Extraction form for project: Schedule of Visits and Televisits for Routine Antenatal Care
Design Details
1. Key Question this study addressed
Select all that apply.
2. Study DESIGN
3. Study DESIGN
4. If an RCT, please choose the randomization level
5. DIRECTIONALITY of the study
6. Registry record (e.g., NCT)
Please provide details on ClinicalTrials.gov NCT number, other country's protocol registry, or journal article protocols
7. Multiple publications
List PMID (if available) or "file name" of ALL publications extracted under this record
8. Study NAME or ACRONYM
Leave blank if there wasn't any. Copy Registry information if available.
9. COUNTRY the study was done
Select all that apply.
10. LOCATION (e.g., Dallas, TX)
11. HOSPITAL details: name and type
| Hospital name | |
| Hospital description | |
| Academic hospital | |
| Non-academic hospital | |
| NR |
12. Number of CENTERS involved in the study
13. FUNDING SOURCE
14. STUDY PERIOD
Leave blank if not specified.
| Start year | End year | |
|---|---|---|
15. Study INCLUSION criteria
Keep succinct. Use common abbreviations. Omit criteria of minor relevance (e.g., language, consent). Enter "NR" if not reported.
16. Study EXCLUSION criteria
Keep succinct. Use common abbreviations. Omit criteria of minor relevance (e.g., language, consent). Enter "NR" if not reported.
17. Specific population
18. Specific population
19. SAMPLE SIZE
20. Power calculation reported (y/n)
21. Primary outcome (for which power calculation was performed)
22. What was the EFFECT SIZE ESTIMATE used to calculate power
Usually RD (although they will describe as change in %). Format: RD +2.5% (5.5% to 8.0%)
23. Was primary outcome adequately powered (N≥ calculated N)
On Sample Characteristics tab, we ask about calculated sample sizes (actual N's).
24. What METHOD was used to account for confounding
25. What FACTORS were adjusted for
| List all factors | |
| Did ALL important factors have been adjusted? (including 1)age, 2)race/ethnicity, 3)at least one of the following factors: pre-existing DM, pre-existing HTN, obesity, prior preterm birth history, prior high risk pregnancy) |
26. NOTES regarding the design or any overall aspects of this study
Leave blank if you don't have any notes.
27. Unextracted outcomes not in protocol
Arms
| Arm Name | Arm Description |
|---|---|
| Less intensive antenatal visits schedule | Baby scripts |
| More intensive antenatal visits schedule | Standard care |
Arm Details
1. BRIEF DESCRIPTION of the intervention
Be specific, but concise.
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
2. Any guidelines (e.g., ACOG) the prenatal visits followed
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
3. Total number of visits
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
4. Number of visits (In person vs. Tele)
Less intensive antenatal visits schedule
| Number of in person visits | |
| Number of tele visits | |
| NR |
More intensive antenatal visits schedule
| Number of in person visits | |
| Number of tele visits | |
| NR |
5. Timing of visit (weeks)
Please provide a list of time of prenatal visit reported by the paper; enter NR if not reported
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
6. Setting of visits (Office vs. Home)
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
7. Format of visits (Group vs. Individual)
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
8. Provider of visits (record % if more than one type of providers were mentioned)
Less intensive antenatal visits schedule
| OB/GYN | |
| Nurse | |
| Nurse practitioner/registered nurse | |
| Midwife | |
| Family medicine clinician | |
| Maternal fetal medicine (MFM) | |
| Physician assistant (associate) | |
| Other licensed personnel | |
| NR |
More intensive antenatal visits schedule
| OB/GYN | |
| Nurse | |
| Nurse practitioner/registered nurse | |
| Midwife | |
| Family medicine clinician | |
| Maternal fetal medicine (MFM) | |
| Physician assistant (associate) | |
| Other licensed personnel | |
| NR |
9. PARTICIPANTS of the visit
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
10. Amount of time per visit
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
11. Tele visits details: TECHNOLOGY
Enter NR if not reported.
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
12. Tele visits details: Synchronous vs. asynchronous INTERACTIONS
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
13. Tele visits details: use of HOME MONITORING DEVICE
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
14. Tele visits details: Occurred during the pandemic
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
15. Other differences between groups
Briefly summarize differences other than number/timing of visits (KQ 1) or use of televisits (KQ 2) between arms.
