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Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

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72395
10.1038/s41598-024-72395-y
Article
Examining how a documentary film can serve as an intervention to shift attitudes and behaviours around sexism in STEM
http://orcid.org/0000-0002-9991-1060
Pietri Evava S. evava.pietri@colorado.edu

1
Weigold Arispa 2
Munoz Lisa M. P. 3
Moss-Racusin Corinne A. 4
1 https://ror.org/02ttsq026 grid.266190.a 0000 0000 9621 4564 Department of Psychology and Neuroscience, University of Colorado Boulder, Muenzinger D244, 345 UCB, Boulder, CO 80309 USA
2 https://ror.org/05gxnyn08 grid.257413.6 0000 0001 2287 3919 Department of Psychology, Indiana University Purdue University Indianapolis, Indianapolis, IN USA
3 SciComm Services, Inc., Washington, USA
4 https://ror.org/04nzrzs08 grid.60094.3b 0000 0001 2270 6467 Psychology Department, Skidmore College, Saratoga Springs, NY USA
19 9 2024
19 9 2024
2024
14 2184414 5 2024
5 9 2024
© The Author(s) 2024
2024
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"Picture a Scientist," a documentary featuring stories and research about bias in STEM, reached a large international audience. Yet, the extent to which this type of engaging media can impact gender bias remains unclear. In a unique collaboration between film creators and researchers, the current large-scale field studies explored whether “Picture a Scientist” functioned as an intervention and persuasive message targeting sexism in STEM. Study 1 found viewers who indicated more knowledge and stronger emotions, perspective-taking, and transportation after the film were more inspired to continue learning sexism in STEM and combating unfair treatment, suggesting the documentary engaged both classic and narrative persuasion processes. Employing a quasi-experimental design, Study 2 demonstrated that compared to those who had not watched the film (but intended to), participants who had viewed the film indicated higher awareness of gender bias, stronger intentions to address this bias, and participants in leadership reported stronger intentions to enact inclusive policies (for example, making it easier to report mistreatment). Our findings suggest that the use of this documentary may be a relatively low-cost and easily scalable online intervention, particularly when organizations lack resources for in-person workshops. These studies can help inform organizational trainings using this or similar documentaries.

Subject terms

Human behaviour
Psychology
issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

In many STEM (Science, Technology, Engineering, and Mathematics) fields, there are well-documented and persistent gender disparities1, and people tend to stereotype scientists as masculine or as having traits associated with men2–4. This lack of gender parity, coupled with masculine stereotypes, can lead to gender bias in hiring, publishing, and prestigious talk invitations5–9. and create hostile environments for women in STEM10–12. Limiting women’s inclusion in these disciplines harms innovation and scientific discoveries13,14, creating a pressing need for validated interventions to address gender biases and disparities15. Moreover, it is critical that such interventions not only change beliefs and attitudes but also encourage support for gender-inclusive policies (parental leave, hiring initiatives)16–18. Effective workshops for reducing sexism typically have relied on in-person formats with trained facilitators, limiting their scalability19–22. Additionally, in-person trainings were often not feasible during the COVID-19 pandemic as organizations moved online23. Given that employees may have felt distracted and fatigued from multiple daily virtual meetings24,25, online formats may have further reduced participation in diversity trainings26,27, during a time when the pandemic exasperated gender disparities in research and publishing28,29.

Media (like films and television) has the potential to reach large audiences and, can promote messages that inspire lasting change while entertaining viewers30–32. During the first year of the pandemic, when diversity workshops were negatively impacted27, a documentary called “Picture a Scientist” reached a large audience through over 1,300 online screenings at universities, companies, and professional societies across 42 countries, and at least 155,476 unique film viewings via these screenings. This documentary featured facts about gender bias in STEM and first-person, emotionally evocative stories from women who personally faced sexism and harassment in their STEM disciplines. We capitalized on this widespread real-world data collection opportunity to explore whether documentary screenings also functioned as successful online diversity interventions and persuasive messages (a message focused on changing beliefs and behaviours) to promote awareness of bias in STEM, spark intentions to confront sexism, and encourage those in leadership to enact inclusive policies (for example, making it easier to report mistreatment). In a unique collaboration between film creators and researchers across two studies, we aimed to test this new conceptualization of persuasive messaging—a documentary integrating both facts and compelling stories.

To help rectify the pervasive gender bias in STEM, researchers and diversity practitioners have developed “bias literacy” interventions, presenting facts about stereotypes and discrimination in STEM to enhance awareness of this sexism15,33. In-person bias literacy workshops have successfully promoted awareness of gender biases and inequities among scientists, STEM faculty, and researchers34,35 and encouraged equitable treatment for women in STEM departments19–22. As one example, the Women in Science and Engineering Leadership Institute (WISELI) held 2.5-h interactive workshops across STEMM (STEM and medicine) departments. During these workshops, facilitators gave presentations outlining empirical evidence of the harmful consequences of gender stereotypes and effective strategies for limiting the impact of these stereotypes. The researchers found that relative to faculty in the control departments, faculty who underwent the WISELI workshop reported higher knowledge of gender bias and awareness of their own biases34.

Workshops, such as the WISELI, are, in part, successful because they present strong persuasive messages about gender bias in STEM, relying on research and facts36,37. Notably, academic scientists are more persuaded by empirical studies than anecdotal stories of sexism38. At the same time, work on attitude change finds that when people are resistant to a message, they will counter-argue against the evidence (for instance, find flaws in a research study)39. As a relevant example, male STEM faculty evaluated evidence of gender bias in STEM as less rigorous than female STEM faculty or male faculty outside of STEM40.

Conveying gender bias information subtly, such as through storytelling or compelling narratives, can address this resistance. Research and theorizing on narrative persuasion posits that engaging stories are uniquely beneficial for changing beliefs partly because individuals do not realize they are being persuaded and, thus, cannot argue against the message31,41. Rather than relying on basic facts, like a classic persuasive appeal, narratives are effective via different processes41. Specifically, stories can change beliefs by transporting (feeling immersed and engrossed) people into the story42–44, evoking emotions such as anger or sadness45–47, sparking empathetic concern for the characters involved in the story48, and encouraging perspective-taking (experiencing the same feelings and reactions as the characters)44,49.

