Amod/mental_health_counseling_conversations

This dataset is a compilation of high-quality, real one-on-one mental health counseling conversations between individuals and licensed professionals. Each exchange is structured as a clear question–answer pair, making it directly suitable for fine-tuning or instruction-tuning language models that need to handle sensitive, empathetic, and contextually aware dialogue. Since its public release, it has been downloaded over 77,000 times (Aug… See the full description on the dataset page: https://huggingface.co/datasets/Amod/mental_health_counseling_conversations.

A Collection of 120 Psychology Patients with 17 Essential Symptoms to Diagnose Mania Bipolar Disorder, Depressive Bipolar Disorder, Major Depressive Disorder, and Normal Individuals. The dataset contains the 17 essential symptoms psychiatrists use to diagnose the described disorders. The behavioral symptoms are considered the levels of patients Sadness, Exhaustness, Euphoric, Sleep disorder, Mood swings, Suicidal thoughts, Anorexia, Anxiety, Try-explaining, Nervous breakdown, Ignore & Move-on, Admitting mistakes, Overthinking, Aggressive response, Optimism, Sexual activity, and Concentration in a Comma Separated Value (CSV) format. The Normal category refer to the individuals using therapy time for specialized counseling, personal development, and life skill enrichments. While such individuals may also have minor mental problems, they differ from those suffering from Major Depressive Disorder and Bipolar Disorder.

Dataset Card for "heliosbrahma/mental_health_chatbot_dataset"

  Dataset Description





  Dataset Summary

This dataset contains conversational pair of questions and answers in a single text related to Mental Health. Dataset was curated from popular healthcare blogs like WebMD, Mayo Clinic and HeatlhLine, online FAQs etc. All questions and answers have been anonymized to remove any PII data and pre-processed to remove any unwanted characters.

  Languages

The… See the full description on the dataset page: https://huggingface.co/datasets/heliosbrahma/mental_health_chatbot_dataset.

Abstract Creative activities have been used as therapeutic resource for people with mental disorders in Brazil and worldwide. There is a need to consolidate the body of evidence on the subject by incorporating qualitative data and the conceptual model of recovery. This paper presents a systematic review on the effects of art making as therapeutic resource in mental health. The databases PubMED, LILACS and SciELO were searched and studies on the subject that had qualitative approach and were published in English or Portuguese between 2000 and 2013 were selected. Benefits were evident in key aspects of the subjects' rehabilitation process, such as the relief of negative feelings, empowerment and social reintegration, which are fundamental principles of recovery. It was found that art has a significant therapeutic potential in the psychosocial rehabilitation of people with mental disorders and may represent a valuable resource in the current scenario of challenges to mental health care.

Data and R code used for the analysis of data for the publication: Coumoundouros et al., Cognitive behavioural therapy self-help intervention preferences among informal caregivers of adults with chronic kidney disease: an online cross-sectional survey. BMC Nephrology

Summary of study

An online cross-sectional survey for informal caregivers (e.g. family and friends) of people living with chronic kidney disease in the United Kingdom. Study aimed to examine informal caregivers' cognitive behavioural therapy self-help intervention preferences, and describe the caregiving situation (e.g. types of care activities) and informal caregiver's mental health (depression, anxiety and stress symptoms).

Participants were eligible to participate if they were at least 18 years old, lived in the United Kingdom, and provided unpaid care to someone living with chronic kidney disease who was at least 18 years old.

The online survey included questions regarding (1) informal caregiver's characteristics; (2) care recipient's characteristics; (3) intervention preferences (e.g. content, delivery format); and (4) informal caregiver's mental health. Informal caregiver's mental health was assessed using the 21 item Depression, Anxiety, and Stress Scale (DASS-21), which is composed of three subscales measuring depression, anxiety, and stress, respectively.

Sixty-five individuals participated in the survey.

See the published article for full study details.

Description of uploaded files

1. ENTWINE_ESR14_Kidney Carer Survey Data_FULL_2022-08-30: Excel file with the complete, raw survey data. Note: the first half of participant's postal codes was collected, however this data was removed from the uploaded dataset to ensure participant anonymity.

2. ENTWINE_ESR14_Kidney Carer Survey Data_Clean DASS-21 Data_2022-08-30: Excel file with cleaned data for the DASS-21 scale. Data cleaning involved imputation of missing data if participants were missing data for one item within a subscale of the DASS-21. Missing values were imputed by finding the mean of all other items within the relevant subscale.

3. ENTWINE_ESR14_Kidney Carer Survey_KEY_2022-08-30: Excel file with key linking item labels in uploaded datasets with the corresponding survey question.

