In Spring 2020, around 40.9 percent of college students in the United States reported having depression, compared to 35.7 percent in Fall 2019. This statistic illustrates the prevalence of select mental health and substance use issues among college students in the United States in Fall 2019 and Spring 2020.

High rates of mental ill-health in postgraduate researchers (PGRs) represent a significant barrier to life satisfaction and academic success. Nevertheless, there is little knowledge about the extent and origins of mental health problems of PGRs in the UK. The current study addresses this gap by assessing investigating the prevalence and provenance of anxiety, depression, sleep problems, subjective mental wellbeing, and suicide behaviours of PGRs in the UK. An online survey (N=479) was used to measure the mental health outcomes and assess their relationship with influence of demographic, trait and academic variables, and social support. We found a high prevalence of mental ill-health and low levels of wellbeing in the current sample. Factors associated with poorer outcomes were female and non-binary gender, non-heterosexual identity, maladaptive perfectionism, workaholism and being in the 5th year of study or above. Resilience, adaptive perfectionism, higher levels of social support and positive evaluations of progress and preparation, departmental climate, and supervisory relationship were associated with more positive outcomes. The current findings contribute new knowledge about the prevalence of mental health symptoms in PGRs in the UK, implying that institutional efforts to improve PGR wellbeing should include strategies to promote equality, diversity, resilience, integration and work-life balance of PGRs.

A survey of college students in the United States in 2023-2024 found that around 38 percent had symptoms of depression. Symptoms of depression vary in severity and can include a loss of interest/pleasure in things once found enjoyable, feelings of sadness and hopelessness, fatigue, changes in sleep, and thoughts of death or suicide. Mental health among college students Due to the life changes and stress that often come with attending college, mental health problems are not unusual among college students. The most common mental health problems college students have been diagnosed with are anxiety disorders and depression. Fortunately, these are two of the most treatable forms of mental illness, with psychotherapy and/or medications the most frequent means of treatment. However, barriers to access mental health services persist, with around 22 percent of college students stating that in the past year financial reasons caused them to receive fewer services for their mental or emotional health than they would have otherwise received. Depression in the United States Depression is not only a problem among college students but affects people of all ages. In 2021, around ten percent of those aged 26 to 49 years in the United States reported a major depressive episode in the past year. Depression in the United States is more prevalent among females than males, but suicide is almost four times more common among males than females. Death rates due to suicide in the U.S. have increased for both genders in the past few years, highlighting the issue of depression and other mental health disorders and the need for easy access to mental health services.

This study examined commonly endured mental health challenges among emerging adults in college before, during, and after the COVID-19 pandemic. In this repeated cross-sectional study, different samples of undergraduates 18-26 years old were recruited from a large public university during pre-pandemic (Fall 2019, N=500), pandemic onset (Spring 2020, N=420), academic year 1 (Fall 2020-Spring 2021, N=700), academic year 2 (Fall 2021-Spring 2022, N=1,195), academic year 3 (Fall 2022-Spring 2023, N=1,004), and post-pandemic (Fall 2023, N=516). Participants completed an online survey assessing stress (Perceived Stress Scale-10), depression (Patient Health Questionnaire-8), and anxiety (Generalized Anxiety Disorder-7) symptoms.

In 2019, ** percent of young people surveyed in the United Kingdom stated that pressure to do well in school or collage has had a significant impact on their mental health. Additionally, ** percent of respondents say that worrying about how they looked caused an impact on their mental health.

The College Experience Study represents the most extensive longitudinal mobile sensing study to date, leveraging passive and automatic sensing data from the smartphones of over 200 Dartmouth students across five years (2017 - 2022). This groundbreaking research aimed to assess their mental health (e.g., depression, stress), the impact of COVID-19, and general behavioral trends.

The study's importance has been magnified during the global pandemic, necessitating a better understanding of mental health dynamics among undergraduate students throughout their college years. By tracking two cohorts of first-year students both on and off campus, we have accumulated a rich dataset offering insights into changing behaviors, resilience, and mental health in college life. We hope that this dataset will serve as a cornerstone for researchers, educators, and policymakers alike, seeking to enhance their understanding and interventions related to student mental health and behavior.

