This dataset describes injury mortality in the United States beginning in 1999. Two concepts are included in the circumstances of an injury death: intent of injury and mechanism of injury. Intent of injury describes whether the injury was inflicted purposefully (intentional injury) and, if purposeful, whether the injury was self-inflicted (suicide or self-harm) or inflicted by another person (homicide). Injuries that were not purposefully inflicted are considered unintentional (accidental) injuries. Mechanism of injury describes the source of the energy transfer that resulted in physical or physiological harm to the body. Examples of mechanisms of injury include falls, motor vehicle traffic crashes, burns, poisonings, and drownings (1,2). Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia. Age-adjusted death rates (per 100,000 standard population) are based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2015 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of injury death are classified by the International Classification of Diseases, Tenth Revision (ICD–10). Categories of injury intent and injury mechanism generally follow the categories in the external-cause-of-injury mortality matrix (1,2). Cause-of-death statistics are based on the underlying cause of death. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics. ICD–10: External cause of injury mortality matrix. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Murphy SL, Xu JQ, Kochanek KD, Curtin SC, and Arias E. Deaths: Final data for 2015. National vital statistics reports; vol 66. no. 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_06.pdf. Miniño AM, Anderson RN, Fingerhut LA, Boudreault MA, Warner M. Deaths: Injuries, 2002. National vital statistics reports; vol 54 no 10. Hyattsville, MD: National Center for Health Statistics. 2006.

Poland Deaths: Male: EC: ow Intentional Self Harm data was reported at 3,895.000 Person in 2023. This records an increase from the previous number of 3,749.000 Person for 2022. Poland Deaths: Male: EC: ow Intentional Self Harm data is updated yearly, averaging 4,695.000 Person from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 5,555.000 Person in 2012 and a record low of 3,749.000 Person in 2022. Poland Deaths: Male: EC: ow Intentional Self Harm data remains active status in CEIC and is reported by Statistics Poland. The data is categorized under Global Database’s Poland – Table PL.G006: Deaths: By Cause.

Background: Despite most suicides occurring in low-and-middle-income countries (LAMICs), limited reports on suicide rates in older adults among LAMICs are available. In Ecuador, high suicide rates have been reported among adolescents. Little is known about the epidemiology of suicides among older adults in Ecuador.Aim: To examine the sociodemographic characteristics of suicides among older adults living in Ecuador from 1997 to 2019.Methods: An observational study was conducted using Ecuador's National Institute of Census and Statistics database from 1997 to 2019 in Ecuadorians aged 60 and older. International Classification of Diseases 10th Revision (ICD-10) (X60-X84)-reported suicide deaths were included in addition to deaths of events of undetermined intent (Y21-Y33). Sex, age, ethnicity, educational level, and method of suicide were analyzed. Annual suicide rates were calculated per 100,000 by age, sex, and method. To examine the trends in rates of suicide, Joinpoint analysis using Poisson log-linear regression was used.Results: Suicide rates of female older adults remained relatively stable between 1997 and 2019 with an average annual percentage increase of 2.4%, while the male rates increased between 2002 and 2009, 2014 and 2016, and maintained relatively stable within the past 3 years (2017–2019). The annual age-adjusted male suicide rate was 29.8 per 100,000, while the female suicide rate was 5.26 per 100,000 during the study period. When adding deaths of undetermined intent, the annual male rate was 60.5 per 100,000, while the same rate was 14.3 for women. The most common suicide method was hanging (55.7%) followed by self-poisoning (26.0%). The highest suicide numbers were reported in urban districts, men, and those with lower education status.Conclusion: This study contributes to building the baseline for further studies on suicide rates of older adults in Ecuador. Results highlight priority areas of suicide prevention. By examining suicide trends over 23 years, findings can help inform policy and future interventions targeting suicide prevention.