4. R Code for Kidney Carer Survey_2022-08-30: R file of R code used to analyse survey data.

5. R code for Kidney Carer Survey_PDF_2022-08-30: PDF file of R code used to analyse survey data.

According to a March 2024 survey conducted in the United States, 32 percent of adults reported feeling that social media had neither a positive nor negative effect on their own mental health. Only seven percent of social media users said that online platforms had a very positive effect on their mental health, while 12 percent of users said it had a very negative impact. Furthermore, 22 percent of respondents said social media had a somewhat negative effect on their mental health. Is social media addictive? A 2023 survey of individuals between 11 and 59 years old in the United States found that over 73 percent of TikTok users agreed that the platform was addictive. Furthermore, nearly 27 percent of those surveyed reported experiencing negative psychological effects related to TikTok use. Users belonging to Generation Z were the most likely to say that TikTok is addictive, yet millennials felt the negative effects of using the app more so than Gen Z. In the U.S., it is also not uncommon for social media users to take breaks from using online platforms, and as of March 2024, over a third of adults in the country had done so. Following mental health-related content Although online users may be aware of the negative and addictive aspects of social media, it is also a useful tool for finding supportive content. In a global survey conducted in 2023, 32 percent of social media users followed therapists and mental health professionals on social media. Overall, 24 percent of respondents said that they followed people on social media if they had the same condition as they did. Between January 2020 and March 2023, British actress and model Cara Delevingne was the celebrity mental health activist with the highest growth in searches tying her name to the topic.

The table Publication Metadata is part of the dataset Counseling and Psychotherapy Transcripts: Volume I [full text data], available at https://stanford.redivis.com/datasets/4ew0-9qer43ndg. It contains 70567 rows across 43 variables.

Abstract

This collection contains plain text transcripts of therapy sessions, associated reference works and published narratives, memoirs, and other client narratives. Documents are sourced from Alexander Street Press' Counseling and Psychotherapy Transcripts: Volume I - Counseling and Psychotherapy Transcripts, Client Narratives, and Reference Works. The transcripts of therapy and counseling sessions illustrate a range of therapeutic techniques and practices. The pairing of these transcripts with associated reference works and published narratives, memoirs, and other client narratives enhances the collection's ability to provide insight into the experience of those undergoing therapy and living with mental illness. The dataset contains more than 2,000 session transcripts, 44,000 pages of client narratives, and 25,000 pages of secondary reference material.

Usage

For a complete list of materials, please see PSYC ESR with texts_QA completed by WS 1.7.21.xlsx (under Supporting files).

Under the **Files **tab:

• **Books/ **contains the plain text of books.

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• Transcripts/ contains the plain text of therapy transcripts.

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• **Raw Files/ **contains, where available, the original, scanned copies of books or therapy transcripts, usually as a pdf or series of jpgs.

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Under the **Tables **tab:

• Filter files by relevant features (e.g. School_of_Therapy, Symptoms) in the **Publication Metadata **table.
• Join the **Publication Metadata **extraction with the file indices to select files for export and analysis.

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This publication provides the most timely statistics available relating to NHS funded secondary mental health, learning disabilities and autism services in England. This information will be of use to people needing access to information quickly for operational decision making and other purposes. These statistics are derived from submissions made using version 3.0 of the Mental Health Services Dataset (MHSDS). This edition includes final statistics for March 2019. NHS Digital review the quality and completeness of the submissions used to create these statistics on an ongoing basis. More information about this work can be found in the Accuracy and reliability section of this report. Fully detailed information on the quality and completeness of particular statistics in this release is not available due to the timescales involved in reviewing submissions and engaging with data providers. The information that has been obtained at the time of publication is made available in the Provider Feedback sections of the Data Quality Reports which accompany this release. Information gathered after publication is released in future editions of this publication series. More detailed information on the quality and completeness of these statistics and a summary of how these statistics may be interpreted is made available later in our Mental Health Bulletin: Annual Report publication series. All elements of this publication, other editions of this publication series, and related annual publication series' can be found in the Related Links below. Please note the following: The Quarter 4 Children and Young People Receiving Second Contact With Services measure will not be included in the June 2019 publication. A validation of this data is currently underway; we expect statistics for the full 2018-19 financial year to be published in the July 2019 publication. This publication includes annual statistics for the 2018-19 year: Annual - People in contact with services - April 2018 to March 2019, with age group breakdowns and Annual - People in contact with services with a hospital provider spell - April 2018 to March 2019, with age group breakdowns. Further annual statistics will be published in the annual Mental Health Bulletin in the Autumn. It was intended that data quality statistics for Provisional April 2019 data, collected via the newly introduced Strategic Data Collection Service (SDCS), be published alongside this publication; due to system issues this has not been possible. An update on this will be given alongside the next publication, published July 2019. As part of the update to include the provider XenZone/ Kooth in the Children and Young People Receiving Second Contact With Services measure (MHS69), in the 2019-20 year, Final March 2019 analysis was to be presented here; this was added here 17 July 2019. NHS Digital apologises for any inconvenience caused. The provider breakdown for AMH04 (People in contact with adult mental health services on CPA at the end of RP with HoNOS recorded) has not been included in this publication and will not be included in future publications until the cause is rectified. NHS Digital will inform users once this issue has been resolved. NHS Digital apologises for any inconvenience caused.