This dataset is unique for several reasons. It encompasses deep phone sensing data and self-reports spanning four continuous years for 200 undergraduate students at Dartmouth College, both during term time and breaks. Additionally, it incorporates periodic brain-imaging data for this cohort of students, along with surveys. The College Experience dataset enables researchers to explore numerous issues in behavioral sensing and brain imaging to advance our understanding of college students' mental health.

:rocket: Updates

• Apr 15th 2025: Raw app usage (i.e., list of running apps) is now available.
• Dec 5th 2024: Raw call logs, sms logs, and unlocks are now available.
• Oct 27th 2024: Raw sensing data will be released in batches over the next few weeks!

Content

College Experience Study makes use of the StudentLife app, developed for Android and iOS, autonomously capturing a variety of human behaviors 24/7, including:

• Bed time, wake up time, and sleep duration
• The number of conversations and the duration of each conversation per day (Android only)
• Physical activity (walking, sitting, running, standing)
• Locations visited and duration of stay (e.g., dorm, class, party, gym)
• Stress levels over weeks and throughout college
• App usage (Android only)
• COVID concern
• and more

In addition to passive sensing data, our study also involved gathering responses from detailed surveys and conducting brain scans throughout the research period. These diverse data sources can be used together to uncover insightful correlations and draw meaningful conclusions. An illustrative example of this potential is explored in the study "Predicting Brain Functional Connectivity Using Mobile Sensing", which demonstrates how mobile sensing data can predict brain functional connectivity, offering new avenues for understanding mental health conditions.

Data Availability

Note: Some features are exclusive to Android phones. Each folder includes a data definition file detailing the features and their availability across Android and iOS. Also, note that some features like conversation tracking initially covered both user groups but were later restricted due to iOS policy changes so they might be available for iOS users only during the beginning of the study.

For more details, refer to the College Experience Study paper and the original StudentLife website.

Term Definitions and Academic Calendars

For additional context and understanding of the timeline relevant to the dataset, below are the archived links to Dartmouth College's calendars. These archives provide an overview and detailed breakdown of significant dates for each academic year covered by the study:

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

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.

Objective: This study aimed to understand Black American women’s attitudes toward seeking mental health services and using mobile technology to receive support for managing anxiety and depression. Methods: A self-administered web-based questionnaire was launched in October 2019 and closed in January 2020. Women who identify as Black/African American were eligible to participate. The survey consisted of approximately 70 questions and covered topics such as attitudes toward seeking professional psychological help, acceptability of using a mobile phone to receive mental health care, and screening for anxiety and depression. Results - Anxiety: The findings of the study (N=395) showed that younger Black women were more likely to have greater severity of anxiety than their older counterparts. Respondents were most comfortable with the use of a voice call or video call to communicate with a professional to receive support to manage anxiety in comparison to text messaging or mobile app. Younger..., , , This README file was generated on 2023-10-04 by Dr. Terika McCall.

GENERAL INFORMATION

1. Title of Dataset: Attitudes Toward Seeking Mental Health Services and Use of Mobile Technology Survey.
2. Author Information A. Principal Investigator Contact Information Name: Terika McCall Institution: Division of Health Informatics, Department of Biostatistics, Yale School of Public Health Address: 60 College Street, New Haven, CT, 06510, United States Email: terika.mccall@yale.edu
3. Date of data collection (single date, range, approximate date): October 2019 to January 2020
4. Geographic location of data collection: United States
5. Information about funding sources that supported the collection of the data: RO1 LM013477, T15 LM012500

SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: None

2. Links to publications that cite or use the data:

   McCall T, Foster M, Schwartz TA. Attitudes toward seeking mental health services and mobile techno...

The Baromètre Santé Jeune (BSJ) is a survey whose aim is to improve our knowledge of the health and health behaviors of young people enrolled in middle and high schools in New Caledonia.

This dataset presents the results of the second edition, carried out in 2019 by the Agence sanitaire et sociale de Nouvelle-Calédonie (ASS-NC).The survey was carried out throughout the territory on a random sample of the population of young people attending secondary school. Data were collected via a self-administered questionnaire administered on a touch-sensitive tablet. In addition to socio-demographic characteristics, the questionnaire covered 10 health topics:diet physical activity and sedentariness addictions and use of psychoactive substances violence and risky driving oral and dental health sexual behavior mental health family and school life health status and access to care perception of environmental risk.