In carefully controlled experiments, researchers have examined classic persuasive messages and narratives for enhancing awareness of sexism in STEM using short, high-quality videos (called “Video Interventions for Diversity in STEM” or VIDS)50. The traditionally strong persuasive message relied on “expert interviews” with a supposed professor and expert in sexism (who, in reality, was an actor) to present facts and research about gender bias. The “narratives” demonstrated instances of gender bias through compelling stories portrayed by professional actors. Researchers found that compared to control videos, the VIDS’ expert interviews and narratives successfully increased awareness of biases, reduced sexism, and enhanced behavioural intentions to address gender bias and inequity among academic scientists, with these effects persisting for at least one week after the intervention38,51.

Critically, the two video formats produced positive effects via distinct processes. The expert interviews encouraged viewers to feel knowledgeable about gender bias facts, whereas the narratives evoked emotions, transportation, and perspective-taking38,51. Among academic scientists, feeling knowledge was crucial, with the expert interviews leading to higher awareness of sexism and behavioural intentions to support women than the narratives38. However, watching a combination of the narratives and expert interviews evoked emotions and transportation while promoting knowledge attainment38.

A documentary that combines emotionally evocative stories about sexism and harassment in STEM with interviews from experts on the topic may be a way to create an ecologically valid version of VIDS’ narratives combined with the expert interviews. VIDS are short videos without a connecting throughline, whereas a documentary can seamlessly and entertainingly connect stories and research. The large international release of “Picture a Scientist” provided a distinctive opportunity to explore the benefits of such a documentary outside of rigid experiments with extensive and diverse samples.

We ran two studies in conjunction with “Picture a Scientist” screenings. Study 1 occurred between September and November 2020, and Study 2 occurred in March and April 2021. The study was advertised to individuals who signed up for screenings and through the documentary’s social media page, and individuals could opt into taking the online study during these periods. Because our only criteria for participation were watching the documentary and being over 18 years of age, we had diverse samples consisting of academics, industry workers, and people employed inside and outside of STEM. Many participants were involved in company, university, and society screenings, similar to how these organizations would implement future workshops featuring a film. Organizations often paired screenings with complimentary panels; however, we do not have data on the exact number of corresponding panels.

Study 1 explored whether different forms of film engagement would relate to more awareness of gender bias in STEM and behaviours documented to reduce sexism in others and promote equity and inclusion in organizations17,52,53. We were also curious how engagement would relate to seeking additional information and resources about gender bias. Engaging with video media can promote lasting changes in beliefs and behaviours by inspiring viewers to continue learning about the topics highlighted in the film54–56. Moreover, a film that forces viewers to reflect on their biases may also motivate them to find resources to help address these biases57,58. Critically, acquiring new information about a topic ultimately shapes people’s attitudes and beliefs59,60 and changes behaviours61–63. Drawing on research and theories from classic and narrative persuasion, we had the following predictions:

Feeling knowledgeable after watching the documentary would relate to positive outcomes (for instance, awareness of bias, behaviours to address sexism, and information seeking), suggesting the documentary was acting as a classic persuasive message (hypothesis 1).

Higher feelings of transportation, emotions, and perspective-taking would relate to positive outcomes, suggesting the documentary was functioning as a persuasive narrative (hypothesis 2).

To more directly explore the benefits of watching (versus not watching) “Picture a Scientist,” we ran a second preregistered study with a quasi-experimental design. We recruited participants who had watched or planned to watch the film (i.e., had signed up for a viewing or participated in an event associated with “Picture a Scientist”). We predicted that:

Those who had watched (versus had not yet watched) the documentary would indicate higher awareness of bias, intentions to address sexism, and information seeking, demonstrating the benefits of the documentary as an online intervention and persuasive message (hypothesis 3).

Results

Study 1

In this first study, all 2756 participants had watched “Picture a Scientist” and completed the time 1 survey after viewing the film. Approximately six weeks later, participants were invited to participate in the time 2 survey (1362 [49.6%] of participants completed this survey). We chose a six-week follow-up because past research looking at videos for bias reduction used the same period44.

All participants answered questions about confronting sexism or harassment, donating their time or money to organizations working to address disparities in STEM, and finding additional information about sexism and ways to combat bias (or information seeking). We also measured specific types of actions among subsets of participants in positions to enact these behaviours. In particular, participants who worked in a university or were graduate students (n = 1705; i.e., participants who might interact with students in the classroom) completed questions about supporting marginalized students. Participants who worked in a university or company (n = 1823) answered questions about creating welcoming climates for women in their organization. Finally, participants in a leadership position (n = 589) completed questions about enacting inclusive policies and initiatives to promote diversity and inclusion in their organizations.

Participants could skip any question that made them uncomfortable. Participants could also choose "Not Applicable" for all behavioural intention items when they could not enact that action (for instance, did not currently work with students, could not influence policies). When participants skipped a question or chose “Not Applicable,” that item was treated as missing. If participants did not answer a subset of questions from a measure, we averaged the items they did complete to create the index. Participants who did not answer all questions from a given index were treated as missing for analyses with that outcome.

We assessed participants' reported behaviours between times 1 and 2. In the six weeks following the film, most of our sample took at least one action related to addressing biases and disparities (see Table 1 for the frequency of different types of behaviours). Behavioural intentions measured at time 1 positively and significantly correlated with participants indicating doing at least one related behaviour at time 2 (see Supplementary Table 1 for these correlations).Table 1 Frequencies of reported new and old behaviours at time 2.

Measures		Did new behaviour	Did new or old behaviour	
Confront sexism (if saw it)	n	180	N/A	
%	47.00%	N/A	
Total n	383	N/A	
Did a seek information behaviour	n	417	927	
%	31.24%	69.44%	
Total n	1335	1335	
Did a donate behaviour	n	121	419	
%	9.15%	31.67%	
Total n	1323	1323	
Did a supporting minoritize student behaviour	n	178	574	
%	27.01%	87.10%	
Total n	659	659	
Did a positive climate behaviour	n	209	610	
%	26.29%	76.73%	
Total n	795	795	
Did a positive leader behaviour	n	85	199	
%	35.27%	82.57%	
Total n	241	241	

Turning to our primary hypotheses, we ran partial correlations controlling for demographic variables because supplementary analyses found that film engagement, awareness of bias, and behavioural intentions varied across different demographic groups (see Supplementary Tables 11–14 for results).

