Greenfluencing Through the Power of Emotions? Impact of Message Frames and Emotionally Matching Background Music on the Effectiveness of Influencers’ Environmental Communication

Abstract

Social media influencers have become increasingly important in persuading people to become environmentally sensitive. As “greenfluencers” have been studied primarily in the context of advertising, it is crucial to investigate the mechanisms and effects of their non-product–related environmental messages. In two studies, we tested different message frames, a well-known persuasion strategy, in the context of Instagram reels (short audiovisual videos), where user-added background music is a prominent feature. In a 2 × 2 between-subjects online experiment (N = 240), we manipulated the message frame (gain vs. loss) and the background music (positive vs. negative emotional valence) and found that loss frames reduced behavioral intention via negative emotions. A second 2 × 2 between-subjects online experiment (N = 207) replicated these findings with an older sample and provided additional evidence that gain frames should be used in environmental communication. Contrary to our assumptions, we found no effect of the emotional valence of music in either study.

Keywords

greenfluencer message frame sustainability background music environmental behavioral intention

Social media influencers (SMIs) no longer only appear in the classic advertising context on social network sites (SNSs), where they test certain products, cooperate with brands, or advertise services. The persuasive power of SMIs in this context means that they have long since acted as digital opinion leaders (De Veirman et al., 2017) who promote a certain lifestyle. However, SMIs are increasingly concerned with educating their followers with regard to social and political topics and convincing them to adopt certain attitudes and behaviors, whether in the context of politics (Naderer, 2022), fitness and food (Sokolova & Perez, 2021), or sustainability and environmental protection (Boerman et al., 2022). SMIs who particularly serve the topics of sustainability and environmental protection are also referred to as “greenfluencers” (e.g., Boerman et al., 2022; Breves & Liebers, 2022). Of course, greenfluencers also advertise green products in the classic sense of advertising and collaborate with ecologically sustainable companies. However, they do more than that: They educate people about greenwashing, give everyday tips, and even sit on talk shows or produce their own podcasts. To make this content entertaining, greenfluencers have increasingly created short videos known as reels in recent years. These are suggested to recipients based on algorithms and are becoming increasingly popular on SNSs such as Instagram or TikTok (Hutchinson, 2022).

Greenfluencers can influence the attitudes and behavioral intentions of social media users (Kapoor et al., 2023; Schorn et al., 2022). The perception of the SMIs themselves and their interactions with followers play an important role in successful persuasion (e.g., Breves & Liebers, 2022; Hasbullah et al., 2020; Knupfer et al., 2023). However, little is known about the effectiveness of their various types of messaging. This seems surprising because, in addition to the perception of the communicator, the formulation of the message can be an important factor in the persuasive effect. Research has shown that messages can have very different effects depending on their type and formulation (Shen & Bigsby, 2013). This raises the question of which wording greenfluencers should choose for environmental messages if they want to convince recipients of their opinions.

We focus on message framing and the underlying idea that messages have different effects depending on whether they are framed as gains or losses (Kahneman & Tversky, 1979). Because message frames trigger certain emotions (e.g., Nabi et al., 2020), they are a common communication tactic in strategic communication (e.g., H. Chang et al., 2015; Huang et al., 2021; Segev et al., 2015). Emotions have been shown to be important explanatory mechanisms in communication about environmental issues (Myrick & Conlin, 2022). Research to date has shown a heterogeneous picture regarding the effectiveness of positive and negative emotions in an environmental context (Nabi et al., 2022). While some studies show that positive emotions are more effective (e.g., Chadwick, 2015; Schneider et al., 2021), others have shown that negative emotions can lead to an increase in environmentally conscious behavioral intentions (e.g., Feldman & Hart, 2018; Smith & Leiserowitz, 2014). We want to investigate the psychological processes that can arise through differently valenced emotions and influence the environmentally conscious behavior, while focusing on the messages of greenfluencers as triggers.

To our knowledge, the efficacy of message frames in the greenfluencer context has not been explored yet. This is an intriguing area of research because environmental messages in short videos, known as reels, are brief and communicate at a rapid pace (Kilgour et al., 2015). It is unclear to what extent conventional media persuasion tactics (Morton et al., 2011; Nabi et al., 2020) are effective in inducing emotions in this particular context. This is where our study comes in. In addition to the wording of the message, we look at another characteristic that is known to generate emotions (e.g., Scott et al., 2022): the background music. The use of music is known from different contexts to be a strong emotionalizing cue (e.g., in the context of movie reception: Herget, 2021; music listening: Kreutz et al., 2008; advertising: Alpert & Alpert, 1989). Reels on SNSs have been designed with background music by influencers for some time now, and apps such as Instagram offer an enormous selection of songs in an app-internal library. In our study, we consider music as a moderator and ask whether background music that matches the formulation of the environmental message can reinforce the emotions emanating from the message.

The overall aim is to answer the following overarching research question: What types and characteristics of environmental messages from greenfluencers on Instagram are particularly effective, and what emotional processes are responsible? Answering the research question can both supplement the literature on the effectiveness of emotions in environmental communication on a theoretical level and advance influencer research by looking at message frames in the greenfluencer context. On a practical level, greenfluencers receive concrete tips on how they can shape their messages most effectively.

