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evidence-based-activism · 2 months ago

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How do you feel about the spontaneous v responsive model of attraction, and their associated sex differences?

Honestly, I don't know much about this topic. (I had not heard about it before this ask!) I've researched it, but empirical research on it is pretty sparse.

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It looks like these models concern the different models of sexual attraction/behavior, in that the "spontaneous" model refers to the "linear" model and the "responsive" model refers to the "circular" model.

The linear model was proposed by William H. Masters and Virginia E. Johnson in their book Human Sexual Response [1]. In brief it suggested that the human sexual response consists of four phases: excitement, plateau, orgasmic, and resolution, which occur linearly.

Rosemary Basson challenged the validity of this model, suggesting that, while it may be accurate for men, it fails to describe women's sexual response [2]. Her model is circular, indicating that "for many women ... sexual arousal and a responsive-type of desire occur simultaneously at some point after the women have chosen to experience sexual stimulation; this choice is based initially on needs other than a desire to experience physical sexual arousal and release" [emphasis mine].

My initial thoughts on this were mixed:

I've found purely linear models for human behavior are almost always overly-simplistic, often to the point of inaccuracy. Almost all the time, future work requires an update to include bidirectional and secondary factor influences.

That being said, the implication I don't believe that women and men have biologically determined differences in sexual response/behavior. I talk about that in this post, but the biggest relevant points are that “sex differences in self‐reported sexual behavior were negligible … [when] participants believed lying could be detected, moderate in an anonymous condition, and greatest [when not anonymous]” indicating “sex differences in self‐reported sexual behavior reflect responses influenced by normative expectations for men and women” [3]. In addition, a review found "many gender differences in sexuality are smaller than researchers once thought, … that within-gender variation is larger than between-gender variation in reported sexual behaviors and attitudes” and that “societal power differentials and social pressures” play a role in any remaining differences" [4].

Beyond that, I also find the implication that it is not only common but normal and reasonable for women to engage in sex without "initial desire" for sex to be concerning. It seems like a way to coerce sexual behavior from women. (Note: I am not saying that Basson intended for it to be used in this way ... I am saying I think it is likely it could/would be used this way.)

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But, I decided to do some further research and found:

Some research appears to suggest that the linear model is not accurate even for men, and that "responsive desire manifests similarly in women and men, emerging from exposure to relevant sexual incentives and accompanying sexual arousal." [5]

A review of research concluded that "there is an increasing body of evidence that the circular pathways ... which involves responsive desire, accurately reﬂects aspects of the female sexual response" [6]

A different study on men, found that only 2.5% of respondents endorsed responsive desire patterns (but keep in mind the earlier discussion about the influence of expectations on study responses) [7]

One study found the majority of women (84.5%) reported at least occasionally engaging in sex without feeling sexual desire at the outset [8]

Another study concluded that "a lack of spontaneous desire is inevitable with time even in satisfying relationships and that, as a result, women often made a conscious decision to engage in sex, based on reasons unrelated to sexual desire" [9]

Another study critiques the DSM diagnosis of "Hypoactive Sexual Desire Disorder" citing "the fact that sexual activity often occurs in the absence of desire for women, conceptual issues in understanding untriggered versus responsive desire, the relative infrequency of unprovoked sexual fantasies in women, and the significant overlap between desire and arousal" as issues [10]

These results all suggest that, whether it is desirable or not, the responsive model is an accurate way of describing women's (and possibly men's) sexual behavior.

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In conclusion, I think research supports the ideas that:

The linear model is too simplistic to accurately describe sexual response

Men's and women's sexual responses are more similar than commonly suggested, but social expectations likely influences both behavior (e.g., women may be more likely to agree to sex without desire) and reporting (e.g., men may more likely to report spontaneous desire due to gender stereotypes)

Many women agree to sex they don't "start out" wanting. I would contend that this is – at the very least – a risk factor for sexual coercion

I hope this helps you!

References under the cut:

Masters, William H. Human Sexual Response. First edition., Little, 1966.

Basson, R. (2000). The female sexual response: A different model. Journal of Sex &Marital Therapy, 26(1), 51-65.

Alexander, M. G., & Fisher, T. D. (2003). Truth and consequences: Using the bogus pipeline to examine sex differences in self‐reported sexuality. Journal of sex research, 40(1), 27-35.

Petersen, J. L., & Hyde, J. S. (2011). Gender Differences in Sexual Attitudes and Behaviors: A Review of Meta-Analytic Results and Large Datasets. Journal of Sex Research, 48(2-3), 149–165. doi:10.1080/00224499.2011.5518

Dawson, S. J., & Chivers, M. L. (2014). Gender differences and similarities in sexual desire. Current Sexual Health Reports, 6, 211-219.

Hayes, R. D. (2011). Circular and linear modeling of female sexual desire and arousal. Journal of Sex Research, 48(2-3), 130-141.

Štulhofer, A., Carvalheira, A. A., & Træen, B. (2013). Is responsive sexual desire for partnered sex problematic among men? Insights from a two-country study. Sexual and Relationship Therapy, 28(3), 246-258.

Carvalheira, A. A., Brotto, L. A., & Leal, I. (2010). Women’s motivations for sex: Exploring the diagnostic and statistical manual, text revision criteria for hypoactive sexual desire and female sexual arousal disorders. The journal of sexual medicine, 7(4_Part_1), 1454-1463.

Duerr, E. (2009). Lack of ‘responsive’sexual desire in women: implications for clinical practice. Sexual and Relationship Therapy, 24(3-4), 292-306.

Brotto, L. A. (2010). The DSM diagnostic criteria for hypoactive sexual desire disorder in women. Archives of sexual behavior, 39, 221-239.

#feminism #patriarchal culture

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lifewithchronicpain · 3 months ago

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A new study shows a link between abdominal fat and chronic musculoskeletal pain, but even the authors admit that it’s unclear which one causes which.

The study, published in the American Society for Regional Anesthesia & Pain Medicine, found that abdominal adipose tissue (fat) is associated with chronic pain in multiple sites and widespread chronic pain. It also found that women were at higher risk for this association than men.

“Reducing abdominal adiposity may be considered a target for chronic pain management, particularly in those with pain in multiple sites and widespread pain," wrote lead author Feng Pan, PhD, Senior Research Fellow at the Menzies Institute for Medical Research in Australia. “The identified stronger effects in women than men may reflect sex differences in fat distribution and hormones.”

In layman's terms, they’re suggesting that chronic pain patients be told to lose weight. Especially if they are women.

However, further down in the study, while discussing its limitations, they admit that the research does not “address the issue of potential bidirectional causality.” In other words, they cannot say whether excess abdominal fat causes chronic pain, or whether chronic pain causes excess abdominal fat…

…While a specific link between abdominal fat and chronic pain may be new, the idea that fat could contribute to chronic pain by making people more sedentary and less likely to exercise has a long history.

However, as a patient who gained weight after developing chronic pain and being put on a number of medications that had weight gain listed as a side effect, I’m always extremely skeptical about which causes which.

Especially because I gained and lost weight multiple times over the 11 years that I’ve been in pain, and have never noticed either one impacting my pain levels.

In my experience, many doctors are quick to dismiss symptoms when they can blame a patient’s weight as the cause. Even when the excess weight was literally caused by medications they prescribed.

Doctors use studies like these to blame pain patients for their problems, while absolving themselves of any responsibility to help. Patients are told their pain is their fault, and if they’d just lose weight, they’d feel better.

Then, when losing weight proves predictably difficult, the doctor can throw up their hands at the whole situation and proclaim that the patient must not want to get better. In other words, doctors set an impossible standard for patients and then blame the patient when they fail to meet it.

As new weight loss GLP-1 medications like Ozempic and related drugs become more popular, it will be interesting to see how they impact conversations about weight loss and chronic pain. If the medications are as good as they claim to be at helping people lose weight, we might finally get some large-scale research into how losing weight actually impacts pain levels.

And if more patients are able to lose weight when their doctors tell them too, physicians may find that they have to do more than just tell their patients to “lose weight” when it comes to treating pain. (Full article at link)

#disability #chronic pain #spoonies #ableism #fatphobia #weight loss #study #article

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angelacademy · 4 months ago

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Clear skin is more than just skincare: Gut Health

(A science based read)

What you eat is shown through your skin and on body. If your constantly shoving junk down your throat, junk is what will be shown on you. Essentially what you eat is what you are.

Eat bad -> bad skin

Eat good -> good skin

If your constantly breaking out and you feel icky. You need to figure out what is up with your gut health.

Research suggests many skin disorders are linked to an altered or unbalanced gut microbiome.

“When the relationship between gut microbiome and the immune system is impaired, subsequent effects can be triggered on the skin, potentially promoting the development of skin diseases.”

“13 Several dermatologic conditions, such as acne, atopic dermatitis, psoriasis, and rosacea are linked with intestinal dysbiosis. 223 Many studies have associated gastrointestinal health with skin homeostasis and allostasis, and there is evidence of a bidirectional interaction between the gut and the skin.”

Diet, drugs and other consumed substances affect skin through gut microbiome:

“Several studies have related the diversity and pathogenicity of the gut microbiome to skin disorders, which can be significantly altered by long-term dietary patterns. 43,105–107 Diet can affect the skin condition both positively and negatively through alteration of the gut microbiome, indicating that there is a relationship between the skin and the gut. 16 Not only diet, but also many synthetic and natural products consumed by humans as drugs can provide direct and indirect evidence on the connection between gut microbiome and skin.”