First, looking at partial correlations between measures assessed at time 1, we found that anger, empathy, knowledge, transportation, and perspective-taking positively related to most of our outcomes (see Table 2 for all partial correlations), supporting hypotheses 1 and 2. Interestingly, feeling sad while watching the film related to significantly lower feelings of self-efficacy (p < 0.001).Table 2 Partial correlations between film engagement and behavioural intentions (all at time 1) controlling for demographic variables.

Measures		Anger	Sadness	Empathy	Knowledge	Transportation	Perspective-taking	
Awareness of gender bias	r	0.31	0.23	0.26	0.15	0.30	0.35	
p	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	2730	2730	2730	2730	2730	2730	
Self-efficacy	r	0.05	− 0.21	0.20	0.35	0.11	0.10	
p	0.018	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	2730	2730	2730	2730	2730	2730	
Confront intentions	r	0.21	− 0.02	0.29	0.18	0.24	0.13	
p	 < 0.001*	0.446	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	2726	2726	2726	2726	2726	2726	
Seek information intentions	r	0.23	0.11	0.31	0.27	0.29	0.22	
p	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	2721	2721	2721	2721	2721	2721	
Donate intentions	r	0.18	0.09	0.22	0.14	0.20	0.19	
p	 < 0.001*	 < 0.001	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	2720	2720	2720	2720	2720	2720	
Supporting minoritized studentsa	r	0.19	0.10	0.23	0.13	0.19	0.17	
p	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	1456	1456	1456	1456	1456	1456	
Positive climate behavioursb	r	0.19	0.09	0.22	0.16	0.21	0.16	
p	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	 < 0.001*	
n	1665	1665	1665	1665	1665	1665	
Leadership behavioursc	r	0.16	− 0.01	0.16	0.13	0.19	0.11	
p	 < 0.001*	0.907	 < 0.001*	0.002*	 < 0.001*	0.012	
n	554	554	554	554	554	554	
Bolded correlations = significant at p < 0.008 Bonferroni corrected value. We controlled for whether participants were leaders, worked or majored in a STEM field, worked in a university, were students, gender (dummy coded with men as the reference group), and race (dummy coded with White participants as the reference group).

aOnly completed among participants who worked in a university or students, and thus, we did not control whether participants worked in a university.

bOnly completed among participants who work in a university or company (i.e., no participants were students), and thus, we did not control for students versus non-students.

cOnly completed by leaders, and thus, we did not control for leader versus non-leader or student versus non-student.

For time 2 behavioural intentions, we explored how film engagement and awareness of gender bias in sciences (all measured at time 1) predicted changes in behavioural intentions from time 1 to time 2. Thus, we ran partial correlations between film engagement and awareness of gender bias at time 1 with behavioural intentions at time 2, controlling for time 1 intentions and demographic variables (see Table 3 for all correlations). We also examined whether reactions to the film and awareness of bias (all measured at time 1) correlated with reported behaviours (i.e., doing at least one new or old behaviour = 1 or not completing a new or old behaviour = 0) at time 2 (controlling for demographic variables; see Table 4 for all correlations). As Tables 3 and 4 demonstrate, our most consistent finding was film engagement relating to seeking out new information about bias, partially supporting hypothesis 1 and 2.Table 3 Partial correlations between film engagement (time 1) and behavioural intentions (time 2) controlling for demographic variables and time intentions.

Measures		Anger	Sadness	Empathy	Knowledge	Transportation	Perspective taking	Aware of gender bias	
Confront intentions	r	0.01	− 0.08	0.07	0.09	0.03	0.03	0.02	
p	0.719	0.003*	0.016	0.001*	0.329	0.302	0.478	
n	1306	1306	1306	1306	1306	1306	1306	
Seek information intentions	r	0.05	− 0.01	0.08	0.14	0.06	0.10	0.11	
p	0.097	0.801	0.004*	 < 0.001*	0.049	0.001*	 < 0.001*	
n	1300	1300	1300	1300	1300	1300	1300	
Donate intentions	r	0.05	0.00	0.06	0.07	0.08	0.10	0.07	
p	0.086	0.970	0.037	0.013	0.003*	 < 0.001*	0.018	
n	1300	1300	1300	1300	1300	1300	1300	
Supporting minoritized studentsa	r	0.13	0.12	0.18	0.08	0.18	0.13	0.18	
p	0.001*	0.002*	 < 0.001*	0.059	 < 0.001*	0.001*	 < 0.001*	
n	634	634	634	634	634	634	634	
Positive climate behavioursb	r	0.05	0.04	0.05	− 0.01	0.08	0.09	0.13	
p	0.201	0.248	0.217	0.853	0.040	0.021	0.001*	
n	710	710	710	710	710	710	710	
Leadership behavioursc	r	0.15	− 0.01	0.12	0.12	0.06	0.11	0.16	
p	0.055	0.874	0.120	0.106	0.470	0.147	0.033	
n	172	172	172	172	172	172	172	
Bolded correlations = significant at p < .007 Bonferroni corrected value. We controlled for whether participants were leaders, worked or majored in a STEM field, worked in a university, were students, gender (dummy coded with men as the reference group), race (dummy coded with White participants as the reference group), and time 1 intentions.

aOnly completed among participants who worked in a university or students, and thus, we did not control whether participants worked in a university.

bOnly completed among participants who work in a university or company (i.e., no participants were students); thus, we did not control for students versus non-students.

cOnly completed by leaders, and thus, we did not control for leader versus non-leader or student versus non-student.

Table 4 Correlations between engagement with the film at time 1 and reported behaviours at time 2 in Study 1.

