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Record W4377042342 · doi:10.1002/cl2.1329

Exploring the effect of case management in homelessness per components: A systematic review of effectiveness and implementation, with meta‐analysis and thematic synthesis

2023· review· en· W4377042342 on OpenAlex
Alison Weightman, Mark Kelson, Ian Thomas, Mala Mann, Lydia Searchfield, Simone Willis, Ben Hannigan, Robin Smith, Rhiannon Cordiner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCampbell Systematic Reviews · 2023
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersHeriot-Watt University
KeywordsPsychological interventionThematic analysisNonprobability samplingSystematic reviewIntervention (counseling)Mental healthLife expectancyPsychologyGrey literatureMeta-analysisPublic healthMEDLINEGerontologyMedicineNursingQualitative researchEnvironmental healthPolitical sciencePsychiatrySociologyPopulationSocial science

Abstract

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Abstract Background Adequate housing is a basic human right. The many millions of people experiencing homelessness (PEH) have a lower life expectancy and more physical and mental health problems. Practical and effective interventions to provide appropriate housing are a public health priority. Objectives To summarise the best available evidence relating to the components of case‐management interventions for PEH via a mixed methods review that explored both the effectiveness of interventions and factors that may influence its impact. Search Methods We searched 10 bibliographic databases from 1990 to March 2021. We also included studies from Campbell Collaboration Evidence and Gap Maps and searched 28 web sites. Reference lists of included papers and systematic reviews were examined and experts contacted for additional studies. Selection Criteria We included all randomised and non‐randomised study designs exploring case management interventions where a comparison group was used. The primary outcome of interest was homelessness. Secondary outcomes included health, wellbeing, employment and costs. We also included all studies where data were collected on views and experiences that may impact on implementation. Data Collection and Analysis We assessed risk of bias using tools developed by the Campbell Collaboration. We conducted meta‐analyses of the intervention studies where possible and carried out a framework synthesis of a set of implementation studies identified by purposive sampling to represent the most ‘rich’ and ‘thick’ data. Main Results We included 64 intervention studies and 41 implementation studies. The evidence base was dominated by studies from the USA and Canada. Participants were largely (though not exclusively) people who were literally homeless, that is, living on the streets or in shelters, and who had additional support needs. Many studies were assessed as having a medium or high risk of bias. However, there was some consistency in outcomes across studies that improved confidence in the main findings. Case Management and Housing Outcomes Case management of any description was superior to usual care for homelessness outcomes (standardised mean difference [SMD] = −0.51 [95% confidence interval [CI]: −0.71, −0.30]; p < 0.01). For studies included in the meta‐analyses, Housing First had the largest observed impact, followed by Assertive Community Treatment, Critical Time Intervention and Intensive Case Management. The only statistically significant difference was between Housing First and Intensive Case Management (SMD = −0.6 [–1.1, −0.1]; p = 0.03) at ≥12 months. There was not enough evidence to compare the above approaches with standard case management within the meta‐analyses. A narrative comparison across all studies was inconclusive, though suggestive of a trend in favour of more intensive approaches. Case Management and Mental Health Outcomes The overall evidence suggested that case management of any description was not more or less effective compared to usual care for an individual's mental health (SMD = 0.02 [−0.15, 0.18]; p = 0.817). Case Management and Other Outcomes Based on meta‐analyses, case management was superior to usual care for capability and wellbeing outcomes up to 1 year (an improvement of around one‐third of an SMD; p < 0.01) but was not statistically significantly different for substance use outcomes, physical health, and employment. Case Management Components For homelessness outcomes, there was a non‐significant trend for benefits to be greater in the medium term (≤3 years) compared to long term (>3 years) (SMD = −0.64 [−1.04, −0.24] vs. −0.27 [−0.53, 0]; p = 0.16) and for in‐person meetings in comparison to mixed (in‐person and remote) approaches (SMD = −0.73 [−1.25,−0.21]) versus −0.26 [−0.5,−0.02]; p = 0.13). There was no evidence from meta‐analyses to suggest that an individual case manager led to better outcomes then a team, and interventions with no dedicated case manager may have better outcomes than those with a named case manager (SMD = −0.36 [−0.55, −0.18] vs. −1.00 [−2.00, 0.00]; p = 0.02). There was not enough evidence from meta‐analysis to assess whether the case manager should have a professional qualification, or if frequency of contact, case manager availability or conditionality (barriers due to conditions attached to service provision) influenced outcomes. However, the main theme from implementation studies concerned barriers where conditions were attached to services. Characteristics of Persons Experiencing Homelessness No conclusions could be drawn from meta‐analysis other than a trend for greater reductions in homelessness for persons with high complexity of need (two or more support needs in addition to homelessness) as compared to those with medium complexity of need (one additional support need); effect sizes were SMD = −0.61 [−0.91, −0.31] versus −0.36 [−0.68, −0.05]; p = 0.3. The Broader Context of Delivery of Case Management Programmes Other major themes from the implementation studies included the importance of interagency partnership; provision for non‐housing support and training needs of PEH (such as independent living skills), intensive community support following the move to new housing; emotional support and training needs of case managers; and an emphasis on housing safety, security and choice. Cost Effectiveness The 12 studies with cost data provided contrasting results and no clear conclusions. Some case management costs may be largely off‐set by reductions in the use of other services. Cost estimates from three North American studies were $45–52 for each additional day housed. Authors' Conclusions Case management interventions improve housing outcomes for PEH with one or more additional support needs, with more intense interventions leading to greater benefits. Those with greater support needs may gain greater benefit. There is also evidence for improvements to capabilities and wellbeing. Current approaches do not appear to lead to mental health benefits. In terms of case management components, there is evidence in support of a team approach and in‐person meetings and, from the implementation evidence, that conditions associated with service provision should be minimised. The approach within Housing First could explain the finding that overall benefits may be greater than for other types of case management. Four of its principles were identified as key themes within the implementation studies: No conditionality, offer choice, provide an individualised approach and support community building. Recommendations for further research include an expansion of the research base outside North America and further exploration of case management components and intervention cost‐effectiveness.

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.

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)0.028
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0340.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.280
GPT teacher head0.475
Teacher spread0.196 · 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