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
16. NOTES regarding the arm details in this study
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Sample Characteristics
1. How many people were ENROLLED in this study
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
2. How many people were ANALYZED in this study
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
3. Required N from Power Calculation
Leave blank if no power calculation. Answer for each arm and total.
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
4. AGE distribution (CONTINUOUS DATA) (in years)
Select and enter data for all that apply.
Less intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
More intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
Total
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
5. AGE distribution (CATEGORICAL DATA) (in years)
Less intensive antenatal visits schedule
| Definition of category | % | |
|---|---|---|
| Youngest category | ||
| 2nd category | ||
| 3rd category | ||
| 4th category | ||
| 5th category | ||
| 6th category | ||
| NR |
More intensive antenatal visits schedule
| Definition of category | % | |
|---|---|---|
| Youngest category | ||
| 2nd category | ||
| 3rd category | ||
| 4th category | ||
| 5th category | ||
| 6th category | ||
| NR |
Total
| Definition of category | % | |
|---|---|---|
| Youngest category | ||
| 2nd category | ||
| 3rd category | ||
| 4th category | ||
| 5th category | ||
| 6th category | ||
| NR |
6. % of maternal age≥35
Please calculate if possible, and enter NR if not reported.
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
7. RACIAL distribution (%)
Less intensive antenatal visits schedule
| % | |
|---|---|
| White (or Caucasian) | |
| Black (or African) | |
| Asian | |
| Hispanic (or Latino) | |
| Other 1 | |
| Other 2 | |
| NR |
More intensive antenatal visits schedule
| % | |
|---|---|
| White (or Caucasian) | |
| Black (or African) | |
| Asian | |
| Hispanic (or Latino) | |
| Other 1 | |
| Other 2 | |
| NR |
Total
| % | |
|---|---|
| White (or Caucasian) | |
| Black (or African) | |
| Asian | |
| Hispanic (or Latino) | |
| Other 1 | |
| Other 2 | |
| NR |
8. BMI distribution pre-pregnancy or at first encounter (CONTINUOUS DATA)
Select and enter data for all that apply.
Less intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
More intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
Total
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
9. BMI distribution pre-pregnancy or at first encounter (CATEGORICAL DATA)
Less intensive antenatal visits schedule
| Definition of category | % | |
|---|---|---|
| Lowest BMI category | ||
| 2nd BMI category | ||
| 3rd BMI category | ||
| 4th BMI category | ||
| 5th BMI category | ||
| 6th BMI category | ||
| NR |
More intensive antenatal visits schedule
| Definition of category | % | |
|---|---|---|
| Lowest BMI category | ||
| 2nd BMI category | ||
| 3rd BMI category | ||
| 4th BMI category | ||
| 5th BMI category | ||
| 6th BMI category | ||
| NR |
Total
| Definition of category | % | |
|---|---|---|
| Lowest BMI category | ||
| 2nd BMI category | ||
| 3rd BMI category | ||
| 4th BMI category | ||
| 5th BMI category | ||
| 6th BMI category | ||
| NR |
10. INCOME distribution (CONTINUOUS DATA)
Select and enter data for all that apply.
Less intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
More intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
Total
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
11. INCOME distribution (CATEGORICAL DATA)
Less intensive antenatal visits schedule
| Definition of category | % | |
|---|---|---|
| Lowest INCOME category | ||
| 2nd INCOME category | ||
| 3rd INCOME category | ||
| 4th INCOME category | ||
| 5th INCOME category | ||
| 6th INCOME category | ||
| NR |
More intensive antenatal visits schedule
| Definition of category | % | |
|---|---|---|
| Lowest INCOME category | ||
| 2nd INCOME category | ||
| 3rd INCOME category | ||
| 4th INCOME category | ||
| 5th INCOME category | ||
| 6th INCOME category | ||
| NR |
Total
| Definition of category | % | |
|---|---|---|
| Lowest INCOME category | ||
| 2nd INCOME category | ||
| 3rd INCOME category | ||
| 4th INCOME category | ||
| 5th INCOME category | ||
| 6th INCOME category | ||
| NR |
12. EDUCATION distribution (%) (CATEGORICAL DATA)
Less intensive antenatal visits schedule
| % | |
|---|---|
| Primary school or below | |
| Junior high school | |
| High school | |
| College or above | |
| NR |
More intensive antenatal visits schedule
| % | |
|---|---|
| Primary school or below | |
| Junior high school | |
| High school | |
| College or above | |
| NR |
Total
| % | |
|---|---|
| Primary school or below | |
| Junior high school | |
| High school | |
| College or above | |
| NR |
13. Yeas of education completed (CONTINUOUS DATA)
Select and enter data for all that apply.