Readme file for ADAM-SDMH: A DAtaset from Manipal for Severity Detection in Tweets related to Mental Health Generated on 2021-02-15Recommended citation for the dataset:P. Surana, M. Yusuf and S. Singh, "Severity Classification of Mental Health-Related Tweets," 2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), 2021, pp. 336-341, DOI: 10.1109/DISCOVER52564.2021.9663651.******************************PROJECT INFORMATION******************************1. Title of dataset: Mental Health Dataset2. Author information:Praatibh Surana, Manipal Institute of Technology,Mirza Yusuf, Manipal Institute of Technology,Sanjay Singh, Manipal Institute of TechnologyPrincipal Investigators Name: Praatibh SuranaAddress: Manipal Institute of TechnologyEmail: praatibhsurana@gmail.comName: Mirza YusufAddress: Manipal Institute of TechnologyEmail: baig.yusuf.cr7@gmail.comCo-InvestigatorName: Sanjay SinghAddress: Manipal Institute of TechnologyEmail: sanjay.singh@manipal.edu3. Date of data collection: Jan 2021 - Feb 2021************************************DATA ACCESS INFORMATION************************************1. Licences/restrictions placed on access to the dataset: CC BY 4.02. Links to publications that use the data:URL: https://ieeexplore.ieee.org/document/9663651,DOI: 10.1109/DISCOVER52564.2021.96636513. Links to a third party or secondary data used in the project (for example, existing datasets, third-party datasets)Pennington, Jeffrey et al. “GloVe: Global Vectors for Word Representation.” EMNLP (2014).DOI: https://doi.org/10.3115/v1/d14-1162*****************************************METHODS OF DATA COLLECTION*****************************************1. Describe the methods for data collection and/or provide links to papers describing data collection methodsPaper DOI :Our research revolved around correctly classifying tweets based on their severity in a mental health context. An effort was also made to make the models detect sarcasm better, as this was something that many models in the past failed to do. Our dataset consists of tweets labeled as ‘0’, ‘1’, and '2' depending on their classes. The labeling rules followed are given in Table 1TABLE 1 - SEVERITY CLASSIFICATION CLASSES AND EXAMPLES-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Class | Rules | Example | |0 | Helping / suggestion for mental health awareness | Are you suffering from anxiety? Check out this page for therapy through Skype! | / positivity / informative | | / motivational | | / questions about mental health | | |1 | Sarcasm/rant/expression of annoyance | Today was so annoying. If my teacher would have called my name, I swear to God I would have killed myself | |2 | Case of slight disturbance | All I am is a burden. I don’t want to live anymore. | / strong indication of disturbance | | / user outright mentions depression | | / anxiety / suicide / self-harm |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------The following steps were performed for data collection:1) Tweets were extracted with the help of Twitter’s official API using hashtags such as #depression, #mentalhealth, #anxiety, #selfharm, #killmyself, and #kms from users.2) Around 40,000 tweets were extracted from Twitter between January and February 2021, out of which the final dataset comprised of 2460 tweets; 820 tweets were distributed equally amongst the three classes.3) Two authors manually annotated the dataset and cross-verified it to ensure accurate labeling.2. Data processing methods:A. Preprocessing1) Removal of numbers, URLs, usernames, and special characters: The first step after extraction of the tweets was ensuring that they were suitable for further use. The “preprocessor” uses the Python library to eliminate numbers, retweets, URLs, emojis, emoticons, and usernames, followed by duplicate tweets removal from the dataset.2) Stopword removal and expansion of standard abbreviations: We made use of Python’s “nltk” library for the removal of common stopwords such as “for,” “the,” “a,” etc. As our data is sourced from Twitter, lots of common internet abbreviations like “lol,” “kms,” “gn,”etc., were used. It was taken care of by converting these short forms to their corresponding complete forms. Lots of short forms like “wanna” for “want to” and “gonna” for “going to” were used. We ensured that these, too, were taken care of to the best of our abilities. 3) Removal of names, so that anonymity is maintained. Names of people, places, twitter handles anything that could compromise the anonymity has been removed, a token named as ‘[redacted]’ has been used in their place instead.*******************************SUMMARY OF DATA FILE*******************************Filename: MentalHealthTweets.csvShort description: This CSV File contains 2460 tweets annotated ‘0’, ‘1’ or ‘2’ based on the class they belong to.*******************************************************************DATA-SPECIFIC INFORMATION FOR NOTE: This section should be copied and pasted for each file*******************************************************************1. Number of variables: 22. Number of cases rows: 24613. Missing data codes: NA4. Variable listThe variables and their properties have been provided in Table 2TABLE 2 - VARIABLE DESCRIPTION TABLE----------------------------------------------------------------------Variable Name | Variable Description | Variable Type | |tweets | Cleaned up tweet | String | |label | Annotation for tweet | Integer----------------------------------------------------------------------

Researchers interested in the psychology of justice have demonstrated that people need to maintain the belief that the world is basically a just, orderly, and non-random place where people get what they deserve and deserve what they get. This project aims to leverage this previous research and theorising to investigate whether concerns about personal deservingness following experiences of random misfortunes influence self-punishment. The project will involve five experiments; the aim is to examine the key question of whether people may adopt self-punishing beliefs about themselves (ie, lowered self-esteem) and engage in self-punishing behaviours (ie, physical self-harm, self-sabotage) in order to justify their random misfortunes as deserved. In these studies, participants will experience everyday good or bad breaks (eg, losing or winning a coin flip) and then will : rate how they feel about themselves and their deservingness of positive outcomes judge how willing they are to self-inflict alleged electrical stimulations be given the opportunity to forego the chance to attribute potential failure during a test to mitigating circumstances. Across the five studies, the researchers have developed experimental methods to specifically test the role that people's concerns about personal deservingness play in self-punishing beliefs and behaviours. Experiments and surveys.

