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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.


Peurs

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Recalculer
La valeur critique du coefficient de corrélation
Distribution normale, par William Sealy Gosset (étudiant) r = 0.0315
Distribution normale, par William Sealy Gosset (étudiant) r = 0.0315
Distribution non normale, par Spearman r = 0.0013
DistributionNon
normal
Non
normal
Non
normal
NormalNormalNormalNormalNormal
Toutes les questions
Toutes les questions
Ma plus grande peur est
Ma plus grande peur est
Answer 1-
Positif faible
0.0518
Positif faible
0.0257
Négatif faible
-0.0203
Positif faible
0.0942
Positif faible
0.0391
Négatif faible
-0.0141
Négatif faible
-0.1546
Answer 2-
Positif faible
0.0178
Négatif faible
-0.0071
Négatif faible
-0.0376
Positif faible
0.0631
Positif faible
0.0501
Positif faible
0.0133
Négatif faible
-0.0955
Answer 3-
Négatif faible
-0.0025
Négatif faible
-0.0083
Négatif faible
-0.0456
Négatif faible
-0.0432
Positif faible
0.0498
Positif faible
0.0768
Négatif faible
-0.0241
Answer 4-
Positif faible
0.0428
Positif faible
0.0297
Négatif faible
-0.0259
Positif faible
0.0175
Positif faible
0.0374
Positif faible
0.0266
Négatif faible
-0.1027
Answer 5-
Positif faible
0.0228
Positif faible
0.1240
Positif faible
0.0115
Positif faible
0.0735
Positif faible
0.0010
Négatif faible
-0.0152
Négatif faible
-0.1755
Answer 6-
Négatif faible
-0.0021
Positif faible
0.0028
Négatif faible
-0.0619
Négatif faible
-0.0110
Positif faible
0.0269
Positif faible
0.0872
Négatif faible
-0.0366
Answer 7-
Positif faible
0.0107
Positif faible
0.0313
Négatif faible
-0.0667
Négatif faible
-0.0310
Positif faible
0.0538
Positif faible
0.0715
Négatif faible
-0.0532
Answer 8-
Positif faible
0.0653
Positif faible
0.0688
Négatif faible
-0.0267
Positif faible
0.0117
Positif faible
0.0398
Positif faible
0.0185
Négatif faible
-0.1345
Answer 9-
Positif faible
0.0740
Positif faible
0.1594
Positif faible
0.0050
Positif faible
0.0612
Négatif faible
-0.0067
Négatif faible
-0.0464
Négatif faible
-0.1836
Answer 10-
Positif faible
0.0754
Positif faible
0.0624
Négatif faible
-0.0144
Positif faible
0.0273
Positif faible
0.0336
Négatif faible
-0.0107
Négatif faible
-0.1359
Answer 11-
Positif faible
0.0626
Positif faible
0.0495
Négatif faible
-0.0084
Positif faible
0.0094
Positif faible
0.0277
Positif faible
0.0251
Négatif faible
-0.1276
Answer 12-
Positif faible
0.0429
Positif faible
0.0889
Négatif faible
-0.0323
Positif faible
0.0317
Positif faible
0.0350
Positif faible
0.0265
Négatif faible
-0.1531
Answer 13-
Positif faible
0.0705
Positif faible
0.0917
Négatif faible
-0.0384
Positif faible
0.0287
Positif faible
0.0437
Positif faible
0.0151
Négatif faible
-0.1634
Answer 14-
Positif faible
0.0812
Positif faible
0.0862
Négatif faible
-0.0035
Négatif faible
-0.0129
Positif faible
0.0076
Positif faible
0.0152
Négatif faible
-0.1208
Answer 15-
Positif faible
0.0555
Positif faible
0.1235
Négatif faible
-0.0340
Positif faible
0.0113
Négatif faible
-0.0139
Positif faible
0.0261
Négatif faible
-0.1160
Answer 16-
Positif faible
0.0715
Positif faible
0.0212
Négatif faible
-0.0388
Négatif faible
-0.0401
Positif faible
0.0745
Positif faible
0.0178
Négatif faible
-0.0772


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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?