High and low fat diet:

“In the gut, a diet high in industrial trans-fatty acids increases the number of harmful microbes (such as Desulfovibrionaceae and Proteobacteria) while suppressing populations of advantageous microorganisms (e.g. members of Bacteroidetes, Lachnospiraceae, and Bacteroidales). 121 Refined and hydrogenated oils (e.g., soybean, sunflower, safflower, canola, corn, and vegetable oils) can cause inflammation in the gut, which then manifests on the skin.”

Industrially produced trans fat can be found in margarine, vegetable shortening, Vanaspati ghee, fried foods, and baked goods such as crackers, biscuits and pies. Baked and fried street and restaurant foods often contain industrially produced trans fat.

Prebiotics:

“133,134 Prebiotics, such as fructooligosaccharides, galactooligosaccharides, inulin, polydextrose, lactulose, sorbitol, and xylitol are a promising group of compounds that modulate the gut microbiome and can also provide skin benefits.”

“The effect of prebiotics on the skin condition is also obvious. For example, a Lactobacillus extract helps to reduce the size of acne lesions as well as inflammation by reducing skin erythema, improving skin barrier function and lowering the microbial counts on skin.”

types of prebiotics include:

Chicory root

Garlic

Onion

Dandelion greens

Apples

Bananas

Jerusalem artichoke

Asparagus

Probiotics:

“Probiotics can prevent gut colonization by pathogens and support anti-inflammatory responses by producing metabolites with anti-inflammatory properties. The most common probiotic microbes currently in use belong to the genera Bacillus, Bifidobacterium, Enterococcus, Escherichia, Lactobacillus, Saccharomyces, and Streptococcus. 143,144 Several beneficial effects of probiotic consumption have been demonstrated on many dermatological conditions, thus proving the existence of the gut-skin axis.”

Common types of probiotics include:

Lactobacillus: This is a common probiotic found in fermented foods, such as yogurt.

Bifidobacterium: This probiotic is found in some dairy products and helps with the symptoms of irritable bowel syndrome.

Saccharomyces boulardii: This is a type of yeast found in many probiotics. You can find these probiotics and more in supplements and select foods.

Yogurt

Buttermilk

Cottage cheese

Miso soup

Sauerkraut

Kefir

Kimchi

Tempeh

Protein:

“The proteins from animal-based food sources may have better effects on gut microbiota compared to plant-based food sources due to the higher protein digestibility of animal proteins and the fact that the digestion of plant proteins may be limited by the presence of antinutritional factors found in plants [67]. Animal proteins have more balanced essential amino acids than plant proteins [68,69] and are thus considered higher quality protein.”

“Dairy and meat protein intake at a recommended level increased the abundance of the genus Lactobacillus and maintained a more balanced composition of gut microbiota compared to soy protein, which is beneficial to the host [25,26,28].”

“Your body makes lots of different peptides, each of which has a different role. Scientists can also make synthetic peptides in the lab. Companies have been adding peptides to skin care products for decades.”

High protein foods:

Salmon

Chicken breast

Tuna

Red split lentils

Tofu

Greek yogurt

Fibre:

“Dietary fibre is comprised of plant-based carbohydrates that cannot be metabolised by digestive enzymes encoded in the human genome, such as amylase. Instead, fibre can only be metabolized by certain species of gut microbiota through anaerobic fermentation, with the main product of this reaction being SCFAs.”

“Dietary fibre is a carbohydrate in plant foods, such as whole grains, vegetables, fruit, and legumes, which have been dominant in human diets for millions of years. From the Paleolithic era, when the hunter-gatherers mainly ate fruit and wild grains, to the agricultural era, when crops began to be cultivated, the ancients consumed more than 100 g of various digestible and indigestible dietary fibre from plants per day [1,2].”

Fibre rich foods:

Chia seeds

Lentils

Broccoli

Avacado

Carrots

Red kidney beans

Raspberries

XOXO

#angelacademy #self improvement #that girl #glow up #beauty #skincare #gut health #digestivehealth #digestive system #digestivewellness #clear skin

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scifigeneration · 5 months ago

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ChatGPT and the movie ‘Her’ are just the latest example of the ‘sci-fi feedback loop’

by Rizwan Virk, Faculty Associate and PhD Candidate in Human and Social Dimensions of Science and Technology at Arizona State University

In May 2024, OpenAI CEO Sam Altman sparked a firestorm by referencing the 2013 movie “Her” to highlight the novelty of the latest iteration of ChatGPT.

Within days, actor Scarlett Johansson, who played the voice of Samantha, the AI girlfriend of the protagonist in the movie “Her,” accused the company of improperly using her voice after she had spurned their offer to make her the voice of ChatGPT’s new virtual assistant. Johansson ended up suing OpenAI and has been invited to testify before Congress.

This tiff highlights a broader interchange between Hollywood and Silicon Valley that’s called the “sci-fi feedback loop.” The subject of my doctoral research, the sci-fi feedback loop explores how science fiction and technological innovation feed off each other. This dynamic is bidirectional and can sometimes play out over many decades, resulting in an ongoing loop.

Fiction sparks dreams of Moon travel

One of the most famous examples of this loop is Moon travel.

Jules Verne’s 1865 novel “From the Earth to the Moon” and the fiction of H.G. Wells inspired one of the first films to visualize such a journey, 1902’s “A Trip to the Moon.”

The fiction of Verne and Wells also influenced future rocket scientists such as Robert Goddard, Hermann Oberth and Oberth’s better-known protégé, Wernher von Braun. The innovations of these men – including the V-2 rocket built by von Braun during World War II – inspired works of science fiction, such as the 1950 film “Destination Moon,” which included a rocket that looked just like the V-2.

Films like “Destination Moon” would then go on to bolster public support for lavish government spending on the space program.

youtube

Creative symbiosis

The sci-fi feedback loop generally follows the same cycle.

First, the technological climate of a given era will shape that period’s science fiction. For example, the personal computing revolution of the 1970s and 1980s directly inspired the works of cyberpunk writers Neal Stephenson and William Gibson.

Then the sci-fi that emerges will go on to inspire real-world technological innovation. In his 1992 classic “Snow Crash,” Stephenson coined the term “metaverse” to describe a 3-D, video game-like world accessed through virtual reality goggles.

Silicon Valley entrepreneurs and innovators have been trying to build a version of this metaverse ever since. The virtual world of the video game Second Life, released in 2003, took a stab at this: Players lived in virtual homes, went to virtual dance clubs and virtual concerts with virtual girlfriends and boyfriends, and were even paid virtual dollars for showing up at virtual jobs.

This technology seeded yet more fiction; in my research, I discovered that sci-fi novelist Ernest Cline had spent a lot of time playing Second Life, and it inspired the metaverse of his bestselling novel “Ready Player One.”

The cycle continued: Employees of Oculus VR – now known as Meta Reality Labs – were given copies of “Ready Player One” to read as they developed the company’s virtual reality headsets. When Facebook changed its name to Meta in 2021, it did so in the hopes of being at the forefront of building the metaverse, though the company’s grand ambitions have tempered somewhat.

Another sci-fi franchise that has its fingerprints all over this loop is “Star Trek,” which first aired in 1966, right in the middle of the space race.

Steve Perlman, the inventor of Apple’s QuickTime media format and player, said he was inspired by an episode of “Star Trek: The Next Generation,” in which Lt. Commander Data, an android, sifts through multiple streams of audio and video files. And Rob Haitani, the designer of the Palm Pilot’s operating system, has said that the bridge on the Enterprise influenced its interface.

In my research, I also discovered that the show’s Holodeck – a room that could simulate any environment – influenced both the name and the development of Microsoft’s HoloLens augmented reality glasses.

From ALICE to ‘Her’

Which brings us back to OpenAI and “Her.”

In the movie, the protagonist, Theodore, played by Joaquin Phoenix, acquires an AI assistant, “Samantha,” voiced by Johansson. He begins to develop feelings for Samantha – so much so that he starts to consider her his girlfriend.

ChatGPT-4o, the latest version of the generative AI software, seems to be able to cultivate a similar relationship between user and machine. Not only can ChatGPT-4o speak to you and “understand” you, but it can also do so sympathetically, as a romantic partner would.

There’s little doubt that the depiction of AI in “Her” influenced OpenAI’s developers. In addition to Altman’s tweet, the company’s promotional videos for ChatGPT-4o feature a chatbot speaking with a job candidate before his interview, propping him up and encouraging him – as, well, an AI girlfriend would. The AI featured in the clips, Ars Technica observed, was “disarmingly lifelike,” and willing “to laugh at your jokes and your dumb hat.”

But you might be surprised to learn that a previous generation of chatbots inspired Spike Jonze, the director and screenwriter of “Her,” to write the screenplay in the first place. Nearly a decade before the film’s release, Jonze had interacted with a version of the ALICE chatbot, which was one of the first chatbots to have a defined personality – in ALICE’s case, that of a young woman.

The ALICE chatbot won the Loebner Prize three times, which was awarded annually until 2019 to the AI software that came closest to passing the Turing Test, long seen as a threshold for determining whether artificial intelligence has become indistinguishable from human intelligence.

The sci-fi feedback loop has no expiration date. AI’s ability to form relationships with humans is a theme that continues to be explored in fiction and real life.