Theoretical Background

The Effectiveness of Greenfluencer

Greenfluencers are influencers who focus strongly on environmental protection and sustainability (Knupfer et al., 2023). Greenfluencers can be purely business-oriented and focus on environmentally friendly, green products (Breves & Liebers, 2022; Kapoor et al., 2023; Pittman & Abell, 2021). However, they can also see themselves as opinion leaders for the pro-social idea and promote the green lifestyle in general rather than specific products (Boerman et al., 2022; Dekoninck & Schmuck, 2022; Schorn et al., 2022). These greenfluencers include not only traditional business-oriented influencers but also activists and scientists (Huber et al., 2022). Overall, most studies focus on the perception of the greenfluencers themselves. For example, several studies are dedicated to the effectiveness of parasocial relationships between greenfluencers and followers (Breves & Liebers, 2022; Dekoninck et al., 2023; Hasbullah et al., 2020; Knupfer et al., 2023). The studies consistently conclude that parasocial relationships increase persuasive effectiveness. Other studies examine the perceived congruence between greenfluencers and their message (Boerman et al., 2022), the effectiveness of different key figures of greenfluencers (Pittman & Abell, 2021), their monetization strategies (Jacobson & Harrison, 2022), or the effectiveness of different contents of environmental messages (Kapoor et al., 2023; Schorn et al., 2022). It is striking that the few studies that look at the environmental message itself (Boerman et al., 2022; Kapoor et al., 2023; Schorn et al., 2022) also consider the perception of greenfluencers (i.e., their perceived trustworthiness, expertise, or authenticity) as central constructs in their impact models. This is quite plausible, as existing research on influencers highlights the significance of the communicator’s perception (e.g., their attractiveness [Farivar et al., 2022], trustworthiness [Schouten et al., 2020], or expertise [Gomes et al., 2022]) for persuasive effectiveness. However, this research focus has neglected to examine the effectiveness of environmental messages themselves and the psychological processes they trigger. Notably, no research has been conducted on the message frames in the context of greenfluencers. It is widely acknowledged in the field of environmental communication that the formulation of messages can have a significant impact on their effectiveness (H. Chang et al., 2015; Diamond & Urbanski, 2022; Shen & Bigsby, 2013). Therefore, it is obvious that greenfluencers who aim to persuade individuals to adopt specific behaviors utilize this type of persuasion strategy. As mentioned in the introductory section, social media reels compress content into a few seconds, making it uncertain how effective environmental messages are at generating emotions here. In contrast to newspaper articles or information brochures, for example, users have much less time to absorb the content and let it sink in. To examine the effectiveness of message frames in the greenfluencer context, we first turn to research on message frames in general.

Message Framing

In general, message frames describe what can be gained by following a certain behavior (gain frame) and what can be lost by not following a certain behavior (loss frame). The origins of message framing can be found in prospect theory, which originated in behavioral economics (Kahneman & Tversky, 1979). The theory assumes that a person’s choice between a riskier vs. a less risky option, with the same chance of occurrence, depends on their level of risk aversion. When people focus on making gains, they are risk averse; however, when they want to avoid losses, they are more likely to act in a risky manner. From this, the researchers deduced that loss frames are more effective when the decision option is risky, whereas gain frames are more effective when the decision option is not risky (Kahneman & Tversky, 1979). Rothman and colleagues (1993, 1999) developed and adapted the gain–loss hypothesis to the health context, with a choice between prevention and detection of breast cancer instead of a choice between safe and unsafe options. Consistent with the original findings of prospect theory, they found that gain frames were more effective for prevention messages, whereas loss frames were more effective for detection messages (Rothman et al., 2006). A recent systematic literature review (Guenther et al., 2020) identified more than 300 peer-reviewed articles on this topic in the health communication literature. However, according to a meta-analysis (O’Keefe & Jensen, 2008), although some of these studies confirmed original findings of Rothman and colleagues (2006), others reported opposite results.

Therefore, in health communication, where message frames are widely used, it has not been clearly established whether gain or loss frames are more appropriate for changing attitudes. It is thus important to take a closer look at the persuasion processes of message frames. According to Kahneman (2003), message frames are capable of changing cognitions, emotions, and behaviors. Several studies have examined the mediating function of emotions in explaining the mechanism of action of message frames in the health context (e.g., H. Lee & Cameron, 2017; Lee-Won et al., 2017; Quick et al., 2015). In their meta-analysis, Nabi and colleagues (2020) reported that 25 studies had tested message framing and emotions using an experimental design. From these studies, the authors concluded that gain frames enhance positive emotions significantly more than loss frames, while loss frames enhance negative emotions significantly more than gain frames (Nabi et al., 2020). Since both positive and negative emotions (e.g., fear appeals) can influence behavioral intentions, it makes sense that both gain and loss frames can be suitable persuasion strategies and that the research findings in this area are mixed.

