Ontario Child Health Study (OCHS)
Detailed information for 2014
Status:
Active
Frequency:
Occasional
Record number:
3824
The survey was conducted by Statistics Canada on behalf of Offord Centre for Child Studies at McMaster University in Hamilton, Ontario. The purpose of the Ontario Child Health Study (OCHS) is to collect up-to-date information about children and youth's mental health in Ontario.
Data release - December 19, 2017
Description
The research data collected will be used to support and develop policies and programs to ensure the health of children in Ontario. A similar study was conducted in 1983, with follow-up studies in 1987 and 2000. Those results were used to advocate for prevention efforts for mental health issues including federally sponsored Early Child Development Initiatives in 1990 and Ontario programs such as Healthy Babies, Healthy Children and the Early Years Centres in 2000. Initial data are now 30 years old, and there is a significant need for updated information.
The 2014 OCHS has five objectives:
to estimate the prevalence of child mental disorders;
to quantify the association between child mental disorders, chronic health conditions, and social and academic functioning; the findings of 1983 OCHS showed a relationship between having a mental disorder and academic and social functioning. The 1983 findings also showed that children with a functional condition had a higher rate of mental disorders versus children who had neither a functional or medical condition. Researchers hope to gain a better understanding of these relationships from 2014 OCHS;
to determine if there has been an increase in the prevalence of child mental disorders between 1983 and 2014 or changes in social gradients for child disorders;
to examine the extent to which families with children exhibiting mental health needs receive mental health services, express satisfaction with them or experience service barriers; and,
to model contextual influences (for example, family, neighbourhood, school) on risk for developing a mental disorder.
Collection period: October 2014 to October 2015
Subjects
- Children and youth
- Health and well-being (youth)
Data sources and methodology
Target population
The target population includes all households with children aged 4 to 17 years whose usual place of residence is a private household in the province of Ontario. Specifically excluded are households living in collective dwellings, as well as those residing on Indian reserves.
Instrument design
Data for this survey are collected using a questionnaire with multiple components. Researchers from McMaster University and from Statistics Canada worked closely together to develop the various components of the collection instrument. The questionnaire underwent an in-depth review by a multidisciplinary team from Statistics Canada and was then tested thoroughly, in collaboration with the agency's Questionnaire Design Resource Centre, using focus groups as well as cognitive interviews. The questionnaire was finalized in September 2014.
Sampling
This is a sample survey with a cross-sectional design.
The sample design used a three-stage sampling plan, with neighbourhoods selected at the first stage, census tracts and dissemination areas selected at the second stage and dwellings where children aged 4 to 17 lived selected at the third stage. Families that no longer lived in the dwelling where they were sampled were not traced. Families that had moved into the selected dwelling were included in the survey if they had a child aged 4 to 17.
A test/retest, which is a method that is used to measure the reliability of a questionnaire, was done for OCHS. Some respondents (selected independently from the main sample) were asked to complete the interview twice, one to two weeks apart. This is used as an indication of quality of the questionnaire and information that the researchers require to publish their analysis in academic journals. The initial sample size for the test/re-test was 700 dwellings.
Data sources
Data collection for this reference period: 2014-10-14 to 2015-10-15
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Statistics Canada interviewers first attempted to contact the selected dwellings over the phone to arrange a personal visit. During this visit, data was collected by various modes. The person most knowledgeable was asked questions about up to four children 4 to 17 years old in the household. This was done by means of a computer-assisted interview as well as self-complete paper questionnaires. The spouse or partner (if applicable) was asked to fill-out a self-complete paper questionnaire about one of the children (the selected child) as well. Youths aged 12 to 17 and the person most-knowledgeable were also asked to fill-out a questionnaire that was self-completed on a laptop. Finally, the interviewer also administered a pen and paper interview to the person most-knowledgeable and the selected child (if 12 to 17 years old).
The length of each household interview was dependent on the composition of each household ranging from 1.5 to 3.5 hours.
Teachers of children from Junior Kindergarten to grade 8 were also asked to fill-out a self-complete paper questionnaire about the child. This was done only if consent to contact the teacher had been obtained from the parent.
Capture Method
Paper questionnaires:
Data was captured at Statistics Canada's head office for the following paper questionnaires:
- Self-complete for the PMK about the selected child and up to 3 additional siblings
- Self-complete for the Partner
- A modified version of the Mini International Neuropsychiatric Interview (MINI) Parent
- MINI for selected child - aged 12 to 17
- Teacher questionnaire
Any document containing at least one item completed by the respondent was captured and a file containing each record was provided to head office staff for further processing. Some quality checks were built in as part of the capture system to flag unusual entries and warn the operators of potentially incorrect entries.
Computer-assisted interviews:
Responses to survey questions were captured directly by the interviewer at the time of the interview using a computerized questionnaire. The computerized questionnaire reduced processing time and costs associated with data entry, transcription errors and data transmission. The response data were encrypted to ensure confidentiality and sent via modem to the appropriate Statistics Canada regional office. From there they were transmitted over a secure line to head office for further processing.
Some editing was done directly at the time of the interview. Where the information entered was out of range (too large or small) of expected values, or inconsistent with the previous entries, the interviewer was prompted, through message screens on the computer, to modify the information. However, for some questions interviewers had the option of bypassing the edits, and skipping questions if the respondent did not know the answer or refused to answer. The response data were then subjected to further edit and imputation processes after arriving to head office.
