MétaCan
Menu
← Back to cohort
Record W4238037944 · doi:10.32920/ryerson.14648937

A multi-method study of youth development and wellbeing: a meta-narrative analysis and program evaluation study

2021· preprint· en· W4238037944 on OpenAlexaff
Sofia A. Puente-Duran

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsToronto Metropolitan UniversitySystems, Applications & Products in Data Processing (Canada)University of Toronto
Fundersnot available
KeywordsData collectionThematic analysisPositive Youth DevelopmentPsychologyNeighbourhood (mathematics)Critical appraisalApplied psychologyGrey literaturePopulationNarrativeQualitative researchDevelopmental psychologySociologySocial scienceMathematicsMedicine

Abstract

fetched live from OpenAlex

Youth are embedded within multiple environmental systems, developing within families, neighbourhoods, and multicultural communities. Such systems influence the formation of identity and wellbeing. It is important to monitor the wellbeing of youth across their environments, given the complexities of diverse youth experiences. Accordingly, the present dissertation comprises two studies to address the topic of youth development and wellbeing using multiple data collection techniques. In Study 1, a meta-narrative analysis was undertaken examining concepts of youth wellbeing across multidimensional indices. A search was performed across the grey literature base and seven indices fit the search criteria. Data were extracted using a codebook to guide a thematic analysis and critical appraisal to compare, contrast, and critique indices. Results showed three key findings. (1) Indices had some overlap to conceptualize wellbeing, using an average of six dimensions. (2) Data collection used similar levels of population-level statistics and self-reported data. (3) A large proportion of measures focused on youth deficits, with less focus placed on positive attributes. In Study 2, an evaluation was conducted assessing the impact of a school-based art program on the socio-emotional wellbeing of adolescents from three grade 8 classrooms, within one inner-city, multicultural neighbourhood. A mixed-method, multi-informant evaluation design was employed, and implementation processes of the program were assessed. Survey data and open-ended responses were collected from 74 students at three time-points (pre, post, follow-up), using multilevel modeling to examine time-points nested within students. Responses were also collected post-program from six artist facilitators and three teachers. Program implementation results showed high levels of fidelity, and high quality ratings. Results from multilevel models showed significant variation at the between-student level. Across students, significant improvements were found over time for art skill, self-expression, and confidence presenting. Qualitative data revealed themes across informants regarding the positive impact of the program on student growth. Findings also indicated the importance of a safe space for adolescents to learn about themselves, and be vulnerable. These two studies shed light on the multiple ways in which youth development and wellbeing are assessed, and the ways in which a local-level community program can support their wellness.

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)0.101
metaresearch head score (Gemma)0.128
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 score0.101
Threshold uncertainty score0.533

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1010.128
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.012
Bibliometrics0.0130.014
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.297
GPT teacher head0.435
Teacher spread0.138 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicArt Therapy and Mental Health→French-language works237,207→