Using Sex Toys and the Assimilation of Tools into Bodies: Can Sex Enhancements Incorporate Tools into Human Sexuality?

Using Sex Toys and the Assimilation of Tools into Bodies: Can Sex Enhancements Incorporate Tools into Human Sexuality? Ahenkora Siaw Kwakye. Sexuality & Culture, Apr 29 2020. https://rd.springer.com/article/10.1007/s12119-020-09733-5

Abstract: The use of vibrators, dildos and other sex toys for sexual stimulation and pleasure is common among women and is growing in popularity. While the phenomenon has positive benefits, it might equally present adverse consequences to users. This research aims to assess the popularity of sex toy use among women from different nations. Furthermore, the study aims to find out if the use of other household items for sexual stimulation is popular among women between the ages of 18 and 50. Finally, the study attempts to discover if sex toy users observe changes arising from the use of various sex toys and if such variations can be attributed to the assimilation of the sex toy used. I employed a convenience sampling in eight countries. The study observed that sex toys are popular among women between the ages of 18 and 50, but sex toy use appears to produce varying effects on users. It was also evident that a majority of participants use vibrating sex toys without a clinician’s recommendation. Some women observe changes in sensitivity levels of their sexual responses after using sex enhancements. It was observed that while there is a crackdown on the use of sex toys in Islamic nations, religion itself has a certain influence on the individual adherent’s desire to explore use of sex enhancements.

Unhappiness & age: Analysis of data from eight well-being data files on nearly 14 million respondents across forty European countries & the United States and 168 countries from the Gallup World Poll

Unhappiness and Age. David G.Blanchflower. Journal of Economic Behavior & Organization, April 29 2020. https://doi.org/10.1016/j.jebo.2020.04.022

Abstract: I examine the relationship between unhappiness and age using data from eight well-being data files on nearly fourteen million respondents across forty European countries and the United States and 168 countries from the Gallup World Poll. I use twenty different individual characterizations of unhappiness including many not good mental health days; anxiety; worry; loneliness; sadness; stress; pain; strain, depression and bad nerves; phobias and panic; being downhearted; having restless sleep; losing confidence in oneself; not being able to overcome difficulties; being under strain; being unhappy; feeling a failure; feeling left out; feeling tense; and thinking of yourself as a worthless person. I also analyze responses to a further general attitudinal measure regarding whether the situation in the respondent's country is getting worse. Responses to all these unhappiness questions show a, ceteris paribus, hill shape in age, with controls and many also do so with limited controls for time and country. Unhappiness is hill-shaped in age and the average age where the maximum occurs is 49 with or without controls. There is an unhappiness curve.

3. Discussion

There appears to be a midlife crisis where unhappiness reaches a peak in mid-life in the late forties across Europe and the United States. That matches the evidence for a nadir in happiness that reaches a low in the late forties also (Blanchflower, 2020a). In that paper it was found that, averaging across 257 individual country estimates from developing countries gave an age minimum of 48.2 for well-being and doing the same across the 187 country estimates for advanced countries gives a similar minimum of 47.2.

Table 14 summarizes the results obtained by solving out the age at which the quadratic fitted to the data reaches a maximum. There are sixteen without controls that average at 47.4 and twenty-eight with controls with the maxima averaging out to 49.1, and 48.6 years overall for the forty-four estimates. This is very close to the finding in Blanchflower (2020a) that the U-shape in happiness data averaged 47.2 in developed countries and 48.2 in developing. The conclusion is therefore that data on unhappiness and happiness are highly consistent at the age when the low point or zenith in well-being occurs.

I add to the growing list of unhappiness variables that have hump shapes in age with or without controls. I find a broadly similar hill or hump shaped curve in twenty measures of unhappiness including being many not good mental health days; being stressed, unhappy; anxious, sad, sleepless; lonely; tired; depressed, tense, under strain; having bad nerves; phobias and panics and being in pain, feeling left out of society and several more. I also found the hump shape for a more general measure relating to the respondent's belief that the country 'is getting worse'. It doesn't seem to matter much how the question about unhappiness is phrased or coded or which country the question is asked or when we get similar results.