A few years after “Her,” “Blade Runner 2049” featured a virtual girlfriend, Joi, with a holographic body. Well before the latest drama with OpenAI, companies had started developing and pitching virtual girlfriends, a process that will no doubt continue. As science fiction writer and social media critic Cory Doctorow wrote in 2017, “Science fiction does something better than predict the future: It influences it.”

#science fiction #sci fi movies #artificial intelligence #metaverse #isaac asimov #arthur c clarke #hg wells #open ai #technology #technopolitics #blade runner #blade runner 2049 #Youtube

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e-carlease · 30 days ago

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The Stellantis group are busy at the moment launching new electric cars left, right and centre, the conglomerate are aiming to be the brand of choice for UK customers. The Italian Fiat group, who are also part of this brand association, are launching their latest SUV in the cost-effective category. The new Grande Panda is coming 2025 and with prices of around £22,000 this will consist of the Red and La Prima range.

But is the Fiat a good EV? This has a usable battery of 43.8 kWh which offers 83 kW (111hp), top speeds of 82 mph and 0 - 62 times of 11.0 seconds. Real-world ranges suggest a combined 135 miles in colder weather with warmer temperatures to allow for 185 miles (on a full charge) - combined overall at 160 miles. The 7.4kW AC allows for 0-100% charging times of 7 hours with the 100 kW DC enabling 10-80% in 32 minutes. It has a 148 mpg equivalent, 361L cargo volume and towing capacity of 550kg (Braked and Unbraked). There is no heat pump on this EV. Bidirectional charging has not been confirmed.

For more information on the latest EV from Fiat, just get in touch with the e-car team.

#fiat #fiat grande panda #ev #electric car #EV #car lease #car leasing

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religion-is-a-mental-illness · 1 year ago

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FACTS AND STATISTICS ON DOMESTIC VIOLENCE AT-A-GLANCE

Spon.sored by the peer-reviewed journal Partner Abuse https://www.springerpub.com/partner-abuse.html

and the Association of Domestic Violence Intervention Providers https://domesticviolenceintervention.net/

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Facts and Statistics on Prevalence of Partner Abuse

Victimization

Overall, 22% of individuals assaulted by a partner at least once in their lifetime (23% for females and 19.3% for males)

Higher overall rates among dating students

Higher victimization for male than female high school students

Lifetime rates higher among women than men

Past year rates somewhat higher among men

Higher rates of intimate partner violence (IPV) among younger, dating populations “highlights the need for school-based IPV prevention and intervention efforts”

Perpetration

Overall, 25.3% of individuals have perpetrated IPV

Rates of female-perpetrated violence higher than male-perpetrated (28.3% vs. 21.6%)

Wide range in perpetration rates: 1.0% to 61.6% for males; 2.4% to 68.9% for women,

Range of findings due to variety of samples and operational definitions of PV

Emotional Abuse and Control

80% of individuals have perpetrated emotional abuse

Emotional abuse categorized as either expressive (in response to a provocation) or coercive (intended to monitor, control and/or threaten)

Across studies, 40% of women and 32% of men reported expressive abuse; 41% of women and 43% of men reported coercive abuse

According to national samples, 0.2% of men and 4.5% of women have been forced to have sexual intercourse by a partner

4.1% to 8% of women and 0.5% to 2% of men report at least one incident of stalking during their lifetime

Intimate stalkers comprise somewhere between one-third and one half of all stalkers.

Within studies of stalking and obsessive behaviors, gender differences are much less when all types of obsessive pursuit behaviors are considered, but more skewed toward female victims when the focus is on physical stalking

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Facts and Statistics on Context

Bi-directional vs. Uni-directional

Among large population samples, 57.9% of IPV reported was bi-directional, 42% unidirectional; 13.8% of the unidirectional violence was male to female (MFPV), 28.3% was female to male (FMPV)

Among school and college samples, percentage of bidirectional violence was 51.9%; 16.2% was MFPV and 31.9% was FMPV

Among respondents reporting IPV in legal or female-oriented clinical/treatment seeking samples not associated with the military, 72.3% was bi-directional; 13.3% was MFPV, 14.4% was FMPV

Within military and male treatment samples, only 39% of IPV was bi-directional; 43.4% was MFPV and 17.3% FMPV

Unweighted rates: bidirectional rates ranged from 49.2% (legal/female treatment) to 69.7% (legal/male treatment)

Extent of bi-directionality in IPV comparable between heterosexual and LGBT populations

50.9% of IPV among Whites bilateral; 49% among Latinos; 61.8% among African-Americans

Motivation

Male and female IPV perpetrated from similar motives – primarily to get back at a partner for emotionally hurting them, because of stress or jealousy, to express anger and other feelings that they could not put into words or communicate, and to get their partner’s attention.

Eight studies directly compared men and women in the power/control motive and subjected their findings to statistical analyses. Three reported no significant gender differences and one had mixed findings. One paper found that women were more motivated to perpetrate violence as a result of power/control than were men, and three found that men were more motivated; however, gender differences were weak

Of the ten papers containing gender-specific statistical analyses, five indicated that women were significantly more likely to report self-defense as a motive for perpetration than men. Four papers did not find statistically significant gender differences, and one paper reported that men were more likely to report this motive than women. Authors point out that it might be particularly difficult for highly masculine males to admit to perpetrating violence in self-defense, as this admission implies vulnerability.

Self-defense was endorsed in most samples by only a minority of respondents, male and female. For non-perpetrator samples, the rates of self-defense reported by men ranged from 0% to 21%, and for women the range was 5% to 35%. The highest rates of reported self-defense motives (50% for men, 65.4% for women) came from samples of perpetrators, who may have reasons to overestimate this motive.

None of the studies reported that anger/retaliation was significantly more of a motive for men than women’s violence; instead, two papers indicated that anger was more likely to be a motive for women’s violence as compared to men.

Jealousy/partner cheating seems to be a motive to perpetrate violence for both men and women.

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Facts and Statistics on Risk Factors

Demographic risk factors predictive of IPV: younger age, low income/unemployment, minority group membership

Low to moderate correlations between childhood-of-origin exposure to abuse and IPV

Protective factors against dating violence: Positive, involved parenting during adolescence, encouragement of nonviolent behavior; supportive peers

Negative peer involvement predictive of teen dating violence

Conduct disorder/anti-social personality risk factors for IPV

Weak association between depression and IPV, strongest for women

Weak association overall between alcohol and IPV, but stronger association for drug use

Alcohol use more strongly associated with female-perpetrated than male-perpetrated IPV

Married couples at lower risk than dating couples; separated women the most vulnerable

Low relationship satisfaction and high conflict predictive of IPV, especially high conflict

With few exception, IPV risk factors the same for men and women

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Facts and Statistics on Impact on Victims, Children and Families

Impact on Partners

Victims of physical abuse experience more physical injuries, poorer physical functioning and health outcomes, higher rates of psychological symptoms and disorders, and poorer cognitive functioning compared to non-victims. These findings were consistent regardless of the nature of the sample, and, with some exceptions were generally greater for female victims compared to male victims.

Physical abuse significantly decreases female victims’ psychological well-being, increases the probability of suffering from depression, anxiety, post-traumatic stress disorder (PTSD) and substance abuse; and victimized women more likely to report visits to mental health professionals and to take medications including painkillers and tranquilizers.

Few studies have examined the consequences of physical victimization in men, and the studies that have been conducted have focused primarily on sex differences in injury rates.

When severe aggression has been perpetrated (e.g., punching, kicking, using a weapon), rates of injury are much higher among female victims than male victims, and those injuries are more likely to be life-threatening and require a visit to an emergency room or hospital. However, when mild-to-moderate aggression is perpetrated (e.g., shoving, pushing, slapping), men and women tend to report similar rates of injury.

Physically abused women have been found to engage in poorer health behaviors and risky sexual behaviors. They are more likely to miss work, have fewer social and emotional support networks are also less likely to be able to take care of their children and perform household duties.

Similarly, psychological victimization among women is significantly associated with poorer occupational functioning and social functioning.

Psychological victimization is strongly associated with symptoms of depression and suicidal ideation, anxiety, self-reported fear and increased perceived stress, insomnia and poor self-esteem

Psychological victimization is at least as strongly related as physical victimization to depression, PTSD, and alcohol use as is physical victimization, and effects of psychological victimization remain even after accounting for the effects of physical victimization.

Because research on the psychological consequences of abuse on male victims is very limited and has yielded mixed findings (some studies find comparable effects of psychological abuse across gender, while others do not) it is premature to draw any firm conclusions about this issue.