Abstract copyright UK Data Service and data collection copyright owner.The Surveys of Psychiatric Morbidity in Great Britain aim to provide up-to-date information about the prevalence of psychiatric problems among people in Great Britain, as well as their associated social disabilities and use of services. The series began in 1993, and so far consists of the following surveys:OPCS Surveys of Psychiatric Morbidity: Private Household Survey, 1993, covering 10,000 adults aged 16-64 years living in private households;a supplementary sample of 350 people aged 16-64 with psychosis, living in private households, which was conducted in 1993-1994 and then repeated in 2000;OPCS Surveys of Psychiatric Morbidity: Institutions Sample, 1994, which covered 1,200 people aged 16-64 years living in institutions specifically catering for people with mental illness;OPCS Survey of Psychiatric Morbidity among Homeless People, 1994, which covered 1,100 homeless people aged 16-64 living in hostels for the homeless or similar institutions. The sample also included 'rough sleepers';ONS Survey of Psychiatric Morbidity among Prisoners in England and Wales, 1997;Mental Health of Children and Adolescents in Great Britain, 1999;Psychiatric Morbidity among Adults Living in Private Households, 2000, which repeated the 1993 survey;Mental Health of Young People Looked After by Local Authorities in Great Britain, 2001-2002;Mental Health of Children and Young People in Great Britain, 2004; this survey repeated the 1999 surveyAdult Psychiatric Morbidity Survey, 2007; this survey repeated the 2000 private households survey. The Information Centre for Health and Social Care took over management of the survey in 2007.Adult Psychiatric Morbidity Survey, 2014: Special Licence Access; this survey repeated the 2000 and 2007 surveys. NHS Digital are now responsible for the surveys, which are now sometimes also referred to as the 'National Survey of Mental Health and Wellbeing'. Users should note that from 2014, the APMS is subject to more restrictive Special Licence Access conditions, due to the sensitive nature of the information gathered from respondents.Mental Health of Children and Young People in England, 2017: Special Licence; this survey repeated the 1999 and 2004 surveys, but only covering England. Users should note that this study is subject to more restrictive Special Licence Access conditions, due to the sensitive nature of the information gathered from respondents.The UK Data Service holds data from all the surveys mentioned above apart from the 1993-1994/2000 supplementary samples of people with psychosis. The main aims of the Mental Health of Children and Young People in Great Britain, 2004 survey were:to examine whether there were any changes between 1999 and 2004 in the prevalence of the three main categories of mental disorder: conduct disorders, emotional disorders and hyperkinetic disordersto describe the characteristics and behaviour patterns of children in each main disorder category and subgroups within those categoriesto look in more detail at children with autistic spectrum disorderto examine the relationship between mental disorder and aspects of children’s lives not covered in the previous survey, for example, medication, absence from school, empathy and social capitalto collect baseline information to enable identification of the protective and risk factors associated with the main categories of disorder and the precursors of personality disorder through future follow-up surveys Main Topics: The data file contains:a subset of information collected in the previous 1999 survey on 10,438 children aged 5-15; these variables included those which were repeated in comparable form in 2004. The full 1999 dataset has also been deposited at UKDA (see 'Abstract' section above)the full data collected in the 2004 survey on 7,977 children aged 5-16any potentially disclosive variables have been removedInformation was provided for the survey from up to three sources: the primary care giver, the child/young person (aged 11-15/16 years) and the child/young person’s teacher (nominated by child/parent). Topics covered in the 2004 survey included: housing, general health, strengths and difficulties, friendship, development, separation anxiety, social and specific phobias, panic attacks and agoraphobia, post-traumatic stress disorder, compulsions and obsessions, generalised anxiety, depression, self-harm, attention and activity, awkward and troublesome behaviours, eating disorders, tics, personality issues, stress and life events, school exclusions. Some data were gathered by self-completion, for example drink and drug use (from child/young person) and parent's/parents' education, employment, income, strengths and difficulties (parent). Clinical raters reviewed the survey data from all sources and then assigned International Classification of Diseases (ICD_10) ratings as necessary (see the documentation for a full description of the methodology). The file also contains derived variables (specifications provided). Standard Measures:General Health Questionnaire (GHQ) (Goldberg and Williams, 1988)Development and Well-Being Assessment Strengths and Difficulties Questionnaire (DAWBA) (Goodman, 1997 and 1998)General Functioning Scale of the MacMaster Family Activity Device (FAD) Multi-stage stratified random sample The sample was selected from Child Benefit records (see documentation for further details) Face-to-face interview Postal survey Self-completion Parents/carers were interviewed face-to-face, children/young persons completed the self-completion questionnaire, and teachers were surveyed by post. 2004 ACCIDENTS ADOLESCENCE AGE AGGRESSIVENESS ALCOHOL USE ALCOHOLIC DRINKS ALCOHOLISM AMPHETAMINES ANABOLIC STEROIDS ANGER ANXIETY ANXIETY DISORDERS ASSAULT ATTITUDES AUTISM SPECTRUM DIS... BEHAVIOURAL DISORDERS BEREAVEMENT BUILDING MAINTENANCE BULLYING CANNABIS CARE IN THE COMMUNITY CARE OF DEPENDANTS CHILDREN CHRONIC ILLNESS COCAINE COGNITION DISORDERS COHABITATION CONCENTRATION COUNSELLING COUNSELLORS CRIME AND SECURITY CRIME VICTIMS Children DAY CARE DEBILITATIVE ILLNESS DECISION MAKING DEPRESSION DIGESTIVE SYSTEM DI... DISABILITIES DISABLED FACILITIES DISEASES DOMESTIC VIOLENCE DRUG ABUSE DRUG ADDICTION DRUG PSYCHOTHERAPY ... DRUG SIDE EFFECTS DRUG USE ECONOMIC ACTIVITY ECSTASY DRUG EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EMOTIONAL DISTURBANCES EMOTIONAL STATES EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS EVERYDAY LIFE FAMILY ENVIRONMENT FAMILY MEMBERS FATIGUE PHYSIOLOGY FEAR FINANCE FINANCIAL RESOURCES FOOD AND NUTRITION FRIENDS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GENDER GENERAL PRACTITIONERS Great Britain HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH CONSULTATIONS HEALTH SERVICES HEROIN HOME OWNERSHIP HOME SHARING HOME VISITS HOMELESSNESS HOSPITAL DISCHARGES HOSPITAL OUTPATIENT... HOSPITAL SERVICES HOSPITALIZATION HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLDS HOUSEWORK HOUSING HOUSING TENURE Health Health care service... INCOME INDUSTRIES INJURIES INTERPERSONAL CONFLICT INTERPERSONAL RELAT... JOB HUNTING LANDLORDS LEAVE LEISURE TIME ACTIVI... LONELINESS MARITAL STATUS MARRIAGE DISSOLUTION MEDICAL CARE MEDICAL DIAGNOSIS MEDICAL PRESCRIPTIONS MEDICINAL DRUGS MEMORY MEMORY DISORDERS MENTAL DISORDERS MENTAL HEALTH MORAL CONCEPTS MORBIDITY MOTOR PROCESSES MUSCULOSKELETAL SYSTEM Morbidity and morta... NERVOUS SYSTEM DISE... NEUROTIC DISORDERS NURSES OBSESSIVE COMPULSIV... OCCUPATIONAL THERAPY OCCUPATIONS PAIN PART TIME EMPLOYMENT PATIENTS PERSONAL HYGIENE PHOBIAS PHYSICIANS PREDOMINANT LANGUAGES PSYCHIATRISTS PSYCHOLOGICAL EFFECTS PSYCHOLOGISTS PSYCHOTHERAPY PSYCHOTIC DISORDERS QUALIFICATIONS READING ACTIVITY REFORMATORY SCHOOLS RENTED ACCOMMODATION RESIDENTIAL CHILD CARE RURAL AREAS SCHOOL PUNISHMENTS SCHOOLS SELF EMPLOYED SELF ESTEEM SENSORY IMPAIRMENTS SEXUAL BEHAVIOUR SHELTERED EMPLOYMENT SICK LEAVE SLEEP SLEEP DISORDERS SMOKING SMOKING CESSATION SOCIAL HOUSING SOCIAL INTEGRATION SOCIAL NETWORKS SOCIAL PARTICIPATION SOCIAL SUPPORT SOLVENT ABUSE SORROW STRESS PSYCHOLOGICAL SUICIDE SUPERVISORY STATUS SYMPTOMS Specific social ser... TAX RELIEF TIED HOUSING TOBACCO TRAINING COURSES TRANQUILLIZERS TRANSPORT UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... UNWAGED WORKERS URBAN AREAS VISITS PERSONAL WEIGHT PHYSIOLOGY YOUTH Youth