Measures		Anger	Sadness	Empathy	Knowledge	Transportation	Perspective taking	Aware of gender bias	
Confront sexism (if see saw it)

(1 = Yes, 0 = No)

	r	− 0.07	− 0.07	0.00	− 0.01	0.01	− 0.11	− 0.10	
p	0.156	0.164	0.948	0.892	0.830	0.034	0.050	
n	372	372	372	372	372	372	372	
Did a new seek information behaviour

(1 = Yes, 0 = No)

	r	0.12	0.12	0.16	0.05	0.18	0.14	0.11	
p	 < 0.001*	 < 0.001*	 < 0.001*	0.054	 < 0.001*	 < 0.001*	 < 0.001*	
n	1321	1321	1321	1321	1321	1321	1321	
Did a new donate behaviour

(1 = Yes, 0 = No)

	r	0.04	0.03	0.06	− 0.02	0.09	0.11	0.08	
p	0.123	0.217	0.031	0.597	0.001*	 < 0.001*	0.007*	
n	1309	1309	1309	1309	1309	1309	1309	
Did a supporting minoritize student behavioura

(1 = Yes, 0 = No)

	r	0.08	0.06	0.06	− 0.05	0.05	0.02	0.04	
p	0.044	0.108	0.165	0.174	0.168	0.540	0.267	
n	648	648	648	648	648	648	648	
Did a new positive climate behavioursb

(1 = Yes, 0 = No)

	r	0.04	0.03	0.06	− 0.03	0.05	0.08	0.07	
p	0.281	0.431	0.075	0.408	0.154	0.036	0.066	
n	782	782	782	782	782	782	782	
Did a positive leader behaviourc

(1 = Yes, 0 = No)

	r	0.01	− 0.04	0.03	0.12	0.10	0.05	0.11	
p	0.847	0.525	0.646	0.081	0.121	0.461	0.107	
n	231	231	231	231	231	231	231	
Bolded correlations = significant at p < 0.007 Bonferroni corrected value. We controlled for whether participants were leaders, worked or majored in a STEM field, worked in a university, were students, gender (dummy coded with men as the reference group), race (dummy coded with White participants as the reference group), and time 1 intentions.

aOnly completed among participants who worked in a university or students, and thus, we did not control whether participants worked in a university.

bOnly completed among participants who work in a university or company (i.e., no participants were students), and thus, we did not control for students versus non-students.

cOnly completed by leaders, and thus, we did not control for leader versus non-leader or student versus non-student.

Given our findings with information seeking, in exploratory analyses, we examined whether seeking additional information after “Picture a Scientist” would lead to further positive actions and a stronger awareness of gender bias. We ran regression analyses predicting time 2 assessments from time 1 assessments (to examine changes across time) and whether participants reported seeking out new information (0 = no, 1 = yes) between time 1 and 2. Interestingly, leaders (versus non-leaders) were more likely to look up information after the documentary (no other demographic variables were significant, see Supplementary Table 2). Thus, we controlled for whether participants identified as leaders in these analyses.

Reported information seeking positively predicted awareness of gender bias (b = 0.21, SE = 0.04, 95% CI [0.18, 0.29], t [1331] = 4.93, p < 0.001, intentions to donate (b = 0.29, SE = 0.06, 95% CI [0.17, 0.41], t [1304] = 4.70, p < 0.001, intentions to support minoritized students, (b = 0.18, SE = 0.05, 95% CI [0.08, 0.29], t [640] = 3.37, p < 0.001), and intentions to create a positive climate (b = 0.44, SE = 0.08, 95% CI [0.13, 0.44], t [1331] = 3.62, p < 0.001) at time 2, controlling for time 1 measures and whether participants were leaders. Seeking out information between times 1 and 2 did not relate to self-efficacy, confrontation intentions, or leadership behaviours (see Supplementary Table 3 for detailed regression results).

Finally, we explored whether demographic groups had different reactions to the film and varied in their behavioural intentions (see Supplementary Tables 11–14 for these findings).

Study 2

To test hypothesis 2 and examine whether there were benefits associated with watching versus not watching “Picture a Scientist.” Study 2 had a quasi-experimental design. We recruited 1255 participants who had watched the film (833, 66.4%) or were planning to watch the film (i.e., had signed up for a viewing or participated in an event associated with the documentary; 422, 33.6%). We also sent a follow-up survey to participants three weeks after the initial survey.

We preregistered our predictions, research questions, and data collection plans (available here: https://osf.io/csjzx/?view_only=e62700073eb04d6f9eee5cfc5bc54f6b). To test hypothesis 2 (the primary goal of this study), we examined—(a) whether, at time 1, participants who had already seen the film would report higher awareness of gender bias, higher intentions to enact behaviours to address gender bias and disparities, and higher information seeking intentions and (b) whether participants who watched the film between time 1 and 2 would show increased awareness of bias and positive behavioural intentions. To further test hypotheses 1 and 2, we examined whether feeling knowledgeable, emotions, perspective taking, and transportation would relate to stronger behavioural intentions.

To first examine hypothesis 2, we ran a series of between-subjects two-sided t-tests, with whether or not participants had watched the film before the time 1 survey as our predictor. Compared to those who had not watched the film, participants who had watched the film were more aware of gender bias in STEM, (mean difference = 0.47, SE = 0.05, 95% CI [0.37, 0.57], d = 0.53, t [1253] = 9.60. p < 0.001), and indicated higher intentions to seek out information, (mean difference = 0.38, SE = 0.06, 95% CI [0.25, 0.50], d = 0.34, t [1249] = 5.88, p < 0.001), to donate to organizations addressing gender bias and disparities, (mean difference = 0.31, SE = 0.08, 95% CI [0.25, 0.50], d = 0.22, t [1248] = 3.88, p < 0.001), and to create welcoming climates in their organizations, (mean difference = 0.43, SE = 0.08, 95% CI [0.26, 0.60], d = 0.38, t [850] = 5.41, p < 0.001). Among those in a leadership position, participants who had viewed the film reported higher intentions to enact policies that would help address bias relative to those who had not watched the film (mean difference = 0.42, SE = 0.12, 95% CI [0.19, 0.66], d = 0.43, t [294] = 3.57, p < 0.001). Participants who watched the film also indicated higher intentions to confront sexism and mentor and support students with marginalized identities; however, these effects were not significant using the Bonferroni corrected p-value (See Supplementary Table 4 for full effects and Fig. 1). Finally, there was a tendency for participants who watched the film to feel lower self-efficacy in addressing gender bias, although this effect also did not reach significance.Fig. 1 The graphed Cohen’s d effect sizes for having watched versus not watched “Picture a Scientist,” with 95% confidence intervals.

Of note, we found a higher percentage of women and university employees had watched "Picture a Scientist." (There were no other differences across demographic groups, see Supplementary Table 5). Thus, we ran follow-up regression analyses predicting our outcome measures from having watched the film (1) versus not (0) while controlling for gender (dummy coded, with men as the reference group) and university affiliation (1 = employed at a university, 0 = not employed at a university). Similar results emerged with these regression analyses, available in Supplementary Table 6.