A referee has noted that if you look at the graphs, you see wave-like patterns (sadness, panics), hump-shaped patterns (sleep, stress), and increasing-to-a-plateau-like patterns (pain and worry with limited controls). No matter the exact shape of the plots in the various charts, it is clear that there is a peak somewhere in mid-life. I don't claim the patterns are all identical, but their broad similarity is striking, with a peak in prime age. There is a clear consistent pattern in the unhappiness and age data.

Blanchflower and Graham (2020) showed that the drop in measured happiness from youth to the mid-point low of the U-shape is quantitatively large and was not "trivial" as some psychologists have claimed. Indeed, they show the decline in well-being was about the equivalent of that observed from losing a spouse or a job. The results on unhappiness are similar. For example, in the Gallup USDTP averaged across the years 2008-2017 the probability of depression in the raw data rose from 12% at age 18 to 21% at age 58. The proportion of the employed who were depressed was 12% versus 24% for the unemployed. In addition, 12% of the married were depressed yesterday versus 19% of the widowed. In the raw data from the BRFSS the proportion who said they had 20 or more bad days in a month was 6.6% at age 18 and 8.4 at age 47, the peak. Among the married the rate was 5.5% versus 8% for the widowed. The rise in unhappiness to the mid-life peak, is thus large and comparable in magnitude to major life events.

So, what is going on in mid-life? In Blanchflower and Oswald (2008) we suggested three possibilities. First, that individuals learn to adapt to their strengths and weaknesses, and in mid-life quell their infeasible aspirations. Second, it could be that cheerful people live systematically longer than the miserable, and that the nadir in happiness in mid-life thus traces out in part a selection effect. A third is that a kind of comparison process is at work: I have seen school-friends die and come eventually to value my blessings during my remaining years. Steptoe et al (2010) suggest that "it is plausible that wellbeing improves when children leave home, given reduced levels of family conflict and financial burden" (p.9986, 2010).

The finding of a nadir in well-being in midlife likely adds important support to the notion that the prime-aged, and especially those with less education, are especially vulnerable to disadvantages and shocks.27 The global Covid-19 pandemic, which is disproportionately impacting marginal workers will likely make matters even harder to deal with for many at a well-being low point (Bell and Blanchflower, 2020). Some especially defenseless individuals might face downward spirals as age and life circumstances interact. Many will not be getting the social/emotional support they need as they are isolated and lonely, in addition to the first-order effects of whatever they are coping with in normal times. Lack of health care coverage in the US may well be a compounding factor where there is also an obesity epidemic. A midlife low is tough and made much harder when combined with a deep downturn and a slow and weak recovery. Peak unhappiness occurs in mid-life. There is an unhappiness curve.

The 168 countries are Afghanistan; Albania; Algeria; Angola; Argentina; Armenia; Australia; Austria; Azerbaijan; Bahrain; Bangladesh; Belarus; Belgium; Belize; Benin; Bhutan; Bolivia; Bosnia Herzegovina; Botswana; Brazil; Bulgaria; Burkina Faso; Burundi; Cambodia; Cameroon; Canada; Central African Republic; Chad; Chile; China; Colombia; Comoros; Congo Brazzaville; Congo Kinshasa; Costa Rica; Croatia; Cuba; Cyprus; Czech Republic; Denmark; Djibouti; Dominican Republic; Ecuador; Egypt; El Salvador; Estonia; Ethiopia; Finland; France; Gabon; Gambia; Georgia; Germany; Ghana; Greece; Guatemala; Guinea; Guyana; Haiti; Honduras; Hong Kong; Hungary; Iceland; India; Indonesia; Iran; Iraq; Ireland; Israel; Italy; Ivory Coast; Jamaica; Japan; Jordan; Kazakhstan; Kenya; Kosovo; Kuwait; Kyrgyzstan; Laos; Latvia; Lebanon; Lesotho; Liberia; Libya; Lithuania; Luxembourg; Macedonia; Madagascar; Malawi; Malaysia; Maldives; Mali; Malta; Mauritania; Mauritius; Mexico; Moldova; Mongolia; Montenegro; Morocco; Mozambique; Myanmar; Nagorno Karabakh; Namibia; Nepal; Netherlands; New Zealand; Nicaragua; Niger; Nigeria; Northern Cyprus; Norway; Oman; Pakistan; Palestine; Panama; Paraguay; Peru; Philippines; Poland; Portugal; Puerto Rico; Qatar; Romania; Russia; Rwanda; Saudi Arabia; Senegal; Serbia; Sierra Leone; Singapore; Slovakia; Slovenia; Somalia; Somaliland; South Africa; South Korea; South Sudan; Spain; Sri Lanka; Sudan; Suriname; Swaziland; Sweden; Switzerland; Syria; Taiwan; Tajikistan; Tanzania; Thailand; Togo; Trinidad and Tobago; Tunisia; Turkey; Turkmenistan; Uganda; Ukraine; UAE; UK; USA; Uruguay; Uzbekistan; Venezuela; Vietnam; Yemen; Zambia and Zimbabwe.

