This is a development key figure, see questions and answers on kolada.se for more information. Share (%) population aged 16-84 with severe anxiety, anxiety or anxiety. The results are taken from the national survey Health on equal terms (National Institute of Public Health). The data refers to year T-2 to year T. Data is available according to gender breakdown.

This is an uncertainty number, for more information see Uncertainty in data on kolada.se. Residents aged 16-84 who are bothered by anxiety and/or anxiety are an excise estimate from a sample survey. This means that the estimate is not necessarily representative of the population as a whole. However, with the point estimate ± the uncertainty number, one can most likely say that the true mean is within the range. Data is available according to gender breakdown.

BackgroundThe rise of depression, anxiety, and suicide rates has led to increased demand for telemedicine-based mental health screening and remote patient monitoring (RPM) solutions to alleviate the burden on, and enhance the efficiency of, mental health practitioners. Multimodal dialog systems (MDS) that conduct on-demand, structured interviews offer a scalable and cost-effective solution to address this need.ObjectiveThis study evaluates the feasibility of a cloud based MDS agent, Tina, for mental state characterization in participants with depression, anxiety, and suicide risk.MethodSixty-eight participants were recruited through an online health registry and completed 73 sessions, with 15 (20.6%), 21 (28.8%), and 26 (35.6%) sessions screening positive for depression, anxiety, and suicide risk, respectively using conventional screening instruments. Participants then interacted with Tina as they completed a structured interview designed to elicit calibrated, open-ended responses regarding the participants' feelings and emotional state. Simultaneously, the platform streamed their speech and video recordings in real-time to a HIPAA-compliant cloud server, to compute speech, language, and facial movement-based biomarkers. After their sessions, participants completed user experience surveys. Machine learning models were developed using extracted features and evaluated with the area under the receiver operating characteristic curve (AUC).ResultsFor both depression and suicide risk, affected individuals tended to have a higher percent pause time, while those positive for anxiety showed reduced lip movement relative to healthy controls. In terms of single-modality classification models, speech features performed best for depression (AUC = 0.64; 95% CI = 0.51–0.78), facial features for anxiety (AUC = 0.57; 95% CI = 0.43–0.71), and text features for suicide risk (AUC = 0.65; 95% CI = 0.52–0.78). Best overall performance was achieved by decision fusion of all models in identifying suicide risk (AUC = 0.76; 95% CI = 0.65–0.87). Participants reported the experience comfortable and shared their feelings.ConclusionMDS is a feasible, useful, effective, and interpretable solution for RPM in real-world clinical depression, anxiety, and suicidal populations. Facial information is more informative for anxiety classification, while speech and language are more discriminative of depression and suicidality markers. In general, combining speech, language, and facial information improved model performance on all classification tasks.

This is a development key figure, see questions and answers on kolada.se for more information. Number of people aged 65 and older with home care on an individual basis who stated that they have severe problems with anxiety, anxiety or anxiety divided by all people aged 65 and older in ordinary housing with home care on an individual basis who responded to the survey of older people’s perceptions. “Do not know/No opinion” is excluded from the denominator. Data from 2012.

Phobia Statistics: Living with the fear of something, just like Ron in Harry Potter was afraid of spiders is what phobia is. There are thousands of phobia types, and millions of people around the world are suffering from the disorder. The most common phobia is fear of animals and closed-in spaces. There is no actual prevention of such disorders, but they are treatable. These Phobia Statistics are written in a way to understand the current situation around the world, with well-researched and recent insights from the United States of America. If you are one of the individuals who have any type of phobia, don’t get scared, it’s okay to talk about it! Editor’s choice 40% of the people suffering from Agoraphobia are suffering from severe issues. In the United States of America, the highest number of people have a fear of animals resulting in 40%. As a result of COVID-19, and following cases of Russia and Ukraine, in the month of July 2022, there were 63% of the people globally, had a fear of relative recession. 15 million Americans are suffering from social phobia, resulting in 7.1% of adults and 5.5% of teenagers. 7% of the worldwide population is suffering from panic disorder, 1.6% of these are male and 3.8% are female. According to Phobia Statistics, there are 31.9% of adolescents aged between 13 to 18 years suffer from anxiety disorders. Women are 2 times more likely to suffer from any specific phobias than men. Specific phobias have affected 9.1% of Americans resulting in 19 million of the population. Patients with anxiety disorder are 3 to 5 times more likely to go for a doctor’s visit, while patients with psychiatric disorders are 6 times more likely to be hospitalized for a similar problem. Around the world, 3.6% of the population is suffering from post-traumatic stress disorder, out of these 1.8% are men and 5.2% are women