######################### Medical scope, Prompt #1 61K instruction PubMED-Unlabeled ###################################################################Instruction: You are a language model specialized in generating JSON or YAML output. Given an instruction, you should generate a valid JSON or YAML object according to the provided guidelines. Your output should conform to the following JSON format: { "key1": "value1", "key2": "value2", ... } Make sure to adhere to the specified key-value pairs and maintain the correct syntax throughout your response. Your goal is to generate accurate and properly structured JSON or YAML output in response to the given instructions withoutany extra comment. Input: As a doctor that only speak in JSON, provide a "answer", "context and "keywords" about following question: Is naturopathy as effective as conventional therapy for treatment of menopausal symptoms? Output:{"answer" :Naturopathy appears to be an effective alternative for relief of specific menopausal symptoms compared to conventional therapy.,"context" :Although the use of alternative medicine in the United States is increasing, no published studies have documented the effectiveness of naturopathy for treatment of menopausal symptoms compared to women receiving conventional therapy in the clinical setting."keywords" :['Anxiety', 'Cohort Studies', 'Confidence Intervals', 'Estrogen Replacement Therapy', 'Female', 'Health Status', 'Hot Flashes', 'Humans', 'Menopause', 'Middle Aged','Naturopathy', 'Odds Ratio', 'Patient Satisfaction', 'Retrospective Studies', 'Risk Factors', 'Severity of Illness Index', 'Sleep Initiation and Maintenance Disorders','Surveys and Questionnaires', 'Time Factors', 'Urinary Incontinence', 'Vaginal Diseases', 'Washington']} ############################### Medical scope, Prompt #2 symptom-disease dataset 1K instruction ######################################################Instruction: You are a language model specialized in generating JSON or YAML output. Given an instruction, you should generate a valid JSON or YAML object according to theprovided guidelines. Your output should conform to the following JSON format: { "key1": "value1", "key2": "value2", ... } Make sure to adhere to the specified key-value pairs and maintain the correct syntax throughout your response. Your goal is to generate accurate and properly structured JSON or YAML output in response to the given instructions without any extra comment. Input: You are a doctor that only speak in JSON. Do not output that is'nt properly formated JSON. Provide following information about Panic disorder disease. Fill information about "symptom", "reason", "TestsAndProcedures" and "commonMedications" about Panic disorder disease in JSON format. Output: {"symptom" :['Anxiety and nervousness', 'Depression', 'Shortness of breath', 'Depressive or psychotic symptoms', 'Sharp chest pain', 'Dizziness', 'Insomnia', 'Abnormal involuntary movements', 'Chest tightness', 'Palpitations', 'Irregular heartbeat', 'Breathing fast'],"reason" :Panic disorder is an anxiety disorder characterized by recurring severe panic attacks. It may also include significant behavioral changes lasting at least a month and of ongoing worry about the implications or concern about having other attacks. The latter are called anticipatory attacks (DSM-IVR). Panic disorder is not the same as agoraphobia (fear of public places), although many afflicted with panic disorder also suffer from agoraphobia. Panic attacks cannot be predicted, therefore an individual may become stressed, anxious or worried wondering when the next panic attack will occur. Panic disorder may be differentiated as a medical condition, or chemical imbalance. The DSM-IV-TR describes panic disorder and anxiety differently. Whereas anxiety is preceded by chronic stressors which build to reactions of moderate intensity that can last for days, weeks or months, panic attacks are acute events triggered by a sudden, out-of-the-blue cause: duration is short and symptoms are more intense. Panic attacks can occur in children, as well as adults. Panic in young people may be particularly distressing because children tend to have less insight about what is happening, and parents are also likely to experience distress when attacks occur. "TestsAndProcedures" : ['Psychotherapy', 'Mental health counseling', 'Electrocardiogram', 'Depression screen (Depression screening)', 'Toxicology screen', 'Psychological and psychiatric evaluation and therapy']"commonMedications" : ['Lorazepam', 'Alprazolam (Xanax)', 'Clonazepam', 'Paroxetine (Paxil)', 'Venlafaxine (Effexor)', 'Mirtazapine', 'Buspirone (Buspar)', 'Fluvoxamine (Luvox)', 'Imipramine', 'Desvenlafaxine (Pristiq)', 'Clomipramine', 'Acamprosate (Campral)']} ############################### Medical scope, Prompt #3 194K instruction MED-MCQA dataset ######################################################Instruction: You are a language model specialized in generating JSON or YAML output. Given an instruction, you should generate a valid JSON or YAML object according to the provided guidelines. Your output should conform to the following JSON format: { "key1": "value1", "key2": "value2", ... } Make sure to adhere to the specified key-value pairs and maintain the correct syntax throughout your response. Your goal is to generate accurate and properly structured JSON or YAML output in response to the given instructions without any extra comment. Input: You are a medical teacher that only speak in JSON. Do not output that is'nt properly formated JSON. Generate a multichoice question and answer inAnatomy field and Urinary tract topic with following format: { "question": "expresion" , "OPA": "expresion", "OPB" : "expresion", "OPC": "expresion","OPD": "expresion", "Answer": "3"}. Output: { "question": Chronic urethral obstruction due to benign prismatic hyperplasia can lead to the following change in kidney parenchyma, "opa": Hyperplasia, "opb": Hyperophy, "opc": Atrophy, "opd": Dyplasia, "Answer": 2. ############################### Finance scope, Prompt #4 38K instruction ######################################################Instruction: You are a language model specialized in generating JSON or YAML output. Given an instruction, you should generate a valid JSON or YAML object according to the provided guidelines. Your output should conform to the following JSON format: { "key1": "value1", "key2": "value2", ... } Make sure to adhere to the specified key-value pairs and maintain the correct syntax throughout your response. Your goal is to generate accurate and properly structured JSON or YAML output in response to the given instructions without any extra comment. Input: You are a financial news analyzer that only speaks in JSON. Do not output that isn't properly formatted JSON. Analyze this news title "Here Why Bitcoin is Likely to See Historic Volatility in the Next Few Days". Provide sentiment as a probability distribution also indicate target market and related asset to the news title in JSON format. Output:{"sentiment": {"positive": 0.4463904500007629, "negative": 0.06607405841350555,"neutral":0.4875355064868927}, "market": "cryptocurrency" , "relatedAsset": ['BTC/USDT']}.