Less intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
More intensive antenatal visits schedule
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
Total
| Mean | Standard deviation (SD) | Standard error (SE) | 95% CI | Median | IQR | Range | NR | |
|---|---|---|---|---|---|---|---|---|
14. RELATIONSHIP status (%)
Less intensive antenatal visits schedule
| % | |
|---|---|
| Married | |
| Unmarried but marriage-like relationships | |
| Single | |
| Other | |
| NR |
More intensive antenatal visits schedule
| % | |
|---|---|
| Married | |
| Unmarried but marriage-like relationships | |
| Single | |
| Other | |
| NR |
Total
| % | |
|---|---|
| Married | |
| Unmarried but marriage-like relationships | |
| Single | |
| Other | |
| NR |
15. EMPLOYMENT distribution
Less intensive antenatal visits schedule
| % | |
|---|---|
| Full time | |
| Part time | |
| Unemployment | |
| Other | |
| NR |
More intensive antenatal visits schedule
| % | |
|---|---|
| Full time | |
| Part time | |
| Unemployment | |
| Other | |
| NR |
Total
| % | |
|---|---|
| Full time | |
| Part time | |
| Unemployment | |
| Other | |
| NR |
16. % of nulliparous women
If answering "NR", enter NR under specific arms, NOT total
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
17. % of unplanned pregnancy
If answering "NR", enter NR under specific arms, NOT total
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
18. % of multiple gestation
If answering "NR", enter NR under specific arms, NOT total
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
19. COMORBIDITIES
Define the comorbidities. If % reported, enter % for total sample and each study arm. Skip those that are not reported.
