MétaCan
Menu
← Back to cohort
Record W4416815162 · doi:10.2196/77521

COVID-19 Pandemic Experiences Among Adults, Youth, and Childcare Providers: Protocol for a Mixed Methods Study

2025· article· en· W4416815162 on OpenAlexvenueno aff
Jacinda K. Dariotis, Dana Eldreth, Chunyuan Xi, Iffat Noor, Rebecca L. Smith

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicProtocol (science)Data collectionQualitative researchHealth careMEDLINE

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic challenged families, youth, and frontline workers, including childcare providers. Studying lived experiences before, during, and near the pandemic's end from multiple perspectives provides a more holistic and deeper understanding of its effects and impacts. OBJECTIVE: This study investigated how parental, childcare provider, and youth stress, mental health, and role overload relate to individual coping and family functioning, as well as vaccine attitudes and uptake patterns among youth, parents, and childcare providers. Information learned from this investigation will inform policy and messaging for future public health crises. METHODS: This study is an explanatory sequential mixed methods study designed to capture the voices of parents of children younger than 18 years of age, childcare providers, and youth aged 12-17 years through surveys and interviews. This retrospective cross-sectional study began with a web-based survey that included demographic questions and validated scales to assess personal well-being, household and family dynamics, behavioral problems, and vaccination-related perceptions, attitudes, and behaviors. Open-ended responses about pandemic experiences for themselves and their families were included. A subsample of parents, youth, and childcare providers was selected for in-depth interviews about their pandemic-related experiences. Descriptive statistics were used to summarize demographic characteristics, and internal consistency was assessed for all survey measures using Cronbach α. Future studies will use inferential statistical techniques to analyze survey measures, thematic analysis for open-ended survey responses and interview data, and mixed methods data integration to synthesize quantitative and qualitative findings. RESULTS: Data collection for the study began in August 2022 and finished in August 2023. Data analysis is currently in progress to address research questions, and study preparation and dissemination efforts are underway. A total of 506 adults and 93 youths answered a study survey, and 45 adults and 21 youths completed in-depth interviews. Among the 506 adults, 166 were childcare providers. The adult sample had a mean age of 42.8 (SD 9.15) years and was predominantly female (467/506, 92.3%), with 9.7% (49/506) identifying as Black, 4.7% (24/506) as Hispanic, and 81.2% (411/506) being parents of children aged 17 years or younger. The youth sample had a mean age of 14.5 (SD 1.63) years, and 55.9% (52/93) were female, 6.4% (6/93) were Black, and 17.2% (16/93) were Hispanic. Several dyads and triads participated. The sample included 42 parent-child dyads, 3 parent-parent dyads, 2 parent-parent-child triads, and 21 parent-child-child triads. CONCLUSIONS: These data will be used to understand the diverse experiences of families, youth, and childcare providers during and after the COVID-19 pandemic. This includes successful and unsuccessful adaptations, responses to policies and mandates, and the unmet needs for health messaging, programs, policies, and services. This research aims to guide the development of effective policies and public health communication, fostering scalable and sustainable messaging resources. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77521.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.075
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.078
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.048
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0050.005
Science and technology studies0.0060.003
Scholarly communication0.0040.004
Open science0.0040.004
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0780.016

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.

Opus teacher head0.507
GPT teacher head0.713
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research Protocols→Same topicCOVID-19 and Mental Health→French-language works237,207→