The dataset on 803 engineering students from 34 universities of Bangladesh provides a comprehensive insight into various aspects of their lives, encompassing demographic information, lifestyle choices, social media habits, educational concerns, family dynamics, personal relationships, past experiences, and mental health (Major Depressive Disorder) indicators. Here is a breakdown of the key variables: Demographic Information: Age, Gender, Department, Relationship/Marital status, Area of living, Socio-economic status (family), Current living arrangement, Year of study Lifestyle: Religious practices, Exercise habits, Sleep-related issues, Satisfaction with sleep quality, Smoking habits, Drinking (alcohol) habits Social Media Addiction: Eagerness to use social media, Morning routine involving social media, Productivity impact due to social media, Quest for internet connectivity for social media, Purposeless use of social media, Late-night social media activity Educational Issue: Lack of concentration during classes, Worries about academic performance, Concerns about job prospects after graduation, Preoccupation with future after university life, Lack of self-confidence Family Issue: Parental misunderstandings, Belonging to a broken family, Relationship status with family members, Sharing feelings of depression with family Personal Relationship: Current status of the romantic relationship, Relationship-induced stress, Relief when partner isn't around Diminished joy in favorite activities due to the relationship, Consideration of breaking up for mental health preservation Past Experience: History of mental disorder diagnosis, Previous consultation with therapists/psychologists, Childhood problems (abuse, early loss of parent), Past experiences of bullying Major Depressive Disorder: The dataset concludes with a series of questions (following PHQ-9) related to the diagnostic criteria for Major Depressive Disorder, encompassing feelings of sadness, loss of interest, sleep disturbances, fatigue, changes in appetite, negative self-perception, concentration issues, psychomotor changes, and suicidal thoughts.

Overall, this dataset provides a holistic understanding of the students' lives, shedding light on both everyday aspects and potential mental health challenges. Researchers and analysts can use this information to explore correlations, patterns, and potential intervention strategies in the context of engineering students in Bangladesh.