Message Framing of Environmental Messages

Climate change is one of the greatest challenges of our time (United Nations, 2020). It is not surprising, therefore, that environmental communication is increasingly concerned with how messages should be formulated to change people’s attitudes and behavioral intentions and persuade them to behave in a more sustainable and environmentally friendly way (e.g., Kapoor et al., 2022; Schorn et al., 2021). In addition, there is a diverse range of topics relating to the use of message frames in environmental communication, such as green advertising (e.g., H. Chang et al., 2015; Huang et al., 2021; Segev et al., 2015) and green tourism/sustainable travel (e.g., Chi et al., 2021; Yoon et al., 2019; Zhang et al., 2020). Of course, the question of whether gain or loss frames have a stronger positive effect is also of great interest in the environmental context. The majority of studies in this area have shown that gain frames are more effective (e.g., green purchasing behavior: Buda & Zhang, 2000; climate-friendly travel: Chi et al., 2021; food waste: Huang et al., 2021; climate change mitigation measures: Morton et al., 2011; green advertising: Segev et al., 2015; green attitudes: Spence & Pidgeon, 2010). Nevertheless, as in health communication, some studies have shown the opposite (e.g., M.-C. Chang & Wu, 2015; Davis, 1995; Li et al., 2021). To understand the effects of the two types of frames in environmental communication, studies have examined emotions as mediators between message frames and behavioral intentions (e.g., Bilandzic et al., 2017; Carfora et al., 2021; Seo & Dillard, 2019). Some have focused on specific emotions such as anger and fear (Carfora et al., 2021), pride (Zubair et al., 2020), guilt (Baek & Yoon, 2017), or hope (Bilandzic et al., 2017), whereas others have focused more generally on positive and negative emotions (e.g., Isham et al., 2022; Millar & Millar, 2000; Perrin, 2011). Regardless of the concreteness of the emotion, the results suggest a mediating function whereby gain frames strengthen positive emotions, whereas loss frames increase negative emotions. Based on these findings, we also assume that message frames influence the types of emotions that arise:

Hypothesis 1 (H1). Gain frames have a stronger positive influence on positive emotions than do loss frames.

Hypothesis 2 (H2). Loss frames have a stronger positive influence on negative emotions than do gain frames.

Emotions can influence our attitudes and behavioral intentions (Nabi, 2002). Some studies on message framing in the environmental domain (e.g., Carfora et al., 2021; Overton, 2018) have examined this relationship in more detail by incorporating two-process models into their constructs to show that different types of processing are triggered by different emotions. Perceived environmental self-efficacy and perceived seriousness of the environmental topic seem to be additional mediating factors that can explain this process and the environment-related outcomes. Self-efficacy expectancy is the belief that one can successfully perform a required behavior to achieve the desired outcomes and have control over one’s own life (Bandura, 1977). Accordingly, perceived self-efficacy influences the way individuals gather and interpret information and the actions they consider in response (Bandura, 1977). Bandura (1977) postulated, in his theory of social cognitive learning, that a person’s self-efficacy expectancy is based on four factors: their own successful performance, vicarious experiences, verbal encouragement, and emotional arousal. The latter point in particular suggests that a person’s assessment of whether they are able to take their fate into their own hands and take action themselves is activated by emotions. Therefore, we propose:

Hypothesis 3 (H3). The stronger the positive emotions, the higher the perceived environmental self-efficacy.

A person’s belief in their ability to perform a required behavior to achieve the desired outcomes might be one of their biggest drivers. In the health context, Bandura (2004) and Krieger and Sarge (2013) showed that high self-efficacy beliefs lead individuals to expect more favorable outcomes, whereas low self-efficacy beliefs lead them to expect more negative outcomes. Perceived self-efficacy is also important in the environmental context (Grazzini et al., 2018). When issues like climate change seem too big and daunting, it is important to realize the associated opportunity to take action ourselves. Schutte and Bhullar (2017) found that participants who had greater environmental self-efficacy and belief in the changeability of their sustainability-related behaviors reported greater motivation to engage in and were more likely to actually enact such behaviors. Self-efficacy beliefs also influence people’s willingness to pay for environmental protection when traveling (Doran et al., 2015) and to participate in local community festivals (Jepson et al., 2014). Thus, in line with the aforementioned research, we propose:

Hypothesis 4 (H4). The stronger the perceived environmental self-efficacy, the stronger the pro-environmental behavioral intention.

Now we turn to loss frames and the negative emotions triggered by them and take a closer look at the concept of the perceived seriousness of the topic. Negative emotions do not necessarily lead to the feeling of being overwhelmed and the inability to act. Indeed, when people make judgments, they are guided by heuristic cues, one of which may be their emotions (B. Lee et al., 2021). For example, when in a bad mood, people tend to rate their overall life satisfaction lower than when in a good mood (Schwarz & Clore, 1983). In their study on climate change, Spence and Pidgeon (2010) showed that this type of assessment based on emotions can also be transferred to environmental topics: The stronger the participants’ fear, the higher they perceived the severity of climate change. We expect a similar finding for the perceived seriousness of an environmental issue and thus infer:

Hypothesis 5 (H5). The stronger the negative emotions, the higher the perceived seriousness of an environmental issue.

The link between the causes and consequences of climate change, as well as the perceived severity of these consequences, are important determinants of behavior (Beckage et al., 2018; Shi et al., 2015). For example, the perception of climate change as high risk leads to positive sustainable behavioral intentions and more environmentally friendly behavior (Maartensson & Loi, 2022). Hidalgo and Pisano (2010) also found a relationship between perceived risk and behavioral intentions related to climate change, and Zhu and colleagues (2020) found that the perception of urban smog as high risk was related to individuals’ intention to adopt smog-reducing behaviors. Again, we believe that these findings can be applied to the seriousness of the environmental problem.

Hypothesis 6 (H6). The higher the perceived seriousness of the environmental problem, the higher the pro-environmental behavioral intentions.