Less intensive antenatal visits schedule
| Definition | % | |
|---|---|---|
| CVD (total) | ||
| Pregestational HTN | ||
| Gestational HTN | ||
| DM, type 1 | ||
| Pregestational DM | ||
| Gestational DM | ||
| Depression | ||
| Anxiety | ||
| Intrauterine growth restriction (IUGR) or fetal growth restriction | ||
| Prior history or risk factors for preterm delivery | ||
| Tobacco, any | ||
| Other pre-existing conditions | ||
| NR |
More intensive antenatal visits schedule
| Definition | % | |
|---|---|---|
| CVD (total) | ||
| Pregestational HTN | ||
| Gestational HTN | ||
| DM, type 1 | ||
| Pregestational DM | ||
| Gestational DM | ||
| Depression | ||
| Anxiety | ||
| Intrauterine growth restriction (IUGR) or fetal growth restriction | ||
| Prior history or risk factors for preterm delivery | ||
| Tobacco, any | ||
| Other pre-existing conditions | ||
| NR |
Total
| Definition | % | |
|---|---|---|
| CVD (total) | ||
| Pregestational HTN | ||
| Gestational HTN | ||
| DM, type 1 | ||
| Pregestational DM | ||
| Gestational DM | ||
| Depression | ||
| Anxiety | ||
| Intrauterine growth restriction (IUGR) or fetal growth restriction | ||
| Prior history or risk factors for preterm delivery | ||
| Tobacco, any | ||
| Other pre-existing conditions | ||
| NR |
20. SOCIAL SUPPORT
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
21. Pregnancy EDUCATION NEEDS
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
22. Live in RURAL/URBAN areas (%)
Less intensive antenatal visits schedule
| % | |
|---|---|
| Rural | |
| Urban | |
| Others | |
| NR |
More intensive antenatal visits schedule
| % | |
|---|---|
| Rural | |
| Urban | |
| Others | |
| NR |
Total
| % | |
|---|---|
| Rural | |
| Urban | |
| Others | |
| NR |
23. % of food insecurity
If answering "NR", enter NR under specific arms, NOT total
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
24. INSURANCE status (%)
Less intensive antenatal visits schedule
| % | |
|---|---|
| Private | |
| Medicare | |
| Medicaid | |
| Others | |
| NR |
More intensive antenatal visits schedule
| % | |
|---|---|
| Private | |
| Medicare | |
| Medicaid | |
| Others | |
| NR |
Total
| % | |
|---|---|
| Private | |
| Medicare | |
| Medicaid | |
| Others | |
| NR |
25. TRANSPORTATION to health care facilities
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
26. % of having internet access at home
If answering "NR", enter NR under specific arms, NOT total
Less intensive antenatal visits schedule
| % | |
|---|---|
| Have internet access |
More intensive antenatal visits schedule
| % | |
|---|---|
| Have internet access |
Total
| % | |
|---|---|
| Have internet access |
27. Other information regarding ACCESS TO CARE
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
28. Any baseline DIFFERENCES between two arms (p<0.05)?
If answering yes, choose yes under "Total", and make a note on what factors
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
29. Experienced gestational age at first prenatal visit (weeks)
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
30. NOTES regarding the sample characteristics in this study
Less intensive antenatal visits schedule
More intensive antenatal visits schedule
Total
Outcomes
- All Participants
- N/A
- All Participants
- First trimester
- 30 (wk)
- Postpartum
| Type | Domain | Specific measurement (i.e., tool/definition/specific outcome) | Populations | Timepoints |
|---|---|---|---|---|
| Continuous | Number of in person visits | |||
| Continuous | Patient satisfaction with antenatal care |
Outcome Details
1. NOTES regarding the outcome
Also indicate when an outcome is extracted from a co-publication (not the primary publication)
Number of in person visits
Patient satisfaction with antenatal care
RCT Risk of Bias Assessment
1. 1.1 Was the allocation sequence random?
| Rating | |
| Notes/Comments: |
2. 1.2 Was the allocation sequence concealed until participants were enrolled and assigned to interventions?
| Rating | |
| Notes/Comments: |
3. 1.3 Did baseline differences between intervention groups suggest a problem with the randomization process?
| Rating | |
| Notes/Comments: |
4. Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
5. 2.1. (effect of assignment to intervention) Were participants aware of their assigned intervention during the trial?
| Rating | |
| Notes/Comments: |
6. 2.2. (effect of assignment to intervention) Were carers and people delivering the interventions aware of participants' assigned intervention during the trial?
| Rating | |
| Notes/Comments: |
7. 2.3. (effect of assignment to intervention) If Y/PY/NI to 2.1 or 2.2: Were there deviations from the intended intervention that arose because of the experimental context?
Consider non-adherence or crossover
| Rating | |
| Notes/Comments: |
8. 2.4. (effect of assignment to intervention) If Y/PY to 2.3: Were these deviations from intended intervention balanced between groups?
| Rating | |
| Notes/Comments: |
9. 2.5. (effect of assignment to intervention) If N/PN/NI to 2.4: Were these deviations likely to have affected the outcome?
| Rating | |
| Notes/Comments: |
10. 2.6. (effect of assignment to intervention) Was an appropriate analysis used to estimate the effect of assignment to intervention?
(modified) intention-to-treat analysis
| Rating | |
| Notes/Comments: |
11. 2.7. (effect of assignment to intervention) If N/PN/NI to 2.6: Was there potential for a substantial impact (on the result) of the failure to analyse participants in the group to which they were randomized?
Should be <5% for crossover
| Rating | |
| Notes/Comments: |
12. Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
13. 2.1. (effect of adhering to intervention) Were participants aware of their assigned intervention during the trial?
| Rating | |
| Notes/Comments: |
14. 2.2. (effect of adhering to intervention) Were carers and people delivering the interventions aware of participants' assigned intervention during the trial?
| Rating | |
| Notes/Comments: |
15. 2.3. (effect of adhering to intervention) If Y/PY/NI to 2.1 or 2.2: Were important co-interventions balanced across intervention groups?
| Rating | |
| Notes/Comments: |
16. 2.4. (effect of adhering to intervention) Were there failures in implementing the intervention that could have affected the outcome?
| Rating | |
| Notes/Comments: |
17. 2.5. (effect of adhering to intervention) Was there non-adherence to the assigned intervention regimen that could have affected participants’ outcomes?
| Rating | |
| Notes/Comments: |
18. 2.6. (effect of adhering to intervention) If N/PN/NI to 2.3 or 2.5 or Y/PY/NI to 2.4: Was an appropriate analysis used to estimate the effect of adhering to the intervention?
| Rating | |
| Notes/Comments: |
19. Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
20. 3.1. Were data for this outcome available for all, or nearly all, participants randomized?