Effects of Partner Violence and Conflict on Children

Significant correlation between witnessing mutual PV and both internalizing (e.g., anxiety, depression) and externalizing outcomes (e.g., school problems, aggression) for children and adolescents

Exposure to male-perpetrated PV: Worse outcomes in internalizing and externalizing problems, including higher rates of aggression toward family members and dating partners, compared to no exposure

Children and teens exposed to female-perpetrated PV significantly more likely to aggress against peers, family members and dating partners compared to those not so exposed

Results mixed regarding additive effect of exposure to PV and experiencing direct child abuse

Witnessing PV in childhood correlated with trauma symptoms and depression in adulthood

Child abuse correlated with family violence perpetration in adulthood

Children more impacted by exposure to conflict characterized by contempt, hostility and withdrawal compared to those characterized only by anger

Greater impact when topic discussed concerns the child (e.g., disagreements over child rearing, blaming the child)

High inter-parental conflict/emotional abuse leads to a decrease in parental sensitivity, warmth and consistent discipline; and an increase in harsh discipline and psychological control

Neurobiological and physical functioning mediate relationship between inter-parental conflict and negative child outcomes

Maternal behaviors somewhat more affected than paternal behaviors, but findings are equivocal, given difficulty in disaggregating male and female perpetrated conflict from couple level operationalizations

Greater effects found for mother-child relationships and child outcomes through the toddler years; greater effects found for father-child relationships and child outcomes during the school-age years

Family systems theory useful in understanding how discord in one part of the family can impact functioning in the family as a whole, even if it poses some methodological and explanatory challenges

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Facts and Statistics on Partner Abuse in Other Populations

Partner Abuse in Ethnic Minority and LGBT Populations

African-Americans: Older studies found higher rates of male-to-female partner violence (MFPV); recent studies have found higher rates of female-to-male partner violence (FMPV)

Psychological aggression reported at significantly higher rates than physical aggression

As with White populations, minor/moderate aggression far more prevalent among Black couples than severe aggression

In dating studies, no gender differences found in rates of physical or psychological victimization, but women reported higher rates of physical aggression than men

Latinos: Mutual and minor/moderate PV most prevalent, but not as much as psychological aggression

No gender differences for physical or psychological aggression, except among migrant farm workers where MFPV was highest

Asian Americans: The one general population study found percentage of mutual violence perpetration to be one-third of total

Overall rates of PV comparable across gender in large population, community and dating samples

Lowest rates found among Vietnamese, compared to respondents who identified as Filipino, Chinese or others of Asian descent

Native Americans: Only three studies found; women reported higher rates of victimization than men, and reported higher levels of injuries incurred

Risk factors for ethnic minority PV include: substance abuse, low SES, and violence exposure and victimization in childhood

LGBT populations: Higher overall rates compared to heterosexual populations

Inconsistent findings regarding PV differences between same-sex subgroups

Risk factors for LGBT groups include discrimination and internalized homophobia

Partner Abuse Worldwide

A total of 162 articles reporting on over 200 studies met the inclusion criteria and were summarized in the online tables for Asia, the Middle East, Africa, Latin America and the Caribbean, and Europe and the Caucasus.

A total of 40 articles (73 studies) in 49 countries contained data on both male and female IPV, with a total of 117 direct comparisons across gender for physical PV.

Rates of physical PV were higher for female perpetration /male victimization compared to male perpetration/female victimization, or were the same, in 73 of those comparisons, or 62%.

There were 54 comparisons made for psychological abuse including controlling behaviors and dominance, with higher rates found for female perpetration /male victimization, in 36 comparisons (67%).

Of the 19 direct comparisons made for sexual PV, rates were found to be higher for female perpetration /male victimization in 7comparisons (37%).

When only adult samples from large population and community surveys were considered, the overall percentage of partner abuse that was higher for female perpetration /male victimization compared to male perpetration/female victimization, or were the same, was found to be 44% for adult IPV, although in many comparisons, the differences were slight.

Studies reporting on female victimization only found the lowest rates for physical abuse victimization in a large population study in Georgia (2%, past year), and the highest in a community survey in Ethiopia (72.5% past year) On the higher end, rates of physical PV far exceed the average found in the United States.

The lowest rates of psychological victimization were found in large population study in Haiti (10.8% past year); highest was 98.7% in Bangkok, Thailand (past year).

Unlike physical IPV, the highest rates of psychological abuse throughout the world are about the same as those found in the United States (80%).

Rates of sexual abuse victimization differed widely across regions, with rates as low as 1% in Georgia (past year); highest rates were found in a study of secondary school students in Ethiopia (68%, lifetime)

Physical injuries were compared across gender in two studies. As expected, abused women were found to experience higher rates of physical injuries compared to men.

Far more frequently mentioned were the psychological and behavioral effects of abuse, and these included PTSD symptomology, stress, depression, irritability, feelings of shame and guilt, poor self-esteem, flashbacks, sexual dissatisfaction and unwanted sexual behavior, changes in eating behavior, and aggression.

Two studies compared mental health symptoms across gender. In Botswana, women were found to evidence significantly more of these than men; whereas in a clinical study in Pakistan male and female IPV victims suffered equally (60% of men and women reported depression, 67% anxiety.)

A variety of health-related outcomes were also found to be associated with IPV victimization, including overall poor physical health, more long-term illnesses, having to take a larger number of prescribed drugs, STDs, and disturbed sleeping patterns. Abused mothers experienced poorer reproductive health, respiratory infections, induced abortion and complications during pregnancy; and in a few studies their children were found to experience diarrhea, fever and prolonged coughing.

The most common risk factors found in this review of IPV in Asia, Africa, the Middle East, Latin America and Europe have also been found to be significant risk factors in the U.S. and other English-speaking industrialized nations.

Most often cited are the risk factors related to low income household income and victim/perpetrator unemployment, at 36. An almost equally high number of studies (35) reported victim’s low education level. Alcohol and substance abuse by the perpetrator was a risk factor in 26 studies. Family of origin abuse, whether directly experienced or witnessed, was cited in 18 studies. Victim’s younger age was also a major risk factor, mentioned in 17 studies, and perpetrator’s low education level was mentioned in 16.

In contrast to the U.S., there is a much higher tolerance by both men and women for IPV in other parts of the world, with rates of approval depending on the country and the type of justification.

Regression analyses indicated that a country’s level of human development (as measured by HDI) was not a significant predictor of male or female physical partner abuse perpetration.

Additional regression analyses indicated that a nation’s gender inequality level, as measured by the Gender Inequality Index (GII), was not predictive of either male or female perpetrated physical partner abuse or female-only victimization in studies conducted with general population or community samples.

Separate regression analyses on data from the IDVS with dating samples indicate that higher gender inequality levels significantly predict higher prevalence of male and female physical partner abuse perpetration. GII level explained the variance for 17% of male partner abuse and 19% of female partner abuse perpetration.

A final analysis examined the association between dominance by one partner and partner violence perpetrated against a partner in dating samples using data from the IDVS. Male dominance scores were not found to be predictive of male partner violence perpetration; however, female dominance scores explained 47% of the variance of female partner violence perpetration.

---

Facts and Statistics on The Role of Law Enforcement and the Criminal Justice System

The Crime Control Effects of Criminal Sanctions

Possible causal mechanisms for the effectiveness of arrest and prosecution: fear of sanctions and victim empowerment; however, because none of the reviewed studies adequately measure such mechanisms, review assumes a general crime control effect that is neutral about causal mechanisms

“Based upon the analyses and conclusions produced by these studies, we find that the most frequent outcome reported is that sanctions that follow an arrest for IPV have no effect on the prevalence of subsequent offending. Among the minority of reported analyses that do report a statistically significant effect, two-thirds of the published findings show sanctions are associated with reductions in repeat offending and one third show sanctions are associated with increased repeat offending.”

Wide range of recidivism from 3.1% to 65.5% , due to high variability in measures of repeat offending (e.g., follow-up time frame)

Studies unclear about then exact nature of the sentence imposed, and what constitutes a “prosecution” or “conviction”

Diversity of analytic methods hinder analysis of effect sizes

Sample selection bias: None of the studies address this issue; for instance, if a small number of low-risk cases are prosecuted, prosecuted offenders are more likely to re-offend compared to those not prosecuted, because of the selection process

Missing data: Often leads to cases being dropped from a study, which in turns creates sample bias

Gender and Racial/Ethnic Differences in Criminal Justice Decision Making

Female arrests affected by high SES, presence of weapons and witnesses

Women more likely than men to be cited rather than be taken into custody, but the gender discrepancy is less when a decision is made on whether to file charges as misdemeanors or felonies

Men are more likely than women to be convicted and to be given harsher sentences

“Males were consistently treated more severely at every stage of the prosecution process, particularly regarding the decision to prosecute, even when controlling for other variables (e.g., the presence of physical injuries) and when examined under different conditions.”

No conclusive evidence of discrimination against ethnic minority groups in either arrest, prosecution and sentencing

Dual arrests were more likely in same-sex couples compared to heterosexual couples, perhaps due to incorrect assumption by police that same-sex couples more likely to engage in mutual violence.

Protective orders far more likely to be granted, and with more restrictions to women than to men (particularly in cases involving less severe abuse histories)

Mock juries more likely to assign blame responsibility to male perpetrators in contrast to female perpetrators, even when presented with identical scenarios

Effectiveness, Victim Safety, Characteristics and Enforcement of Protective Orders

A large percentage of women who are issued protective orders (POs) tend to be unemployed or under-employed as income ranged between $10,000 to $15,000, and almost 50% of women are financially dependent on their partners.

At least half of women obtaining POs are married, and married women are more likely to stay with their abusers and be pregnant.