The last decade has seen a steady rise in self-harm rates in young people in developed countries. Understanding the experience of self-harm in young people can provide insight into what may be driving this increase. The aim of the current review was therefore to synthesise qualitative research examining precipitating and motivating factors underlying self-harm in young people. PsychInfo, Embase and Medline were systematically searched for articles published up to September 2024. A total of 50 qualitative studies (study N ranging from 3–115) were identified, and key findings were synthesised using Attride-Stirling’s Thematic Network Analysis process. The quality of included studies was assessed using a modified version of two Joanna-Briggs Institute Checklists. Control was identified as a global theme. Precipitants were informed by young people’s perception of an absence of control and the desire to gain control was identified as an underlying motivation for self-harm. The findings from this review highlight the need to support and educate young people to improve their distress tolerance, particularly in respect to situations outside of their control. Furthermore, therapeutic interventions, and training and educational programs targeting young people who self-harm and their family members might be effective interventions for self-harm in young people.

Poland Deaths: Rural: Male: EC: ow Intentional Self Harm data was reported at 1,892.000 Person in 2023. This records an increase from the previous number of 1,849.000 Person for 2022. Poland Deaths: Rural: Male: EC: ow Intentional Self Harm data is updated yearly, averaging 2,308.000 Person from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 2,796.000 Person in 2012 and a record low of 1,849.000 Person in 2022. Poland Deaths: Rural: Male: EC: ow Intentional Self Harm data remains active status in CEIC and is reported by Statistics Poland. The data is categorized under Global Database’s Poland – Table PL.G006: Deaths: By Cause.

