960.910.930.890.05
3.MGS-AO Ethnicity368.531213.050.940.940.970.920.940.910.04
4. MGS-MT166.14941.770.970.970.980.930.970.950.02
5. MGS-MT Gender261.03942.780.960.950.970.930.960.930.04
6.MGS-MTEthnicity294.871262.340.970.950.970.950.950.970.03
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Raza, S.H.; Zaman, U.; Iftikhar, M. Examining the Effects of Media-Generated Stereotypes on Receivers’ Trust and Attitude in Pakistan. Moderating Influence of Ethnicity and Gender. Information 2021, 12, 35. https://0-doi-org.brum.beds.ac.uk/10.3390/info12010035

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Raza SH, Zaman U, Iftikhar M. Examining the Effects of Media-Generated Stereotypes on Receivers’ Trust and Attitude in Pakistan. Moderating Influence of Ethnicity and Gender. Information. 2021; 12(1):35. https://0-doi-org.brum.beds.ac.uk/10.3390/info12010035

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Raza, Syed Hassan, Umer Zaman, and Moneeba Iftikhar. 2021. "Examining the Effects of Media-Generated Stereotypes on Receivers’ Trust and Attitude in Pakistan. Moderating Influence of Ethnicity and Gender" Information 12, no. 1: 35. https://0-doi-org.brum.beds.ac.uk/10.3390/info12010035

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