Message Frames and Emotional Background Music

As described in the previous section, message frames deliver a kind of emotionalizing promotion for pro-environmental behavioral intentions that differs in the valence of the emotional experiences it evokes. In addition to the content of the message, the design of the message can also lead to a stronger emotional experience (Schneider et al., 2019). For example, in environmental communication, the use of emotive images of nature has proven to be an emotional amplifier (Hartmann & Apaolaza-Ibáñez, 2010). Another important factor that has received little attention so far is the background music. Background music has become an important feature of Instagram reels in recent years. When examining background music in the audiovisual context of Instagram reels, it seems sensible to first take a closer look at music’s own emotionalizing potential. The interplay of specific parameters of a musical composition can carry perceivable emotional expressions (for an overview, see Gabrielsson & Lindström, 2010), which lead to consistent perceptions, at least within a given culture (Wirth & Schramm, 2005). Furthermore, several studies have shown that music possesses an inherent capability to evoke emotions in recipients (e.g., Kreutz et al., 2008; Zentner et al., 2008). Remarkably, with regard to the influence of emotions in the media context, it does not matter whether the musical pieces are familiar (Herget, 2021) or they are of great length (Scott et al., 2022), which both seem promising premises for using background music as an emotionalizing cue in Instagram reels.

Second, according to research on background music, the degree to which the music fits the rest of the content and shows a certain congruence to the medium seems to be crucial for its effective use in audiovisual formats. This has been shown in non-fictional contexts such as documentaries (Herget & Albrecht, 2022), for fictional content such as films (Cohen, 2013), and for advertising (MacInnis & Park, 1991). More specifically, a better fit between the music and various dimensions has a more favorable influence on information processing and, in turn, has greater persuasive effects on attitudes and behavioral intentions (e.g., Herget et al., 2022; North et al., 2016).

Taking these two perspectives together, we can expect particular background music in a greenfluencer’s reel to have predictable outcomes concerning the valence of emotional reactions. Furthermore, as gain and loss frames themselves are anticipated to cause distinct emotional responses, it seems plausible to expect that the overall emotional reaction should be strongest if the valence of both emotional cues (music and frame) is consistent. We assume, therefore, that the emotional consequences of receiving gain frames are reinforced by the use of corresponding music with positive emotional valence, whereas for loss frames, this effect is expected through music with a negative emotional valence.

Hypothesis 7a (H7a). Background music with a positive emotional valence leads to stronger positive emotions in the case of gain frames than background music with negative emotional valence.

Hypothesis 7b (H7b). Background music with negative emotional valence leads to stronger negative emotions in the case of loss frames than background music with positive emotional valence.

Figure 1 shows the expected relationships between the previously introduced constructs.

Figure 1.

Hypothesis model.

Study 1

Method

Study Design and Pretest

To test the effect of message frames and matching background music in Instagram reels, an online study with a 2 × 2 between-subjects experimental design was implemented in Germany. The dichotomous independent variable was the message frame (gain vs. loss), and the moderator variable was the emotional valence of the music (positive vs. negative). We created an Instagram reel with a male fictitious SMI on the topic of “environmental pollution due to plastic waste.” We gave no other information about the SMI, to ensure the external validity was as high as possible. Reels are not only shown to followers (i.e., people who know the SMI) but are also randomly suggested to users based on user data. In both reel conditions, three statements were made about plastic consumption, formulated as either a loss (e.g., “If we don’t switch from plastic to cloth bags now, we’ll be harming the environment with every purchase we make”) or a gain frame (e.g., “If we switch from plastic to cloth bags now, we’ll help the environment with every purchase we make”). A pretest was conducted to select the most appropriate music. Only instrumental music pieces were chosen, to exclude the potential unintended effects of lyrics and to simplify the assignment of emotional valence. This approach was considered appropriate because formal musical features like mode and tempo are in themselves capable of conveying different emotional expressions (for an overview, see Herget et al., 2018, p. 368). Lyrics with their own inherent message on the other hand have been found to have an individual influence on thoughts (Ruth & Schramm, 2021) which are not to be investigated in the present study. For each type of emotional valence (positive or negative), we selected one piece with piano music and one with guitar music to address the potential problem of musical clichés and associations that are potentially linked with the tone and nature of certain instruments (e.g., stereotypically perceiving an instrument as more feminine than another, see Cooper & Burns, 2021; Wych, 2012). All the pieces of music used in the study were available in Instagram’s own music library, which is implemented in the app as part of the reels’ design tools. They therefore represent pieces of music that could potentially also be used by real Instagram users, which contributes to the external validity of the stimulus material. For the pretest (N = 30), we created eight versions of the reel by distinguishing between gain and loss frames, negative and positive music, and guitar and piano music. Using a within-subjects design, the participants rated the eight versions in terms of emotionality and musical fit. The results showed that the positive music differed significantly from the negative music in its emotional perception (p < .01), and the perceived musical fit was as desired. All descriptive values can be found in Table 1. Consequently, all eight versions were used in the main study. All reels are available online (https://osf.io/ev95q/?view_only=4e159357a9c240399730732afffbde10).

Table 1.

Pretest: Descriptive Results.

Reel	Emotions^a		Musical fit^b
	M	SD	M	SD
Gain Negative Music Piano	3.97	1.31	3.85	1.62
Gain Negative Music Guitar	3.88	.99	3.39	1.35
Gain Positive Music Piano	4.94	.99	4.88	1.08
Gain Positive Music Guitar	4.76	1.06	4,76	1.35
Loss Negative Music Piano	3.48	1.25	4.42	1.60
Loss Negative Music Guitar	3.67	1.14	3.42	1.32
Loss Positive Music Piano	4.48	1.25	3.45	1.60
Loss Positive Music Guitar	4.27	1.28	3.42	1.60

N = 30.

Five-point Likert-type scale from 1 (very negative) to 5 (very positive)

Five-point Likert-type scale from 1 (very inappropriate) to 5 (very appropriate).

