Large-Scale Public Stigma Reduction Toward Individuals With Psychosis Using Brief Videos: A Secondary Data Analysis

Abstract

Background

Stigma toward individuals living with psychosis impacts treatment seeking and outcomes among youth. Brief social contact-based video interventions (<3 min long) can be disseminated via social media to reduce stigma. However, it is unclear how these videos impact distinct components of stigma (negative attitudes and behavioral intentions) and whether matching on demographic characteristics (race and gender) between protagonist and viewer bolsters effects.

Study Design and Hypothesis

We explored these questions in a secondary data analysis of 6 prior randomized controlled trials varying in presenter characteristics (race, gender, lived experience, actor) and video modality (selfie vs traditional style) in 6946 United States youth, ages 18-30, recruited via Prolific. It was hypothesized that our results would replicate previous findings on efficacy of brief videos on reducing stigma and that there would be a significant impact on cognitive and behavioral subdomains and a matching effect for gender and race.

Study Results

Results replicated prior findings that video interventions were effective at reducing stigma across 5 domains (social distance, stereotyping, separateness, social restriction, and perceived recovery) and contributed to an overall shift in stigmatizing attitudes and behavioral intentions at post-intervention and 30-day follow-up. Videos that matched viewers’ gender or race had significantly stronger stigma-reduction effects on certain domains, though effect sizes were small.

Study Conclusions

Results highlight that brief, easy-to-disseminate videos can effectively change stigmatizing perceptions and behavioral intentions toward individuals with psychosis. Future studies should explore how behavioral intentions translate to action and the impact of matching between presenters and participants.

Introduction

Rising stigma levels toward individuals living with psychosis in the United States (US) highlight the need for stigma-reduction interventions.^1,2 Public stigma, conceptualized as including negative attitudes, emotions, and/or intended behavior (eg, social rejection, discrimination) toward people with mental illness, influences treatment-seeking and contributes to social isolation in individuals with psychosis.^3–8 In prior studies, we examined the impact of 1-3 min brief video-based interventions (BVIs) and tested specific characteristics such as video modality (selfie vs production company) and presenter attributes (race, gender, lived experience, or actor) on public stigma in young adult cohorts.^9–14 It remains unclear how these studies collectively influence stigmatizing attitudes and behavioral intentions, and whether specific matching between protagonist and viewer played a role in stigma reduction. Aggregating these data can allow for a deeper understanding of the broader impact of these interventions and provides more power to detect differences in matching of gender and race.

Prior research suggests that social contact-based interventions involving individuals from a stigmatized group sharing personal stories of struggles and recovery are effective.^15–17 Low cost, easy to disseminate, video-based interventions have shown similar efficacy to in-person interventions.^16,18 However, prior interventions have lasted up to an hour, whereas younger individuals may prefer briefer content, similar to social media videos.^16,19 Brief video-based interventions involving young adult presenters sharing personal stories that moderately disconfirms stereotypes provide an avenue to reach young people in a “targeted” (ie, focusing contact efforts on a specific community, like young adults), “local” (ie, presenting relatable characteristics and content), and “credible” (ie, presenting stories that highlight positive outcomes in a believable way) manner.²⁰ A recent meta-analysis of stigma interventions toward individuals with mental illness suggests that interventions significantly impact cognitions, affective responses, and behavioral intentions at post-intervention, but only cognitions and behavioral intentions at follow-up.⁸ Examination of the impact of BVIs at the item level can increase understanding of how to improve these interventions. Other ways to further refine and enhance efficacy include the consideration of whether video narratives should be tailored to specific ethnoracial or gender experiences. Prior research suggests that Black individuals with psychosis face unique barriers including increased discrimination and decreased likelihood of receiving mental health services,^21–23 in comparison with other racial/ethnic groups.^24–28 Similarly, women face unique gender-related stressors, including receiving higher doses of antipsychotics and experiencing high rates of victimization, such as sexual assault.^29–32 Intersectionality of these marginalized identities with mental illness may worsen public stigma.^33–35 To address this issue, Oexle and Corrigan³³ recommend culturally tailored interventions; however, of 4 studies including culturally tailored interventions, none targeted psychosis and all were psychoeducational.³⁴