As the sample size for the Northern provinces and Loyalty Islands was over-represented in relation to its actual distribution, the raw sample is not representative of the NC middle and high school population. The statistical weight of individuals was therefore adjusted by margin calibration (province cross-referenced with gender, cross-referenced with age, cross-referenced with school sector) based on data from the Vice-Rectorat. Statistical analyses based on this file must therefore take into account the weights assigned to each individual ("Pond" column) in all calculations.. In compliance with the GDPR, sensitive and personal data have been blacked out.

BDD_FINALE_BSJ2019_DATAGOUV.csv : the results file in CSV formatQuestionnaire_BSJ_2019_VF.pdf : the BSJ-2019 questionnaire barometre-sante-jeune-2019.pdf : the BSJ-2019 report with objectives, protocol and results/li>annexe-des-tableaux.pdf : table appendixes barometre-2019-page-accueil.pdf :the explanatory sheet for understanding the content of the summary sheetsFICHES de SYNTHÈSE BSJ2019 VF.pdf : BSJ-2019 summary sheets

The COVID-19 pandemic was a substantial stressor, especially for pregnant individuals.

• This Dataset aimed to understand the impact of COVID-19-related stresses on pregnant individuals and their infants and collected survey-based data across Canada as part of the Pregnancy during the COVID-19 Pandemic (PdP) project.

• Here are some information about the data:

• Maternal_Age: Maternal age (years) at intake

• Household_Income: What is the total household income, before taxes and deductions, of all the household members from all sources in 2019

• Maternal_Education: Maternal education 1- Less than high school 2- diploma 3- High school diploma 4- College/trade school 5- Undergraduate degree 6- Master's degree 7- Doctoral Degree

• EPDS: Edinburgh Postnatal Depression Scale (you can find the survey on the internet)

• PROMIS_Anxiety: Score from 7 to 35 with higher scores indicating greater severity of anxiety.

• GAbirth: Gestational age at birth (in weeks)

• Delivery_Date: Delivery Date (Dates converted to month/year of birth)

• Birth_Length: Birth length in cm

• Birth_Weight: Birth weight in grams

• Delivery_Mode: Vaginally or Caesarean-section (c-section)

• NICU_stay: Was your infant admitted to the NICU?

• Language: Survey language

• Threaten_Life: How much do (did) you think your life is (was) in danger during the COVID-19 pandemic? (0-100)

• Threaten_Baby_Danger: How much do (did) you think your unborn baby's life is (was) in danger at any time during the COVID-19 pandemic? (0-100)

• Threaten_Baby_Harm: How much are you worried that exposure to the COVID-19 virus will harm your unborn baby? (0-100)

I hope you find it useful

IntroductionPsychological wellbeing in university students is receiving increased focus. However, to date, few longitudinal studies in this population have been conducted. As such, in 2019, we established the Student Wellbeing At Northern England Universities (SWANS) cohort at the University of York, United Kingdom aiming to measure student mental health and wellbeing every six months. Furthermore, the study period included the COVID-19 pandemic, giving an opportunity to track student wellbeing over time, including over the pandemic.MethodsEligible participants were invited to participate via email. Data were collected, using Qualtrics, from September 2019 to April 2021, across five waves (W1 to W5). In total, n = 4,622 students participated in at least one wave of the survey. Data collection included sociodemographic, educational, personality measures, and mental health and wellbeing. Latent profile analyses were performed, exploring trajectories of student wellbeing over the study period for those who had completed at least three of the five waves of the survey (n = 765), as measured by the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS).ResultsFive latent profile trajectories of student wellbeing were identified. Of these, the two latent classes with initially higher wellbeing scores had broadly stable wellbeing across time (total n = 505, 66%). Two classes had lower initial scores, which lowered further across time (total n = 227, 30%). Additionally, a fifth class of students was identified who improved substantially over the study period, from a mean WEMWBS of 30.4 at W1, to 49.4 at W5 (n = 33, 4%). Risk factors for having less favourable wellbeing trajectories generally included identifying as LGBT+, self-declaring a disability, or previously being diagnosed with a mental health condition.ConclusionOur findings suggest a mixed picture of the effect of the COVID-19 pandemic on student wellbeing, with a majority showing broadly consistent levels of wellbeing across time, a smaller but still substantial group showing a worsening of wellbeing, and a small group that showed a very marked improvement in wellbeing. Those from groups traditionally underrepresented in higher education were most at risk of poorer wellbeing. This raises questions as to whether future support for wellbeing should target specific student subpopulations.