Background

Intentional self-harm is a common cause of hospital presentations in New Zealand and across the world, and self-poisoning is the most common method of self-harm. Paracetamol (acetaminophen) is frequently used in impulsive intentional overdoses, where ease of access may determine the choice of substance.

Objective

This cross-sectional study aimed to determine how much paracetamol is present and therefore accessible in urban New Zealand households, and sources from where it has been obtained. This information is not currently available through any other means, but could inform New Zealand drug policy on access to paracetamol.

Methods

Random cluster-sampling of households was performed in major urban areas of two cities in New Zealand, and the paracetamol-containing products, quantities, and sources were recorded. Population estimates of proportions of various types of paracetamol products were calculated.

Results

A total of 174 of the 201 study households (86.6%) had at least one paracetamol product. Study households had mostly prescription products (78.2% of total mass), and a median of 24.0 g paracetamol present per household (inter-quartile range 6.0-54.0 g). Prescribed paracetamol was the main source of large stock. Based on the study findings, 53% of New Zealand households had 30 g or more paracetamol present, and 36% had 30 g or more of prescribed paracetamol, specifically.

Conclusions

This study highlights the importance of assessing whether and how much paracetamol is truly needed when prescribing and dispensing it. Convenience of appropriate access to therapeutic paracetamol needs to be balanced with preventing unnecessary accumulation of paracetamol stocks in households and inappropriate access to it. Prescribers and pharmacists need to be aware of the risks of such accumulation and assess the therapeutic needs of their patients. Public initiatives should be rolled out at regular intervals to encourage people to return unused or expired medicines to pharmacies for safe disposal.

Methods The stocks of paracetamol-containing medicines (acetaminophen) held at a single time point in New Zealand households are described in this dataset. These data were collected via a cluster-sampling survey of two cities in New Zealand.

A door-to-door survey study with random, clustered sampling of consenting household members in two cities in New Zealand was designed. A total of 201 households in 40 meshblocks in two Major Urban Areas (MUAs; areas of 100,000 or more residents) of Dunedin and Auckland were sampled. Meshblocks are Statistics NZ’s smallest geographic unit, and roughly correspond to a city block or part of it. Random cluster-sampling of 20 meshblocks in each city was performed by deprivation level, where all eligible MUA meshblocks were stratified by their New Zealand Deprivation Index 2013 (NZDep2013) index scores, which describe the level of area deprivation by taking into account multiple relevant area and household variables. Six meshblocks were randomly selected from each city from NZDep2013 8-10 meshblocks (most deprived), eight from NZDep 4-7, and 6 from NZDep2013 1-2 (least deprived), for a total of 40 meshblocks. This was done to obtain a sample that would be representative of the general New Zealand population by levels of deprivation. Each meshblock was sampled by starting from a random end of the street and then tossing a dice to choose a house to approach, and repeating this until either five households were recruited or there were no more households to sample.

Trained Research Assistants (RAs) knocked on the doors of domiciles in each meshblock to be sampled, chosen by tossing a dice as described. Inclusion criteria: person present and usually residing in a domicile in a meshblock which was sampled, and aged 16 or over. Exclusion criteria: not able to give informed consent (intoxicated, aggressive, otherwise not safe to approach – nobody was excluded for this reason).

Household members aged 16 years and over were eligible to participate, and if consent was obtained, basic demographics were collected about the household (number of people usually residing in the household, their age, sex, ethnicity). Participants were then shown images of paracetamol-containing products (sole and combination), and requested to bring out all paracetamol products of their own, and any that were shared by the household in communal areas of the domicile. Private stock of any other residents of the household who were not present and were therefore unable to consent was not recorded for ethical reasons. If there were no paracetamol products present, that was recorded. If there were paracetamol products present, product type, strength, expiry date, purchase date and means of obtaining (by prescription, pharmacy over-the-counter [OTC], other retailer [i.e. not a pharmacy; e.g. supermarket, petrol station], other, unknown) were recorded.

The data were entered into a main database which is fully de-identified. Meshblock numbers are included in the dataset, but households are only given an identifier derived from the meshblock code. It would not be possible to identify a specific household from the data. Paracetamol product names were cleaned in the dataset (if there were any misspellings), and new variables were calculated to summarise the data (e.g. total household stock of prescribed paracetamol products, etc.).