In a series of randomized controlled trials, each following the same design and inclusion criteria (ie, US young adults ages 18-30 recruited via Prolific) and including BVIs that moderately disconfirmed stereotypes and included young adult presenters, we demonstrated the efficacy of BVIs in reducing public stigma toward individuals with psychosis at post-intervention and 30-day follow-up. These trials compared: (1) gender-tailored videos to non-tailored versions,¹⁴ (2) racially tailored videos to non-tailored versions,¹² (3) videos addressing public stigma to those targeting self-stigma (the internalization of negative public perceptions by individuals living with mental illness),^11,36 (4) public stigma among friends and family of individuals with serious mental illness,¹³ (5) selfie-style videos to those produced by a production company,⁹ and (6) videos featuring an actor versus a person with lived experience.¹⁰ All videos were associated with significant reductions in stigma with greater reductions among women who watched videos with gender-specific content¹⁴ and Black individuals with racially tailored videos.¹² In the current secondary data analysis, we consider these studies in aggregate to better understand the impact of these interventions on specific cognitive and behavioral subdomains of stigma in a large cohort of US young adults. We also try to understand whether there is a matching effect of protagonist gender or race to viewer demographics, as we lacked power to do so in prior studies. It was hypothesized that our results would replicate previous findings on efficacy of BVIs on reducing stigma and that there would be a significant impact on cognitive and behavioral subdomains and a significant matching effect for gender and race.

Methods

Participants and Recruitment Procedure

We conducted a secondary data analysis of combined data from 6 prior randomized control trials in which we investigated the impact of brief videos on public stigma by combining the samples of each of the studies.^9–14 All studies followed the same exact design and inclusion criteria with US young adults ages 18-30 recruited via Prolific,³⁷ a crowdsourcing platform. One study specifically recruited for individuals who identified as friends or family members of someone who has been diagnosed with a serious mental illness¹³; however, these participants did not differ on any other demographic characteristics from the rest of the included studies. Participants were not allowed to participate in more than 1 of our studies. Participants were compensated $1.10 for each study step, with a maximum study total of $2.20. Studies were approved by the New York State Psychiatric Institute Review Board and participants reviewed an information sheet prior to beginning the study. Data were collected between September 2021 and April 2023.

Interventions

In all 6 studies, participants were randomized to a BVI aimed at reducing stigma that was shown after completing a baseline questionnaire or a control group that did not receive any intervention. A timer was embedded in the video screen to prevent participants from advancing until the video had played in full, ensuring full exposure to the content. Each BVI (ranging from 80 to 158 s) featured a young adult describing lived experiences with psychosis, including symptom onset, struggle, and a hopeful message of recovery. Interventions varied on production style (selfie-style vs professionally produced), presenter type (individual with lived experience vs actor delivering a lived experience-based script), and demographic characteristics (eg, gender, race/ethnicity). However, all interventions followed the same narrative structure and were grounded in a shared theoretical model of moderately disconfirming stereotypes through social contact. The consistency in message, structure, and hypothesized mechanism across videos supports their consideration as a cohesive class of interventions. Online Supplement Table S1 presents information regarding characteristics of each of the videos in the 6 studies.