This report presents findings from the third (wave 3) in a series of follow up reports to the 2017 Mental Health of Children and Young People (MHCYP) survey, conducted in 2022. The sample includes 2,866 of the children and young people who took part in the MHCYP 2017 survey. The mental health of children and young people aged 7 to 24 years living in England in 2022 is examined, as well as their household circumstances, and their experiences of education, employment and services and of life in their families and communities. Comparisons are made with 2017, 2020 (wave 1) and 2021 (wave 2), where possible, to monitor changes over time.

This is a development key figure, see questions and answers on kolada.se for more information. Number of people aged 65 and older living in special public housing who reported having severe anxiety, anxiety or anxiety divided by all persons aged 65 years and older, residents in special housing under public authority who responded to the survey of older people’s perceptions. “Do not know/No opinion” is excluded from the denominator. Data from 2012.

Percentage of the population with self-reported mental health outcomes of anxiety, bipolar and depression for Statistical Area 2 (2018) units. Original data sourced from Census 2018 and New Zealand Health Survey 2017/18 and 2018/19. Data provided are synthetic data produced from spatial microsimulation modelling.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

Percentage of persons aged 15 years and over by frequency with which they feel lonely, by gender, for Canada, regions and provinces.

A social and psychological profile of Norwegian youth exposed to violence and poly-victimization (percent).

IntroductionThe prevalence of overweight and obesity among college girls is a significant public health concern. This cross-sectional study investigated the relationships between nutritional intake, appetite regulation, and mental health with body composition among overweight and obese college girls.MethodsThis study involved 72 college girls. Standardized instruments measured the corresponding variables. The data analysis utilized Pearson and Spearman correlations.ResultsResults show that energy and carbohydrate intake were positively correlated with body fat percentage and waist circumference (both p ≤ 0.007). Fat intake was positively correlated with all body composition variables (all p < 0.001). Anxiety was negatively correlated with all body composition variables (all p ≤ 0.027). Hunger at 0 min was positively correlated with body fat percentage and waist circumference (both p ≤ 0.002). Hunger at 60 min was positively correlated with BMI and waist circumference (both p ≤ 0.012). Desire to eat at 0 and 60 min were positively correlated with all body composition variables (all p ≤ 0.003). Desire to eat at 30 min was positively correlated with BMI (p = 0.005). Desire to eat at 90 min was negatively correlated with body fat percentage (p = 0.047). Fullness at 0 min was positively correlated with waist circumference (p = 0.040). Fullness at 30 min was positively correlated with body fat percentage and waist circumference (both p ≤ 0.018). Fullness at 120 min was negatively correlated with all body composition variables (all p ≤ 0.023). Prospective food consumption at 0 min was positively correlated with all body composition variables (all p < 0.001). Prospective food consumption at 30, 60, and 120 min was positively correlated with BMI (all p ≤ 0.008).DiscussionOverall, overweight and obese college girls should manage energy intake, fat intake, carbohydrate intake, anxiety, and appetite regulation to reduce fat levels. Further research suggests exploring counterintuitive correlations between body composition with anxiety, desire to eat at 90 min, and fullness at 0 and 30 min, along with limitations related to causal relationships, measurement accuracy, the relationship with physical activity, and population diversity.

Prevalence of different degrees of stress and anxiety among the participants.