This publication contains the official statistics about uses of the Mental Health Act ('the Act') in England during 2023-24. Under the Act, people with a mental disorder may be formally detained in hospital (or 'sectioned') in the interests of their own health or safety, or for the protection of other people. They can also be treated in the community but subject to recall to hospital for assessment and/or treatment under a Community Treatment Order (CTO). In 2016-17, the way we source and produce these statistics changed. Previously these statistics were produced from the KP90 aggregate data collection. They are now primarily produced from the Mental Health Services Data Set (MHSDS). The MHSDS provides a much richer data source for these statistics, allowing for new insights into uses of the Act. People may be detained in secure psychiatric hospitals, other NHS Trusts or at Independent Service Providers (ISPs). All organisations that detain people under the Act must be registered with the Care Quality Commission (CQC). In recent years, the number of detentions under the Act have been rising. An independent review has examined how the Act is used and has made recommendations for improving the Mental Health Act legislation. In responding to the review, the government said it would introduce a new Mental Health Bill to reform practice. This publication does not cover: 1. People in hospital voluntarily for mental health treatment, as they have not been detained under the Act (see the Mental Health Bulletin). 2. Uses of section 136 where the place of safety was a police station; these are published by the Home Office.

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 Adult Psychiatric Morbidity Survey, 2007 (APMS 2007) is the third survey of psychiatric morbidity in adults living in private households. The main aim of the survey was to collect data on poor mental health among adults aged 16 and over living in private households in England. The specific objectives of the survey were:to estimate the prevalence of psychiatric morbidity according to diagnostic category in the adult household population of England. The survey included assessment of common mental disorders; psychosis; borderline and antisocial personality disorder; Asperger syndrome, substance misuse and dependency; and suicidal thoughts, attempts and self-harmto screen for characteristics of eating disorder, attention deficit hyperactivity disorder, posttraumatic stress disorder, and problem gamblingto examine trends in the psychiatric disorders that have been included in previous survey years (1993 and 2000) to identify the nature and extent of social disadvantage associated with mental illnessto gauge the level and nature of service use in relation to mental health problems, with an emphasis on primary care to collect data on key current and lifetime factors that might be associated with mental health problems, such as experience of stressful life events, abusive relationships, and work stressto collect data on factors that might be protective against poor mental health, such as social support networks and neighbourhood cohesion Further information can be found on the Information Centre for Health and Social Care survey web page. For the fourth edition (September 2017), three new weighting variables were added to the data, to be used for analysis when combining the 2007 and 2014 APMS datasets (the 2014 survey is not yet available from the UK Data Service). In addition, derived alcohol variables DVAudit1, AUDITgp, SADQCSC, SADQGP, AUDSAD2, AUDSAD3 and DRNKPROB were replaced to correct previous errors. The documentation has also been updated to cover these changes. Main Topics: Topics covered include: general health and health conditions; activities of daily living; caring responsibilities; service use and medication; self-perceived height and weight (for calculation of BMI); common mental disorders; suicidal behaviour and self-harm; psychosis screening questionnaire; attention deficit hyperactivity disorder; work related stress; smoking; drinking; drug use; personality disorder and social functioning; problem gambling; Asperger syndrome; post traumatic stress disorder and military experience; domestic violence and