Abstract

The GSHS is a school-based survey which uses a self-administered questionnaire to obtain data on young people's health behaviour and protective factors related to the leading causes of morbidity and mortality among children and adults worldwide.

Geographic coverage

National plus Montevideo and Rest of country

Analysis unit

Individuals

Universe

School-going adolescents aged 13-17 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage cluster sample design was used to produce data representative of all students in grades CB-3 BD in Uruguay. At the first stage, 66 schools were selected with probability proportional to enrollment size. At the second stage, classes were randomly selected and all students in selected classes were eligible to participate.

Mode of data collection

self-administered

Research instrument

The following core modules were included in the survey: alcohol use dietary behaviours mental health physical activity protective factors sexual behaviours tobacco use violence and unintentional injury

Cleaning operations

All data processing (scanning, cleaning, editing, and weighting) was conducted WHO and the US Centers for Disease Control.

Response rate

The school response rate was 94%, the student response rate was 69%, and the overall response rate was 64%.

The SEP-MD study is a linked cohort created to explore the relationships between neighbourhood and individual factors and mortality, inpatient admissions and long-term unemployment in people with severe mental health conditions. Using individual data from the 2011 United Kingdom Census, combined with clinical records from the South London & Maudsley Trust, and death registrations, the study created a linked cohort which includes almost 20,000 individuals with a diagnosis of severe mental illness. Participants are followed up through routinely collected clinical, census and mortality data, which currently spans from 2007 to 2019.

This study fits into the field of behavioural medicine which tries to better understand the mind-body connection. That is, why does what we think and feel affect our bodies in ways which can cause us to become unwell? Quantitative research has repeatedly shown that depression is associated with the onset and progression of multiple different physical illnesses. However, we are still trying to understand why this is the case. We propose that the experience of depression in the physically ill may partly explain this, however this has yet to be addressed in previous research. Qualitative methods involve asking participants about their experiences of living with disease. In this study we propose to ask persons with 4 different diagnoses (depression only, depression comorbid with: coronary heart disease, arthritis or type 2 diabetes) in order to look for similarities and differences in individual experiences. We are particularly interested to know whether the symptoms of depression present themselves differently across the different physical illness groups and the timeline and course of depressive symptoms in relation to an individual’s physical illness symptoms. Such questions are possible to answer using quantitative methods using sophisticated statistical techniques, however such approaches strip away the context of the diagnosis which might help researchers to understand the finer details of this important issue. Three physical illness groups have been selected since they are all prevalent in the UK primary care setting and have all been associated with depression in cross-sectional and prospective analyses. These illness are: arthritis, coronary heart disease and type 2 diabetes. These three diseases have also been selected since they have all been shown to have involve inflammatory processes, which is one hypothesised mechanism linking depression to physical illness. Importantly each of the three diseases manifest themselves with different symptoms, physical limitations and treatment regimes, making cross-group comparisons possible. Using face-to-face interviews of up to 60 primary care patients we aim to better delineate the similarities and differences in the experience of depression between those patients with a psychiatric diagnosis but who are otherwise physically healthy in comparison to those with depression and a comorbid physical illness. This research will help us to better understand the experience of depression in physical illness, helping to inform studies on the early identification and treatment of depression in primary care.

