MétaCan
Menu
Back to cohort
Record W4300687628 · doi:10.1093/humupd/dmac034

Efficacy of psychological interventions for mental health and pregnancy rates among individuals with infertility: a systematic review and meta-analysis

2022· review· en· W4300687628 on OpenAlexafffund
Loveness Dube, Katherine Bright, Alix Hayden, Jennifer L. Gordon

Bibliographic record

VenueHuman Reproduction Update · 2022
Typereview
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of CalgaryAlberta Health ServicesUniversity of Regina
FundersCanadian Institutes of Health Research
KeywordsPsychological interventionMedicineAnxietyMeta-analysisRandomized controlled trialInfertilityPsycINFOMEDLINESystematic reviewDistressClinical psychologyPregnancyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Depression and anxiety are highly prevalent among individuals struggling with infertility. Thus, numerous psychological interventions have been adapted to infertility, with the aim of relieving distress as well as increasing pregnancy rates. OBJECTIVE AND RATIONALE: This systematic review and meta-analysis aimed to identify all randomized controlled trials (RCTs) evaluating the effect of psychological interventions on infertility-related distress and pregnancy rates among individuals and/or couples with infertility and to analyse their overall effect. It also sought to examine potential treatment moderators, including intervention length, format and therapeutic approach. SEARCH METHODS: An electronic search of 11 databases, including MEDLINE, EMBASE, PsycINFO and Cochrane Central Register of Controlled Trials, was performed for studies published until January 2022. The inclusion criteria were RCTs conducted on humans and published in English. Psychological outcomes of interest included anxiety, depression, infertility-related distress, wellbeing and marital satisfaction. The Cochrane Risk of Bias tool was used to assess study quality, and the Grading of Recommendations Assessment, Development and Evaluation was used to assess the overall quality of the research evidence. OUTCOMES: There were 58 RCTs in total, including 54 which included psychological outcomes and 21 which assessed pregnancy rates. Studies originated from all regions of the world, but nearly half of the studies were from the Middle East. Although a beneficial effect on combined psychological outcomes was found (Hedge's g = 0.82, P < 0.0001), it was moderated by region (P < 0.00001) such that studies from the Middle East exhibited large effects (g = 1.40, P < 0.0001), while the effects were small among studies conducted elsewhere (g = 0.23, P < 0.0001). Statistically adjusting for study region in a meta-regression, neither intervention length, therapeutic approach, therapy format, nor participant gender (P > 0.05) moderated the effect of treatment. A beneficial treatment effect on pregnancy (RR (95% CI) = 1.25 (1.07-1.47), P = 0.005) was not moderated by region, treatment length, approach or format (P > 0.05). Largely due to the lack of high quality RCTs, the quality of the available evidence was rated as low to moderate. WIDER IMPLICATIONS: This is the first meta-analysis of RCTs testing the effect of psychological interventions on infertility-related distress and pregnancy rates. These findings suggest that in most regions of the world, psychological interventions are associated with small reductions in distress and modest effects on conception, suggesting the need for more effective interventions. These findings must be considered in light of the fact that the majority of the included RCTs were deemed to be at high risk of bias. Rigorously conducted trials are needed.

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)0.014
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0190.036
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.328
GPT teacher head0.499
Teacher spread0.172 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations68
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueHuman Reproduction UpdateSame topicReproductive Health and TechnologiesFrench-language works237,207