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Psychological Analysis of Fear-Based Healthcare Messaging: Comparing HIV/AIDS and COVID-19 Through the Lens of Spiral Dynamics

Dr. Tomás Campbell [1], a member of the BPS Division of Clinical Psychology Faculty for HIV and Sexual Health, article "Towards more inclusive and Empowering Healthcare Campaigns" [2] presents a compelling analysis of the evolution of HIV/AIDS messaging over four decades, tracing a path from fear-based approaches to more empowering, inclusive strategies. This progression reflects significant advances in both medical understanding and psychological approaches to public health communication. 

The SDTEST® survey data on fears provides an excellent opportunity to examine how these evolving messaging strategies align with contemporary fear psychology and value systems as described by Spiral Dynamics theory.


Comparative Analysis of HIV/AIDS and COVID-19 Fear Prevalence


The SDTEST® survey "Fears" involving 3,679 participants across 105 countries reveals that HIV/AIDS now ranks relatively low at 4%, while COVID-19 ranks even lower at just 2%. Below is a abridged version of the survey results. The full results are available for free in the FAQ section after login or registration.


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Recalculer
La valeur critique du coefficient de corrélation
Distribution normale, par William Sealy Gosset (étudiant) r = 0.0318
Distribution normale, par William Sealy Gosset (étudiant) r = 0.0318
Distribution non normale, par Spearman r = 0.0013
DistributionNon
normal
Non
normal
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normal
NormalNormalNormalNormalNormal
Toutes les questions
Toutes les questions
Ma plus grande peur est
Ma plus grande peur est
Answer 1-
Positif faible
0.0524
Positif faible
0.0258
Négatif faible
-0.0180
Positif faible
0.0949
Positif faible
0.0355
Négatif faible
-0.0146
Négatif faible
-0.1537
Answer 2-
Positif faible
0.0175
Négatif faible
-0.0058
Négatif faible
-0.0387
Positif faible
0.0669
Positif faible
0.0494
Positif faible
0.0116
Négatif faible
-0.0969
Answer 3-
Négatif faible
-0.0035
Négatif faible
-0.0091
Négatif faible
-0.0441
Négatif faible
-0.0435
Positif faible
0.0477
Positif faible
0.0747
Négatif faible
-0.0199
Answer 4-
Positif faible
0.0412
Positif faible
0.0255
Négatif faible
-0.0229
Positif faible
0.0192
Positif faible
0.0353
Positif faible
0.0246
Négatif faible
-0.0990
Answer 5-
Positif faible
0.0227
Positif faible
0.1271
Positif faible
0.0109
Positif faible
0.0770
Négatif faible
-0.0005
Négatif faible
-0.0175
Négatif faible
-0.1774
Answer 6-
Négatif faible
-0.0055
Positif faible
0.0042
Négatif faible
-0.0622
Négatif faible
-0.0080
Positif faible
0.0249
Positif faible
0.0863
Négatif faible
-0.0354
Answer 7-
Positif faible
0.0084
Positif faible
0.0331
Négatif faible
-0.0656
Négatif faible
-0.0297
Positif faible
0.0523
Positif faible
0.0696
Négatif faible
-0.0522
Answer 8-
Positif faible
0.0629
Positif faible
0.0710
Négatif faible
-0.0267
Positif faible
0.0130
Positif faible
0.0379
Positif faible
0.0184
Négatif faible
-0.1339
Answer 9-
Positif faible
0.0711
Positif faible
0.1602
Positif faible
0.0072
Positif faible
0.0643
Négatif faible
-0.0106
Négatif faible
-0.0484
Négatif faible
-0.1819
Answer 10-
Positif faible
0.0740
Positif faible
0.0656
Négatif faible
-0.0150
Positif faible
0.0292
Positif faible
0.0321
Négatif faible
-0.0123
Négatif faible
-0.1359
Answer 11-
Positif faible
0.0629
Positif faible
0.0524
Négatif faible
-0.0098
Positif faible
0.0104
Positif faible
0.0253
Positif faible
0.0247
Négatif faible
-0.1270
Answer 12-
Positif faible
0.0433
Positif faible
0.0921
Négatif faible
-0.0338
Positif faible
0.0335
Positif faible
0.0331
Positif faible
0.0257
Négatif faible
-0.1540
Answer 13-
Positif faible
0.0687
Positif faible
0.0957
Négatif faible
-0.0396
Positif faible
0.0304
Positif faible
0.0408
Positif faible
0.0151
Négatif faible
-0.1630
Answer 14-
Positif faible
0.0781
Positif faible
0.0884
Négatif faible
-0.0003
Négatif faible
-0.0096
Positif faible
0.0050
Positif faible
0.0138
Négatif faible
-0.1228
Answer 15-
Positif faible
0.0539
Positif faible
0.1269
Négatif faible
-0.0339
Positif faible
0.0148
Négatif faible
-0.0172
Positif faible
0.0237
Négatif faible
-0.1160
Answer 16-
Positif faible
0.0690
Positif faible
0.0248
Négatif faible
-0.0372
Négatif faible
-0.0385
Positif faible
0.0703
Positif faible
0.0205
Négatif faible
-0.0792


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This modest fear prevalence contrasts sharply with the historical positioning of HIV/AIDS as a primary existential threat during the 1980s-90s. As the article aptly notes, early HIV/AIDS campaigns relied heavily on fear-based messaging, leveraging protection-motivation theory to drive behavioral change through graphic depictions of mortality and disease. The current survey results suggest these diseases have been partially normalized in the public consciousness, supporting the article's observation that medical advancements have transformed HIV from a death sentence to a manageable chronic condition.