Among participants who watched the film, 471 (37.2%) viewed it within the previous month, and 361 (27.1%) saw it a month or longer before the survey. We ran exploratory (i.e., not preregistered) between-subjects ANOVAS with three groups (participants who had not watched the film vs. participants who watched the film within the past month vs. participants who watched the film over a month before the survey; see Supplementary Table 7 for full ANOVA results). Participants who viewed “Picture a Scientist” a month or more before the survey did not show lower scores on our outcome measures and tended to have higher scores than those who had watched the documentary more recently. Thus, these analyses provided some initial evidence suggesting "Picture a Scientist" can have a lasting impact.

We next tested whether there were benefits associated with watching the film between time 1 and 2, particularly for participants who had not watched the documentary at time 1. We had 668 participants (53.2%) complete the time 2 survey, and among these participants, 237 (35.5% of time 2 respondents, 18.8% of total sample) watched the film between time 1 and 2. Focusing on participants who had watched the film between the two time points, we ran a mixed model ANOVA with time as the within-subjects factor and having watched the film at time 1 versus not as our between-subjects factor (96 had already watched the film at time 1 and 141 had not watched the film at time 1; see Supplementary Table 8 full ANOVA results). We specified that we would only conduct these analyses among participants who had watched the film between time 1 and 2 in our preregistration.

There were significant time (time 1 versus time 2) by having watched the film at time 1 (versus not watched) interactions for awareness gender bias in the sciences, F (1,235) = 10.83, p = 0.001, ηp2 = 0.044, confrontation intentions, F (1,235) = 19.55, p < 0.001, ηp2 = 0.077, and intentions to create a positive organizational climate F (1,149) = 8.65, p = 0.004, ηp2 = 0.055. Among participants who had not watched the film at time 1, there was a significant increase from time 1 to time 2 on awareness of gender bias (mean difference = 0.36, SE = 0.07, 95% CI [0.22, 0.50], d = 0.36, p < 0.001), intentions to confront sexism (mean difference = 0.22, SE = 0.05, 95% CI [0.11, 0.32], d = 0.35, p < 0.001), and intentions to foster a positive organizational climate (mean difference = 0.22, SE = 0.09, 95% CI [0.04, 0.39], d = 0.23, p = 0.017). We found a similar pattern of results for intentions to seek information and leadership behaviour intentions, although the effect of time did not reach significance for these outcomes. These lack of significant effects may have been because we had a small sample watch the film between time 1 and 2. Unexpectedly, participants who had already watched the film at time 1, showed a significant decrease in confrontation intentions from time 1 to time 2 (mean difference = − 0.14, SE = 0.06, 95% CI [− 0.27, 0.02], d = 0.26, p = 0.023); however, that was the only effect of time among these participants. Thus, we did not see any added benefit to watching the film between time 1 and 2, when participants had already seen the film at time 1. In contrast, we did find positive effects on awareness of gender bias, confrontation intentions, and creating positive climate intentions among participants who had not previously seen the film at time 1.

Providing further support for hypotheses 1 and 2, we found that feeling knowledgeable, emotions, perspective taking, and transportation related to awareness of gender bias and behavioural intentions at time 1 (see Supplementary Tables 9–10 for full results.)

We also examined whether demographic groups differed in their film engagement (see Supplementary Tables 15–16) and whether demographic variables moderated the effect of watching versus not watching the film (see Supplementary Table 17–22). The only consistent moderation effect was that watching the documentary (versus not watching the film) was more impactful among participants who were in a STEM field (i.e., job or major) compared to those not in a STEM (see Supplementary Table 20). These findings were most likely due to the content (i.e., sexism and harassment in STEM) of the film being most relevant for participants in STEM fields and STEM majors.

During this second study, there was a large-scale panel event associated with "Picture a Scientist" and the themes presented during the film. We found that 34.5% of our sample also had watched the panel at time 1. There were benefits associated with the panel among participants who had not watched "Picture a Scientist" (see Supplementary Tables 23–24). Finally, we did not find that watching the panel nor demographic variables moderated changes on outcome variables from time 1 to time 2 (see Supplementary Tables 26 and 27).

Discussion

Our two large-scale studies demonstrate that the many viewings of "Picture a Scientist" were effective online interventions during a time when in-person workshops were not feasible. Study 1 showed the documentary was effective via classic and narrative persuasion processes. Feeling more knowledgeable after watching the film (relevant to classic persuasion) and emotions, perspective taking, and transportation (relevant to narrative persuasion) related to higher awareness of gender bias and a higher likelihood of engaging in behaviours to combat bias and seeking additional relevant information. Exploratory analyses showed that interacting with this new information, in turn, predicted increased awareness of gender bias and intentions to help address unfair treatment and disparities. Critically, preregistered quasi-experimental Study 2 found that compared to those who had not yet seen the documentary (but intended to), participants who viewed the film indicated more awareness of gender bias and stronger intentions to seek out information, donate to causes addressing biases, create welcoming organizational climates, and enact inclusive policies. Moreover, participants who initially had not viewed “Picture a Scientist” and then watched the film during the following three weeks (i.e., before the second survey) showed increased awareness of gender bias, confrontation intentions, and intentions to create welcoming organizational climates.

Using randomized control trial experiments, previous VIDS research demonstrated that presenting facts about gender bias research (classic persuasion) and engaging stories demonstrating sexism (narrative persuasion) can cause increased recognition of gender bias and behavioural intentions to combat sexism and disparities38,50,51. “Picture of a Scientist” represented a more ecologically valid version of VIDS in naturally occurring situations (i.e., already scheduled viewings/screenings). However, by examining the benefits of the film in these naturalistic settings, we were limited in our control. For instance, many screenings of “Picture a Scientist” were paired with panels discussing the topics featured in the film. Thus, the benefits associated with watching the film in Study 2 most likely were an effect of the documentary and a result of attending a related panel or looking up additional readings on sexism. Although we expect that "Picture a Scientist" alone can inspire positive actions, our Study 1 findings suggest that the film may encourage persisting beliefs and behaviours by motivating viewers to continue engaging with the topics featured in the documentary (e.g., attending panels or reading articles). Nevertheless, future research might run more controlled experiments to isolate the unique positive outcomes of viewing the film and examine any additional benefits of participating in a panel or reading related articles. In Study 2, 34% of our participants also attended a virtual panel event associated with “Picture a Scientist.” Supplemental analyses suggested this panel was valuable for participants who had not yet watched the documentary.

