Combined interventions vs no intervention: Re‐employment Measured as percentage or number of participants who obtained paid employment
Combined interventions probably leads to higher re‐employment Measured as percentage or number of participants who… compared with no intervention (moderate certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Combined interventions vs no intervention Re‐employment Measured as percentage or number of participants who obtained paid employment · Unemployed job seekers Combined interventions probably leads to higher re‐employment Measured as percentage or number of participants who… compared with no intervention (moderate certainty). Health‐improving interventions for obtaining employment in unemployed job seekers (2020) · Cochrane Headline outcomes only | RR 1.12 [1.06, 1.2] | 6 studies · 4101 participants | Moderate |
Combined interventions vs no intervention Re‐employment Measured as percentage or number of participants who obtained paid employment · Unemployed job seekers It is very uncertain whether combined interventions changes re‐employment Measured as percentage or number of participants who… compared with no intervention (very low certainty). Health‐improving interventions for obtaining employment in unemployed job seekers (2020) · Cochrane Headline outcomes only | RR 1.18 [0.78, 1.79] | 1 study · 66 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Health‐improving interventions for obtaining employment in unemployed job seekers 2020 · Cochrane Headline outcomes only | Not reported | list not extracted yet | Not assessed |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.