abuse; eating disorder; discrimination and sexual identity; intellectual functioning (TICS-M, National Adult Reading Test, Animal naming test); stressful life events; social support networks; parenting; religion and spirituality; social capital and participation; socio-demographics. Standard Measures CIS-R: revised Clinical Interview Schedule SCID-II: Structured Clinical Interview for DSM-IV AUDIT: Alcohol Use Disorders Identification Test SADQ-C: Severity of Alcohol Dependence Questionnaire SF-12: General health NART: National Adult Reading Test TICS-m: modified Telephone Interview for Cognitive Screening. Multi-stage stratified random sample Face-to-face interview Self-completion 2006 2007 ADULTS AGE AGGRESSIVENESS ALCOHOL USE ALCOHOLIC DRINKS ALCOHOLISM ALLERGIES AMPHETAMINES ANABOLIC STEROIDS ANGER ANTHROPOMETRIC DATA ANTISOCIAL BEHAVIOUR ANXIETY ANXIETY DISORDERS ARTHRITIS ASPERGERS SYNDROME ASSAULT ASTHMA AUTISM SPECTRUM DIS... BACTERIAL AND VIRUS... BEDROOMS BEHAVIOURAL DISORDERS BEREAVEMENT BRONCHITIS BUILDING MAINTENANCE BULLYING CANCER CANNABIS CARE IN THE COMMUNITY CARE OF DEPENDANTS CARERS BENEFITS CHILD BENEFITS CHRONIC ILLNESS COCAINE COGNITION DISORDERS COHABITATION CONCENTRATION COUNSELLING COUNSELLORS DAY CARE DEBILITATIVE ILLNESS DEBTS DEMENTIA DEPRESSION DIABETES DIGESTIVE SYSTEM DI... DISABILITIES DISABLED FACILITIES DISCRIMINATION DISEASES DOMESTIC VIOLENCE DRINKING OFFENCES DRUG ABUSE DRUG ADDICTION DRUG PSYCHOTHERAPY ... DRUG SIDE EFFECTS DRUG USE EATING DISORDERS ECONOMIC ACTIVITY ECSTASY DRUG EDUCATIONAL BACKGROUND EMOTIONAL DISTURBANCES EMOTIONAL STATES EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES EPILEPSY ETHNIC GROUPS EVERYDAY LIFE England FAMILY BENEFITS FAMILY ENVIRONMENT FAMILY MEMBERS FATIGUE PHYSIOLOGY FEAR FINANCIAL DIFFICULTIES FINANCIAL RESOURCES FRIENDS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GAMBLING GENDER GENERAL PRACTITIONERS HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH SERVICES HEARING IMPAIRMENTS HEART DISEASES HEATING SYSTEMS HEIGHT PHYSIOLOGY HEROIN HOME HELP HOMELESSNESS HOSPITAL OUTPATIENT... HOSPITAL SERVICES HOSPITALIZATION HOURS OF WORK HOUSEHOLD INCOME HOUSEHOLDS HOUSING HOUSING AGE HOUSING CONDITIONS HOUSING TENURE Health Health care service... ILL HEALTH INCOME INDUSTRIES INFORMAL CARE INJURIES INTERPERSONAL CONFLICT INTERPERSONAL RELAT... JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS LEARNING DISABILITIES LEISURE TIME ACTIVI... LIFE EVENTS LIVING CONDITIONS LONELINESS LSD DRUG MAGIC MUSHROOMS MARITAL STATUS MATERNITY BENEFITS MEDICAL CARE MEDICAL DIAGNOSIS MEDICAL HISTORY MEDICAL PRESCRIPTIONS MEDICAL TREATMENT M... MEDICINAL DRUGS MEMORY MEMORY DISORDERS MENTAL DISORDERS MENTAL HEALTH METHADONE MIGRAINES MILITARY PERSONNEL MORAL CONCEPTS MORBIDITY MOTOR PROCESSES Morbidity and morta... NEIGHBOURHOODS NERVOUS SYSTEM DISE... NEUROTIC DISORDERS NURSES OBSESSIVE COMPULSIV... OCCUPATIONAL ACCIDE... OCCUPATIONAL THERAPY OCCUPATIONS PAIN PARENTS PART TIME EMPLOYMENT PATIENTS PERSONAL DEBT REPAY... PHOBIAS PHYSICAL MOBILITY PHYSICIANS PREGNANCY PRESCRIPTION DRUGS PSYCHIATRISTS PSYCHOLOGICAL EFFECTS PSYCHOLOGISTS PSYCHOTHERAPY PSYCHOTIC DISORDERS QUALIFICATIONS READING TESTS RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RELIGIOUS BELIEFS RESPIRATORY TRACT D... RHEUMATIC DISEASES SELF EMPLOYED SELF ESTEEM SELF HARM SELF HELP GROUPS SENILE DEMENTIA SENSORY IMPAIRMENTS SEXUAL ABUSE SEXUAL ASSAULT SEXUAL OFFENCES SEXUALITY SHELTERED EMPLOYMENT SICK LEAVE SICK PAY SICKNESS AND DISABI... SKIN DISEASES SLEEP SLEEP DISORDERS SLIMMING DIETS SMOKING SMOKING CESSATION SOCIAL CAPITAL SOCIAL INTEGRATION SOCIAL NETWORKS SOCIAL PARTICIPATION SOCIAL SECURITY BEN... SOCIAL SUPPORT SOCIAL WORKERS SOLVENT ABUSE SORROW SPINAL DISORDERS STANDARD OF LIVING STATE RETIREMENT PE... STATUS IN EMPLOYMENT STOMACH DISORDERS STRESS PSYCHOLOGICAL SUBSTANCE USE SUICIDE SUPERVISORS SUPERVISORY STATUS SYMPTOMS Specific social ser... TEETOTALISM TERMINATION OF SERVICE TIED HOUSING TRAFFIC OFFENCES TRANQUILLIZERS TRAUMA PSYCHOLOGICAL UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... UNWAGED WORKERS VASCULAR DISEASES VISION IMPAIRMENTS WAR VETERANS BENEFITS WEIGHT PHYSIOLOGY WORK LIFE BALANCE WORKING CONDITIONS

