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Record W4283317095 · doi:10.2196/37966

The Health Impact of Social Community Enterprises in Vulnerable Neighborhoods: Protocol for a Mixed Methods Study

2022· article· en· W4283317095 on OpenAlexvenueno aff
Erik Hendriks, Maria Koelen, Kirsten Verkooijen, Jan Hassink, Lenneke Vaandrager

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyProtocol (science)Empirical researchMental healthIntervention (counseling)Applied psychologyPublic relationsGerontologyEnvironmental healthMedicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: This 4-year research project focuses on 6 social community enterprises (SCEs) that operate in 5 neighborhoods in a Dutch city. Residents of these neighborhoods face problems such as poor average levels of physical and mental health, high unemployment rates, and weak social cohesion. SCEs offer residents social, cultural, and work-related activities and are therefore believed to help these persons develop themselves and strengthen the social ties in the community. Because of a lack of empirical evidence; however, it is unclear whether and how SCEs benefit the health and well-being of participants. OBJECTIVE: This paper outlines a protocol for an evaluation study on the impact of SCEs, aiming to determine (1) to what extent SCEs affect health and well-being of participating residents, (2) what underlying processes and mechanisms can explain such impact, and (3) what assets are available to SCEs and how they can successfully mobilize these assets. METHODS: A mixed methods multiple-case study design including repeated measurements will be conducted. Six SCEs form the cases. An integrated model of SCE health intervention will be used as the theoretical basis. First, the impact of SCEs is measured on the individual and community level, using questionnaires and in-depth interviews conducted with participants. Second, the research focuses on the underlying processes and mechanisms and the organizational and sociopolitical factors that influence the success or failure of these enterprises in affecting the health and well-being of residents. At this organizational level, in-depth interviews are completed with SCE initiators and stakeholders, such as municipal district managers. Finally, structurally documented observations are made on the organizational and sociopolitical context of the SCEs. RESULTS: This research project received funding from the Netherlands Organization for Health Research and Development in 2018. Data collection takes place from 2018 until 2022. Data analysis starts after the last round of data collection in 2022 and finalizes in 2024. Expected results will be published in 2023 and 2024. CONCLUSIONS: Despite the societal relevance of SCEs, little empirical research has been performed on their functioning and impact. This research applies a variety of methods and includes the perspectives of multiple stakeholders aiming to generate new empirical evidence. The results will enable us to describe how SCE activities influence intermediate and long-term health outcomes and how the organizational and sociopolitical context of SCEs may shape opportunities or barriers for health promotion. As the number of these initiatives in the Netherlands is increasing rapidly, this research can benefit many SCEs attempting to become more effective and increase their impact. The findings of this research will be shared directly with relevant stakeholders through local and national meetings and annual reports and disseminated among other researchers through scientific publications. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37966.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.085
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.273
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0850.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0210.000
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0000.008
Insufficient payload (model declined to judge)0.0010.000

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 head0.618
GPT teacher head0.763
Teacher spread0.145 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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