Future workshops incorporating the documentary might also benefit from including carefully developed panels. Although many positive outcomes were associated with watching "Picture a Scientist," self-efficacy to combat bias was slightly lower among participants who had watched the film in Study 2. Experiencing sadness while watching the documentary was also related to lower self-efficacy across both studies. These findings align with past work, finding raising awareness of unfair treatment without strategies to reduce the mistreatment can undermine self-efficacy51 and feeling sad can harm motivation for action64. However, providing concrete tips during a follow-up panel may help address these issues, enhance self-efficacy, and further motivate viewers to take action51. Given that processes related to narrative persuasion correlated with more positive outcomes (i.e., awareness of bias, behavioural intentions), future work might also test manipulations to foster this engagement, such as encouraging viewers to take the perspective of the women in the film49.

We acknowledge that many of our measures examined gender-related issues or intentions to support minoritized individuals generally. Although “Picture a Scientist” discussed topics pertinent to sexism and gender harassment in STEM, it also highlighted the distinctive biases encountered by Black women in STEM due to their dual marginalized identities65. Encouraging recognition of intersectional biases (i.e., the prejudices faced by individuals with multiple marginalized and intersecting identities) promotes additional positive outcomes beyond increasing awareness of a singular bias66. Future research examining the benefits of “Picture a Scientist” and diversity interventions broadly should recognize issues of intersectionality.

To help address sexism in STEM, it is critical to employ interventions that alter personal attitudes and behaviours without eliciting annoyance or boredom67 and implement new inclusive organizational-level policies16–18. “Picture a Scientist’s” presence on streaming platforms (e.g., Netflix, PBS) and rating on IMDb (7.7/10 or a good/very good rating) highlights the film’s broad appeal, suggesting that people may find interventions incorporating the documentary enjoyable and informative. It is particularly promising that relative to leaders who did not watch “Picture a Scientist,” those who viewed the documentary had stronger intentions to enact new diversity and inclusion policies, which are crucial for addressing disparities in STEM16,17. Screenings of similar documentaries highlighting stories and facts about bias, may produce comparable effects as those found with “Picture a Scientist.” Thus, the current findings can help inform company and university policies by demonstrating the benefits of organizational diversity workshops incorporating films like "Picture a Scientist."

Methods

The Institutional Review Board at Indiana University approved the protocols for both Study 1 and Study 2. The methods for both studies were performed in accordance with relevant guidelines and regulations of the IRB-approved protocol and the IRB at Indiana University. All participants read an informed consent and consented before beginning the surveys.

As part of the surveys sent out to participants in Study 1 and 2, there were items and indices related to separate research questions/studies (i.e., how the documentary impacts belonging). Analyses from these items will be part of a different manuscript. Critically, no measures or outcomes reported in the current paper will be included in any other manuscript or publication.

Study 1

Participants

“Picture a Scientist” screenings were hosted at universities and organizations across multiple countries, and individuals who signed up for these viewings were sent emails inviting them to participate in the current research study. Participants also were recruited through the “Picture a Scientist” social media pages (i.e., Twitter and Facebook). In total, 2779 participants completed the full time 1 survey. To ensure participants had watched film, we included easy film memory questions (see below for questions). We excluded 23 participants who did not pass this attention check, leaving a final total of 2756 participants. We did not have a target number of participants but rather had a pre-determined stopping date for the time 1 survey. We ran a power sensitivity analysis with this sample size using G*Power68 and looking at an analysis with 9 control predictor variables and one primary predictor (i.e., the partial correlations we ran for time 1 variables controlling for demographic characteristics). This analyses revealed we were adequately powered to find a small effect (f2 = 0.007, R2-change = 0.007) at p < 0.008 and 95% power.

The racial composition of this final group of participants was: 2006 White (72.7%), 58 (2.1%) Black/African American, 195 (7.1%) Latinx, 142 (5.1%) East Asian, 113 (4.1%) South Asian, 5 (0.2%) Southwest Asian, 44 (1.6%) Middle Eastern, 3 (0.1%) Native Hawaiian/Pacific Islander, 3 (0.1%) American Indian/Native American/Alaska Native/Indigenous, 128 (4.6%) Multiracial, 49 (1.8%) other, 12 (0.4%) did not answer. We also had 2347 who identified as female (85.1%), 374 who identified as male (13.6%), 31 who identified as Other (1.1%), and 6 who did not answer (0.2%). There were 814 (29.5%) participants who identified as students, and 1994 (70.5%) were not students. Among participants who were not students, 1186 (43.0%) worked in a university, and 758 (27.5%) were not employed by a university. For participants who worked in a university or company, 589 (21.4%) reported being in a leadership position, and 1233 (44.7%) were not in a leadership role. Of participants who were students or worked in a university or company, 2393 (86.8%) were in a STEM field or major, and 244 (8.8%) were not in a STEM field. Finally, the age range for participants was 18–86 (M = 38.8, SD = 13.79). (Additional demographic information about participants is available in Supplementary Table 28).

Procedure and measures (time 1)

All participants in the current study watched “Picture a Scientist.” This one-hour and 43-min documentary film follows the stories of three female scientists facing inequitable treatment and harassment in their respective STEM fields. Two of the featured women were White and full professors (one in geology and another in biology). The third woman was a Black chemist and associate professor. The women’s stories included a variety of examples of gender bias, including receiving fewer resources than their male colleagues, facing overt sexual harassment during a research exhibition, and having their credibility questioned. Scattered throughout the film are interviews with prominent researchers studying bias and discrimination in STEM. For example, the documentary discussed empirical evidence that STEM faculty evaluate a female candidate less favourably than a male candidate6. Thus, viewers watch emotionally evocative stories while also learning about the research related to this mistreatment. Participants either watched the film via their professional societies/organizations (762, 27.6%), through their university or college (1501, 54.4%), through their company (457, 16.6%) or did not indicate how they viewed the film (38, 1.4%).