Should be <10% lost to follow-up
| Rating | |
| Notes/Comments: |
21. 3.2. If N/PN/NI to 3.1: Is there evidence that the result was not biased by missing outcome data?
| Rating | |
| Notes/Comments: |
22. 3.3. If N/PN to 3.2: Could missingness in the outcome depend on its true value?
| Rating | |
| Notes/Comments: |
23. 3.4. If Y/PY/NI to 3.3: Is it likely that missingness in the outcome depended on its true value?
| Rating | |
| Notes/Comments: |
24. Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
25. 4.1. Was the method of measuring the outcome inappropriate?
| Rating | |
| Notes/Comments: |
26. 4.2. Could measurement or ascertainment of the outcome have differed between intervention groups?
| Rating | |
| Notes/Comments: |
27. 4.3. If N/PN/NI to 4.1 and 4.2: Were outcome assessors aware of the intervention received by study participants?
| Rating | |
| Notes/Comments: |
28. 4.4. If Y/PY/NI to 4.3: Could assessment of the outcome have been influenced by knowledge of intervention received?
| Rating | |
| Notes/Comments: |
29. 4.5. If Y/PY/NI to 4.4: Is it likely that assessment of the outcome was influenced by knowledge of intervention received?
| Rating | |
| Notes/Comments: |
30. Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
31. 5.1. Were the data that produced this result analysed in accordance with a pre-specified analysis plan that was finalized before unblinded outcome data were available for analysis?
| Rating | |
| Notes/Comments: |
32. 5.2. Is the numerical result being assessed likely to have been selected, on the basis of the results, from multiple outcome measurements (e.g. scales, definitions, time points) within the outcome domain?
| Rating | |
| Notes/Comments: |
33. 5.3. Is the numerical result being assessed likely to have been selected, on the basis of the results, from multiple analyses of the data
| Rating | |
| Notes/Comments: |
34. Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
35. Other potential bias
36. Overall Risk-of-bias judgement
| Rating | |
| Notes/Comments: |
NRCS Risk of Bias Assessment
1. 1.1 Is there potential for confounding of the effect of intervention in this study?
In rare situations, such as when studying harms that are very unlikely to be related to factors that influence treatment decisions, no confounding is expected and the study can be considered to be at low risk of bias due to confounding, equivalent to a fully randomized trial. There is no NI (No information) option for this signalling question. If N/PN to 1.1: the study can be considered to be at low risk of bias due to confounding and no further signalling questions need be considered. If Y/PY to 1.1: determine whether there is a need to assess time-varying confounding:
| Rating | |
| Notes/Comments: |
2. 1.2 Was the analysis based on splitting participants’ follow up time according to intervention received?
If participants could switch between intervention groups then associations between intervention and outcome may be biased by time-varying confounding. This occurs when prognostic factors influence switches between intended interventions. If N/PN, answer questions relating to baseline confounding (1.4 to 1.6). If Y/PY, proceed to question 1.3.
| Rating | |
| Notes/Comments: |
3. 1.3 Were intervention discontinuations or switches likely to be related to factors that are prognostic for the outcome?
If intervention switches are unrelated to the outcome, for example when the outcome is an unexpected harm, then time-varying confounding will not be present and only control for baseline confounding is required.
| Rating | |
| Notes/Comments: |
4. 1.4. Did the authors use an appropriate analysis method that controlled for all the important confounding domains?
Appropriate methods to control for measured confounders include stratification, regression, matching, standardization, and inverse probability weighting. They may control for individual variables or for the estimated propensity score. Inverse probability weighting is based on a function of the propensity score. Each method depends on the assumption that there is no unmeasured or residual confounding. if Propensity score matching/adjustment or equivalent, answer Y. If regression or other matching answer PY with a note reporting method. IMPORTANT CONFOUNDING DOMAINS defined by our team include: 1)age, 2)race/ethnicity, 3)at least one of the following factors: pre-existing DM, pre-existing HTN, obesity, prior preterm birth history, prior high risk pregnancy.
| Rating | |
| Notes/Comments: |
5. 1.5. If Y/PY to 1.4: Were confounding domains that were controlled for measured validly and reliably by the variables available in this study?