Measurement and Procedure

Before the participants were shown the reels, they were welcomed and informed about the procedure of the study. They then answered the demographic questions. After performing a short sound test, they were shown the Instagram reel. The sound test consisted of a short audio sample of an animal sound and the subsequent question as to which animal sound was heard to make sure that everyone had their audio output device switched on. The results show that all participants passed the test. After watching the reel, they were asked to indicate which emotions they felt during the reception. We measured the emotions using the PANAS scale by Breyer and Bluemke (2016; M_positive = 2.64, SD_positive = .69, α_positive = .85; M_negative = 1.86, SD_negative = .65, α_negative = .83). The scale asks about emotions such as “active,” “enthusiastic,” or “anxious.” A five-point Likert-type scale (strongly disagree—strongly agree) was used throughout the questionnaire. Next, we measured perceived self-efficacy with three items by Grazzini and colleagues (2018; M = 3.71, SD = .76, α = .63; e.g., “I have the feeling that I can make a difference by avoiding plastic”) and the perceived seriousness of the environmental issue with four items by B. Lee and colleagues (2021; M = 4.20, SD = .66, α = .70; e.g., “How urgent do you think it is to reduce the amount of plastic?”). To capture the environmentally friendly behavioral intention, we followed Morton et al. (2011) in asking about various green behaviors, some of which appeared in the reel itself, and others whose wording was taken from an environmental organization (World Wide Fund for Nature, 2023; 9 items, M = 4.16, SD = .50, α = .69). Here, we asked about behaviors such as “Use reusable cloth bags for shopping” or “Separate waste.” Afterwards, the participants watched the reel again and were asked to rate its credibility with the item “I perceived the reel I just saw as genuine” on a five-point Likert-type scale (M = 3.58, SD = 1.23), as well as the credibility of the SMI with 12 items (M = 4.46, SD = .91) from Ohanian (1990) on a six-point Likert-type scale.

Sample

To determine the appropriate sample size for the study, an a priori power analysis was conducted using G*Power (power = .80; alpha error probability = .05). For the effect size, we followed studies on the persuasive influence of musical fit (Herget et al., 2022) and aimed for an effect size of η² = 0.057. The calculation recommended a minimum of 231 participants, so we aimed to recruit at least 250 participants to compensate for exclusions. We recruited the participants via a test subject system at a German university. Ultimately, 240 cases were included in our analysis (N = 240; 76.3% female; M_Age = 20.97, SD_Age = 1.79; 100% students). We conducted several randomization checks to ensure that the experimental groups did not differ in terms of other factors. No group differences were found in terms of gender, χ² (9) = 11.85, p = .26, age, F(3, 236) = .77, p = .51, education, χ² (6) = 4.28, p = .64, social media use, χ² (15) = 11.70, p = .70, or perceived credibility of the influencer, F(3, 236) = 1.74, p = .16.

Results

To test our hypotheses, a customized parallel moderated mediation model with two serial mediators was conducted using PROCESS (Hayes, 2018; see Appendix Figure A1). The message frame did not have a significant effect on positive emotions (b = –.07, 95% CI [–.32, .17]), so H1 was rejected. However, there was a significant effect of the message frame on negative emotions (b = .25, 95% CI [.04, .48]), which confirmed our assumption that loss frames reinforce negative emotions more than gain frames. We therefore accepted H2. Perceived self-efficacy was positively related with positive emotions (b = .29, 95% CI [.15, 43]), and in turn, perceived self-efficacy was significant positively related with environmentally friendly behavioral intention (b = .10, 95% CI [.01, .18]). Thus, H3 and H4 were also accepted. However, there was no significant relationship between the negative emotions and the perceived seriousness of the issue (b = –.03, 95% CI [–.16, 11]), leading to the rejection of H5. H6 was accepted because we found a significant positive association between the perception of the issue as a more serious and environmentally friendly behavioral intention (b = .26; 95% CI [.17, .37]). The presumed moderating influence of music on the correlations assumed in H7a and H7b was not significant (b = .11, 95% CI [–.24, .46]; b = .11, 95% CI [–.12, .51]). In addition, apart from our hypothesis testing, we found an indirect effect of message framing on the behavior intention only mediated by negative emotions (b = –.04, 95% CI [–.095, –.002]).

Discussion

The first of our two studies showed that loss frames had a negative influence on environmentally friendly behavioral intention via negative emotions. Thus, as we hypothesized, loss frames generate negative emotions (Baek & Yoon, 2017; Carfora et al., 2021). However, loss frames directly influenced green behavioral intentions and not, as we assumed, via a stronger perception of the seriousness of the problem. Accordingly, SMIs are advised to avoid the use of loss frames. However, our study shows that gain frames are not a good alternative: Contrary to our expectation, they had no influence on positive emotions. However, the results showed that evoking positive emotions is positively related to behavioral intention through an increase in perceived self-efficacy. Contrary to our expectation, we found no effect for music. We speculate that our results can be explained by the composition of the sample, which was very young. Because a young audience is particularly likely to use SNSs such as Instagram (We Are Social et al., 2023), they may be too accustomed to the used background music on SNSs and therefore may not be able to fully perceive or differentiate the music during watching the reel. Furthermore, research on other topics (e.g., Holmberg et al., 2016; Tiggemann & Zaccardo, 2018) suggests that the Instagram platform already uses very positive language, so gain frames may not be strong enough to increase positive emotions. We must also point out that we did not control the perception of the message frames or the perception of the music. Even if the pretest was successful with regard to the perception of the music, the participants may not have perceived the different types of music in the study. We also cannot ensure that the loss and gain frames were perceived as such. To ensure that the results are not due to non-perception of the manipulation and that the manipulation of the music was successful as in the pretest, we decided to perform an additional manipulation check when repeating the study.