The email invitation and the information provided at the beginning of the study described this study as being interested in participants' "reactions to the film, as well as [participants'] plans for future and specific actions inspired by the film." We noted that "[t]he results from this survey will help us identify the positive impact of this film and explore how reactions to films may influence beneficial changes in behaviour.” All participants completed the study measures on a personal device, using the Qualtrics Survey platform. Participants began the survey by answering a subset of demographic questions, which influenced which questions Qualtrics would display throughout the survey. These initial demographic questions included whether or not participants were a student, worked in a university or organization, and were in a leadership position. (Participants also answered more general demographic questions at the end of the time 1 survey, including questions related to their gender, race/ethnicity, and age.)

Participants next completed the measures assessing their film engagement (i.e., anger, sadness, empathy, knowledge, transportation, and perspective-taking) and indicated their awareness of gender bias in the sciences and self-efficacy to combat gender bias after watching the documentary. The survey then asked participants to reflect on their future actions after watching the documentary, and participants completed the behavioural intention measures.

In Supplementary Table 29, we present detailed measure information from Study 1, including an example time, the scale end-points, and scale reliabilities. Additionally, all of the questions’ wording are available online in the study’s code book. We modified past measures assessing anger, sadness, and empathy from previous research looking at the influence of emotional reactions on attitudes and behaviour64,69,70. Specifically, for this study, we shortened the measures because the study was voluntary, and we wanted to ensure the survey took no longer than 10 min. All of these new measures had acceptable reliabilities ranging from α = 0.73–0.79. We also altered previous indices of transportation and perspective-taking from studies testing the impact of engaging stories and media42,71. The transportation measure initially included 4 items; however, one item did not correlate strongly with the other three items, harming reliability (“I found myself thinking of ways the film could have turned out differently.”), and was removed from the scale. Researchers have employed similar emotions, transportation, and perspective-taking measures in VIDS (Video Intervention for Diversity in STEM) experiments38,50. Finally, we took the knowledge measure from earlier VIDS work50 (α = 0.79).

We used shortened versions of the awareness of gender bias in sciences and self-efficacy measures from past VIDS research38,50,51. These shortened measures maintained acceptable reliability at time 1 (α = 0.84 and 0.74) and time 2 (α = 0.90 and 0.72). Additionally, the behavioural intentions indices were modified from previous VIDS work38. The film team for “Picture a Scientist” provided screening hosts with a list of potential action steps for viewers after watching the film. This list highlighted organizations working to address gender disparities in STEM and bystander interventions trainings. Thus, some of our behavioural intention items were directly related to supporting these organizations and participating in/implementing the suggested trainings. All of the new and modified behavioural intention measures had good to excellent reliabilities at time 1 (α = 0.83 to 0.91) and time 2 (α = 0.82 to 0.90) except for donation intentions, which was 0.67 at both time points.

To ensure participants had watched and remembered the documentary, at the end of the survey, participants answered three easy multiple-choice memory check questions (e.g., “Of the three main people whose stories were featured in the film: (a) all three were male, (b) two were female, one was male, (c) all three were female [correct answer].” Using similar criteria from previous research38,50, we excluded participants if they failed to answer 2 out of the 3 easy questions. Of note, we added these questions into the survey after we posted the survey on social media. Forty-three participants, who took part in online screenings and received the study email invitation, completed the survey before we added these questions. Because these participants were associated with specific screenings, we retained them in the sample.

Finally, we asked participants whether they were willing to participate in the follow-up survey. If participants agreed, we asked them to provide their preferred email addresses. We had 2181 participants (79.1%) agree to complete this second and provided their email information. (If participants did not agree to take part in the second survey, we directed them to the study debriefing.) Among these 2181, 1362 (62.4% of those who agreed to complete the survey and 49.6% of the full sample) completed the time 2 survey. Participants who were contacted but chose not to complete the second survey did not vary systematically across time 1 measures (see Supplementary Table 30 for these analyses). We ran a second power sensitivity analysis with the time 2 sample for an analysis with 10 control predictor variables and 1 primary predictor (i.e., the partial correlations we conducted between time 2 behavioural intentions and film engagement controlling for demographic variables and time 1 intentions). We found that we were adequately powered to find a small effect (f2 = 0.01, R2-change = 0.01) at p < 0.008 and 95% power.

Procedure and measures (Time 2)

We emailed participants, who opted-in to the follow-up survey, a link to the time 2 survey approximately six weeks after the time 1 survey. Participants completed the same film engagement measures and behavioural intention measures from time 1.

In addition to indicating behavioural intentions, participants also reported whether they did various behaviours since watching the documentary film. To examine whether participants confronted bias, we first asked participants whether they had witnessed an instance of sexism. Among participants who completed the time 2 survey, 867 said they did not see an example of bias. An additional 105 participants indicated learning about a situation involving sexism but were not physically present during the event (i.e., saw it on T.V., learn about bias after it occurred). Thus, 383 participants were physically present for an instance of mistreatment. We asked these participants, “Did you confront or say something to the perpetrator of bias?” (“Yes” or “No”).

For all remaining behaviours reported in results, participants could choose from 6 options 1 = Yes, I did this behaviour, 2 = Yes, I did this behaviour, but I also did this behaviour before the film, 3 = No, I did not do this behaviour, 4 = No, but I have done this behaviour before the film, 5 = No, but I plan to do this behaviour in the future, 6 = Not Applicable. We created two indices of past behaviours. Specifically, we measured whether participants did a new behaviour after watching the film or selected "Yes, I did this behaviour." We also assessed whether participants did any behaviour after the film (i.e., a new or old behaviour) or selected “Yes, I did this behaviour” or “Yes, I did this behaviour, but I also did this behaviour before the film." We created two dichotomous scores indexing whether participants completed any new behaviour (1 = did at least one new behaviour, 0 = did not do a new behaviour) and whether they did any (i.e., new or old) behaviour (1 = did at least one behaviour, 0 = did not do a behaviour). See Supplementary Table 31 for additional details about the past behaviour measures.

Study 2

Participants

Similar to Study 1, we invited individuals who registered for viewings of the documentary to participate in the current study. We also advertised the study through the "Picture a Scientist" social media pages. New to Study 2, individuals who had signed up to watch, but had not yet viewed the film, were sent an email invitation to participate in the current research, and we encouraged them to complete the survey before they watched the film. Finally, we also advertised the survey during a panel event hosted by Scientific American, which discussed the topics featured in the documentary. We had 1257 participants complete the full time 1 survey. We excluded two participants for failing the easy memory attention check items, leaving a final sample of 1255 participants. Similar to Study 1, we did not have a target number of participants but instead had a pre-determined stopping date for the time 1 survey, which we specified in our preregistration. We ran a power sensitivity analysis with our final sample size using G*Power68. We found that we were adequately powered to find a small effect (d = 0.26) for a between-subjects t-test at p < 0.006 and 95% power.

