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Record W4229374007 · doi:10.2196/36255

Web-Based Psychological Interventions for People Living With and Beyond Cancer: Meta-Review of What Works and What Does Not for Maximizing Recruitment, Engagement, and Efficacy

2022· review· en· W4229374007 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
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

VenueJMIR Cancer · 2022
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNorth West Cancer Research
KeywordsPsychological interventionCINAHLPsychosocialPsycINFODistressMedicineAnxietyMEDLINEIntervention (counseling)Clinical psychologyPsychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Despite high levels of psychological distress experienced by many patients with cancer, previous research has identified several barriers to accessing traditional face-to-face psychological support. Web-based psychosocial interventions have emerged as a promising alternative. OBJECTIVE: This meta-review aimed to synthesize evidence on recruitment challenges and enablers, factors that promote engagement and adherence to web-based intervention content, and factors that promote the efficacy of web-based psychosocial interventions for patients with cancer and cancer survivors. METHODS: We conducted a systematic search of previous reviews that investigated the recruitment, engagement, and efficacy of web-based and app-based psychosocial interventions in adult patients with cancer and cancer survivors. We searched PubMed, CINAHL, PsycINFO, and the Cochrane Library database for relevant literature. The search terms focused on a combination of topics pertaining to neoplasms and telemedicine. Two independent authors conducted abstract screening, full text screening, and data extraction for each identified article. RESULTS: A total of 20 articles met eligibility criteria. There was inconsistency in the reporting of uptake and engagement data; however, anxiety about technology and perceived time burden were identified as 2 key barriers. Web-based psychosocial oncology interventions demonstrated efficacy in reducing depression and stress but reported weak to mixed findings for distress, anxiety, quality of life, and well-being. Although no factors consistently moderated intervention efficacy, preliminary evidence indicated that multicomponent interventions and greater communication with a health care professional were preferred by participants and were associated with superior effects. CONCLUSIONS: Several consistently cited barriers to intervention uptake and recruitment have emerged, which we recommend future intervention studies address. Preliminary evidence also supports the superior efficacy of multicomponent interventions and interventions that facilitate communication with a health care professional. However, a greater number of appropriately powered clinical trials, including randomized trials with head-to-head comparisons, are needed to enable more confident conclusions regarding which web-based psychosocial oncology interventions work best and for whom. TRIAL REGISTRATION: PROSPERO CRD42020202633; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=202633.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.783
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
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)0.0010.000

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 head0.261
GPT teacher head0.462
Teacher spread0.201 · 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