The purpose of this research is to understand more about biosocial pathways in health by studying depression symptoms and how they relate to physical illnesses such as diabetes, heart disease and cancer. We already know that people suffering from these diseases are more likely to experience symptoms of depression than those without them. We also know that people who experience depression symptoms are more likely to develop a physical illness later in life. However, as yet, we are not sure why depression symptoms and physical illnesses are related in these ways. I am particularly interested in the biological pathways linking depression symptoms and physical illnesses. These pathways include things like how our bodies respond to stress and how well our immune system works. For example, I am interested in a substance called cortisol which is released by the body when we feel stressed or sad. I am also interested in part of the immune system which is responsible for levels of inflammation. Research has shown that cortisol and inflammation do not work as well as they should in people who have depression symptoms or a physical illness. Therefore, I am interested in finding out whether changes in these things can explain the link between depression symptoms and physical illness morbidity in people who suffer from a variety of different physical illnesses. My research fits in well with the ESRC's priorities for this award: biosocial research and secondary analyses of longitudinal data. I am proposing to conduct biosocial research since I am planning to study the biology of a problem that society is facing. In addition, I intend to use longitudinal data that has already been collected, but has not yet been used to answer the questions I am interested in. I will use two main methods to analyse my data: quantitative analyses of existing data and qualitative analyses of a new study. I will use data from studies such as Whitehall II, the English Longitudinal Study of Ageing (ELSA), and Midlife in the United States study (MIDUS) among others. Using these datasets will allow me to partly answer my questions using statistical analyses. In addition, I will conduct a qualitative study in order to speak to individuals living with either a mental or physical illness about their experiences of depression symptoms. This will enable me to explore how people think, feel and cope with their illnesses and their mood. This research is important for a number of reasons. First of all, research has shown that people who have depression symptoms and a physical illness are likely to experience more symptoms of their physical illness than those without depression symptoms. In other words, they are more likely to feel sicker than those without depression symptoms. This links to the second important reason. If we understand why people with physical illness also get depression symptoms then we can improve our treatment of these individuals. At the moment, our current treatment options are not always very effective. So, not only do these people suffer more symptoms of their illness, their depression symptoms do not always go away with treatment. If we can improve treatment, then we can reduce suffering. Another reason that this research is important is the scale of the problem. Currently a lot of people with a physical illness also experience depression symptoms. Sadly, research has shown that a lot of these patients do not get identified by doctors as needing extra help. I plan to raise awareness of this issue during the course of my fellowship by ensuring I reach out to policymakers, health professionals and the public.

The NYC KIDS Survey is a population-based telephone survey conducted by the Health Department. The survey provides robust data on the health of children aged 13 years or younger (2017: children aged 0-13 years; 2019: children aged 1-13 years) in New York City, including citywide and borough estimates, on a broad range of topics including physical and mental health, health care access, and school and childcare enrollment and learning. For more information, visit https://www1.nyc.gov/site/doh/data/data-sets/child-chs.page

The data has been generated by ethnographic observations, interviews and interactions with migrant workers in two sites in Shanghai in 2017/2018: Songjiang District on the south-western outskirts, and the inner-city Huangpu District, in proximity to some of the city’s most famous tourist attractions, such as the Bund or Nanjing Road. Ethnography, with its focus on everyday experience, can yield significant insights into understanding migrant mental health in contexts where signs of severe mental distress remain largely imperceptible, and more generally, into how stresses and strains are lived through the spaces, times and affective atmospheres of the city. Migrant ethnography can help us reconsider the oft-made connection between everyday stress and mental ill health. In this research, drawing on field evidence in central and peripheral Shanghai, we highlight the importance of attending to the forms of spatial and temporal agency through which migrants actively manage the ways in which the city affects their subjectivity. These everyday subjective practices serve to problematize the very concept of ‘mental health’, enabling us to engage in a critical dialogue with sociological and epidemiological research that assesses migrant mental health states through the lens of the vulnerability or resilience of this social group, often reducing citiness to a series of environmental ‘stressors’.