Changes in sexual behaviors in young people during COVID-19: 44% of participants reported a decrease in the number of sexual partners & about 37% of participants reported a decrease in sexual frequency

Changes in sexual behaviors of young women and men during the coronavirus disease 2019 outbreak: a convenience sample from the epidemic area. Weiran Li et al. The Journal of Sexual Medicine, April 29 2020, https://doi.org/10.1016/j.jsxm.2020.04.380

Abstract
Background: In March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a pandemic. Currently, data on changes in sexual behavior during the COVID-19 outbreak are limited.

Aim: The present study aimed to obtain a preliminary understanding of the changes in people’s sexual behavior, as a result of the pandemic and explore the context in which they manifest.

Methods: A convenience sample of 270 men and 189 women who completed an online survey consisting of 12 items plus an additional question were included in the study.

Outcomes: The study outcomes were obtained using a study-specific questionnaire to assess the changes in people’s sexual behavior.

Results: While there was a wide range of individual responses, our results showed that 44% of participants reported a decrease in the number of sexual partners and about 37% of participants reported a decrease in sexual frequency. Multiple regression analysis showed that age, partner relationship and sexual desire were closely related to sexual frequency. In addition, we found that most individuals with risky sexual experiences had a rapid reduction in risky sexual behavior.

Clinical Implications: The current findings contribute to identifying another potential health implication associated with the COVID-19 pandemic and report preliminary evidence of the need to provide potential interventions for the population.

Strength & Limitations: This study is the first to perform a preliminary exploration of sexual behavior during the COVID-19 outbreak. The generalizability of the results is limited, given that only a small convenience sample was used.

Conclusion: During the height of the COVID-19 outbreak, overall sexual activity, frequency, and risky behaviors declined significantly among young men and women in China.

Key words: COVID-19Sexual activitiesSexual frequencyRisky sexual behavior

DISCUSSION

In general, at the height of the COVID-19 epidemic, we found that both sexual activities and sexual satisfaction of young men and women decreased. Low sexual desire and unsatisfying partner relationships were significant factors affecting sexual activities, which is in agreement with previous studies 6.

In addition, we found that most individuals with a history of risky sexual experiences had a rapid reduction in risky sexual behaviors. This may be because the participants may have experienced a great deal of psychological stress during this particular period, such as anxiety, fear, boredom, and disappointment. In addition, it is undeniable that strict physical restrictions have directly impacted the possibility of having new sexual partners and risky sexual behaviors. However, in the supplementary question, 32% of men and 18% of women indicated that they were inclined to increase the number of sexual partners or risky sexual behaviors once the epidemic ended. A significant minority will be engaged in behaviors that could increase the risk of contracting sexually transmitted diseases7.

There are several potential limitations to our research that should be noted. First, race and ethnic culture appear to have a significant association with the occurrence of sexual problems8. For example, most young Chinese people live with their parents (72% in the current study), which is different from results reported in other countries and may be a significant factor that can limit their sexual behaviors. Therefore, the small sample size from a single ethnicity and the lack of randomization are also limitations for the extrapolation of the results to the global general population. Second, the use of unverified questionnaires and retrospective evaluations of sexual behavior was also a weakness of the study. In addition, we did not collect data form participants who did not complete the questionnaire. Hence, the characteristics of these individuals and their impact on the overall data were not analyzed.