Final Impact Evaluation Report Tables Template for Healthy Marriage and Responsible Fatherhood Grantees
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NOTE: In all tables and figures in this template, example information is included in italics. Please use as a guide and remove before completing tables/figures. Please use a regular font in your final tables. Instructions for completing all tables are included in the impact report instructions document.
Table Il.1. Description of intended intervention and counterfactual components and target populations
Component |
Curriculum and content |
Dosage and schedule |
Delivery |
Target Population |
Intervention |
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Relationship skills workshops |
Healthy relationships curriculum: Understanding partner’s perspectives; avoiding destructive conflict; and communicating effectively |
20 hours, with 2-hour sessions occurring twice a week, or 4-hour sessions occurring every Saturday |
Group lessons provided at the intervention’s facilities by two trained facilitators in every session |
Low-income married couples |
Economic stability workshops |
Resume preparation; interview and communication skills; appropriate work attire; financial literacy |
Monthly 2-hour workshops |
Workshops are provided by one facilitator |
Individual members of the couple who need job search assistance |
Counterfactual |
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Economic stability workshops |
Resume preparation; interview and communication skills; appropriate work attire; financial literacy |
Monthly 2-hour workshops |
Workshops are provided by one facilitator |
Individual members of the couple who need job search assistance |
Notes: [Anything important to note about the information above]
Table II.2. Staff training and development to support intervention and counterfactual components
Component |
Education and initial training of staff |
Ongoing training of staff |
Intervention |
||
Relationship skills workshops |
Facilitators are male and female and hold at least a bachelor’s degree and received four days of initial training. |
Facilitators receive a half-day of semi-annual refresher training in the intervention’s curricula from study staff. |
Economic stability workshops |
Facilitators are male and female and hold at least a bachelor’s degree and received two days of initial training. |
Facilitators receive a half-day of semi-annual refresher training in the intervention’s curricula from study staff. |
Counterfactual |
||
Economic stability workshops |
Facilitators are male and female and hold at least a bachelor’s degree and received two days of initial training. |
Facilitators receive a half-day of semi-annual refresher training in the intervention’s curricula from study staff. |
Notes: [Anything important to note about the information above]
Table IV.1a. Individual sample sizes by intervention status (Only use for studies with individual-level assignment; if your design uses cluster-level assignment, skip this table and use Table IV.1b instead)
Number of individuals |
Intervention sample size |
Comparison sample size |
Total sample size |
Total response rate |
Intervention response rate |
Comparison response rate |
Assigned to condition |
1a |
1b |
1c (=1a + 1b) |
N/A |
NA |
N/A |
Contributed a baseline survey |
2a |
2b |
2c (=2a + 2b) |
=2c/1c |
=2a/1a |
=2b/1b |
Contributed to first follow-up survey (timing) |
3a |
3b |
3c (=3a + 3b) |
=3c/1c |
=3a/1a |
=3b/1b |
Contributed to first follow-up (timing) (accounts for item non-response and any other analysis restrictions) |
4a |
4b |
4c (=4a + 4b) |
=4c/1c |
=4a/1a |
=4b/1b |
Contributed to second follow-up survey (timing) |
5a |
5b |
5c (=5a + 5b) |
=5c/1c |
=5a/1a |
=5b/1b |
Contributed to second follow-up (timing) (accounts for item non-response and any other analysis restrictions) |
6a |
6b |
6c (=6a + 6b) |
=6c/1c |
=6a/1a |
=6b/1b |
Notes: [Anything important to note about the information above]
Reminder from instructions: For rows that account for item non-response and other analysis restriction, note that you may have very different sample sizes for two outcomes of interest because of very different rates of missing data for the outcomes. If this is the case, please add a row for each outcome in each time period, as needed. Indicate in a table note to which outcome the sample sizes apply. For example, if you have two primary outcomes and there was very different response rates on the items needed to construct these outcomes, you should include two rows for “Contributed to first follow-up (accounts for item non-response and other analysis restrictions)”: one for the analysis sample for outcome one and one for the analysis sample for outcome two.
