Influence of Contact Experience and Germ Aversion on Negative Attitudes Toward Older Adults: Role of Youth Identity

The world’s population is currently aging, and the issue of ageism has become serious worldwide, including in Japan. Negative attitudes toward older adults can have undesirable effects on the mental and physical health of this group. We focused on the effects of contact experience with older adults and germ aversion, or the degree of aversion to infection, on negative attitudes toward older adults. Additionally, we included a moderating variable; youth identity, or the sense of belonging with younger rather than older age groups. An online survey was conducted with Japanese participants (N = 603). We conducted multiple regression analyses and the results showed that the interaction effect between youth identity and contact experience on negative attitudes toward older adults was significant. The findings suggest that contact experience may help in reducing negative attitudes toward older adults among people with low youth identity. The interaction effect between youth identity and germ aversion, however, was not significant. Academic research on the effects of some psychological interventions (e.g., intergenerational social exchange) should pay particular attention to the role of youth identity. Future directions for empirical studies are also discussed.

Artificial Intelligence in hair research: A proof-of-concept study on evaluating hair assembly features

OBJECTIVE

The first objective of this study was to apply computer vision and machine learning techniques to quantify the effects of haircare treatments on hair assembly and to identify correctly whether unknown tresses were treated or not. The second objective was to explore and compare the performance of human assessment with that obtained from artificial intelligence (AI) algorithms.

METHODS

Machine learning was applied to a data set of hair tress images (virgin and bleached), both untreated and treated with a shampoo and conditioner set, aimed at increasing hair volume whilst improving alignment and reducing the flyway of the hair. The automatic quantification of the following hair image features was conducted: local and global hair volumes and hair alignment. These features were assessed at three time points: t₀ (no treatment), t₁ (two treatments) and t₂ (three treatments). Classifier tests were applied to test the accuracy of the machine learning. A sensory test (paired comparison of t₀ vs t₂ ) and an online front image-based survey (paired comparison of t₀ vs t₁ , t₁ vs t₂ , t₀ vs t₂ ) were conducted to compare human assessment with that of the algorithms.

RESULTS

The automatic image analysis identified changes to hair volume and alignment which enabled the successful application of the classification tests, especially when the hair images were grouped into untreated and treated groups. The human assessment of hair presented in pairs confirmed the automatic image analysis. The image assessment for both virgin hair and bleached only partially agreed with the analysis of the subset of images used in the online survey. One hypothesis is that treatments changed somewhat the shape of the hair tress, with the effect being more pronounced in bleached hair. This made human assessment of flat images more challenging than when viewed directly in 3D. Overall, the bleached hair exhibited effects of higher magnitude than the virgin hair.

CONCLUSIONS

This study illustrated the capacity of artificial intelligence for hair image detection and classification, and for image analysis of hair assembly features following treatments. The human assessment partially confirmed the image analysis and highlighted the challenges imposed by the presentation mode.

A novel UV-fluorescence approach to assess the long wear efficacy of foundations

BACKGROUND

The long wear properties of foundations are regarded as a must-have in terms of claims. Here, we propose an instrumental approach based on UV-fluorescence imaging as an alternative to clinical grading methods.

METHODS

A method was developed, with UV-fluorescence images captured with the Visia CR as a first step, followed by images analysis using Image-Pro plus. Repeated-measures correlation was used to assess the degree of association between the UV-fluorescence method and a grading method when removing the foundation incrementally from the skin using wipes. Thresholds to ascertain whether a foundation pass or fail long-wearing using the newly developed method were established using a mixed linear model and cross-validated using two subsets of a panel of 20 women.

RESULTS

The method could measure incremental removal of foundation using wipes, in a similar fashion to a grading method, as outlined with repeated measures correlation (r = -.86). Pass/fail thresholds established with the mixed linear model were tested versus the grading method when assessing a foundation under real conditions for a duration over 24 hours, with minimal discrepancies between the two methods.

CONCLUSION

By capitalising on foundation physical/chemical properties, the proposed method allows to assess their long wear properties, irrespective of basal skin tone or foundation shade. It offers the advantage of appealing visuals for efficacy and to be less resource intensive than a clinical grading approach.

The Skin Interactome: A Holistic "Genome-Microbiome-Exposome" Approach to Understand and Modulate Skin Health and Aging

Higher demands on skin care cosmetic products for strong performance drive intense research to understand the mechanisms of skin aging and design strategies to improve overall skin health. Today we know that our needs and influencers of skin health and skin aging change throughout our life journey due to both extrinsic factors, such as environmental factors and lifestyle factors, as well as our intrinsic factors. Furthermore, we need to consider our microflora, a collection of micro-organisms such as bacteria, viruses, and fungi, which is a living ecosystem in our gut and on our skin, that can have a major impact on our health. Here, we are viewing a holistic approach to understand the collective effect of the key influencers of skin health and skin aging both reviewing how each of them impact the skin, but more importantly to identify molecular conjunction pathways of these different factors in order to get a better understanding of the integrated “genome-microbiome-exposome” effect. For this purpose and in order to translate molecularly the impact of the key influencers of skin health and skin aging, we built a digital model based on system biology using different bioinformatics tools. This model is considering both the positive and negative impact of our genome (genes, age/gender), exposome: external (sun, pollution, climate) and lifestyle factors (sleep, stress, exercise, nutrition, skin care routine), as well as the role of our skin microbiome, and allowed us in a first application to evaluate the effect of the genome in the synthesis of collagen in the skin and the determination of a suitable target for boosting pro-collagen synthesis. In conclusion, we have, through our digital holistic approach, defined the skin interactome concept, as an advanced tool to better understand the molecular genesis of skin aging and further develop a strategy to balance the influence of the exposome and microbiome to protect, prevent, and delay the appearance of skin aging signs and preserve good skin health condition. In addition, this model will aid in identifying and optimizing skin treatment options based on external triggers, as well as helping to design optimal treatments modulating the intrinsic pathways.