Impact of COVID-19 on healthcare access for Australian adolescents and young adults
Bibliographic record
Abstract
ABSTRACT Background Access to healthcare for young people is essential to build the foundation for a healthy life. We investigated the factors associated with healthcare access by Australian young adults during and before the COVID-19 pandemic. Methods We included 1110 youths using two recent data collection waves from the Longitudinal Study of Australian Children (LSAC). Data were collected during COVID-19 in 2020 for Wave 9C1 and before COVID-19 in 2018 for Wave 8. The primary outcome for this study was healthcare access. Both bivariate and multivariate logistic regression models were employed to identify the factors associated with reluctance to access healthcare services during COVID-19 and pre-COVID-19 times. Results Among respondents, 39.6% avoided seeking health services during the first year of the COVID-19 pandemic when they needed them, which was similar to pre-COVID-19 times (41.4%). The factors most strongly impacting upon reluctance and/or barriers to healthcare access during COVID-19 were any illness or disability, and high psychological distress. In comparison, prior to the pandemic the factors which were significantly impeding healthcare access were country of birth, state of residence, presence of any pre-existing condition and psychological distress. The most common reason reported (55.9%) for avoided seeking care was that they thought the problem would go away. Conclusions A significant proportion of youths did not seek care when they felt they needed to seek care, both during and before the COVID-19 pandemic. What is known about the subject? Some adolescents and young adults do not access healthcare when they need it. Healthcare access and barriers to access is best understood through a multi-system lens including policy, organisational, and individual-level factors. For instance, policy barriers (such as cost), organisational barriers (such as transportation, or difficulty accessing a timely appointment) and individual barriers (such as experiences, knowledge or beliefs). Barriers to care may differ for sub-groups e.g. rural During the COVID-19 pandemic, public health restrictions including the stricter “lockdowns” have reduced healthcare access. The burden of cases upon the healthcare system has further reduced healthcare access. What this study adds? A significant proportion of youth did not seek healthcare when they felt they needed to seek care, both before (41.4%) and during the first year of the COVID-19 pandemic (39.6%) Youth with a disability or chronic condition, asthma and/or psychological distress were more likely to avoid accessing healthcare during COVID-19 times. The most common reason for not seeking healthcare when it was felt to be needed was because the youth thought the problem would go away (pre-COVID-19 35.7% of the sample versus during the first year of COVID-19 55.9%) During the coronavirus restriction period (“lockdown”) the most common reason for not seeking healthcare when it was felt to be needed was because the youth did not want to visit a doctor during lockdown (21.8%) with the next most common reason being because telehealth was the only appointment option available at the time (8.4%)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".