Table IV.1b. Cluster and individual sample sizes by intervention status (Only use studies with cluster-level assignment; if your design uses individual-level assignment, skip this table and use Table IV.1a instead)
Number of: |
Intervention sample size |
Comparison sample size |
Total
|
Total response rate |
Intervention response rate |
Comparison response rate |
Clusters |
|
|
|
|
|
|
Clusters: At beginning of study |
1a |
1b |
1c (=1a + 1b) |
N/A |
NA |
N/A |
Clusters: Contributed at least one individual at baseline |
2a |
2b |
2c (=2a + 2b) |
=2c/1c |
=2a/1a |
=2b/1b |
Clusters: Contributed at least one individual at first follow-up (timing) |
3a |
3b |
3c (=3a + 3b) |
=3c/1c |
=3a/1a |
=3b/1b |
Clusters: Contributed at least one individual at second follow-up (timing) |
4a |
4b |
4c (=4a + 4b) |
=4c/1c |
=4a/1a |
=4b/1b |
Individuals in non-attriting clustersa |
|
|
|
|
|
|
Individual: At time that clusters were assigned to condition |
5a |
5b |
5c (=5a + 5b) |
N/A |
NA |
N/A |
Individual: Who consented |
6a |
6b |
6c (=6a + 6b) |
=6c/5c |
=6a/5a |
=6b/5b |
Individual: Contributed a baseline survey |
7a |
7b |
7c (=7a + 7b) |
=7c/5c |
=8a/5a |
=8b/5b |
Individual: Contributed to first follow-up survey (timing) |
8a |
8b |
8c (=8a + 8b) |
=8c/5c |
=9a/5a |
=9b/5b |
Individual: Contributed to the impact analysis at first follow-up (timing) (accounts for item non-response and any other analysis restrictions)b |
9a |
9b |
9c (=9a + 9b) |
=9c/5c |
=9a/5a |
=9b/5b |
Individual: Contributed to second follow-up survey (timing) |
10a |
10b |
10c (=10a + 10b) |
=10c/5c |
=10a/5a |
=10b/5b |
Individual: Contributed to the impact analysis at second follow-up (timing) (accounts for item non-response and any other analysis restrictions)b |
11a |
11b |
11c (=11a + 11b) |
=11/5c |
=11a/5a |
=11b/5b |
a For all rows in this section, do not include individuals from clusters that dropped (attrited) over the course of the study. For example, if you randomly assigned 10 clusters (5 to each condition), and one intervention group cluster (e.g. school) dropped from the study, you would only include individuals in this section from the 9 clusters that did not drop from the study. Because the cluster-level response rate in the above rows already captures that dropped cluster, you do not need to count individuals from the lost clusters in your individual-level response rates.
b See guidance in section IV.A for defining your analytic sample(s).
Reminder from instructions: For rows that account for item non-response and other analysis restriction, note that you may have very different sample sizes for two outcomes of interest because of very different rates of missing data for the outcomes. If this is the case, please add a row for each outcome in each time period, as needed. Indicate in a table note to which outcome the sample sizes apply. For example, if you have two primary outcomes and there was very different response rates on the items needed to construct these outcomes, you should include two rows for “Contributed to first follow-up (accounts for item non-response and other analysis restrictions)”: one for the analysis sample for outcome one and one for the analysis sample for outcome two.