The racial composition of this final group of participants was: 915 White (72.9%), 33 (2.6%) Black/African American, 102 (8.1%) Latinx, 62 (4.9%) East Asian, 51 (4.1%) South Asian, 1 (0.1%) Southwest Asian, 18 (1.4%) Middle Eastern, 3 (0.2%) Native Hawaiian/Pacific Islander, 1 (0.1%) American Indian/Native American/Alaska Native/Indigenous, 45 (1.8%) Multiracial, 23 (1.8%) other, 1 (0.1%) did not answer. We also had 1081 participants who identified as female (86.1%), 156 who identified as male (12.4%), 18 who identified as Other (1.4%). There were 324 (25.8%) participants who identified as students, and 931 (74.2%) were not students. Among those who did not identify as students, 529 (42.2%) worked in a university, and 402 (32.0%) were not employed by a university. For participants working in a university or company, 302 (24.1%) reported being in a leadership position, and 580 (46.2%) were not in a leadership role. Among participants who were students or worked in a university or company, 1066 (84.9%) were in a STEM field or major, and 140 (11.2%) were not in a STEM field. The age range for participants was 18–86 (M = 38.8, SD = 13.79). (Additional demographic information about participants is available in Supplementary Table 32).

New to Study 2, we also collected data on participants' current country of residence. The majority of participants resided in the U.S.A. (901, 71.8%); however, participants reported being from an additional 43 countries/U.S.A. territories. The complete list of countries is available in Supplementary Table 33.

Procedure and measures (Time 1)

Similar to Study 1, participants completed study measures on personal devices using the Qualtrics Survey platform. The survey also was described as having the goal of helping to "identify the positive impact of this film and explor[ing] how reactions to films may influence beneficial changes in behaviour.” The survey began by asking participants whether they had watched "Picture a Scientist" (833 [66.4%] had watched the film, 422 [33.6%] had not yet seen the film). We also asked participants to indicate how they had watched or planned to view the documentary. We found that 298 (23.7%) had/planned to watch through their professional societies/organizations, 677 (53.9%) had/planned to watch via their universities/colleges, 247 (19.7%) had/planned to watch through their companies (247, 19.7%), and 33 (2.6%) did not indicate how they had/planned to watch the film. Among those who had watched the film, we asked how long ago they had viewed the documentary and found that 471 (56.5%) had watched "Picture a Scientist" within the past month ago, and 361 (43.3%) had viewed the film over a month ago (1 person did not answer this question). Because we recruited participants via the Scientific American Panel, we also asked participants whether they had attended this panel (433 [34.5%] had watched the panel, 822 [65.5%] had not watched the panel). Using the same procedure as Study 1, participants then completed a series of demographic questions to determine which behavioural intentions items they would see later in the study.

Participants who indicated watching the film completed the same measures from Study 1 assessing film engagement. Moreover, using the same assessments from Study 1, all participants completed indices examining their general awareness of gender bias in the sciences, their feelings of self-efficacy to combated gender, and their behavioural intentions. We present detailed measure information in Supplementary Table 34.

At the end of the survey, participants who already view "Picture a Scientist" completed the easy memory attention check questions from Study 1, and we again excluded participants who failed to answer at least two questions correctly. The survey ended by asking participants whether they were willing to participate in the follow-up survey, and if they agreed, they provided their email addresses. Participants who were not interested in completing the second survey were shown the study debriefing. There were 1126 participants who chose to take part in the time 2 survey, and provided their email information. Among these 1126 participants, 671 (59.6% who agreed to complete the survey and 53.5% of the full sample) completed the time 2 survey. (Participants who were emailed the second survey but chose not to complete it did not vary systematically across time 1 measures; see Supplementary Table 35 for these analyses).

Procedure and measures (Time 1)

We emailed participants who opted-in to the follow-up survey a link to the time 2 survey approximately 2–3 weeks after the first survey. For our time 2 analyses, we were specifically interested in changes among participants who watched the film between time 1 and time 2. We had 240 (35.8% of time 2 participants) watched the documentary between time 1 and 2. Of these participants, 237 (98.8%) passed the memory attention questions for the film. Participants who indicated watching the documentary completed the same film engagement measures and memory questions from time 1. In addition, all participants completed the same awareness of bias, self-efficacy, and behavioural intentions measures from time 1.

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-72395-y.

Acknowledgements

The authors thank Sharon Shattuck, Ian Cheney, Manette Pottle, Amy Brand, and the "Picture a Scientist" film team, Sarah Goodwin and the Wonder Collaborative/Science Communication Lab team; ro*co films, and the more than 1,300 institutions who screened "Picture a Scientist" and helped recruit participants for these studies.

Author contributions

E.P. and CM-R designed and conceptualized the study, with input from LM and AW. EP and AW programmed the studies. LM assisted with participant recruitment and AW sent study invitations and follow-up survey emails. EP and AW analyzed the findings. EP wrote a first draft of the manuscript, with input and edits from all co-authors. All authors approved this submission.

Data availability

The datasets, codebooks, syntax files, and word documents of the Qualtrics surveys are available on the Study 1’s Open Science Framework page: https://osf.io/45c8y/?view_only=a81c2c26acef470db84ac2e3f0fd2b4b and Study 2’s Open Science Framework page: https://osf.io/tyuxj/?view_only=a264b9682efc42c3aa2dfa2828aec2b0.

Competing interests

The current studies explored the benefits of watching the documentary "Picture a Scientist." Co-author Lisa M.P. Munoz was part of the film team and was employed as the film's publicist and outreach producer. Co-authors Evava S. Pietri, Arispa Weigold, and Corinne Moss-Racusin had no financial ties to the documentary; however, Corinne Moss-Racusin was featured during an interview in the film. This research occurred and received IRB approval while Evava S. Pietri was at Indiana University-Purdue University Indianapolis. Dr. Pietri has switched institutions and is at the University of Colorado Boulder, where the majority of the writing for this manuscript took place.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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