Study 2

Method

Design, Materials, and Measurement

In Study 2, we tested the results of Study 1 on a more diverse sample with fewer students. As in Study 1, we conducted a 2 × 2 between-subjects online experiment in which we manipulated both the message frame (gain vs. loss) and the emotional valence of the music (positive vs. negative). Due to the surprising results from Study 1, we took another critical look at the stimulus material. Although the pretest showed the desired significant differences for all versions, the perceived musical match between frame and music was higher for piano music, especially in the “loss frame/negative music” condition (see Table 1). Therefore, we only used the four versions with piano music in Study 2.

In line with the first study, we first welcomed the participants and asked them to answer the demographic questions, then conducted a short sound test before they were randomly assigned to watch one of the four reels. After watching the reel, we measured the participants’ emotions using the PANAS scale of Breyer and Bluemke (2016; M_positive = 2.55, SD_positive = .83, α_positive = .97; M_negative = 1.78, SD_negative = .63, α_negative = .78). The scale asks about emotions such as “active,” “enthusiastic,” or “anxious.” Again, we measured perceived self-efficacy using three items from Grazzini et al. (2018; M = 3.70, SD = .84, α = .70; e.g., “I have the feeling that I can make a difference by avoiding plastic”) and perceptions of the seriousness of the environmental issue using four items from B. Lee and colleagues (2021; M = 4.32, SD = .60, α = .62; e.g., “How urgent do you think it is to reduce the amount of plastic?”). We also adopted the measurement of behavioral intention (Morton et al., 2011) from Study 1 (M = 4.03, SD = .50, α = .58; e.g., “Use reusable cloth bags for shopping”). We have also included two manipulation tests. Again, the participants watched the reel a second time and were asked to rate its credibility with the item “I perceived the reel I just saw as genuine” on a five-point Likert-type scale (M = 3.53, SD = 1.22) as well as the credibility of the SMI with 12 items (M = 3.69, SD = .79) from Ohanian (1990) on a six-point Likert-type scale.

At the end of the questionnaire, participants were asked to indicate whether they perceived gain or loss frames in their reel. A chi-square test showed that the respective conditions differed significantly from each other overall as desired, F(2) = 116.98, p < .001.

The people were also asked to rate the emotional valence of the music on a scale from 1 (very negative) to 7 (very positive). People who listened to negatively valenced music in the reel perceived the music less positive (M = 3.11, SD = 1.57) than people who listened to positively valenced music, M = 5.12, SD = 1.82; F(1, 205) = 71.99, p < .001. This manipulation was also successful.

Sample

We used the same power analysis as for Study 1 to determine the sample size. After excluding the participants who did not pass the sound test, we ended up with 207 cases (N = 207; 68% female; M_ag_e = 28.02, SD_age = 9.59; 54% students). We recruited the participants via various social media. In this way, we wanted to ensure that the participants used SNSs. It also allowed us to recruit people of different ages. The average age of the participants was higher than that in the first study, but they were still young enough to be active Instagram users. In addition, only about 50% of the participants were students. We again conducted several randomization checks to ensure that the experimental groups did not differ in terms of other factors. As in Study 1, no group differences were found in terms of gender, χ² (6) = 9.11, p = .17, age, F(3, 206) = .60, p = .62; education, χ² (15) = 11.77, p = .70; social media use, χ² (12) = 6.98, p = .86; or perceived credibility of the influencer, F(3, 203) = .76, p = .52.

Results

To test our hypotheses, a customized parallel moderated mediation model with two serial mediators was conducted using PROCESS (Hayes, 2018; Appendix Figure A2). The message frame did not have a significant effect on positive emotions (b = –.10, 95% CI [–.42, .23]); thus, H1 was rejected. However, we found a significant effect of message frames on negative emotions (b = .41, 95% CI [.17, .64]), and therefore H2 was accepted. Positive emotions were positively related to perceived self-efficacy (b = .21, 95% CI [.08, .35]), which in turn was positively related to environmental behavioral intentions (b = .06, 95% CI [.06, .17]). Thus, H3 and H4 were also accepted. However, there was no significant association between negative emotions and the perceived seriousness of the issue (b = .04, 95% CI [–.10, 18]), leading to the rejection of H5. The perception of the problem as more serious was also positively related to the intention to engage in an environmentally friendly behavior (b = .32, 95% CI [.21, .43]); thus, H6 was accepted. We did not find a significant effect for the presumed moderating influence of music on the correlations assumed in H7a and H7b (b = .11, 95% CI [–.34, .57]; b = –.06, 95% CI [–.39, .26]). In addition to testing our hypothesis, we found that the message frame had a direct effect on self-efficacy (b = –.27, 95% CI [–.49, –.05]).

Discussion

In Study 2, we were able to replicate the results of Study 1. In line with the literature (e.g., Bilandzic et al., 2017; Carfora et al., 2021), loss frames increased negative emotions, while surprisingly, gain frames again had no significant effect on positive emotions. Positive emotions were positively related to self-efficacy (Bandura, 1977), which in turn was positively related to the intention to behave in an environmentally conscious manner. In addition to confirming our previous results, we found a residual influence of gain frames on self-efficacy. Thus, formulating the environmental message to clearly show the benefits of adhering to a certain behavior strengthened the recipients’ belief that they could be active in bringing about a change in environmental protection. Thus, based on the second study, it is recommended that SMIs use gain frames in their messages if they want to change behavioral intentions among an older target group. We again found no effect for the influence of the music. Why this might be the case in both studies leads us to an overall discussion of our research.