Women who are issued POs tend to have more mental health issues (i.e., depression, PTSD) and rural women tend to experience more abuse and mental health issues than urban women

Only a few studies have examined characteristics of men seeking a PO

“Effectiveness” defined as violations of protective orders (POs) and/or re-victimization

Some studies have found POs to reduce violence against victims, with an almost 80% reduction in violence reported to police

Victims report feeling safer and having greater psychological well-being after obtaining a protective order; still, POs violated at a rate of between 44% to 70%

Nearly 60% of women who had secured a PO reported to have subsequently been stalked

Severity of criminal charges on the offender, as well as previous violations, best predictors of new PO violations

Although there is no significant difference in the amount of abuse suffered by married and unmarried victims, married victims less likely to seek final protective orders, perhaps because they are more likely to be re-victimized

Women granted POs at significantly higher rates than men, especially in cases involving lower level violence

No gender differences in the enforcement of POs, and no differences in rates of recidivism

---

Facts and Statistics on Assessment and Treatment

Risk Assessment

Little agreement in the literature with regard to the most appropriate approach (actuarial, structured clinical judgment) nor which specific measure has the strongest empirical validation behind it, leaving clinicians and policy makers with little clear guidance

Review yielded studies reporting on the validity and reliability of eight IPV specific actuarial instruments and three general actuarial risk assessment measures.

Range of area under the curve (AUC) values reported for the validity of the Ontario Domestic Assault Risk Assessment (ODARA) predicting recidivism was good to excellent (0.64 – 0.77)

The single study that reported on the Domestic Violence Risk Appraisal Guide (DVRAG) reported an AUC = 0.70 (p < .001). The inter-rater reliability for both instruments was excellent

The Domestic Violence Screening Inventory (DVSI) and Domestic Violence Screening Inventory – Revised (DVSI-R) were found to be good predictors of new family violence incidents and IPV recurrence (AUC range 0.61 – 0.71)

Three studies examined the Psychopathy Checklist – Revised (PCL-R) and Violence Risk Appraisal Guide (VRAG), neither of which are IPV specific, reporting AUCs ranging from 0.66 – 0.71 and 0.67 – 0.75, respectively.

The Level of Service Inventory – Revised (LSI-R) and Level of Service Inventory – Ontario Revision (LSI-OR) were discussed in four articles, reporting two AUC values of 0.50 and 0.73, both of which were predicting IPV recidivism

Two structured professional judgment instruments were included in the review, the Spousal Assault Risk Assessment guide (SARA) and the Brief Spousal Assault Form for the Evaluation of Risk (B-SAFER. The SARA research reports nine AUCs ranging from 0.52-0.65. The interrater reliability (IRR) for the SARA was excellent for total scores, good for the summary risk ratings, and poor for the critical items. Although neither of the articles examining the B-SAFER reported the predictive validity of the instrument one did report the IRR based on 12 cases with a mean interclass coefficient (ICC) of 0.57.

The Danger Assessment (DA) has the largest body of literature behind it, but there are limitations in the research that inhibit a clear determination of the psychometric properties of the measure, thus far. Victim appraisals of the risk of future IPV show some evidence of predictive accuracy; however, further research is needed to determine the best means with which to collect the victim’s reports and determining the conditions (e.g., stalking) and characteristics of victims that should be considered (e.g., PTSD, substance use).

Overall, the literature reveals moderate postdictive/predictive accuracy across measures with little evidence to support one as being highly superior to others, particularly given the heterogeneity of perpetrators and victims, study limitations, and the small body of empirical literature to date.

Several themes emerged when we examined the synthesized literature: (1) There is a relatively small body of empirical evidence evaluating IPV violence risk assessment measures. (2) The need for continued advancements in the methodological rigor of the research including prospective studies, research that compares multiple measures within single studies, and research that uses large samples and appropriate outcome indicators. In terms of clinical implications, the review demonstrates the considerable promise of several IPV risk assessment measures but generally reveals modest postdictive/predictive accuracy for most measures.

Victim appraisals, while the research has a considerable ways to go, were found to have clinical relevance. However, preliminary evidence suggests that clinicians may want to be particularly cautious when working with some sub-groups when taking into account victims’ perceptions (e.g., PTSD symptoms, substance use, stalking and severe abuse experienced) and supplement the woman’s input with an additional structured assessment.

When clinicians and administrators are faced with the challenge of determining which measure(s) to use to assess risk of IPV they should carefully consider the purpose of the assessment (Heilbrun, 2009). Assessors also should take into account the context, setting, and resources when evaluating which measure best suits their needs.

Consideration must be given to the characteristics of the population to be assessed (e.g., age, gender, ethnicity, socio-economic status) and the extent to which a measure has been cross-validated in similar samples is required

Assessors need to be clear about the outcome of concern (verbal abuse, physical abuse, severe violence, stalking, femicide) and knowledgeable about relevant base rates

Based on the available literature, we are also unable to provide guidance on the clinical relevance and utility of these instruments with female perpetrators, male victims, and in same-sex relationships due to the lack of studies using relevant populations.

Effectiveness of Primary Prevention Efforts

All studies incorporated a curriculum-based intervention, with the primary goal of lowering rates of PV

Schools provided the setting for two-thirds of the interventions; the rest were conducted in community settings

Of the five most methodologically-sound school based studies, only one, the Safe Dates Program, found a clear-cut positive outcome on PV behavior (emotional abuse, mild physical abuse and sexual coercion)

In contrast, each of the five most methodologically-sound community-based studies was deemed effective in reducing PV; among them were two interventions targeting couples and one family-based intervention involving parents and their adolescent children

Although outcomes are mixed, especially for the school-based studies, and no studies were replicated, the authors suggest that “because prevention is generally cost-effective, programming is badly needed to prevent IPV before it begins.”

Effectiveness of Intervention Programs for Perpetrators and Victims

Authors reviewed studies all utilized either a randomized or quasi-experimental design

Mixed evidence for the effectiveness of perpetrator interventions

Evidence that group or couples format can be effective, but many studies flawed

More promising results for programs with alternative content (e.g., programs that encourage a strong therapist-client relationship and group cohesion, use some form of Motivational Interviewing technique)

Inconsistent effects for brief interventions

Structured interventions found to reduce rates of re-victimization compared to no-treatment controls when they include supportive advocacy

Cognitive-behavioral treatment (CBT) most effective in reducing the deleterious effects of PV on victims and enhancing their emotional functioning

Little evidence to indicate the superiority of one type of intervention over another. Thus, there is no empirical justification for agencies, state organizations, judges, mental health professionals, or others involved in improving the lives of those impacted by IPV to limit the type of services offered to clients, or to restrict the theoretical and ideological underpinnings of such methods.

Despite mentally-ill, fanatical ideologues claiming otherwise, domestic violence is not gendered. And they have literally no evidence to the contrary.

#domestic violence #intimate partner violence #male victims of abuse #male victims of domestic violence #male victims of domestic abuse #domestic abuse #violent women #radfems #Karen Ingala Smith #mental illness #religion is a mental illness

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droctaviolovecraft · 7 months ago

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ANM-420: Vigilant Eye

http://mothrainstitution.wikidot.com/anm-420

**ANM №: ANM-420**

**Lead Researcher: Dr. Octavio**

**Identification: Vigilant Eye**

**Danger Level: Darlig 🔴 (Cognitive)**

**Containment Difficulty: 4 (Very difficult)**

**Type of Anomaly: ???**

**Containment:** The entity must be confined in a specially designed room within the heavy zone, devoid of windows and with walls coated with anti-reflective material to mitigate any form of visual reflection or projection. The environment is monitored 24/7 by infrared cameras, with entry restricted to authorized personnel with level 4 access.

**Description:** Designated as ANM-420, the "Vigilant Eye" is a unique visual entity, consisting of a colossal eye surrounded by complex, intricate patterns that appear to be in constant motion. The eye is highly sensitive and consciously reacts to human presence, fixing its gaze on individuals present. The surrounding patterns induce altered states of consciousness in observers, resulting in intense visual hallucinations and disorientation. This phenomenon reveals the anomaly's unique ability to influence human perception in a remarkable way.

The central iris of ANM-420 displays a mutable coloration, shifting through a wide range of hues, including unconventional colors. Researchers have reported observing geometric patterns and symbols that seem to transcend conventional human cognitive understanding. The eye's responsiveness to environmental stimuli is notable. In perceived risk situations, the entity exhibits a defensive reaction, manifesting more intense light patterns and more frenetic movements. This response suggests a primitive intelligence and an adaptation to its current state of confinement.

The cognitive effects induced by the visual patterns around the eye are highly variable, ranging from surreal hallucinations to perceived temporal distortions. The anomaly appears to influence the human mind subjectively, adapting to the unique experiences of each observer. These findings highlight the need for controlled observation protocols to better understand the limits and potential risks associated with it.

Prolonged interaction with ANM-420 raises questions about the possibility of developing bidirectional communication with the entity, exploring its understanding of the environment and its responses to specific stimuli. However, such experiments would require in-depth ethical considerations and a more comprehensive understanding of the long-term implications for the mental health of those involved.

Strategic containment, centered on the absence of external visual stimuli, aims to control the entity's effects. The incorporation of infrared cameras underscores the importance of constantly monitoring the anomaly, while restricting access to individuals with level 4 authorization highlights the seriousness of the cognitive threat posed by the Vigilant Eye. Continued study of ANM-420 is essential for a deeper understanding of its properties and potential applications in anomalous research, while emphasizing the imperative need for rigorous containment measures to safeguard the safety of the research team and potential interactions with the anomaly.

#mothra institution #project #scp #scp foundation #site #writing #anomaly #art

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wheel-of-fandoms · 1 year ago

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It’s a biological fact that fish do indeed change their sex to keep the male/female ratio balanced in their school population.