Electronic data reporting (laptop)
For the electronic questionnaire, responses to survey questions were entered directly by the respondents. The electronic questionnaire reduced processing time and costs associated with data entry, transcription errors and data transmission. The responses were secured through industry standard encryption protocols, firewalls and encryption layers.
The data were subjected to further edit processes after they were submitted to head office.
Administrative information from the Ontario Ministry of Education was linked to the 2014 Ontario Child Health Study (OCHS). The purpose of this linkage was to obtain accurate data on educational achievement, special education requirements, program type and school behaviour. This information provides researchers valuable information that will be used to study the relationships between overall health, mental health and academic performance.
As well, the Ontario Child Health Study was linked to the McMaster 2014 School Mental Health Survey (SMHS) aggregate scores. The main objective was to allow for a more complete portrait of children's mental health in Ontario.
Respondents were asked permission for Statistics Canada to link their survey data with data from the Ontario Ministry of Health and Long-Term Care (MOHLTC) and with the Ontario Ministry of Education to examine whether or not these services are being used effectively.
View the Questionnaire(s) and reporting guide(s).
Error detection
The first stage of survey processing undertaken at head office was the replacement of any "out-of-range" values on the data file with blanks. This process was designed to make further editing easier.
The first type of error treated was errors in questionnaire flow, where questions which did not apply to the respondent (and should therefore not have been answered) were found to contain answers. In this case a computer edit automatically eliminated superfluous data by following the flow of the questionnaire implied by answers to previous, and in some cases, subsequent questions.
The second type of error treated involved a lack of information in questions which should have been answered. For this type of error, a non-response or "not-stated" code was assigned to the item.
Imputation
Birthdate and income imputation was applied on the OCHS file. Some respondents refused to provide answers to the income question. Among those who refused, some respondents did provide estimates of their total household income using ranges. Income imputation was carried out to fill in the holes resulting from partial and full non-response. Income imputation was done using the nearest-neighbour imputation method. The first step of this method is to find a respondent (the donor) who answered the income section and has characteristics similar to those of the respondent who did not provide complete income information (the recipient). The donor's record is then used to calculate the values to be imputed to the recipient's record.
Estimation
The OCHS is a probability survey. As is the case with any probability survey, the sample is selected so as to be able to produce estimates for a reference population. Therefore, each unit in the sample represents a number of units in the population.
Survey weights are calculated by taking the dwelling design weight and making adjustments for survey non-response and post-stratification to ensure that the final survey weights sum to known counts of dwellings with children in Ontario. The design weight is the inverse of the probability of selection, that is, the probability that a dwelling with children in the population is selected for the OCHS sample.
The non-response adjustment was performed in two steps, using two different logistic models. Non-responding dwellings were divided in two groups: noncontacts and other (mostly refusals). For the first adjustment, the weights of the cases that we were not able to contact were distributed to cases for which a contact was made (respondents and other non-respondents) while with the second adjustment, the weights of the other non-respondents were given to the respondents. Then, another adjustment was made to ensure consistency between the estimates produced by OCHS and Statistics Canada's population estimates. This method is called post-stratification. The purpose of this adjustment is to ensure that the sum of the weights match known population totals. Finally, a trimming procedure was applied to the weights that were deemed too high within their strata.
Six different sets of weights were created for OCHS: dwelling weight, secondary sampling unit weight, sibling weight, selected child weight, sibling weight for the teacher component and selected child weight for the teacher component.
Given the complexity of the OCHS sampling design, the Generalized Bootstrap method was used to prepare the sets of bootstrap weights. The generalized bootstrap weights can be used with a software the same way the regular bootstrap weights are being used, with the difference that standard error estimates obtained through a software has to be multiplied by an adjustment factor. For OCHS, this adjustment factor is 5.
Quality evaluation
While rigorous quality assurance mechanisms are applied across all steps of the statistical process, validation and scrutiny of the data by statisticians are the ultimate quality checks prior to dissemination. Many validation measures were implemented, they include:
a. Verification of estimates through comparison of similar measures within the survey
b. Verification of estimates through cross-tabulations
c. Confrontation with other similar sources of data
d. Consultation with stakeholders internal to Statistics Canada
e. Consultation with external stakeholders
f. Coherence analysis based on quality indicators
Disclosure control
Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
The micro data file does not contain any personal identifiers. Individual responses and results for very small groups will not be published.
For aggregate or tabular data, confidentiality will be maintained by both cell collapsing and suppression of data where necessary.
Revisions and seasonal adjustment
This methodology does not apply to this survey.
Data accuracy
The OCHS is based upon a complex sample design, with stratification, multiple stages of selection, and unequal probabilities of selection of respondents. Using data from such complex surveys presents problems for analysis because the survey design and the selection probabilities affect the estimation and variance calculation procedures that should be used. The survey weights must be used in estimates and analyses to reduce bias.
While many analysis procedures found in statistical packages allow weights to be used, the meaning or definition of the weight in these procedures may differ from that which is appropriate in a sample survey framework, with the result that while in many cases the estimates produced by the packages are correct, the variances that are calculated are poor.
The quality of estimates produced with OCHS data is measured with the coefficient of variation (CV), produced using bootstrap weights. The CV magnitude will depend on the domain of interest and the prevalence of the characteristic.
Given the complexity of the OCHS sampling design, the Generalized Bootstrap method was used to prepare the sets of bootstrap weights. The generalized bootstrap weights can be used with a software the same way the regular bootstrap weights are being used, with the difference that standard error estimates obtained through a software has to be multiplied by an adjustment factor. For OCHS, this adjustment factor is 5.
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