Instruments

In all studies, public stigma was assessed across 5 domains: social distance, stereotyping, separateness, social restriction, and perceived recovery. All items were selected from widely used, validated instruments in the field of mental health stigma research. Six items were adapted from Boyd et al.³⁸ to measure social distance, such as willingness to have a person with schizophrenia as a neighbor. These items showed good internal consistency (Cronbach’s α = 0.89). Four items were adapted from the General Social Survey to measure stereotyping, such as perceptions of violence (α = 0.70). Four items measured separateness, or perceived differences between those with schizophrenia and other people (Phelan³⁹; α = 0.78). Three items measured social restriction, such as ability for someone with schizophrenia to have children (Pescosolido et al.⁴⁰; α = 0.72). Two items evaluated perceptions regarding recovery (Corrigan⁴¹; α = 0.73). Table 2 includes individual items on the scales. These domains include items measuring stigmatizing attitudes (eg, beliefs that a person with schizophrenia has plans about recovery), and behavioral intentions (eg, social distance items regarding willingness to have someone with schizophrenia as a neighbor).

Table 2.

Proportion of Participants Who Reversed Stigmatizing Perception Following the Intervention

	Stigmatizing perceptions toward individuals with psychosis							Changes from stigmatizing to non-stigmatizinga
Items	Baseline (n = 5 115)		Post (n = 5 020)		30-day FU (n = 3 881)		Baseline to post			Baseline to FU
	n	%	n	%	n	%	%	Χ2	d	%	Χ2	d
Social distance: Would you be willing to…
1 have someone with schizophrenia as a neighbor?	1 161	23	550	11	572	15	52	1 213.9	0.41	35	990.5	0.29
2 be close friends with someone with schizophrenia?	1 344	26	638	13	687	18	50	1 365.8	0.43	31	1 060.8	0.25
3 have a person with schizophrenia working closely with you on a job?	1 477	29	685	13	692	18	55	1 262.1	0.45	38	920.5	0.34
4 allow a child of yours to date a person with schizophrenia?	2 320	46	1 413	28	1 307	34	39	1 856.6	0.43	26	1 479.5	0.23
5 allow a child of yours to marry a person with schizophrenia?	2 320	46	1 534	30	1 321	35	35	2 175.8	0.38	24	1 520.2	0.20
6 allow a child of yours to have a baby with a person with schizophrenia?	2 580	51	1 862	37	1 503	40	27	2 311.6	0.35	22	1 477.7	0.20
Stereotyping: How able is a person with schizophrenia to…
7 make his own decisions about the treatment he should receive?	902	18	313	6	259	7	67	672.1	0.60	61	450.1	0.48
8 make his/her own decisions about managing his own money?	835	16	301	6	238	6	62	640.7	0.55	63	342.5	0.45
9 do something violent toward other people?	2 374	47	1 567	32	1 216	32	32	1 775.7	0.37	32	839	0.32
10 do something violent toward himself?	3 856	76	2 606	53	2 115	56	30	1 233.1	0.58	26	616.52	0.47
Separateness
11 When you think of a person with schizophrenia, how different do you think he is from other people?	3 556	70	2 454	48	2 102	55	31	915.48	0.53	21	566.9	0.40
12 Although a person with schizophrenia may seem just like everyone else, he is actually different in important ways	3 926	77	3 135	62	2 425	64	19	956.5	0.42	17	452	0.34
13 Someone with arthritis has just one thing wrong with them, but a person with schizophrenia is very different from other people	2 694	53	2 153	42	1 585	42	21	1 667.7	0.25	21	624.57	0.24
14 Although he may be like other people in many ways, a person with schizophrenia is fundamentally different from other people	3 419	67	2 690	53	2 090	55	21	1 412	0.36	18	777.42	0.31
Social restriction: A person with schizophrenia…
15 could be trusted to babysit small children	3 118	61	2 027	42	1 696	45	31	1 317.4	0.51	26	818.9	0.43
16 shouldn’t get married—that is, he should stay single	616	12	531	10	288	8	17	1 205.1	0.18	33	528	0.15
17 shouldn’t have children of his own—that is, he should remain childless	1 434	28	1 136	22	701	19	21	1 958.9	0.23	32	871.2	0.21
Recovery: I believe that a person with schizophrenia…
18 has a plan for how to stay well	992	20	436	9	434	11	55	956.3	0.45	45	460.4	0.33
19 can meet his current personal goals	478	9	248	5	228	6	44	981.2	0.26	33	492.8	0.18

^aHigher percentage indicates higher improvement in stigmatizing attitudes; items 9, 10, 15, 18, and 19 are reverse-scored; Cohen’s d effect sizes; bold indicates significance at P < .001 (McNemar’s test).