This is qualitative data collection of semi-structured interviews conducted between June-July 2023, and online surveys conducted throughout 2022, within a study that examined how the Prisons and Probation Ombudsman (seek to) effect change in prisons following prisoner suicides and how verbatim film can help to increase the impact of research findings. The study ran from 2021-2023. Prisoner suicide rates are consistently higher than rates among communities living outside. Between 2012 and 2016, England and Wales’s prison suicide rates more than doubled, hitting record numbers in 2016. Often those most invested in prison safety are those personally impacted, and campaigns by prisoners’ families can have material effects. This project included a collaboration between an academic research team, a bereaved parent and a theatre company, which aimed to raise awareness of prison suicide through verbatim film and communicate key messages to stakeholders across criminal justice.In May 2019, Dutch courts refused to deport an English suspected drug smuggler, citing the potential for inhuman and degrading treatment at HMP Liverpool. This well publicised judgment illustrates the necessity of my FLF: reconceptualising prison regulation, for safer societies. It seeks to save lives and money, and reduce criminal reoffending. Over 10.74 million people are imprisoned globally. The growing transnational significance of detention regulation was signalled by the Optional Protocol to the United Nations Convention against Torture/OPCAT. Its 89 signatories, including the UK, must regularly examine treatment and conditions. The quality of prison life affects criminal reoffending rates, so the consequences of unsafe prisons are absorbed by our societies. Prison regulation is more urgent than ever. England and Wales' prisons are now less safe than at any point in recorded history, containing almost 83,000 prisoners: virtually all of whom will be released at some point. In 2016, record prison suicides harmed prisoners, staff and bereaved families, draining 385 million punds from public funds. Record prisoner self-harm was seen in 2017, then again in 2018. Criminal reoffending costs £15 billion annually. Deteriorating prison safety poses a major moral, social, economic and public health threat, attracting growing recognition. Reconceptualising prison regulation is a difficult multidisciplinary challenge. Regulation includes any activity seeking to steer events in prisons. Effective prison regulation demands academic innovation and sustained collaboration and implementation with practitioners from different sectors (e.g. public, voluntary), regulators, policymakers, and prisoners: from local to (trans)national levels. Citizen participation has become central to realising more democratic, sustainable public services but is not well integrated across theory-policy-practice. I will coproduce prison regulation with partners, including the Prisons and Probation Ombudsman, voluntary organisations Safe Ground and the Prison Reform Trust, and (former) prisoners. This FLF examines three diverse case study countries: England and Wales, Brazil and Canada, developing multinational implications. This approach is ambitious and risky, but critical for challenging commonsensical beliefs. Interviews, focus groups, observation and creative methodologies will be used. There are three aims, to: i) theorise the (potential) participatory roles of prisoners and the voluntary sector in prison regulation ii) appraise the (normative) relationships between multisectoral regulators (e.g. public, voluntary) from local to (trans)national scales iii) co-produce (with multisectoral regulators), pilot, document and disseminate models of participatory, effective and efficient prison regulation in England and Wales (and beyond) - integrating multisectoral, multiscalar penal overseers and prisoners into regulatory theory and practice. This is an innovative study. Punishment scholars have paid limited attention to regulation. Participatory networks of (former) prisoners are a relatively new formation but rapidly growing in influence. Nobody has yet considered agencies like the Prisons Inspectorate and Ombudsman alongside voluntary sector organisations and participatory networks, nor their collective influences from local to transnational scales. Nobody has tried to work with all of these agencies to reconceptualise prison regulation and test it in practice. Findings will be developed, disseminated and implemented internationally. The research team will present findings and engage with diverse stakeholders and decision makers through interactive workshops (Parliament, London, Manchester, Liverpool and Birmingham), and multimedia outputs (e.g. infographics). This FLF has implications for prisons and detention globally, and broader relevance as a case study of participatory regulation of public services and policy translation. Within this project, 2 semi-structured interviews were undertaken with film co-creators and 27 anonymous online surveys were completed by audience members in film screenings. The sample was purposive for all groups, as appropriate for our exploratory analysis and the resources available, however the sample is not representative of collaborative film creators or audiences. Telephone and videoconferencing (Microsoft TEAMS) interviews (at the participant’s preference) were conducted with filmmakers between June and July 2023. Anonymous online surveys were completed at film screenings between March and November 2022.