Appropriate control of confounding requires that the variables adjusted for are valid and reliable measures of the confounding domains. For some topics, a list of valid and reliable measures of confounding domains will be specified in the review protocol but for others such a list may not be available. Study authors may cite references to support the use of a particular measure. If authors control for confounding variables with no indication of their validity or reliability pay attention to the subjectivity of the measure. Subjective measures (e.g. based on self-report) may have lower validity and reliability than objective measures such as lab findings.
| Rating | |
| Notes/Comments: |
6. 1.6. Did the authors control for any post-intervention variables that could have been affected by the intervention?
Controlling for post-intervention variables that are affected by intervention is not appropriate. Controlling for mediating variables estimates the direct effect of intervention and may introduce bias. Controlling for common effects of intervention and outcome introduces bias.
| Rating | |
| Notes/Comments: |
7. 1.7. Did the authors use an appropriate analysis method that adjusted for all the important confounding domains and for time-varying confounding?
Adjustment for time-varying confounding is necessary to estimate the effect of starting and adhering to intervention, in both randomized trials and NRSI. Appropriate methods include those based on inverse probability weighting. Standard regression models that include time-updated confounders may be problematic if time-varying confounding is present.
| Rating | |
| Notes/Comments: |
8. 1.8. If Y/PY to 1.7: Were confounding domains that were adjusted for measured validly and reliably by the variables available in this study?
See 1.5 above
| Rating | |
| Notes/Comments: |
9. 2.1. Was selection of participants into the study (or into the analysis) based on participant characteristics observed after the start of intervention?
This domain is concerned only with selection into the study based on participant characteristics observed after the start of intervention. Selection based on characteristics observed before the start of intervention can be addressed by controlling for imbalances between experimental intervention and comparator groups in baseline characteristics that are prognostic for the outcome (baseline confounding). If N/PN to 2.1: go to 2.4
| Rating | |
| Notes/Comments: |
10. 2.2. If Y/PY to 2.1: Were the post-intervention variables that influenced selection likely to be associated with intervention?
Selection bias occurs when selection is related to an effect of either intervention or a cause of intervention and an effect of either the outcome or a cause of the outcome. Therefore, the result is at risk of selection bias if selection into the study is related to both the intervention and the outcome.
| Rating | |
| Notes/Comments: |
11. 2.3 If Y/PY to 2.2: Were the post-intervention variables that influenced selection likely to be influenced by the outcome or a cause of the outcome?
| Rating | |
| Notes/Comments: |
12. 2.4. Do start of follow-up and start of intervention coincide for most participants?
If participants are not followed from the start of the intervention then a period of follow up has been excluded, and individuals who experienced the outcome soon after intervention will be missing from analyses. This problem may occur when prevalent, rather than new (incident), users of the intervention are included in analyses.
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13. 2.5. If Y/PY to 2.2 and 2.3, or N/PN to 2.4: Were adjustment techniques used that are likely to correct for the presence of selection biases?
It is in principle possible to correct for selection biases, for example by using inverse probability weights to create a pseudo-population in which the selection bias has been removed, or by modelling the distributions of the missing participants or follow up times and outcome events and including them using missing data methodology. However such methods are rarely used and the answer to this question will usually be ‘No’.
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14. 3.1 Were intervention groups clearly defined?
A pre-requisite for an appropriate comparison of interventions is that the interventions are well defined. Ambiguity in the definition may lead to bias in the classification of participants. For individual-level interventions, criteria for considering individuals to have received each intervention should be clear and explicit, covering issues such as type, setting, dose, frequency, intensity and/or timing of intervention. For population-level interventions (e.g. measures to control air pollution), the question relates to whether the population is clearly defined, and the answer is likely to be ‘Yes’
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15. 3.2 Was the information used to define intervention groups recorded at the start of the intervention?
In general, if information about interventions received is available from sources that could not have been affected by subsequent outcomes, then differential misclassification of intervention status is unlikely. Collection of the information at the time of the intervention makes it easier to avoid such misclassification. For population-level interventions (e.g. measures to control air pollution), the answer to this question is likely to be ‘Yes’.
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16. 3.3 Could classification of intervention status have been affected by knowledge of the outcome or risk of the outcome?
Collection of the information at the time of the intervention may not be sufficient to avoid bias. The way in which the data are collected for the purposes of the NRSI should also avoid misclassification.
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17. 4.1. Were there deviations from the intended intervention beyond what would be expected in usual practice?