Abbreviation: FU—follow-up

Analysis

We combined data from prior studies into 1 control and 1 intervention group and analyzed data using SPSS 28.0. Pearson’s chi-square and one-way analyses of variance (ANOVAs) were used to compare demographic characteristics among the groups. Main outcome measures included changes in mean stigma scores across 5 stigma domains: social distance, stereotyping, separateness, social restriction, and perceived recovery. Repeated measures ANOVAs were used to compare mean stigma scores for each stigma domain across 2 groups (video intervention and control) and 3 time points (baseline, post-intervention, and 30-day follow-up). When group by time interactions were significant, independent samples t-tests were used to compare changes between baseline and post-intervention and baseline and follow-up.

In addition, to examine item level changes in stigmatizing beliefs and behavioral intentions over time in individuals who had a stigmatizing belief at baseline (eg, answering the question “would you be willing to have someone with schizophrenia as a neighbor” with “definitely unwilling, “probably unwilling” or “prefer not to answer”), we examined changes from baseline to post-intervention and baseline to 30-day follow-up using McNemar’s tests. Linear mixed models were used to test whether there was a matching effect for gender (woman and men) and race (White, Black, and Asian), respectively, with presenters of the same characteristics in participants in the video intervention group. For all statistical tests, we used a Bonferroni correction to adjust for the 5 subscales in the stigma measures and considered P < .01 to be significant.

Results

Sample Characteristics

After we excluded 323 (4%) participants who failed validity tests, 6946 individuals completed the pre-intervention assessment. Of these, 6800 (98%) completed an immediate post-intervention assessment and 5257 (76%) completed a 30-day follow-up assessment (Figure 1). Mean participant age was 25.3 ± 4.2 years (range 18-30). Nearly half of participants reported being female (n = 3239, 47%), 3341 (48%) male, and 331 (5%) transgender/nonbinary. Overall, 1006 (15%) participants self-identified as Hispanic, 832 (12%) non-Hispanic Black, 4096 (59%) non-Hispanic White, 775 (11%) non-Hispanic Asian, 25 (0.3%) non-Hispanic Native American, and 173 (2%) Other. Of respondents, 3940 (57%) replied affirmatively to the question “Do you have a friend or a family member diagnosed with serious mental illness?” (Table 1). We did not ask individuals about self-identification. Participants of all study groups who knew people with serious mental illness had significantly lower baseline scores across the 5 scales.

Figure 1.

Study Profile

Table 1.

Demographic Characteristics of Study Participants

Items	Intervention n = 5 115		Control n = 1 831		Total n = 6 946		Statistic
	Mean	SD	Mean	SD	Mean	SD	t	P
Agea	25.4	4.3	25.2	4.0	25.3	4.2	−2.39	.017
	n	%	n	%	n	%	X 2	P
Gender							1.47	.689
Female	2 407	47	832	45	3 239	47
Male	2 439	48	902	49	3 341	48
Transgender/nonbinary	243	5	88	5	331	5
Prefer not to answer	26	1	9	1	35	1
Race and ethnicity							2.97	.888
Hispanic	744	15	262	14	1 006	15
Non-Hispanic Black	628	12	204	11	832	12
Non-Hispanic White	2 994	59	1 102	60	4 096	59
Non-Hispanic Asian	574	11	201	11	775	11
Non-Hispanic Native American	18	0	7	0	25	0
Non-Hispanic Otherb	127	2	46	3	173	2
Prefer not to answer	30	1	9	1	39	1
Education							10.0	.123
Never completed high school	67	1	20	1	87	1
High school graduate	755	15	277	15	1 032	15
Some college credit	1 810	35	614	34	2 424	35
Bachelor’s degree	1 925	38	688	38	2 613	38
Master’s degree	453	9	187	10	640	9
Doctorate degree	80	2	40	2	120	2
Prefer not to answer	21	0	3	0	24	0
Familiarity with a person with SMI	2 773	54	1 167	64	3 940	57	49.8	<.001
Closeness/intimacy with person with SMI							3.71	.157
Very close/intimate	1 272	25	565	31	1 837	26
Somewhat close/intimate	1 138	22	472	26	1 610	23
Not close/intimate	363	7	130	7	493	7