The survey Epidemiological Survey on Substance Abuse in Germany 2018 (ESA) is a representative survey on the use and abuse of psychoactive substances among adolescents and adults aged 18 to 64 years, which has been conducted regularly nationwide since 1980. The data collection took place between March and July 2018 and was conducted by infas Institut für angewandte Sozialwissenschaft GmbH on behalf of the IFT, Institute for Therapy Research in Munich. The nationwide study was conducted in a mixed-mode design as a standardised telephone survey (CATI: Computer Assisted Telephone Interview), as a written-postal survey (PAPSI: Paper and Pencil Self Interview) and as an online survey. The study is financially supported by the Federal Ministry of Health. The survey covered 30-day, 12-month and lifetime prevalence of tobacco use (tobacco products as well as shisha, heat-not-burn products and e-cigarettes), alcohol, illicit drugs and medicines. For conventional tobacco products, alcohol, selected illicit drugs (cannabis, cocaine and amphetamines) and medications (painkillers, sleeping pills and tranquillisers), additional diagnostic criteria were recorded with the written version of the Munich Composite International Diagnostic Interview (M-CIDI) for the period of the last twelve months. Furthermore, a series of socio-demographic data, the physical and mental state of health, nutritional behaviour, mental disorders as well as modules on the main topics of children from families with addiction problems, reasons for abstinence in the field of alcohol and the perception or knowledge of the health risk posed by alcohol were recorded. Physical and mental health status: self-assessment of health status; self-assessment of mental well-being; chronic illnesses; frequency of physical problems or pain without clear explanation, anxiety attack / panic attack, frequent worries, strong fears in social situations, strong fears of public places, means of transport or shops, strong fears of various situations, e.g. use of lifts, tunnels, aeroplanes as well as severe weather, sadness or low mood, loss of interest, tiredness or lack of energy, unusually happy, over-excited or irritable, stressful traumatic events, psychiatric, psychological or psychotherapeutic treatment in the last 12 months; physical activity and diet in the last three months: frequency of physical activity (moving from place to place, recreational sports, work-related physical activity) per week; duration of physical activity; consumption of selected foods (low-fat dairy products, raw vegetables, fresh salads, herbs, fresh fruit, cereal products, herbal tea or fruit tea); illness caused by excessive alcohol consumption. 2. Medication use: type of medication use (painkillers, sleeping pills, tranquilizers, stimulants, appetite suppressants, antidepressants, neuroleptics and anabolic steroids) in the last 12 months; frequency of use of painkillers, sleeping pills, tranquilizers, stimulants, appetite suppressants, antidepressants and neuroleptics in the last 30 days and respective prescription by a physician; use of painkillers, sleeping pills or tranquilizers in the last 12 months; tendencies towards dependence: In the last 12 months, the following were asked: significant problems related to the use of painkillers, sleeping pills and tranquillisers (neglect of household and children, poor performance, injury-prone situations while under the influence of medication, unintentional injuries such as accidents or falls, legal problems, accusations from family or friends, broken relationship, financial difficulties, physically attacking or hurting someone, use in larger quantities or for longer periods than prescribed or intended by the doctor, discomfort when stopping the medication. discomfort when stopping the medication and then continuing to take the medication to avoid discomfort, higher doses required for desired effect or weakened effect, unsuccessful attempts to reduce or stop medication use, large amount of time required to obtain medication or recover from effects, restriction of activities, taking medication despite knowledge of harmful effects, craving for medication so strong that resisting or thinking otherwise was not possible. 3. Smoking: smoking status; smoking behaviour: smoked more than 100 cigarettes, cigars, cigarillos, pipes in total during lifetime; type of tobacco use (cigarettes, cigars, cigarillos, pipe); age of initiation of tobacco use; time of last tobacco use; specific number of days in the last month on which cigarettes (or cigars, cigarillos or pipes) were smoked and average number smoked per day; average daily consumption of 20 or more cigarettes (or 10 cigarillos, 7 pipes, 5 cigars) in the last 12 months; smoking behaviour in the last 12 months (had to smoke more than before to get the same effect, effect of smoking decreased, smoked much more than intended, tried unsuccessfully to cut down or quit smoking for a few days, chain smoker, gave up important activities because of smoking, continued to smoke during serious illness, smoking interfered with work, school or housework, smoked in situations where there was a high risk of injury, continued to smoke even though it made other people angry or unhappy, unable to resist strong cravings for tobacco, unable to think of anything else because of strong cravings for tobacco); physical or mental health problems in the last 12 months due to smoking; continued to smoke in spite of physical or mental health problems; health problems due to smoking cessation in the last 12 months (low mood, insomnia, irritability/annoyance, restlessness, difficulty concentrating, slow heartbeat, weight gain); started smoking again to avoid complaints; serious attempts to stop smoking in the last 12 months; successful attempt to quit smoking; ever used shisha (hookah), a Neat-Not-Burn product or an e-cigarette, e-shisha, e-pipe, e-cigar and time of last use; age at first use of e-cigarette/e-cigar/e-shisha/e-pipe and frequency of use in the last 30 days; use of e-cigarettes/e-cigars/e-shishas/e-pipes with or without nicotine. 4. Alcohol consumption: age at first glass of alcohol; alcohol consumption at least once a month; age of onset of regular alcohol consumption; alcohol excesses (binge drinking) in the past and frequency of alcohol excesses in the last 12 months; age at first alcohol excess; time of last alcohol consumption; total number of days with alcohol consumption in the last 30 days or 12 months; concrete information on the average amount of beer, wine/sparkling wine and mixed drinks containing alcohol (alcopops, long drinks, cocktails or punch) consumed in the last 30 days or 12 months. 12 months; concrete information on the average amount of beer, wine/sparkling wine, spirits and mixed drinks containing alcohol (alcopops, long drinks, cocktails or punch) consumed in the last 30 days or in the last 12 months; number of days with consumption of at least five glasses of alcohol in the last 30 days or 12 months; problems caused by alcohol in the last 30 days or 12 months; number of days with consumption of at least five glasses of alcohol in the last 30 days or 12 months. 12 months; problems caused by alcohol in the last 12 months (significant difficulties at work, school or home, situations involving risk of injury, trouble with the police, accusations from family or friends, broken relationship, financial difficulties, physically attacking or hurting someone); alcohol consumption behaviour in the last 12 months (had to drink more than before to get the same effect, effect of alcohol consumption decreased, drank much more than intended, tried unsuccessfully to drink less alcohol or to stop drinking altogether, drank a lot of alcohol over several days, been drunk or suffered from the effects of alcohol, gave up important activities because of alcohol, could not resist strong craving for alcohol, could not think of anything else because of strong craving for alcohol); symptoms after alcohol withdrawal (trembling, insomnia, anxiety, sweating, hallucinations (seizure), nausea, vomiting, urge to move, rapid heartbeat); drank alcohol to avoid such complaints; physical illnesses or mental problems related to alcohol in the last 12 months; alcohol consumption despite physical or mental problems; increased cancer incidence in the last 12 months; alcohol consumption in spite of physical or mental problems. increased cancer risk due to alcohol consumption (stomach cancer, ovarian cancer, breast cancer, mouth and oesophagus cancer, brain tumour, bowel cancer, liver cancer, bladder cancer); alcohol consumption in the last 30 days; personal reasons for abstaining from alcohol (alcohol causes people to lose control, condition of illness worsens due to alcohol, parents had an alcohol problem, family is against alcohol consumption, alcohol consumption is against my spiritual/religious attitude, I do not like the taste and/or smell of alcohol, own pregnancy or partner´s pregnancy). 5. Drug use: drug experience with cannabis (hashish, marijuana), stimulants, amphetamines, ecstasy, LSD, heroin, other opiates such as e.g. codeine, methadone, opium, morphine), cocaine, crack, sniffing substances and mushrooms as intoxicants or never tried any of these drugs before; ever used substances that imitate the effect of illegal drugs (legal highs, research chemicals, bath salts, herbal mixtures or new psychoactive substances (NPS); used such legal substances in the last 12 months; form of substances consumed (herbal mixtures for smoking, powders, crystals or tablets as well as liquids); generally tried drugs; frequency of drug use in total, in each case related to cannabis (hashish, marijuana), stimulants, amphetamines, ecstasy, LSD, heroin, other opiates, cocaine, crack cocaine, sniffing substances, mushrooms resp. Legal highs, research chemicals, bath salts, herbal mixtures, NPS; time of last use of any of the above drugs (in the