Deviations that happen in usual practice following the intervention (for example, cessation of a drug intervention because of acute toxicity) are part of the intended intervention and therefore do not lead to bias in the effect of assignment to intervention. Deviations may arise due to expectations of a difference between intervention and comparator (for example because participants feel unlucky to have been assigned to the comparator group and therefore seek the active intervention, or components of it, or other interventions). Such deviations are not part of usual practice, so may lead to biased effect estimates. However these are not expected in observational studies of individuals in routine care.
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18. 4.2. If Y/PY to 4.1: Were these deviations from intended intervention unbalanced between groups and likely to have affected the outcome?
Deviations from intended interventions that do not reflect usual practice will be important if they affect the outcome, but not otherwise. Furthermore, bias will arise only if there is imbalance in the deviations across the two groups.
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19. 4.3. Were important co-interventions balanced across intervention groups?
Risk of bias will be higher if unplanned co-interventions were implemented in a way that would bias the estimated effect of intervention. Co-interventions will be important if they affect the outcome, but not otherwise. Bias will arise only if there is imbalance in such co-interventions between the intervention groups. Consider the co-interventions, including any pre-specified co-interventions, that are likely to affect the outcome and to have been administered in this study. Consider whether these co-interventions are balanced between intervention groups.
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20. 4.4. Was the intervention implemented successfully for most participants?
Risk of bias will be higher if the intervention was not implemented as intended by, for example, the health care professionals delivering care during the trial. Consider whether implementation of the intervention was successful for most participants.
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21. 4.5. Did study participants adhere to the assigned intervention regimen?
Risk of bias will be higher if participants did not adhere to the intervention as intended. Lack of adherence includes imperfect compliance, cessation of intervention, crossovers to the comparator intervention and switches to another active intervention. Consider available information on the proportion of study participants who continued with their assigned intervention throughout follow up, and answer ‘No’ or ‘Probably No’ if this proportion is high enough to raise concerns. Answer ‘Yes’ for studies of interventions that are administered once, so that imperfect adherence is not possible.
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22. 4.6. If N/PN to 4.3, 4.4 or 4.5: Was an appropriate analysis used to estimate the effect of starting and adhering to the intervention?
It is possible to conduct an analysis that corrects for some types of deviation from the intended intervention. Examples of appropriate analysis strategies include inverse probability weighting or instrumental variable estimation. It is possible that a paper reports such an analysis without reporting information on the deviations from intended intervention, but it would be hard to judge such an analysis to be appropriate in the absence of such information. Specialist advice may be needed to assess studies that used these approaches. If everyone in one group received a co-intervention, adjustments cannot be made to overcome this.
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23. 5.1 Were outcome data available for all, or nearly all, participants?
‘Nearly all’ should be interpreted as ‘enough to be confident of the findings’, and a suitable proportion depends on the context. In some situations, availability of data from 95% (or possibly 90%) of the participants may be sufficient, providing that events of interest are reasonably common in both intervention groups. One aspect of this is that review authors would ideally try and locate an analysis plan for the study.
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24. 5.2 Were participants excluded due to missing data on intervention status?
Missing intervention status may be a problem. This requires that the intended study sample is clear, which it may not be in practice.
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25. 5.3 Were participants excluded due to missing data on other variables needed for the analysis?
This question relates particularly to participants excluded from the analysis because of missing information on confounders that were controlled for in the analysis.
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26. 5.4 If PN/N to 5.1, orY/PY to 5.2 or 5.3: Are the proportion of participants and reasons for missing data similar across interventions?
This aims to elicit whether either (i) differential proportion of missing observations or (ii) differences in reasons for missing observations could substantially impact on our ability to answer the question being addressed. ‘Similar’ includes some minor degree of discrepancy across intervention groups as expected by chance.
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27. 5.5 If PN/N to 5.1, orY/PY to 5.2 or 5.3: Is there evidence that results were robust to the presence of missing data?
Evidence for robustness may come from how missing data were handled in the analysis and whether sensitivity analyses were performed by the investigators, or occasionally from additional analyses performed by the systematic reviewers. It is important to assess whether assumptions employed in analyses are clear and plausible. Both content knowledge and statistical expertise will often be required for this. For instance, use of a statistical method such as multiple imputation does not guarantee an appropriate answer. Review authors should seek naïve (complete-case) analyses for comparison, and clear differences between complete-case and multiple imputation-based findings should lead to careful assessment of the validity of the methods used.