Pearson chi-square; ^aIndependent samples t-test; ^bNon-Hispanic Other: multiracial (n = 98), Pacific Islander (n = 7), Middle Eastern (n = 4), unspecified (n = 64)

Abbreviation: SMI—serious mental illness.

Intervention Effects

As expected from merging these convergent trials, outcomes differed significantly across study arms. A 2 × 3 group-by-time ANOVA showed a significant group-by-time interaction in mean stigma scores across all 5 stigma domains: social distance (F(1,2) = 255.5, P < .001), stereotyping (F(1,2) = 362.9, P < .001), separateness (F(1,2) = 153.5, P < .001), social restriction (F(1,2) = 142.1, P < .001), and perceived recovery (F(1,2) = 96.3, P < .001). Figure 2 presents mean score curves of the study arms over time for each stigma domain, showing that the control arm changed minimally across time points, in contrast to the intervention arm, which showed a sharp decrement in stigma post-intervention and subsequent slight rebound over time. Independent samples t-tests showed significant between-group changes between intervention video and control from baseline to post-intervention and from baseline to 30-day follow-up across all 5 stigma domains (Online Supplement Table S2). Cohen’s d effect sizes ranged from 0.40 to 0.73 for baseline to post-intervention changes, and 0.29 to 0.59 for baseline to 30-day follow-up changes.

Figure 2.

Mean Scores on Public Stigma Domains Between Video (n = 5096) and No-Intervention Control (n = 1823) Over Time [Note: F/U—30-day follow-up; higher scores indicate greater stigma; social distance (range 6-24); stereotyping (range 4-16); separateness (range 4-16); social restriction (range 3-12); perceived recovery (range 2-8). Independent samples t-test: t ranged from −41.9 to −21.1 for baseline-post changes and −15.5 to −9.3 for baseline-F/U changes; Cohen’s d effect sizes ranged from 0.40 to 0.73 for baseline-post changes, and 0.29 to 0.59 for baseline-F/U changes.]

In addition to examining mean changes in stigma scores, we also examined changes of stigmatizing attitudes and behavioral intentions in people who had these attitudes at baseline from baseline to post-intervention and 30-day follow-up (Table 2). For example, 62% (n = 518) of the 835 participants who initially disagreed that someone with schizophrenia can make decisions about managing their money changed their minds right after seeing the video and a similar percentage persisted in this change at 30-day follow-up. We observed similar changes across all 5 stigma domains. Specifically, average score changes were seen in 43% of the participants in the social distance domain (Cohen’s d effect size ranged from 0.35 to 0.45 from baseline to post-intervention and 0.20 to 0.34 from baseline to 30-day follow-up), 48% in stereotyping (0.37 to 0.60 and 0.32 to 0.48), 50% in recovery (0.26 to 0.45 and 0.18 to 0.33), 23% in separateness (0.25 to 0.53 and 0.24 to 0.40), and 23% in social restriction (0.18 to 0.51 and 0.15 to 0.43) (Table 2).