Some fish do exhibit bidirectional sequential hermaphroditism. From what I found, it seems unclear just how much this occurs in nature, though it does occur at least in some cases there as well as in captivity. I didn't see any sources specifically claiming that it was used to keep an even sex ratio (but I only did a few brief searches and skimmed a few papers) Fish do all kinds of different strategies when it comes to sex. Some do an age based M -> F. Some do age based F -> M. Some can go back and forth depending on environmental factors. Some depend on local social structure, like some clownfish were there is one big female and her several smaller males, if she dies, one of the males gets bigger and becomes female.

Most fish are just male or just female their whole life more like what we mammals are used to.

I don't know offhand of any fish that are simultaneously male and female (producing viable sperm and eggs in the same general period of time), but maybe there are and I just haven't heard of them. Ah here is at least one case: "Evidence for Hermaphroditism in the Squalius alburnoides Allopolyploid Fish Complex"

Totally fair to base merfolk off of the idea of balancing the sex ratio, BTW, not saying otherwise! But want to be clear that that exact thing may not be known in fish, and if present, is part of a great variety of fish sex strategies.

Some of the interesting papers I saw in my brief searches: Hermaphroditism in fish: incidence, distribution and associations with abiotic environmental factors

Bidirectional Sex Change in Seven Species of Priolepis (Actinopterygii: Gobiidae)

Bidirectional Sex Change in Marine Fishes

and some other info:

https://en.wikipedia.org/wiki/Sequential_hermaphroditism

https://evolution.berkeley.edu/fisheye-view-tree-of-life/gender-bending-fish/

https://karger.com/sxd/article/10/5-6/223/296444/Bending-Genders-The-Biology-of-Natural-Sex-Change

tired: mermaids are all women

wired: much like elves, merfolk are mistaken by sailors for being all women because they have long hair and are very pretty

#science #fish #biological sex #merfolk #sequential hermaphroditism #speculative biology

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portlanddental · 29 days ago

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Periodontal disease, also known as gum disease, is a common yet often overlooked condition that affects the tissues surrounding your teeth. While many people focus on the impact periodontal disease has on their oral health, research has shown that this condition can also have significant implications for your overall well-being. In fact, gum disease has been linked to a variety of serious health issues, ranging from heart disease to diabetes and even Alzheimer’s disease. Understanding the connection between periodontal disease and overall health is crucial not only for your dental hygiene but for your general health as well.

What is Periodontal Disease?

Periodontal disease is an infection of the tissues that hold your teeth in place. It typically starts as gingivitis, a mild form of gum disease that causes redness, swelling, and bleeding of the gums. If left untreated, gingivitis can progress to periodontitis, a more severe form of gum disease where the infection spreads deeper into the tissues and can cause tooth loss.

The primary causes of periodontal disease include poor oral hygiene, smoking, genetics, certain medications, and conditions that affect the immune system. Factors like age, poor nutrition, and stress can also contribute to the development of periodontal disease. Regular dental checkups and good oral hygiene practices, such as brushing and flossing, are essential to preventing gum disease.

The Link Between Periodontal Disease and Heart Disease

One of the most significant connections between periodontal disease and overall health is the increased risk of heart disease. Studies have shown that people with gum disease are more likely to suffer from heart disease and other cardiovascular issues.

The bacteria from infected gums may enter the bloodstream, leading to an increased inflammatory response in the body. Chronic inflammation is a known risk factor for atherosclerosis (narrowing of the arteries), which can contribute to heart attacks, strokes, and other cardiovascular problems.

Diabetes and Periodontal Disease: A Two-Way Street

Diabetes and periodontal disease have a complex, bidirectional relationship. People with diabetes are more susceptible to gum disease because high blood sugar levels can weaken the immune system and make it harder for the body to fight infections, including gum infections.

The inflammation associated with gum disease can lead to higher blood sugar levels, increasing the risk of complications for people with diabetes. Research has shown that treating periodontal disease can improve blood sugar control in people with diabetes, further emphasizing the importance of maintaining good oral health in managing this chronic condition...Read More

#gum disease #periodontal treatment #periodontal disease

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fabzen123 · 1 month ago

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Socket IO Tester for Mobile Applications: Challenges and Solutions

Introduction

Socket.IO is widely used for enabling real-time, bidirectional communication in web and mobile applications. However, testing Socket.IO in mobile environments poses unique challenges due to the diverse nature of mobile devices and network conditions. Ensuring reliable performance and seamless user experiences across various mobile platforms requires effective testing strategies. In this article, we will explore the key challenges associated with Socket.IO testing for mobile applications and provide practical solutions to address these issues.

Challenges in Testing Socket.IO for Mobile Applications

1. Network Variability: Mobile applications often operate in environments with varying network conditions, including fluctuating signal strengths and switching between different types of networks (Wi-Fi, 4G, 5G). These variations can impact the stability and performance of Socket.IO connections.

2. Resource Constraints: Mobile devices have limited CPU, memory, and battery resources compared to desktop computers. Socket.IO test connections can be resource-intensive, potentially leading to performance degradation or increased battery consumption if not managed properly.

3. Latency and Bandwidth: Mobile networks generally have higher latency and lower bandwidth compared to wired connections. Testing must account for these limitations to ensure that the Socket.IO implementation performs optimally under real-world mobile network conditions.

4. Background App Activity: Mobile operating systems often put apps into a background state to conserve resources. This can disrupt Socket.IO connections, making it challenging to maintain a consistent real-time communication channel.

5. Device Fragmentation: The wide range of mobile devices with different operating systems, screen sizes, and hardware capabilities adds complexity to testing. Ensuring compatibility and consistent performance across all these devices requires extensive testing.

Solutions for Effective Socket.IO Testing on Mobile

1. Simulating Network Conditions: Use network simulation tools to replicate various mobile network scenarios, such as poor signal strength, intermittent connectivity, and varying latencies. Tools like Network Link Conditioner (for macOS) or Charles Proxy can help simulate these conditions and assess how the Socket.IO implementation handles them.

```shell

Example command to simulate network conditions using Charles Proxy

charles-proxy --simulate network -r "Slow 3G"

```

2. Optimizing Resource Usage: Implement techniques to minimize the resource impact of Socket.IO connections on mobile devices. This includes optimizing data payloads, reducing the frequency of updates, and using efficient data formats like JSON or Protocol Buffers.

```javascript

// Example of optimizing data payload

const sendMessage = (socket, message) => {

const optimizedMessage = JSON.stringify(message); // Efficient data format

socket.emit('message', optimizedMessage);

};

```

3. Handling Background State: Design your application to manage online Socket.IO tester connections when the app goes into the background. Implement mechanisms such as automatic reconnection strategies, background services, or reduced functionality while the app is not active.

```javascript

// Example of handling background state

socket.on('disconnect', () => {

if (document.hidden) {

// Reconnect or handle background state

setTimeout(() => {

socket.connect();

}, 5000);

}

});

```

4. Automated Testing: Utilize automated testing tools and frameworks that support mobile environments. Tools like Appium, Detox, or BrowserStack allow you to automate Socket.IO tests on various mobile devices and operating systems, ensuring broad coverage and consistent results.

```javascript

// Example of using Appium for automated Socket.IO testing

const { remote } = require('webdriverio');

(async () => {

const driver = await remote({

capabilities: {

platformName: 'Android',

deviceName: 'Pixel 3',

app: '/path/to/your/app.apk'

}

});

await driver.execute('mobile: performEditorAction', { action: 'sendMessage' });

// Implement further testing logic here

})();

```

5. Performance Monitoring: Implement real-time monitoring to track Socket.IO performance on mobile devices. Use tools like Firebase Performance Monitoring, New Relic, or custom monitoring solutions to gain insights into connection stability, latency, and throughput.

```javascript

// Example of integrating Firebase Performance Monitoring

import { getPerformance } from 'firebase/performance';

const perf = getPerformance(app);

// Monitor performance data

```

6. Extensive Device Testing: Test your Socket.IO implementation across a wide range of mobile devices and operating systems. Use emulators and cloud-based device farms to replicate different environments and identify device-specific issues.

7. Fallback Mechanisms: Implement fallback mechanisms for scenarios where Socket.IO connections fail or experience issues. This might include switching to alternative communication methods, such as HTTP polling, to ensure that the app remains functional.

```javascript

// Example of fallback to HTTP polling

socket.on('error', () => {

fetch('https://yourserver.com/polling-endpoint')

.then(response => response.json())

.then(data => {

// Handle data received via polling

});

```

Conclusion

Testing Socket.IO for mobile applications involves addressing a range of challenges related to network variability, resource constraints, and device fragmentation. By employing strategies such as simulating network conditions, optimizing resource usage, handling background states, leveraging automated testing tools, and implementing robust monitoring, developers can effectively ensure the reliability and performance of their real-time applications. Comprehensive testing across diverse devices and scenarios will help in delivering a seamless and dependable user experience, making Socket.IO tester online a powerful tool for real-time communication in mobile applications.

0 notes

wovetherapy · 1 month ago

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Phone Addiction and Mental Health

Google trends have shown increases in searches for “phone addiction” and “social media addiction” since 2004 (AddictionCenter). This global and societal issue has been seriously exacerbated and continuously enmeshed with mental health issues by the COVID-19 pandemic and its aftermath, as options to connect with others became predominantly virtual and people were forced into and now out of isolation. Colloquially termed “nomophobia” (the fear of being without mobile device), teens are particularly more susceptible to the algorithm traps set by tech companies as their brains are not yet fully developed. Although there are no specific metrics to diagnose phone addiction, it is recognized as a very real issue with very real mental health consequences.