Table IV.2. Outcome measures used for primary impact analyses research questions (this template includes example data in italics, as an example for you to consider for your own report)
Outcome measure |
Description of the outcome measure |
Source |
Timing of measure |
Marriage status |
The outcome measure is a yes/no response taken directly from the question in the survey, “Are you currently married?” |
Local follow-up survey |
6 months after intervention ends |
Level of affection |
The outcome measure is a scale (value range 1 to 5) calculated from both partners’ responses as the average of five survey items measuring support, intimacy, commitment, trust, and friendship. Cronbach’s alpha (if applicable): [enter number] |
Local follow-up survey |
6 months after intervention ends |
Notes: [Anything to note about the information above]
Table IV.3. Outcome measures used for secondary impact analyses research questions (this template includes example data italics, as a sample for you to consider for your own report)
Outcome measure |
Description of outcome measure |
Source |
Timing of measure |
Level of affection |
The outcome measure is a scale (value range 1 to 5) calculated from both partners’ responses as the average of five survey items measuring support, intimacy, commitment, trust, and friendship. Cronbach’s alpha (if applicable): [enter number] |
nFORM exit survey |
At post-test (immediately after intervention ends) |
Notes: [Anything important to note about the information above]
Table IV.4. Summary statistics of key baseline measures and baseline equivalence across study groups, for individuals/couples completing [Outcome measure at survey follow-up period]
Baseline measure |
Intervention mean (standard deviation) |
Comparison mean (standard deviation) |
Intervention versus comparison mean difference (p-value of difference) |
Effect size (optional) |
Female (%) |
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Race/ethnicity (%) |
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Hispanic |
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Non-Hispanic White |
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Non-Hispanic Black |
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Non-Hispanic Asian |
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Socioeconomic status |
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Outcome measure 1 (range: 1 to 5) |
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Outcome measure 2 |
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Sample size |
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Notes: p-values are include in parentheses. Effect sizes are calculated by dividing the differences in means by the standard deviation of the comparison group. [Anything else important to note about the information above]
Reminder from instructions: Please present an equivalence table for each analytic sample (sample on which impacts are estimated) being used to answer the primary research questions.
Table V.1. Covariates included in impact analyses
Covariate |
Description of the covariate |
Age |
Age (in years) as of the baseline data collection |
Baseline marital status |
Marital status (1 = married; 0 = not married) as of the baseline data collection |
Notes: [Anything to note about the analysis.]
Table V.2. Post-intervention estimated effects using data from [Survey follow-up time period] to address the primary research questions
Outcome measure |
Intervention mean or % (standard deviation) |
Comparison mean or % (standard deviation) |
Intervention compared to comparison mean difference (p-value of difference) |
Effect size (optional) |
Outcome 1 |
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Outcome 2 |
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Sample Size |
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Source: [Name for the Data Collection, Date. For instance, first follow-up surveys administered 12 months after the program.]
Notes: p-values are included in parentheses. Effect sizes are calculated by dividing the differences in means by the standard deviation of the comparison group. [Anything to note about the analysis. See Table IV.2 for a more detailed description of each measure and Chapters IV and V.B for a description of the impact estimation methods]
Table V.3. Differences in means between intervention and comparison groups estimated using alternative methods
Outcome |
Benchmark approach |
No covariate adjustment |
Name of sensitivity approach 2 |
Name of sensitivity approach 3 |
Primary Research Questions |
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Outcome 1 |
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Outcome 2 |
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Outcome 3 |
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Source: [Name for the Data Collection, Date. For instance, Follow-up surveys administered six to eight months after the program.]
**/*/+ Differences are statistically significant at the .01/.05/.10 levels, respectively.
Notes: [Anything to note about the analysis]
Table V.4. Post-intervention estimated effects using data from [Survey follow-up time period] to address the secondary research questions
Outcome measure |
Intervention mean or % (standard deviation) |
Comparison mean or % (standard deviation) |
Intervention compared with comparison mean difference (p-value of difference) |
Effect size (optional) |
Outcome 1 |
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Outcome 2 |
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Sample Size |
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Source: [Name for the Data Collection, Date. For instance, first follow-up surveys administered 12 months after the program.]
Notes: p-values are included in parentheses. Effect sizes are calculated by dividing the differences in means by the standard deviation of the comparison group. [Anything else to note about the analysis. See Table IV.3 for a more detailed description of each measure and Chapters IV and IV.B for a description of the impact estimation methods.]