For the race matching effect, we compared changes in stigma scores from baseline to post-intervention and baseline to 30-day follow-up between matched pairs of White, Black, and Asian participants and presenters of the same race in the video intervention group. Linear mixed modeling showed a significant matching effect for race/ethnicity in social distance (B = −0.2 greater improvement for race-matching on a scale with range 6-24; (F(3, 4654) = 5.44, P < .001), social restriction (B = −0.1 on a scale with range 3-12; F(3, 4470) = 4.68, P = .003), and perceived recovery (B = −0.2 on a scale with range 2-8; F(3, 4820) = 4.07, P = .007) from pre- to post-intervention, and in social distance (B = −0.07; F(3, 3547) = 5.26, P = .001) and perceived recovery (B = −0.2; F(3, 3649) = 4.48, P = .004) from pre-intervention to 30-day follow-up. We did not find significant effects for stereotyping and separateness from pre- to post-intervention, or for stereotyping, separateness, and social restriction from pre-intervention to 30-day follow-up. Regarding the gender matching effect, we compared changes in stigma scores from baseline to post-intervention and baseline to 30-day follow-up between matched pairs of women and men viewers and presenters of the same gender in the video intervention group. Linear mixed modeling showed a significant matching effect for gender in social distance (B = 0.1; F(2, 4656) = 8.60, P < .001) and social restriction (B = .09; F(2, 4472) = 5.61, P = .004) from pre- to post-intervention, and only in perceived recovery (B = 0.2; F(2, 3651) = 8.16, P < .001) from pre-intervention to 30-day follow-up. We did not find significant effects for stereotyping, separateness, and perceived recovery from pre- to post-intervention and social distance, stereotyping, separateness, and social restriction from pre-intervention to 30-day follow-up.

Discussion

Our secondary analysis examined the cumulative impact of 6 randomized controlled trials of brief social contact-based video interventions on stigma toward psychosis in 6946 young adults living in the US. Videos ranged from 1 to 3 min and varied in modality (selfie filming style vs production company), presenter characteristics (race, gender, lived experience vs actor reading a script created by a person with lived experience), and 2 of 6 included content tailored to gender¹⁴ and race¹² experiences. Results replicated our previous findings that video interventions are effective at reducing stigma immediately after viewing the intervention and at 30-day follow-up for all 5 stigma subscale.^{9–12,14,42,43} Although studies with further long-term follow-up are needed, these results suggest that it may be possible to change population-level attitudes on a large scale by distributing brief videos through avenues such as social media or through TV commercials or other streaming services.^44,45 Changing population attitudes may even have trickle-down impacts on self-stigma and help-seeking among individuals who are living with psychosis; however, this remains to be explored.

In addition to examining changes in mean scores (which tell us overall differences between groups but do not tell us how many people had a stigmatizing perception at baseline and changed their mind following the intervention), we examined item-level changes in stigmatizing perceptions and behavioral intentions across time. Results suggested an overall shift in stigmatizing attitudes and behavioral intentions among the participants, similar to results from a prior study⁷ where we examined data in aggregate from other studies that were not included in the current analysis.^42,43 Although all stigma domains showed significant reductions, results suggested that while some subscales showed greater change, such as social distance (43% on average), stereotyping (48%), and recovery (50%), others, like separateness (23%) and social restriction (23%), showed less improvement. These domains include items that may be more affectively charged and fear based, such as “A person with schizophrenia could be trusted to babysit small children,” which may be more difficult to change. Social contact-based video interventions may help begin to challenge these perceptions by providing opportunities for “connections” with members of an outgroup.⁴⁶ However, domains such as separateness or social restriction may be more rooted in implicit biases and reinforced through societal stigma that might require more intensive interventions, such as booster sessions, community- and structural-level interventions, or interventions that include more interactive elements, such as role plays, in order to challenge more ingrained misconceptions or prejudices.