Overall Discussion

In the two studies, we aimed to determine which kind of environmental messages are particularly effective for greenfluencers and which psychological constructs are responsible. From previous research, we first inferred that message frames trigger certain emotions depending on their wording (Nabi, 2002). From environmental communication studies, we drew on perceived self-efficacy (Bandura, 1977) and perceived seriousness of the environmental problem (B. Lee et al., 2021) as two additional constructs to explain why the use of both gain and loss frames can be effective.

In our first study, we found that although positive emotions are positively related to behavioral intentions and that this relationship is mediated by self-efficacy, positive emotions were not influenced by message frames. In Study 2, the message frames also did not lead to positive emotions. These results are only sporadically consistent with research on message frames. As a meta-analysis shows, several studies in the field of environmental communication show that gain frames lead to positive emotions (Nabi et al., 2020). When examining the studies that demonstrate this effect, it is worth noting that several of them measure specific positive emotions, such as hope (Bilandzic, 2021) or pride (Zubair et al., 2020). The fact that we followed a different approach to measurement could explain the different findings. It is also possible that positive wording on SNSs is not enough to generate positive feelings. We assume that recipients are too accustomed to positive communication on Instagram (Holmberg et al., 2016; Tiggemann & Zaccardo, 2018) and that more emotionalizing stimuli are needed. Research shows, for example, that a particularly high level of creativity in posts can evoke positive emotions (Casaló et al., 2021). Since it is an audiovisual platform, it seems obvious that the focus is on the visual level and that recipients are emotionally influenced primarily using positive images. The visual level as an emotionalization amplifier has already been proven several times for environmental issues (Hartmann & Apaolaza-Ibáñez, 2010; Yu et al., 2023). Dale et al. (2020) also found that images of nature on SNSs are posts that trigger particularly strong self-transcendent emotions. While there were no effects for gain frames in a young student sample, gain frames at least led to higher perceived self-efficacy in an older, heterogeneous sample (Study 2). As the frequency of SNS use is higher among younger people in Germany (Koch, 2023), the lower level of experience with positive content on SNSs therefore appears to result in positive formulations having a motivating effect among the older target group. The relationship between gain frame and motivation has already been demonstrated in research (e.g., Nan, 2012; Sherman et al., 2006; Yan et al., 2012).

In line with research, we found a positive influence of loss frames on negative emotions in both studies (e.g., Bilandzic et al., 2017; Carfora et al., 2021). Negative communication seems to be only marginally represented on Instagram beyond the comments on posts. A negatively worded message is particularly noticeable and leads to negative reactions. Study 1 also showed a negative indirect effect of loss frames on environmentally conscious behavioral intentions, mediated by negative emotions. Although we assumed based on literature (Maartensson & Loi, 2022; Zhu et al., 2020) that negative emotions lead to more positive behavioral intentions via an increase in perceived seriousness, the relationship found can also be plausibly explained: Studies of fear appeals have shown that people respond differently to negatively framed messages (Witte, 1992). When people perceive a threat as too serious, they want to protect themselves and control the danger. Control usually consists of reactive behavior, rejection of the information, or counterproductive behavior (Witte, 1992).

Contrary to our assumption, neither study found a moderating effect of music on the relationship between message frames and emotions. This result seems surprising given that the effect of suitable music has already been shown in other audiovisual contexts such as documentaries (Herget & Albrecht, 2022), movies (e.g., Boltz, 2001; Bullerjahn & Güldenring, 1994; Cohen, 2013), or classic advertising (e.g., Anisimova et al., 2014; Hahn & Hwang, 1999; Herget et al., 2022). We explain this result by the increasingly strong emotionalization on SNSs (Bakir & McStay, 2020), which means that an unfamiliar, purely instrumental song is not enough of an emotional trigger. As stated in the method, instrumental music was selected for the sake of internal validity. It can be assumed that this selection may be responsible for the lack of correlations found. We already know from research that music with vocals lead to a stronger emotional experience than music without (Loui et al., 2013).

As described earlier, gain frames have been shown in the past to be effective for persuasion through environmental messages (e.g., green purchasing behavior: Buda & Zhang, 2000; climate-friendly travel: Chi et al., 2021; food waste: Huang et al., 2021; climate change mitigation measures: Morton et al., 2011; green advertising: Segev et al., 2015; green attitudes: Spence & Pidgeon, 2010). Based on our research, we can only confirm this for the environmental communication of greenfluencers for an older, heterogeneous sample. However, loss frames are also not a good alternative for a younger target group. On the contrary: the use of loss frames leads to an opposite effect to the message content. If greenfluencers can generate positive emotions, they should enhance environmentally friendly behavioral intentions. The question now is how to arouse stronger positive emotions in the context of the short reception situation on SNSs, if it is not possible to do so with young users through gain frames. It is possible that communicator factors play an important role here, as research has shown that who announces the environmental message is especially significant (Breves & Liebers, 2022; Knupfer et al., 2023). In this context, the role of emotions should also be given greater consideration in the future.

Limitations and Further Research

To keep internal validity high, we only distinguished between gain and loss frames and the valence of the music in the two conditions. However, this meant that the emotionality generated by the SMI in the reel was very low, which reduced its credibility and thus the external validity. Looking at reels on SNSs such as Instagram, the emotional valence of the message is usually supported by the expression of the SMI. However, we could not adjust this factor as it would have resulted in further influencing factors. In turn, for the sake of external validity, we did not give participants any further information about the SMI, as users do not need to follow SMIs to have their reels displayed in their news feeds. However, further research could aim to make it easier for participants to identify the SMI as a greenfluencer and rate them as authentic.