Gender differences among various self-harm variables.

ABSTRACT Objectives: Analyze the suicide mortality time trends among adolescents in Brazil from 2000 to 2015. Methods: Data were collected from the Brazilian Mortality Database and from the Brazilian Institute of Geography and Statistics. Study variables were sex, year and underlying cause of death. The study included deaths from Intentional Self-Harm, X60-X84 – according to the 10th Revision of the International Classification of Diseases (ICD-10), of adolescents aged 10 to 19. The simple linear regression technique was used and results were considered statistically significant when p ≤ 5%. Results: From 2000 to 2015, there were 11,947 deaths due to suicide of adolescents in Brazil and 67% of these occurred in male adolescents, which corresponds to a 2,06:1 male-female ratio. There was a statistically significant increase in adolescent suicide mortality in Brazil (p = 0.016), which increased from 1.71 per 100,000 inhabitants in 2000 to 2.51 in 2015, a raise of 47%. The increase occurred in behalf of the increment in suicides of male adolescents (p = 0.001) specifically in the North (p < 0.001) and Northeast (p < 0.001) of Brazil. In regard to the female group, there was a downtrend of mortality by suicide in the Center West region (p = 0.039), but when it comes to Brazil as a whole, there was a stabilization behavior of mortality by suicide. Conclusions: These results indicate an increase in the suicide rate of adolescents in Brazil, particularly in the male population. The improvement of suicide prevention strategies in Brazil is imperative.

Demographic characteristics of all patients and in comparison, with self-harm and non-self-harm patients.

ObjectivesThe period of entry into university represents one of vulnerability to substance use for university students. The goal of this study is to document the 12-month prevalence of substance use disorders among first year university students in Kenya, and to test whether there is an association between substance use disorders and mental disorders.MethodsThis was a cross-sectional online survey conducted in 2019 and 2020 as part of the World Health Organization’s World Mental Health International College Student (WMH-ICS) survey initiative. A total of 334 university students completed the survey. Descriptive statistics were used to summarize the demographic characteristics of the participants. Multivariate logistic regression was used to assess the association between substance use disorder and mental disorders after adjusting for age and gender.ResultsThe 12-month prevalence for alcohol use disorder was 3.3%, while the 12-month prevalence for other substance use disorder was 6.9%. Adjusting for age and gender, there was an association between any substance use disorder and major depression, generalized anxiety disorder, bipolar 1 disorder, intermittent explosive disorder, social anxiety disorder, suicidal ideation, suicide attempt, and non-suicidal self-injury.ConclusionThese findings highlight the need to institute policies and interventions in universities in Kenya that address substance use disorders and comorbid mental disorders among first-year students.