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Record W4401509866 · doi:10.1101/2024.08.11.24311834

“It’s because they are my kids and I love them”: The impact of family and community substance use on children and families

2024· preprint· en· W4401509866 on OpenAlexaff
Meghan K. Ford, Ryan Truong, Bruce Knox, Susan A. Bartels, Colleen Davidson, Michelle Cole, Logan Jackson, Eva Purkey, Imaan Bayoumi

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsQueen's University
Fundersnot available
KeywordsThematic analysisFocus groupContext (archaeology)Qualitative researchPsychologySubstance useSubstance abuseMental healthPsychological resilienceParticipatory action researchDevelopmental psychologyPsychiatrySocial psychologySociology

Abstract

fetched live from OpenAlex

Abstract Background Substance use disorders (SUD) significantly impact the physical, social, and mental health of individuals, their families, and the wider community. Parental substance use can lead to long-term social and health problems for children. Examining resilience and its determinants among families directly affected by SUD (e.g., having a parent who misuses substances) or indirectly exposed to substance use (e.g., living in a community impacted by drug use) may uncover valuable insights to support families addressing SUD. The existing literature does not adequately address substance use within the context of families with young children and community resilience. The current study aims to enhance our understanding of the daily impact of family member substance use (direct substance use) or exposure to substance use within the community (indirect substance use) on children and families through qualitative interviews. Methods The present study was a qualitative secondary analysis. Families were recruited within the Kingston, Frontenac, Lennox, and Addington area during 2022 and 2023 with a focus on maximum variation. Families were eligible to participate if they: 1) included at least one adult caring for a child under 18; 2) had a history of adversity; 3) were interested in participating; and 4) could consent to all parts of the study. Arts-based qualitative methods and community based participatory methods were employed. Participating families created a visual timeline, participated in a focus group discussion, and an individual interview. The qualitative transcripts were then analyzed following reflexive thematic analysis. Findings Six families (12 adults, 4 children) were included in the secondary analysis. The analysis generated four themes: (1) How children affect resilience in families affected by SUD; (2) Service needs of parents with SUD to enhance family resilience; (3) The role of social support in family resilience; and (4) How perceptions of safety and trust challenge community resilience. The main limitation of this study was a small sample size. Conclusions The study highlights the significant impact of family and community on the resilience of individuals affected by SUD. It emphasizes the importance of developing addictions services and social environments that are supportive of families with young children. These spaces should be designed to be substance-free, inclusive, and welcoming to children. Additionally, there is a need to improve service navigation and address the barriers to care commonly experienced by individuals affected by SUD.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0010.002
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 head0.116
GPT teacher head0.408
Teacher spread0.292 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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