What contributes to phone addiction?

Brain chemicals

Dopamine is the brain’s major reward and pleasure neurotransmitter. It is a common misconception that dopamine makes you happy - rather, the hormone actually reinforces behaviorsthat make you happy. GABA is also a neurotransmitter that strongly interacts with dopamine and influences dopamine activity in the brain. Main functions of these interacting neurotransmitters include reward system and cognitive flexibility, like task-switching performance. Smartphones and apps are designed to be addictive in a way that alters reward circuits in the brain chemically. After the rush of feel-good hormones, a dip occurs which worsens with addiction and continued binging. Chronic phone overuse can have lasting impacts on the brain’s chemical balance and reward circuits.

Lack of boundaries

Struggling to identify and uphold one’s boundaries can make it easier to become addicted to one’s phone. Others may begin to expect a constant online presence, whether with work, friends, family, or one’s own expectations of themself. One may feel a professional, social, or justice obligation to be responsive and constantly accessible or informed and aware of upcoming events or recent happenings. It may feel particularly urgent at this time to consume and share media in a way that aligns with one’s values. However, lack of boundaries can lead to a detrimental relationship with one’s phone and mental health.

Impulse-control problems

The ease and instant gratification of smartphone usage can exacerbate impulse-control problems such as virtual relationships, compulsive web surfing, cybersex addiction, and online compulsions (i.e., gaming, gambling, stock trading, online shopping, bidding on auction sites, etc.). This unlimited access can provide an outlet or escape from certain real life difficulties while creating a different set of difficult-to-escape real life issues. For example, online friendships can provide a bubble for relationships where conflict and messy demands of real-world relationships do not need to exist. Although this may relieve people of social anxieties and awkwardness, it may also increase real-life intimacy issues and prevent people from learning how to navigate various social interactions. Online compulsions may also contribute to various life stressors like relationship stress, financial stress, and job-related problems which may feed into the cycle of smartphone addiction and feeling the need to escape reality.

Mental health impacts and interactions

Anxiety, depression, emotional stability, and stress

Low emotional stability, chronic stress, anxiety, and depression have all been positively associated with phone usage. One may lose track of time and neglect other activities or people in favor of phone usage, creating difficult and stressful situations in various aspects of life (e.g., school, work, interpersonal relationships, etc.) to consistently navigate and repair. Additionally, phone addiction typically comes with withdrawal symptoms, including anxiety and irritability as well as physical symptoms like sweating, shaking, and heart palpitations. It is important to recognize the bidirectional impacts of phone usage and mental health issues, creating a cycle of phone addiction and mental health struggles.

Relationship issues and loneliness

Phone addiction often contributes to isolation from social interactions in the form of less real-world interactions with friends, family, and peers, as well as less meaningful relationships and healthy connections and conversations. One may lose relationships as their time and attention is consumed via phone usage. It is stressful to feel the need to maintain constant online presence and availability as well as in-person relationships, and it may feel easier to let go of the latter - further exacerbating mental health struggles. Feelings of isolation, loneliness, depression, and anxiety are all highly interrelated and have been associated with increased risk of suicide and suicide rates among teenagers.

Low self-esteem

Phone addiction can severely impact one’s sense of self-esteem through relationship issues and comparison on social media. Distortion of reality and unrealistic standards from comparisons to what is portrayed via social media can lead to feelings of inadequacy, insecurity, worthlessness, stress, anxiety, and depression. Constant phone usage can also lead to negative thinking, loneliness, frustration, irritability, and fatigue.

Poor sleep

It is now more commonly known that the light emitted by a cell phone screen can interfere with natural melatonin production, which regulates the sleep-wake cycle. This can negatively affect sleep quality, ability to fall asleep or stay asleep throughout the night, and feelings of daytime fatigue. Sleep is an essential part of one’s mental health and wellbeing.

Creativity blocks

Smartphones and a constant online presence interrupts humans’ ability to daydream and think independently. It blocks concentration and prevents people from reaching their flow state. Relevant to low self-esteem that often accompanies comparison, creatives may suffer from the constant influx of content which may feel suffocating towards one’s own ideas and perceived abilities. Time spent on one’s phone may contradict with one’s creative pursuits as well as the physical time and space often required to create in a meaningful and fulfilling way.

Warning sign examples of phone addiction

Isolation from family and friends

Concealing your smartphone use

Trouble completing tasks at work or home due to phone usage

Feeling of dread, anxiety, or panic if you leave your smartphone at home

Phantom vibrations (i.e. thinking you receive a phone notification but there are no new messages or updates upon checking)

Experiencing withdrawal symptoms (e.g., irritability, sweating, shaking, heart palpitations) when you try to cut back on smartphone use

Tips to changing your smartphone habits - whether “nomophobia” applies to you or if you are wanting to readjust your relationship with your smartphone, here are some ways to start making changes:

Be intentional and set your own boundaries - understand your smartphone usage and habits. Be thoughtful about when urges to use your phone occur, how you feel before reaching for your phone, and what you could be doing away from your phone. Be honest with what feels like necessary phone usage and what you could cut out. As a reminder, it does not help anyone if you cannot continue to show up in a meaningful way.

Learn to tolerate being bored and with your thoughts - it is okay to be bored at times. Sometimes the stimulus-free, slow passage of time can be essential in having necessary thoughts and thought processes and allowing your brain to form connections. Use the time to grow curiosity and introspection. Rediscover yourself. Build your coping skills and relaxation techniques.

Create distance between yourself and your phone/apps - turn off notifications when you can. Leave your phone in another room. Delete social media off your phone or take a “social media break”. You can still access it on other devices, but not having the app on your phone makes it less handy and adds an extra step to the process.

Seek support offline - strengthen your support network. Find people with similar interests and rediscover real-life interactions and connections. Meet with a mental health therapist in-person if possible, and have discussions on the real-life impacts of feeling out of control when it comes to phone usage. You are not alone!

#mental health #mental health counseling #individual counseling #stress #self care #trauma #mindfulness

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humancaremagazine · 2 months ago

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Understanding the Gut-brain Connection: How Your Microbiome Affects Your Mental Health?

The gut-brain connection has emerged as a fascinating area of research, revealing the intricate relationship between the gut microbiome and mental health. This article delves into the complex interplay between the gut and the brain, exploring how the composition of the microbiome influences mental well-being. From neurotransmitter production to immune system regulation, the article examines the various mechanisms through which gut health impacts mental health. Additionally, it explores practical strategies for optimizing gut health to support overall mental well-being.

The Gut-brain Axis: A Two-Way Communication System

The gut-brain axis represents a bidirectional communication system linking the central nervous system (CNS) with the gastrointestinal tract. This complex network involves a constant exchange of signals between the gut microbiota, the enteric nervous system (ENS), and the brain. These signals encompass neurotransmitters, hormones, immune molecules, and microbial metabolites, collectively influencing brain function, mood, and behavior.

Influence of the Microbiome on Neurotransmitter Production

The gut microbiome plays a crucial role in the production of neurotransmitters, and chemical messengers that regulate mood, cognition, and behavior. For example, certain gut bacteria are involved in the synthesis of serotonin, a neurotransmitter known for its role in mood regulation. Alterations in the composition of the microbiome can disrupt serotonin production, potentially contributing to mood disorders such as depression and anxiety.

Regulation of Immune Function and Inflammation

The gut microbiome also exerts a significant influence on immune function and inflammation, which are closely linked to mental health. Dysbiosis, or an imbalance in gut bacteria, can trigger immune dysregulation and chronic inflammation, both of which have been implicated in the pathogenesis of psychiatric disorders. Conversely, a diverse and balanced microbiome supports immune homeostasis, reducing the risk of inflammation-related mental health conditions.

Gut Microbiome and Stress Response

Emerging research suggests that the gut microbiome plays a role in modulating the body’s response to stress. Stress can disrupt the balance of gut bacteria, leading to dysbiosis and exacerbating symptoms of anxiety and depression. Conversely, interventions that promote a healthy microbiome, such as probiotics and dietary modifications, may help mitigate the effects of stress on mental health.

Practical Strategies for Optimizing Gut Health

Maintaining a healthy gut microbiome is essential for supporting overall mental well-being. Several lifestyle factors influence gut health, including diet, exercise, sleep, and stress management. Incorporating fiber-rich foods, fermented foods, and prebiotics into your diet can promote microbial diversity and resilience. Regular physical activity and adequate sleep also contribute to a healthy microbiome and improved mental health.

Probiotics and Prebiotics: Supporting Gut Health

Probiotics are live microorganisms that confer health benefits when consumed in adequate amounts. These beneficial bacteria can help restore microbial balance, enhance immune function, and improve mood. Prebiotics, on the other hand, are dietary fibers that serve as fuel for beneficial gut bacteria, promoting their growth and activity. Incorporating probiotic-rich foods such as yogurt, kefir, and sauerkraut, as well as prebiotic foods like garlic, onions, and bananas, can support gut health and mental well-being.

Harnessing the Power of Nutritional Psychiatry

Nutritional psychiatry is an emerging field that explores the relationship between diet and mental health. Research suggests that certain dietary patterns, such as the Mediterranean diet, rich in fruits, vegetables, whole grains, and healthy fats, are associated with a lower risk of depression and anxiety. Conversely, diets high in processed foods, sugar, and unhealthy fats have been linked to an increased risk of mental health disorders.