Appendix A: Logic Model (if applicable)
[Paste logic model here]
Appendix B: Data, Sample, and Measures (if applicable)
Table B.1. Data used to address implementation research questions
Implementation element |
Research question |
Data source |
Timing/frequency of data collection |
Party responsible for data collection |
Fidelity |
Were all intended intervention components offered and for the expected duration? |
Workshop sessions in nFORM |
All sessions delivered |
Intervention staff |
Fidelity |
What content did the clients receive? |
Fidelity tracking log or protocol; attendance logs; session observations |
Every session for fidelity tracking and attendance logs; two times a year for session observations |
Intervention staff for fidelity tracking and attendance logs; study staff for session observations |
Fidelity |
Who delivered services to clients? |
Staff applications; hiring records; training logs |
One time X months after start of implementation; annually |
Intervention staff |
Fidelity |
What were the unplanned adaptations to key intervention components? |
Adaptation request; work plan; 6-month progress report; annual progress report |
Annually; ad hoc |
Intervention staff; study staff |
Dosage |
How often did clients participate in the intervention on average? |
Workshop sessions and individual service contacts in nFORM; attendance logs |
All sessions delivered |
Intervention staff |
Quality |
What was the quality of staff–participant interactions? |
Observations of interaction quality, using protocol developed by study staff |
X percentage of sessions selected at random for observation |
Study staff |
Engagement |
How engaged were clients in the intervention? |
Observations of engagement, possibly using an engagement assessment tool; ratings from facilitator fidelity logs; engagement ratings from participant satisfaction surveys |
Y percentage of sessions selected at random for observation |
Study staff |
Context |
What other HM/RF programming was available to study participants? |
Interviews with staff from partnering agencies in the community; survey items on baseline and follow-up assessments; websites of other agencies in the community providing HM/RF programming |
Once a year; ad hoc |
Study staff |
Context |
What external events affected implementation? |
Interviews with community/county representatives; list of site/school closures |
Once a year; ad hoc |
Study staff |
Note: We use “clients” in the questions above to avoid redundancy.
Table B.2. Key features of the impact analysis data collection
|
Data source |
Timing of data collection |
Mode of data collection |
Party responsible for data collection |
Start and end date of data collection |
Intervention |
Intervention group study participants |
Enrollment (baseline) End of intervention (8 months after enrollment)
|
In-person online survey (nFORM)
|
Program staff |
September 2016 through January 2020 |
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|
3 months after the end of the intervention (11 months after enrollment) 6 months after the end of the intervention (14 months after enrollment) |
Telephone survey |
Evaluation staff |
August 2017 through March 2021 |
Counterfactual |
Comparison group study participants |
Enrollment (baseline) 8-month follow-up |
In-person online survey (nFORM) |
Program staff |
September 2016 through January 2020 |
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11-month follow-up 14-month follow-up |
Telephone survey |
Evaluation staff |
August 2017 through March 2021 |
[Paste updated CONSORT diagram from you Analysis Plan here.]
Appendix C: Compromised RCT, Attrition, and/or Baseline Equivalence of original RCT sample (if applicable)
C.1 If your study was originally an RCT but had to construct equivalent groups using a QED approach because of high attrition, lack of baseline equivalence, and/or another issue that compromised the random assignment, please describe the details in this appendix. Table C.1 can be used to summarize baseline equivalence of the RCT sample.
Table C.1. Baseline equivalence of the original RCT intervention and control groups
Baseline measure |
Intervention mean (standard deviation) |
Comparison mean (standard deviation) |
Intervention versus comparison mean difference (p-value of difference) |
Effect size |
Female (%) |
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Race/ethnicity (%) |
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Hispanic |
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Non-Hispanic White |
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Non-Hispanic Black |
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Non-Hispanic Asian |
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Outcome measure 1 (range: 1 to 5) |
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Outcome measure 2 |
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Sample size |
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Notes: p-values are include in parentheses. Effect sizes are calculated by dividing the differences in means by the standard deviation of the comparison group. [Anything else important to note about the information above]
C.2. For both QEDs and RCTs that had to construct equivalent groups, please describe the approach to constructing equivalent groups in this appendix.
File Type | application/vnd.openxmlformats-officedocument.wordprocessingml.document |
Author | William Garrett |
File Modified | 0000-00-00 |
File Created | 2023-10-26 |