Singapore's fertility rate is currently below 1.2, raising concerns about population ageing and long-term sustainability. The fertility decline is characterized by falling birth rates among women in their 20s with almost no recuperation among women in their 30s. This project explores a) whether informational imperfections help to account for high intended ages at childbearing in Singapore, b) whether informational interventions significantly affect ideal and expected ages at marriage and childbearing, and expected probability of undergoing social egg freezing, and c) whether informational interventions significantly affect expected and actual educational outcomes and labor market outcomes. Our hypotheses are: 1. University students have knowledge gaps about age-related onset of infertility, assisted reproductive technologies and local policy initiatives related to age at marriage and childbearing, especially among male students. 2. Being exposed to accurate information in these domains leads to significantly lower ideal/expected ages at marriage and childbearing, and higher expected probability of undergoing social egg freezing, immediately after the intervention. 3. Being exposed to accurate information in these domains does not lead to lower educational and labor market expectations immediately after the intervention among either male or female students, or to significant differences in module choices, Cumulative Average Point (CAP), starting salary and employment status of university students in the following academic semester and six months after graduation, among either male or female students.
The project conducts a randomized controlled trial involving 1000 full-time undergraduate students at NUS. The trial has three stages. In the first stage, participants will be recruited through campus advertisements. In the second stage, participants who meet the eligibility criteria will complete a 30-40 minute online survey. The survey includes the following: 1. a background survey on items including age, race, family income and parental background, 2. a section on dating history, 3. questions on ideal/expected ages at marriage, expected probability of undergoing social egg freezing, and fertility and educational and career expectations, 4. a section on mental wellbeing, 5. an awareness survey on age-related onset of infertility, assisted reproductive technologies, and local policy initiatives related to age at marriage and childbearing, 6. an informational intervention. One-third of participants (333 individuals) are randomly assigned to receive accurate information on the age-related fertility survey items. One-third of participants (333 individuals) are randomly assigned to receive accurate information on policy-related survey items. One-third of participants (334 individuals) receives a fact sheet on diabetes in Singapore. Participants are asked to read the information thoroughly, 7. selected questions from c), which collects data on after-intervention intended ages at marriage and fertility and educational and career expectations, as well as questions about whether the questions were useful or led to anxiety. In the third stage, the students' responses are linked to the Educational Data Lake managed by ALSET, Provost's Office, NUS, which collects data on students' module choices (whether within the same major, in a different major within the same faculty or in a different faculty) and CAP in the following academic semester and at graduation, graduation status, and starting salary and employment status six months after graduation. All participants are informed and these linkages are mentioned in the consent form. After the data collection is completed, we will analyse the data using a difference-in-differences econometric model. Our model compares three sets of dependent variables at different points in time: 1. Ideal/expected ages at marriage and fertility, expected probability of undergoing social egg freezing, and educational and career expectations, compared before and immediately after the intervention, 2. Module choices and CAP, compared before the survey and in the following academic semester and at graduation, and graduation status, 3. Starting salary and employment status, compared between the control and treatment groups six months after graduation (multiple regression rather than difference-in-differences model) The results are compared by gender, faculty, educational and career expectations, and other background characteristics, including dating history and mental wellbeing.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
1,000
The following information is provided: Age and fertility IVF success rates and side effects
The following information is provided: Assisted reproductive technology treatment subsidies Other fertility-related policies
The following information is provided: Diabetes risk factors and treatment Diabetes-related policies
National University of Singapore
Singapore, Singapore
Ideal age at marriage (both self and future spouse), first birth and number of children
During initial survey: Continuous
Time frame: Within one year and two years of initial survey
Expected age at marriage (both self and future spouse), first birth and number of children
During initial survey: Continuous percent chance by the following ages A. 25 B. 30 C. 35 D. 40
Time frame: Within one year and two years of initial survey
Expected probability of undergoing social egg freezing (only for females respondents)
During initial survey: Continuous percent chance of social egg freezing if available at the following ages: A. 25 B. 30 C. 35 D. 40
Time frame: Within one year and two years of initial survey
Expected levels of education (both self and future spouse)
During initial survey: Continuous percent chance: A. Less than Bachelor's Degree B. Bachelor's Degree or higher C. Master's Degree or higher D. Doctoral Degree or higher
Time frame: Within one year and two years of initial survey
Expected earnings (both self and future spouse)
During initial survey: Continuous at the following ages: A. 25 B. 30 C. 35 D. 40
Time frame: Within one year and two years of initial survey
Expected full-time working status
During initial survey: Continuous percent chance by the following ages A. 25 B. 30 C. 35 D. 40
Time frame: Within one year and two years of initial survey
Expected occupation (self) at age 35
During initial survey: Continuous percent chance: A. Full-time homemaker B. Manager or administrator in a private company C. Manager or administrator in the government/education sector D. Professional without doctoral degree (e.g. engineer, architect, accountant, social worker, teacher) E. Professional with doctoral degree or equivalent (lawyer, physician, scientist, college professor) F. Sales (e.g. insurance agent, real estate) G. Other (e.g. small business owner, etc.)
Time frame: Within one year and two years of initial survey
Expected contribution to housework and childcare if married with young children
During initial survey: Continuous percentage
Time frame: Within one year and two years of initial survey
Usefulness and anxiety over information presented
During initial survey: Strongly disagree, Disagree, Neither agree nor disagree, Agree, Strongly agree
Time frame: Within one year and two years of initial survey
Cumulative Point Average (CAP)
Measured in the following academic semester and at graduation
Time frame: Within two years and six years of initial survey
Module choices
Whether within the same major, in a different major within the same faculty or in a different faculty, in the following academic semester and at graduation
Time frame: Within two years and six years of initial survey
Graduation and honours
Whether graduated and class of honours
Time frame: Within six years of initial survey
Employment status six months after graduation
Whether employed, full-time status
Time frame: Within six years of initial survey
Starting salary
Continuous
Time frame: Within six years of initial survey
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