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28. 6.1 Could the outcome measure have been influenced by knowledge of the intervention received?
Some outcome measures involve negligible assessor judgment, e.g. all-cause mortality or non-repeatable automated laboratory assessments. Risk of bias due to measurement of these outcomes would be expected to be low.
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29. 6.2 Were outcome assessors aware of the intervention received by study participants?
If outcome assessors were blinded to intervention status, the answer to this question would be ‘No’. In other situations, outcome assessors may be unaware of the interventions being received by participants despite there being no active blinding by the study investigators; the answer this question would then also be‘No’. In studies where participants report their outcomes themselves, for example in a questionnaire, the outcome assessor is the study participant. In an observational study, the answer to this question will usually be ‘Yes’ when the participants report their outcomes themselves.
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30. 6.3 Were the methods of outcome assessment comparable across intervention groups?
Comparable assessment methods (i.e. data collection) would involve the same outcome detection methods and thresholds, same time point, same definition, and same measurements.
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31. 6.4 Were any systematic errors in measurement of the outcome related to intervention received?
This question refers to differential misclassification of outcomes. Systematic errors in measuring the outcome, if present, could cause bias if they are related to intervention or to a confounder of the intervention-outcome relationship. This will usually be due either to outcome assessors being aware of the intervention received or to non-comparability of outcome assessment methods, but there are examples of differential misclassification arising despite these controls being in place.
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32. 7.1. (Is the reported effect estimate likely to be selected, on the basis of the results, from) multiple outcome measurements within the outcome domain?
For a specified outcome domain, it is possible to generate multiple effect estimates for different measurements. If multiple measurements were made, but only one or a subset is reported, there is a risk of selective reporting on the basis of results.
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33. 7.2. (Is the reported effect estimate likely to be selected, on the basis of the results, from) multiple analyses of the intervention-outcome relationship?
Because of the limitations of using data from non-randomized studies for analyses of effectiveness (need to control confounding, substantial missing data, etc), analysts may implement different analytic methods to address these limitations. Examples include unadjusted and adjusted models; use of final value vs change from baseline vs analysis of covariance; different transformations of variables; a continuously scaled outcome converted to categorical data with different cut-points; different sets of covariates used for adjustment; and different analytic strategies for dealing with missing data. Application of such methods generates multiple estimates of the effect of the intervention versus the comparator on the outcome. If the analyst does not pre-specify the methods to be applied, and multiple estimates are generated but only one or a subset is reported, there is a risk of selective reporting on the basis of results.
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34. 7.3. (Is the reported effect estimate likely to be selected, on the basis of the results, from) different subgroups?
Particularly with large cohorts often available from routine data sources, it is possible to generate multiple effect estimates for different subgroups or simply to omit varying proportions of the original cohort. If multiple estimates are generated but only one or a subset is reported, there is a risk of selective reporting on the basis of results.
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Single Group Risk of Bias Assessment
N/A
Results
Continuous
Patient satisfaction with antenatal care
| Descriptive Statistics | Between Arm Comparisons | ||||
|---|---|---|---|---|---|
| Less intensive antenatal visits schedule | More intensive antenatal visits schedule | All Arms (ANOVA) | |||
First trimester | |||||
| Total (N analyzed) | p value | ||||
| Mean | |||||
| SD | |||||
30 (wk) | |||||
| Total (N analyzed) | p value | ||||
| Mean | |||||
| SD | |||||
Postpartum | |||||
| Total (N analyzed) | p value | ||||
| Mean | |||||
| SD | |||||
| Within Arm Comparisons | Net Comparisons | ||||
| Less intensive antenatal visits schedule | More intensive antenatal visits schedule | All Arms (ANOVA) | |||
Number of in person visits
| Descriptive Statistics | Between Arm Comparisons | ||||
|---|---|---|---|---|---|
| Less intensive antenatal visits schedule | More intensive antenatal visits schedule | ||||
N/A | |||||
| Total (N analyzed) | Odds Ratio (OR) | ||||
| Mean | 95% CI low (OR) | ||||
| SD | 95% CI high (OR) | ||||
| p value | |||||
| Within Arm Comparisons | Net Comparisons | ||||
| Less intensive antenatal visits schedule | More intensive antenatal visits schedule | ||||