The gut microbiome plays a central role in mediating the effects of diet on mental health. Dietary components influence the composition and function of gut bacteria, which in turn impact neurotransmitter production, immune function, and inflammation. By adopting a diet that supports gut health, individuals can promote optimal brain function and reduce the risk of mental health disorders.

Lifestyle Interventions for Gut Health and Mental Well-being

In addition to diet, several lifestyle factors contribute to gut health and mental well-being. Regular physical activity has been shown to promote microbial diversity, reduce inflammation, and enhance mood. Exercise stimulates the release of endorphins, neurotransmitters that produce feelings of happiness and well-being. Incorporating regular exercise into your routine can have profound effects on both gut health and mental health.

Read More: https://humancaremagazine.com/understanding-the-gut-brain-connection-how-your-microbiome-affects-your-mental-health/

#HumanCaremagazine #Gut-brainConnection #Gut-brain

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epulse-health · 2 months ago

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Understanding the Gut-Brain Connection: How Your Diet Impacts Mental Health — Explore the Science of Nutrition and Mood

Introduction

In this article, we’ll explore the science behind the gut-brain connection, how food choices impact mood, and the practical steps you can take to improve your mental health through diet. From probiotics to fiber-rich foods and specific dietary patterns, we’ll provide actionable tips to support your journey toward mental clarity and emotional wellness.

1. What Is the Gut-Brain Connection?

The gut-brain connection refers to the bidirectional communication between the digestive tract and the brain. This relationship is complex, involving physical pathways, chemical messengers, and a unique ecosystem of microorganisms known as the gut microbiome. In short, our brains and guts are constantly “talking,” influencing each other’s functions. Through the vagus nerve and biochemical messengers, the gut can impact brain activity, affecting mood, cognitive function, and even how we respond to stress.

Key Functions of the Gut-Brain Axis

The gut-brain axis plays several roles in mental health:

Regulating Neurotransmitters: Certain gut bacteria produce or influence neurotransmitters like serotonin and dopamine, which help regulate mood.

Controlling Inflammation: A balanced gut can reduce inflammation, which is often linked to conditions like depression and anxiety.

Boosting Immunity: The gut microbiome supports immune functions that, when disrupted, can impact mental health.

A well-balanced gut leads to a balanced mind. Start prioritizing your gut health to help improve your mood and resilience to stress.

2. The Gut Microbiome: A Key Player in Mental Health

The gut microbiome consists of trillions of bacteria, fungi, and other microorganisms that perform essential functions in digestion and immunity. However, recent studies have shown that a healthy microbiome is just as critical for mental well-being.

How Your Microbiome Impacts Mental Health

Research highlights several ways the gut microbiome affects mental health:

Neurotransmitter Production: Around 90% of serotonin, often called the “happiness hormone,” is produced in the gut. Certain gut bacteria synthesize serotonin, influencing mood directly.

Stress Response Regulation: Gut bacteria regulate cortisol levels, the stress hormone, affecting mood stability and stress resilience.

Inflammation Reduction: A balanced microbiome reduces inflammation, while imbalances are linked to chronic inflammation, a factor in many mental health disorders.

When we think of mental health holistically, it becomes clear that a healthy gut microbiome is crucial for emotional stability and cognitive clarity.

3. How Diet Affects the Gut-Brain Connection

Our food choices directly impact the gut microbiome. Diets high in processed foods, refined sugars, and unhealthy fats can create an imbalance in gut bacteria, called dysbiosis, which has been associated with higher rates of depression and anxiety. On the other hand, a nutrient-dense, fiber-rich diet can nurture beneficial bacteria, leading to positive mental health outcomes.

Foods That Benefit the Gut-Brain Connection

Here are some foods scientifically shown to support a healthy gut and brain:

Probiotic-Rich Foods: Yogurt, kefir, sauerkraut, and kombucha contain live bacteria that benefit the gut.

Prebiotic Foods: High-fiber foods like bananas, garlic, onions, and asparagus feed good bacteria, promoting a balanced microbiome.

Omega-3 Fatty Acids: Found in fatty fish, walnuts, and flaxseeds, omega-3s have anti-inflammatory effects that support brain health.

Antioxidant-Rich Foods: Blueberries, dark chocolate, and leafy greens protect brain cells from oxidative stress.

Eating nutrient-dense foods benefits not only physical health but mental clarity and emotional well-being. Consider incorporating more gut-friendly foods into your diet for better mental health.

4. The Role of Probiotics and Prebiotics in Mental Wellness

Probiotics are beneficial bacteria that help balance the gut microbiome, while prebiotics are fibers that feed these bacteria. Together, they maintain a healthy gut environment, which in turn supports neurotransmitter production, mood regulation, and mental health.

Benefits of Probiotics and Prebiotics for Mental Health

Research has shown that consuming probiotics and prebiotics can:

Lower Anxiety and Depression Symptoms: Certain probiotic strains, such as Lactobacillus and Bifidobacterium, are linked to lower cortisol levels, reducing stress and anxiety.

Boost Cognitive Function: A healthy gut environment can enhance cognitive functions like memory, focus, and problem-solving.

Increase Emotional Resilience: A balanced gut microbiome can help with mood swings, irritability, and overall emotional regulation.

To support your mental wellness, try incorporating probiotic and prebiotic-rich foods into your daily diet.

5. The Science Behind Serotonin Production in the Gut

One of the most fascinating discoveries in gut-brain research is that approximately 90% of serotonin is produced in the gut, not the brain. Known as the “feel-good” neurotransmitter, serotonin is responsible for regulating mood, sleep, appetite, and cognitive functions.

How Diet Impacts Serotonin Production

Certain foods can help increase serotonin production:

Tryptophan-Rich Foods: Turkey, eggs, cheese, and tofu contain tryptophan, an amino acid essential for serotonin synthesis.

Complex Carbohydrates: Whole grains, sweet potatoes, and oats increase serotonin production by making tryptophan more available to the brain.

Fermented Foods: Probiotic-rich foods improve gut health, which in turn supports serotonin production.

To naturally boost serotonin levels, include foods high in tryptophan and complex carbohydrates in your diet for a balanced mood and improved mental wellness.

6. Common Diets and Their Effects on Mental Health

Different dietary patterns can either support or hinder mental health through the gut-brain axis. Here’s a look at some popular diets and how they affect mental wellness:

Mediterranean Diet: Known for its high intake of fruits, vegetables, whole grains, and healthy fats, the Mediterranean diet has been linked to reduced symptoms of depression. It’s rich in fiber, antioxidants, and anti-inflammatory properties that support both gut and brain health.

Ketogenic Diet: This low-carb, high-fat diet has shown promise for stabilizing mood by balancing blood sugar levels and reducing inflammation. However, it may not be suitable for everyone, so it’s important to consult a healthcare provider.

Whole-Food, Plant-Based Diet: This diet is packed with fiber, antioxidants, and a variety of nutrients that support gut health. Studies show it can reduce stress, improve mood, and protect against cognitive decline.

Interested in optimizing your mental health through diet? Consider exploring a Mediterranean or plant-based diet for a balanced gut and mind.

7. Tips for Maintaining a Gut-Healthy Diet for Mental Wellness

Transitioning to a gut-healthy diet doesn’t have to be difficult. Here are some simple, effective tips for getting started:

Include Fiber-Rich Foods Daily: Foods high in fiber, like beans, lentils, and whole grains, feed beneficial bacteria in the gut.

Limit Processed Foods: Reducing intake of processed foods, sugars, and unhealthy fats prevents dysbiosis and promotes a balanced gut microbiome.

Incorporate Fermented Foods: Yogurt, kimchi, and other fermented foods provide probiotics, supporting a healthy gut environment.

Stay Hydrated: Proper hydration is essential for digestion and gut health, so aim for 8–10 cups of water per day.

If you’re ready to improve your mood naturally, try implementing these small but impactful changes in your daily routine.

Conclusion

The gut-brain connection is a powerful reminder that mental health goes beyond the mind — it’s also rooted in our diet and gut health. By eating nutrient-dense, gut-friendly foods, we can nourish both body and brain, fostering better mood stability, cognitive clarity, and emotional resilience.

Take charge of your mental health by making conscious dietary choices. Prioritize gut health, and experience the profound benefits on your mind and mood.

FAQs

What is the gut-brain connection, and why is it important? The gut-brain connection is the communication between the gut and the brain, influencing mood and cognitive health. It’s crucial for maintaining mental well-being.

How does diet impact mental health? Diet affects gut health, which in turn influences neurotransmitter production and mood regulation, underscoring the connection between nutrition and mental wellness.

What are the best foods for supporting the gut-brain axis? Foods rich in probiotics, prebiotics, fiber, and omega-3 fatty acids are excellent for maintaining a healthy gut-brain connection.

Can probiotics help with anxiety? Yes, certain probiotics can reduce cortisol levels and balance neurotransmitter production, which helps alleviate anxiety symptoms.

What diet is best for mental health? The Mediterranean diet, with its high fiber and nutrient content, is widely recognized for supporting mental health through the gut-brain axis.

#healthy food #food #healthy eating #diet #healthylifestyle #health and wellness #mental health #nutrition #weight loss diet

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