We also chose a male influencer. As female influencers are generally more popular (Hudders & De Jans, 2022), this may have influenced our results. As both our samples consist of large proportions of female participants, a group comparison of the hypotheses between men and women is difficult. However, future research should aim to achieve a more balanced sample and, ideally, work with both a female and a male influencer as stimulus material to rule out gender effects. Nonetheless, we were able to show for both studies that the experimental groups did not differ in terms of gender ratio. Furthermore, research has not yet been able to clearly demonstrate a different effect of message frames depending on gender (Kim, 2012; Nan, 2012).

In our studies, we did not ask about preconceptions such as environmental concern or the personal relevance of environmental issues. Accordingly, it was not possible for us to include such factors as covariates in our calculations. We know from research that perceived environmental self-efficacy is related to people’s environmental concern (Clayton et al., 2017), as well as that preconceptions influence the generation of positive emotions (Ibanez & Roussel, 2021). The level of environmental concern also has a strong direct influence on the intention to behave in an environmentally conscious manner (Hameed & Waris, 2018; Mainieri et al., 1997; Poortinga et al., 2004). Similar personal characteristics such as closeness to nature also determine how environmentally friendly people act (Nisbet et al., 2009). Accordingly, we cannot rule out the possibility that the relationships we found in our models are not also influenced by preconceptions. Future research should in any case ask about these preconceptions to either incorporate them as central constructs or at least include them as covariates to control for their influence. With regard to our results, it should be noted that, strictly speaking, we can only speak of correlations between the mediators and dependent variables without a proven direction. The effects reported are based on the theoretically derived model. A statistical examination of causality has not been carried out.

We have already touched on the possibility that the perception, and thus the type, of SMI is more important than the type of message. This could apply in particular to message frames, which only differ from each other in detail. For other message types, such as benefit appeals, differences in the effect have already been shown (Schorn et al., 2022). In the future, the influence of parasocial phenomena on the effect of message frames and emotions should be investigated, for which participants will almost inevitably require prior information. Future research should also investigate other factors provided by the platforms themselves, such as the number of likes or comments. The use of emotional images should be considered given the importance of emotions shown in our study.

With regard to the influence of music on emotions, we need to critically reflect on the choice of musical pieces. Although the unknown pieces of instrumental music employed in this study ensured internal validity to a certain degree by eliminating familiarity effects and the potential persuasive effects of the lyrics, and external validity by using original music from Instagram’s own library, in reality, popular songs from well-known artists are normally used in reels. Thus, denying music’s potential to influence the emotional effects of reels would be inappropriate. Rather, the current study should be seen as a starting point for further investigating music’s impact on social media message reception using more externally valid settings and manipulations.

Finally, it is important to reiterate our understanding of greenfluencers. We consider greenfluencers as individuals who genuinely care about the environment and aim to encourage others to live a sustainable lifestyle. Nevertheless, it must be noted that greenfluencers do not necessarily have verifiable fact-based knowledge. Greenfluencers can be real experts, but they can also be laypeople who only pretend to be particularly knowledgeable (Huber et al., 2022). This harbors the risk that misinformation can be passed on, whether consciously or unconsciously, and SNS users can be deceived. Such deception is already known from green advertising as greenwashing (e.g., Schmuck et al., 2018). The risk of being deceived by greenfluencers is particularly dangerous, as influencers generally enjoy a high level of trustworthiness. Breves et al. (2021) were able to show that their messages lead to little reactance, as there is a kind of blind trust. Messages are rarely checked for accuracy, which poses a dangerous situation considering the substantial amount of people that follow personal influencers. It is crucial for Instagram users to verify the content of greenfluencers and not be deceived by their positive perception. Future investigation should aim to explore how recipients can more effectively identify misinformation.

Implications for Greenfluencers

From a theoretical perspective, it seems worth looking further into the design of greenfluencers’ persuasive messages: Our results suggest that although the findings and implications derived from other media contexts can be used, they cannot be simply transferred without embracing the specifics of social media message reception. From a practical standpoint, it is possible to make initial recommendations on how to use messaging on social media to sensitize people to environmental issues and persuade them to rethink their behavior. We were able to determine that environmentally conscious behavior emerges when a positive type of communication takes place. It is therefore important to formulate and design environmental messages in such a way that users perceive them as positive. At the same time, negative communication, such as a loss frame containing a fear scenario, should be avoided because it evokes negative emotions that have a negative effect on environmentally conscious behavior.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Zoe Olbermann

Author Biographies

Zoe Olbermann (M.A., Hanover University of Music, Drama and Media) is Research Associate and Ph.D. student in communication at the University of Wuerzburg, Germany. Her research focuses on persuasive communication, specifically in advertising, and environmental communication, with focus on emotional and parasocial processes and effects.

Fabian Mayer (M.Sc., University of Wuerzburg) is Research Associate and Ph.D. student in communication at the University of Wuerzburg, Germany. His research focuses on advertising, environmental communication, and music in the media, with focus on emotional and persuasive processes and effects.

Holger Schramm (Ph.D., Hanover University of Music, Drama and Media) is Professor of Communication at the University of Wuerzburg, Germany. His research focuses on entertainment, music, sports, advertising, and environmental communication, with focus on emotional and parasocial processes and effects.

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