In addition, although we measured behavioral intentions through the domain of social distance (which may be more directly linked with observable behaviors such as willingness to socialize with individuals living with psychosis), and found significant reductions, it is unclear whether these intentions will translate to actual behavioral change. Prior research in this area has been limited due to heterogeneity in how behavior is defined, with some studies using proxies of behavior such as likelihood of encouraging someone to seek help for a mental health-related condition, and others measuring actual behavior.⁴⁷ Further research in this area is needed and requires a clear description of what types of behaviors can be measured. These can include measurement of positive behaviors (eg, providing concrete social support or actively challenging stigmatizing perceptions of others), negative behaviors (eg, use of coercive tactics, withholding help, and avoidance), and microaggressions (eg, language).^7,48–50 In addition, there is a need to understand which attitudinal stigma domains are most influential for behavioral change and the role of more difficult to change domains (eg, social restriction and separateness) on behavior.

Our findings also indicated a significant matching effect for viewer and presenter demographic characteristics (race and gender) on some domains, including social distance and perceived recovery at post-intervention and 30-day follow-up and social restriction at post-intervention for race, and social distance and social restriction at post-intervention but not follow-up and perceived recovery at follow-up but not post-intervention for gender, though effect sizes were small. These findings are contrary to prior research with no significant matching effects for gender and race when content was not tailored to individual experiences,⁴² but similar to a study that found a significant matching effect for treatment-seeking-related stigma among treatment-naïve participants.⁵¹ In the study that found no significant matching effect, female viewers who watched female presenters and Black viewers who watched Black presenters had a greater numerical reduction in stigma scores, suggesting that it may have been underpowered to find significant effects for some domains that were significant in our current study.⁴² In addition, in our current study, only a few hundred out of 5000 participants in the intervention group viewed videos that were tailored with specific content to gender and race, suggesting that for some limited stigma domains, visual matching regardless of tailoring may bolster the impact of videos due to increased representation of certain groups; however, this effect is very small. It may suggest the need for additional culturally specific content rather than simply having visual representation or psychoeducation interventions alone, as in prior studies.³⁴ More research is needed regarding impact of culturally tailored interventions that go beyond visual representation.

Findings regarding social distance are promising, given that this is a proxy for behavioral intentions, and suggest that adequate representation of particular racial/ethnic groups or genders may potentially impact stigmatizing behaviors. In addition, perceptions of recovery may correlate with treatment seeking. Social restriction, which showed less reduction overall in our item-level analysis had a significant matching effect, suggesting that videos including diverse presenters may impact this domain. The lack of a sustained effect for gender is not surprising given that only 2 out of 6 studies included videos with specifically tailored narratives regarding gender or race experiences. Similarly, lack of effect on stereotyping and separateness might have been due to the videos not overtly disconfirming culturally specific stereotypes.³⁴ A question remains of how much tailoring is needed and what videos might look like in practice to have the largest effect. In addition, the impact of intersectionality of race and gender remains unexplored.

Limitations

Our study has some limitations, including that our sample is comprised of Prolific participants, who might not be fully representative of the young adult population, and might limit generalizability of results. We also do not have information regarding the relative distribution of participants across the US, for example, in rural versus urban areas, or whether participants self-identified as living with psychosis. Our measures primarily focus on beliefs and behavioral intent, rather than actual behavioral change. In addition, the analysis of matching effects across distinct interventions without fully accounting for intervention-level differences may complicate interpretation. Future studies should examine ways to incorporate such measures in addition to examining mediators and moderators of change and continue to examine the impact of matching and intersectionality on stigma reduction.

Conclusions

Public stigma toward individuals living with psychosis can have detrimental impacts on treatment-seeking and quality of life among individuals living with psychosis. This secondary analysis replicated and extended prior findings regarding the significant impact of brief videos at reducing public stigma among young adults, and suggested that although all stigma domains improved, separateness and social restriction might have been more difficult to change. More work is needed regarding behavior and affective responses. Lastly, results suggest the importance of matching participant race and gender to bolster impact of such interventions and the need for more work on understanding how to tailor narratives to create the most impact.

Funding

None declared.

Conflicts of Interest

The authors report no conflicts of interest.