When examining broader fear contexts, it's noteworthy that personal concerns about "illness of relatives and children" (11%) and general "illness" (8%) outrank specific disease fears like HIV/AIDS or COVID-19. This pattern indicates that abstract illness threats generate more anxiety than particular diseases that have been subject to extensive public education campaigns. This finding aligns with the article's discussion of how healthcare messaging has evolved toward destigmatization and normalization, particularly for HIV/AIDS.


Spiral Dynamics Correlations: Understanding Value Systems and Fear Responses


The correlation data between disease fears and Spiral Dynamics stages provides fascinating insights into how different value systems engage with health threats. HIV/AIDS shows a positive correlation (0.0662) with Orange-level thinking, which represents achievement-oriented, strategic value systems. This alignment makes psychological sense, as Orange thinking prioritizes personal agency and risk management. Individuals operating from this value system may respond more actively to diseases perceived as consequences of personal behavior choices.


Conversely, HIV/AIDS fears correlate negatively with Yellow (-0.0516) and more strongly with Turquoise (-0.1776) value systems. These second-tier thinking systems in Spiral Dynamics represent more complex, integrative worldviews that may contextualize disease within a broader systemic understanding. The stronger negative correlation with Turquoise thinking is particularly notable, as this holistic perspective tends to integrate mortality and vulnerability into a comprehensive worldview, potentially reducing fear responses to specific conditions.


For COVID-19, the correlation pattern differs significantly. The positive correlation with Green thinking (0.0637) suggests that communitarian, egalitarian value systems may experience heightened concern about highly communicable diseases that threaten community well-being. This aligns with the article's discussion of how modern healthcare campaigns increasingly emphasize collective responsibility and community protection. The negative correlations with Blue (-0.0342), Orange (-0.0409), and Turquoise (-0.0748) value systems suggest varied psychological responses across the spiral.


Implications for Evolving Healthcare Messaging


The article chronicles a shift from fear-based campaigns toward empowerment and behavioral strategies, noting how psychological frameworks like self-efficacy theory and social norm theory have informed this evolution. The SDTEST® data supports the efficacy of this shift by demonstrating relatively low fear ratings for HIV/AIDS despite its historical stigma. This suggests that destigmatizing, empowering messaging approaches may have successfully normalized the condition in public consciousness.


The varying correlations between fears and Spiral Dynamics stages also validate the article's emphasis on intersectionality and tailored messaging. Different value systems appear to process disease threats through distinct psychological frameworks, which has significant implications for public health communication. The article notes that "campaigns are now much more carefully designed to address diverse populations," which aligns with the need to consider value system diversity in designing effective interventions.


Advancing Psychologically Informed Healthcare Communications


The relatively weak correlation between disease fears and specific Spiral Dynamics stages (with the critical value of the correlation coefficient for a normal distribution, by William Sealy Gosset (Student) r = 0.0323) suggests that fears of HIV/AIDS and COVID-19 transcend value systems but manifest differently within them. This finding supports the article's conclusion that messaging must "remain effective, compassionate, and mindful of nuance." The positive correlation between HIV/AIDS fears and Orange thinking, contrasted with COVID-19's positive correlation with Green thinking, demonstrates how different diseases activate different value concerns.


The article's discussion of digital and social media platforms as vectors for modern healthcare messaging presents opportunities for even more targeted value-specific communications. Understanding the psychological frameworks through which different Spiral Dynamics stages process health information could enable micro-targeted campaigns that resonate more effectively with diverse audiences. For instance, messaging aimed at Orange-dominant thinkers might emphasize personal agency and achievement in health management, while Green-focused messaging might highlight community protection and collective responsibility.


Conclusion


The evolution of HIV/AIDS messaging described in the article reflects a sophisticated understanding of psychological principles, moving from protection-motivation theory toward self-efficacy and social norm approaches. The SDTEST® data validates this progression by showing relatively modest contemporary fear responses to HIV/AIDS despite its historical stigmatization. The correlation patterns between disease fears and Spiral Dynamics stages provide valuable insights for further refining healthcare communications to resonate with different value systems.


The comparative data between HIV/AIDS and COVID-19 fears, particularly their different correlation patterns with Spiral Dynamics stages, suggests that disease characteristics interact with value systems to produce distinct psychological responses. As the article argues, effective healthcare campaigns must continue to evolve based on evidence rather than prejudice. The SDTEST® data offers this evidence, demonstrating how fears of specific conditions correlate with different psychological frameworks and value systems.


This integration of fear psychology, mathematical correlation, and Spiral Dynamics theory provides a robust foundation for developing increasingly sophisticated, psychologically informed healthcare messaging strategies that can effectively engage diverse populations across the spiral of human development.



Sources

[1] https://www.linkedin.com/in/tomas-campbell-40202785/
[2] https://www.bps.org.uk/blog/towards-more-inclusive-and-empowering-healthcare-campaigns


2025.02.28
Valerii Kosenko
Product Owner SaaS SDTEST®

Valerii a obtenu son diplôme de pédagogue social-psychologue en 1993 et ​​a depuis appliqué ses connaissances à la gestion de projets.
Valerii a obtenu un master et le diplôme de chef de projet et de programme en 2013. Au cours de son programme de master, il s'est familiarisé avec Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) et Spiral Dynamics.
Valerii est l'auteur de l'exploration de l'incertitude du V.U.C.A. concept utilisant la dynamique spirale et les statistiques mathématiques en psychologie, et 38 sondages internationaux.
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Bonjour à tous! Permettez-moi de vous demander, connaissez-vous déjà la dynamique en spirale?