This data was collected as part of a Master of Research in Anthropology exploring the medicalisation of companion animals in Australia. Ethnographic data was collected along with interviews.The data set contains the transcripts of interviews conducted with individuals involved in animal-assisted therapy, who have a service animal, or believe their companion animals significantly impact their mental health.Further research outputs by Katherine Fletcher use this data to discuss the intersubjective relationships between humans and their companion animals, the complexities of these relationships, and the ethical considerations of using another lively social creature as an instrument of therapy.The data has been de-identified.Unspecified consent was obtained by the research participants for data to be used in future research projects.Data context:This data was collected in various locations of the Central Coast NSW Australia.This data was collected to answer a research question: What is the lived experience of people who utilise their relationship with companion species to better their mental health? This was an anthropological project and utilised ethnographic methods, observations and phenomenological theories.Abstract of masters thesis:In modern Australian society, viewing negative human experiences as pathological events is becoming increasingly common. Experiences of suffering, trauma, stress, poverty, neurodivergence and anxiety are conceptualised in terms of clinical disorders, treatable through medical interventions. Human interactions with companion animals have also been medicalised through animal-assisted therapy, service animals, and individually proclaimed ‘emotional support animals’. In the process, interactions with non-humans have been commodified, researched, and medically sanctioned for their utility for human mental health. Yet, while these companions play a hugely significant role in human lives, their relationship to human health is more complicated and ambiguous than clinical psychological models allow. Medical literature often reduces the agency, individualism, and contextual behaviour of non-human species in favour of finding a statistically significant connection between the reduction of pathological symptoms and various human-animal interactions. Critiquing this project, this thesis explores the experience of living, healing, and suffering with non-human companions through a phenomenological lens. It looks beyond clinical psychological models to explore the intersubjective encounters, lively responses, and inevitable conflicts between different social species. Interactions with companion species can allow people to view themselves from different perspectives and undergo animal-motivated self alteration. However, multispecies healing experiences are subjective. They involve an intersection of particular bonds between entities, the interests of the animals, and the attitudes and expectations of humans. Our shared mortality and sociality bind humans and our companion animals together but also create conflicts, existential suffering, and change.Data processing declaration:This data has been processed to ensure the anonymity of the research participants.Details such as names, ages, and locations have been omitted or changed.Some data has been intentionally left out as it cannot be anonymised and still reflect a true research context. This data includes details surrounding medical diagnosis, medication regimes, and specific event details.Please be aware that if you intend to use this data in your research, these anonymising details may change certain aspects of your research results.The words of participants remain as unchanged as possible to ensure the sentiment of their words and their experiences can be used accurately within other research projects.

The HealthLink BC Mental Health and Substance Use (MHSU) data set includes the following: Programs that offer early intervention, transitional care or other services that supplement and facilitate primary and adjunctive therapies; which offer community mental health education programs; or which link people who are in need of treatment with appropriate providers. Programs that provide preventive, diagnostic and treatment services in a variety of community and hospital-based settings to help people achieve, maintain and enhance a state of emotional well-being, personal empowerment and the skills to cope with everyday demands without excessive stress or reliance on alcohol or other drugs. Treatment may include emotional support, introspection and problem-solving assistance using a variety of modalities and approaches, and medication, as needed, for individuals who have a substance use disorder involving alcohol and/or other drugs or for people who range from experiencing difficult life transitions or problems in coping with daily living to those with severe, chronic mental illnesses that seriously impact their lives. Multidisciplinary programs, often offered on an inpatient basis with post-discharge outpatient therapy, that provide comprehensive diagnostic and treatment services for individuals who have anorexia nervosa, binge-eating disorder, bulimia or a related eating disorder. Treatment depends on the specific type of eating disorder involved but typically involves psychotherapy, nutrition education, family counseling, medication and hospitalization, if required, to stabilize the patient's health. Alliance of Information & Referral Systems (AIRS) / 211 LA County taxonomy is the data classification used for all HealthLink BC directory data, including this MHSU data set (https://www.airs.org/i4a/pages/index.cfm?pageid=1). AIRS taxonomy and data definitions are protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)