We have known, since at least the early twentieth century, that there is an association between living in a city and being diagnosed with a mental illness. But questions around the specificity of relationship between urban life and have continued well into the twenty-first century. We still don't know, for example, exactly why mental illness clusters in cities; we don't know how it relates to experiences of urban poverty, deprivation, overcrowding, social exclusion, and racism; and we don't know the precise biological and sociological mechanisms that turn difficult urban lives into diagnosable mental health conditions. What we do know is that migrants into cities bear a disproportionately large share of the burden of urban mental illness; we know that dense living conditions seem to exacerbate the problem; and we know that the general stress, tumult and precarity of urban living can, sometimes, create the basis for the development of clinical problems. If there are unanswered questions around the relationship between mental health and the city, these questions are particularly acute in contemporary China: China has urbanised at an unprecedented rate in the last decade, and has now become a majority urban society. But whereas in nineteenth-century Europe urbanization came from a growth in population, in twenty-first century China the situation is different: most of the growth is from rural migrants coming into the cities. In China, then, the link between urban transformation and mental illness is a critical issue: (1) Development in China is related to migration from the countryside into the cities; (2) Unrecognized and untreated mental disorder is a key factor in casting individuals and families into poverty and social exclusion; (3) Effective development of urban mental health policu requires far greater understanding of the related problems of urban stress, precarious living conditions and mental disorder. This project is an attempt to understand the relationship between migration and mental health in one Chinese mega-city: Shanghai. Given what we know about the relationship between urban mental health and particular patterns of social life (poverty, migration, dense housing, and so on), it starts from the position that this question requires new input from the social sciences. At the heart of the project is an attempt to mix what we know about mental health in contemporary Shanghai with a new kind of close-up, street-level data on what the daily experience of being a migrant on Shanghai is actually life - especially with regard to stress, housing, and access to services. We will then connect these two forms of knowledge to produce a new kind of survey for getting a new sociological deep surveying instrument for mapping migrant mental health in Shanghai. The project, which is split between researchers in the UK and China, asks: (1) How is mental disorder actually patterned in Shanghai, and how is that pattern affected by recent migration? (2) How are immigrants absorbed in Shanghai, and what is daily life actually like in Shanghai's migrant communities? (3) What policies, services, or laws might alleviate mental health among migrants in Shanghai? (4) What can be learned in Shanghai for similar problems in other developing mega-cities (such as Sao Paolo or Lagos). This project should also us to also produce new data on two of the major research-areas that are prioritised under this join UK-China research-scheme: 'Migration and public services,' where we will look at the relationship between the welfare system and migration, and analyse the services that currently help to alleviate this problem, as well as migrants' access to those services; (2) 'Inequalities and everyday life,' where we will develop a close-up, street-level analysis of the lived inequalities of everyday migrant life in Shanghai, and try to understand how urban inequality might contribute to the development of mental health problems?

Abstract

The GSHS is a school-based survey which uses a self-administered questionnaire to obtain data on young people's health behaviour and protective factors related to the leading causes of morbidity and mortality among children and adults worldwide.

Geographic coverage

Rodrigues

Analysis unit

Individuals

Universe

School-going adolescents aged 13-17 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage cluster sample design was used to produce data representative of all students in grades 8-12 in Rodrigues. At the first stage, schools were selected with probability proportional to enrollment size. At the second stage, classes were randomly selected and all students in selected classes were eligible to participate.

Mode of data collection

self-administered

Research instrument

The following core modules were included in the survey: alcohol use dietary behaviours drug use hygiene mental health physical activity protective factors sexual behaviours tobacco use violence and unintentional injury

Cleaning operations

All data processing (scanning, cleaning, editing, and weighting) was conducted at the US Centers for Disease Control.

Response rate

The school response rate was 100%, the student response rate was 87%, and the overall response rate was 87%.

Abstract

The GSHS is a school-based survey which uses a self-administered questionnaire to obtain data on young people's health behaviour and protective factors related to the leading causes of morbidity and mortality among children and adults worldwide.

Geographic coverage

National plus Luzon, Mindanao and Visayas.

Analysis unit

Individuals

Universe

School-going adolescents aged 13-17 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage cluster sample design was used to produce data representative of all students in grades 7-Fourth Year in the Philippines. At the first stage, schools were selected with probability proportional to enrollment size. At the second stage, classes were randomly selected and all students in selected classes were eligible to participate.

Mode of data collection

self-administered

Research instrument

The following core modules were included in the survey: alcohol use dietary behaviours drug use hygiene mental health physical activity protective factors violence and unintentional injury

Cleaning operations

All data processing (scanning, cleaning, editing, and weighting) was conducted at WHO and the US Centers for Disease Control.

Response rate

The school response rate was 100%, the student response rate was 85%, and the overall response rate was 85%.