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Record W6959621298 · doi:10.7939/r3-2f6y-wg37

Bridging the Psychological Treatment Gap Using Peer Support and Supportive Text Messaging

2022· dissertation· en· W6959621298 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2022
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicRice Cultivation and Yield Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthThematic analysisObservational studyPeer supportBridging (networking)Public healthSocial supportMental health servicePsychological intervention

Abstract

fetched live from OpenAlex

Background: Most discharged psychiatric patients in Alberta are offered follow-up appointments with Alberta Health Services (AHS) Addiction and Mental Health (A&MH) community providers. It is typical to wait weeks or months for a follow-up appointment, resulting in a substantial psychological treatment gap. The significance of this treatment gap became more evident during the COVID-19 pandemic. Objectives: 1) Evaluate effectiveness of innovative peer support worker services (PSWs) and of supportive text messages (Text4Support) provided to the patients discharged from acute care, in Edmonton, Alberta.; 2) Implement and evaluate effectiveness of a supportive texting service (Text4Hope) provided to the general public during the COVID-19 pandemic; 3) Identify the prevalence of mental health conditions during this pandemic. Methodology: Through a prospective, rater-blinded, four-arm controlled observational pilot trial, we examined the use of PSS and text messages (TxM) of Text4Support for post-discharged patients from acute psychiatric care. Patients (n=181) with mental health disorder were recruited and randomised to either (1) PSWs alone; (2) PSWs + TxM; (3) TxM alone; or (4) treatment as usual (TAU). During the pandemic, we provided a three-month supportive TxM to the general public (Text4Hope) service to support and monitor mental health in Alberta. Validated self-report questionnaires were used to assess mental health conditions. Data were collected at baseline, program midpoint (6 weeks), and endpoint (12 weeks). Statistical analyses including descriptive, correlational, inferential statistics and longitudinal data analysis, using SPSS, and thematic analysis using NVivo software. Results: Sixty-five patients completed assessments at each time point of the pilot study. Improved scores were reported for PSW+TxM compared with TAU condition on the total recovery assessment score and willingness to ask for help and personal confidence and hope domains, along with environment domain (physical safety and security) of WHO-QOL scale, and the functioning domain of CORE-OM scale. The PSW+TxM group consistently achieved better outcomes on CORE-OM recovery, clinical and reliable improvement. TxM and PSW+TxM arms significantly reduced prevalence of risk of self/other harm symptoms after six-month intervention. After one-year of Text4Hope service, participants providing valid responses to baseline, six-week, and three-month surveys comprised groups of 9214, 4110 and 1286, respectively. Statistically significant reductions mid-point reductions were observed for likely prevalence and mean scores of moderate or high stress and likely anxiety but not likely depression. After 3 months of using Text4Hope, there were significant reductions of prevalence and mean score compared with baseline on: the GAD-7 by 22.7%, PHQ-9 by 10.3%, and PSS-10 scores by 5.7%. Similar reductions were reported after one year of the service, with the largest reduction in anxiety (32.9%). By the time of exiting the service, 89.4% subscribers reported high satisfaction with Text4Hope, and 60.6-85.7% agreed that the service helped them in diverse ways. Messages were read and well-perceived by more than 90% of the subscribers. Conclusions: Positive outcomes were reported after implementing PSW and TxM programs in terms of clinical and functional improvements, customer satisfaction; and effective surveillance methodology for tracing changes in mental health, during the COVID-19 pandemic. Free mobile-based services such as Text4Hope or Text4Support can overcome financial barriers, while maintaining essential physical distancing required during pandemics, and providing means of support for those with no access to conventional mental health services. This work indicates the potential value of incorporating such interventions in routine service.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.030
GPT teacher head0.244
Teacher spread0.214 · 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 designOther design
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
Published2022
Admission routes1
Has abstractyes

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