JMIR Publications

ABSTRACT

Background:

Perceived and unmet mental health needs are important factors in the decision-making process regarding mental health services planning and resources allocation.

Objective:

To develop prediction models to forecast perceived and unmet mental health needs at the provincial and health regional levels.

Methods:

Data from 2018, 2019 and 2020 Canadian Community Health Survey (CCHS) and Canadian Urban Environment were used (n = 65000 each year). Perceived and unmet mental health needs were measured by the Perceived Needs for Care Questionnaire. Using 2018 data, we developed the prediction models through the application of regression synthetic estimation for Atlantic, Central and Western regions. The models were validated in 2019 and 2020 data at provincial level and in 10 randomly selected health regions by comparing the observed and predicted proportions of the outcomes.

Results:

The absolute differences between the observed and predicted proportions of perceived and unmet mental health needs in Ontario, Quebec and British Columbia were less than 1%. For the rest of the provinces, regional models predicting unmet mental health needs had better calibration than the models predicting perceived mental health need.

Conclusions:

Predicting perceived and unmet mental health at the population level is feasible. There are common factors that contribute to perceived and unmet mental health needs across regions, at different magnitudes, due to different population characteristics. Therefore, predicting perceived and unmet mental health needs should be region specific.