BackgroundSingle-session mental health interventions are frequently attended by children and young people (CYP) in both web-based and face-to-face therapy settings. The Session “Wants” and “Needs” Outcome Measure (SWAN-OM) is an instrument developed in a web-based therapy service to overcome the challenges of collecting outcomes and experiences of single-session therapies (SSTs). It provides pre-defined goals for the session, selected by the young person prior to the intervention, on which progress toward achievement is scored at the end of the session.ObjectiveThe objective of this study was to evaluate the instrument's psychometric properties, including concurrent validity against three other frequently used outcome and experience measures, at a web-based and text-based mental health service.MethodsThe SWAN-OM was administered for a period of 6 months to 1,401 CYP (aged 10–32 years; 79.3% white; 77.59% female) accessing SST on a web-based service. Item correlations with comparator measures and hierarchical logistic regressions to predict item selection were calculated for concurrent validity and psychometric exploration.ResultsThe most frequently selected items were “Feel better” (N = 431; 11.61%) and “Find ways I can help myself” (N = 411; 11.07%); unpopular items were “Feel safe in my relationships” (N = 53; 1.43%) and “Learn the steps to achieve something I want” (N = 58; 1.56%). The SWAN-OM was significantly correlated with the Experience of Service Questionnaire, particularly the item “Feel better” [rs(109) = 0.48, p < 0.001], the Youth Counseling Impact Scale, particularly the item “Learn the steps to achieve something I want” [rs(22) = 0.76, p < 0.001], and the Positive and Negative Affect Schedule, particularly the items “Learn how to feel better” [rs(22) = 0.72, p < 0.001] and “Explore how I feel” [rs(70) = −0.44, p < 0.001].ConclusionThe SWAN-OM demonstrates good concurrent validity with common measures of outcome and experience. Analysis suggests that lesser-endorsed items may be removed in future iterations of the measure to improve functionality. Future research is required to explore SWAN-OM's potential to measure meaningful change in a range of therapeutic settings.

Australia’s headspace initiative is world-leading in nation-wide youth mental healthcare reform for young people aged 12 to 25 years, now with 16 years of implementation. This paper examines changes in the key outcomes of psychological distress, psychosocial functioning, and quality of life for young people accessing headspace centres across Australia for mental health problems. Routinely collected data from headspace clients commencing an episode of care within the data collection period, 1 April 2019 to 30 March 2020, and at 90-day follow-up were analysed. Participants came from the 108 fully-established headspace centres across Australia, and comprised 58,233 young people aged 12–25 years first accessing headspace centres for mental health problems during the data collection period. Main outcome measures were self-reported psychological distress and quality of life, and clinician-reported social and occupational functioning. Most headspace mental health clients presented with depression and anxiety issues (75.21%). There were 35.27% with a diagnosis: overall, 21.74% diagnosed with anxiety, 18.51% with depression, and 8.60% were sub-syndromal. Younger males were more likely to present for anger issues. Cognitive behavioural therapy was the most common treatment. There were significant improvements in all outcome scores over time (P

The experimental figures presented in this annual report provide a picture of activity in Improving Access to Psychological Therapies (IAPT) services and of the people that used them in 2013-14. The IAPT programme is designed to provide services for those experiencing anxiety and depressive disorders and the purpose of the IAPT dataset is to support reporting on the treatment of these individuals. Locally IAPT services may have expanded to treat other psychological disorders. The information presented uses version one of the IAPT dataset, which was first reported on in quarter one of 2012-13. The report also uses the latest (mid-2013) population estimates from the Office for National Statistics.

The data is comprised of transcripts of conversations (approximately 45 minutes in length) that were conducted with mental health professionals. These professionals (therapists, clinical psychologists and doctors), as well as charity workers, were asked to critique concepts and prototypes from a digital design event that sought to create digital tools for individuals affected by self-harm.

The HealthLink BC Mental Health and Substance Use (MHSU) data set includes the following: Programs that offer early intervention, transitional care or other services that supplement and facilitate primary and adjunctive therapies; which offer community mental health education programs; or which link people who are in need of treatment with appropriate providers. Programs that provide preventive, diagnostic and treatment services in a variety of community and hospital-based settings to help people achieve, maintain and enhance a state of emotional well-being, personal empowerment and the skills to cope with everyday demands without excessive stress or reliance on alcohol or other drugs. Treatment may include emotional support, introspection and problem-solving assistance using a variety of modalities and approaches, and medication, as needed, for individuals who have a substance use disorder involving alcohol and/or other drugs or for people who range from experiencing difficult life transitions or problems in coping with daily living to those with severe, chronic mental illnesses that seriously impact their lives. Multidisciplinary programs, often offered on an inpatient basis with post-discharge outpatient therapy, that provide comprehensive diagnostic and treatment services for individuals who have anorexia nervosa, binge-eating disorder, bulimia or a related eating disorder. Treatment depends on the specific type of eating disorder involved but typically involves psychotherapy, nutrition education, family counseling, medication and hospitalization, if required, to stabilize the patient's health. Alliance of Information & Referral Systems (AIRS) / 211 LA County taxonomy is the data classification used for all HealthLink BC directory data, including this MHSU data set (https://www.airs.org/i4a/pages/index.cfm?pageid=1). AIRS taxonomy and data definitions are protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)