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Record W4290988752 · doi:10.1101/2022.08.09.22278279

Online anxiety resources for Canadian youth: a systematic environmental scan

2022· preprint· en· W4290988752 on OpenAlexafffundabout
Megan Pohl, Liza Bialy, Shannon D. Scott, Lisa Hartling, Sarah A. Elliott

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Alberta
FundersChildren's Hospital FoundationStollery Children’s Hospital FoundationWomen and Children's Health Research InstituteKidscan Children's Cancer ResearchChildren's Health Research Institute
KeywordsAnxietyPsychologyInclusion (mineral)Resource (disambiguation)Mental healthThe InternetPopulationFocus groupMedical educationApplied psychologyMedicinePsychiatrySocial psychologyEnvironmental healthComputer scienceSociologyWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Introduction In a recent child health research priority setting exercise conducted in Alberta (CA), youth identified “mental health” as a priority topic. Specifically, youth were interested in understanding what the early signs and symptoms of anxiety were, and when they should seek help. Objective The objective of this study was to understand what information is currently available online for Canadian youth about the signs and symptoms of anxiety, what resources are available for self-assessment, and what are youth’s behaviors, experiences and information needs around seeking help for anxiety. Methods We conducted a systematic environmental scan of Internet resources and academic literature. Internet and literature search results (Information Sources) were screened by one reviewer and verified by another. Relevant information (e.g., self-assessment resource features and population characteristics such as age, presence of anxiety, and education) were then extracted and verified. Information Sources were categorized relating to the research concepts regarding; signs and symptoms, self-assessments, information needs and experiences. We complimented our environmental scan with youth consultations to understand how anxiety resources are perceived by youth, and what if anything, could be improved about the information they are receiving. Consultations were conducted over Zoom with three Canadian Youth Advisory Groups (2 provincial, 1 national) and took a semi-structured focus group format. Results A total of 99 Information Sources (62 addressing signs and symptoms, 18 self-assessment resources, and 19 reporting on information and help-seeking behaviors) met the inclusion criteria. The majority of Information Sources on signs and symptoms were webpage-based articles, and 36 (58%) specifically stated that they were targeting youth. 72% of anxiety self-assessment resources were provided by private institutions. The resources varied markedly in the post-assessment support provided to youth according to their source (i.e. private, academic, governmental). Regarding information and help-seeking preferences, three main themes were apparent and related to 1) obtaining in-person professional help, 2) searching for online help, and 3) stigma associated with seeking help for anxiety disorders. The Youth Group consultations identified several areas that need to be considered when developing resources for youth. The key considerations highlighted by youth across the consultations suggested resources needed to be; youth friendly, align with a credible institute (e.g. University, Health Institution), and provide useful resources post online assessment and tangible action items to support help seeking. Conclusion Awareness of the information and resources available to youth, coupled with an understanding of their help-seeking behaviors and information needs can help support the development and dissemination of appropriate knowledge translation tools around youth anxiety.

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)0.027
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.148
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.091
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0680.073
Science and technology studies0.0060.003
Scholarly communication0.0060.004
Open science0.0030.006
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.029
GPT teacher head0.266
Teacher spread0.237 · 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 designSystematic review
Domainnot available
GenreEmpirical

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

Citations3
Published2022
Admission routes3
Has abstractyes

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