You will be shown the abstract of a medical clinical trial report. Your task is to extract all the findings from this report into a JSON array. Each finding should contain the following five elements:

- Intervention: The medical intervention being tested. This should be a text span copied from the input passage.
- Comparator: The baseline against which the intervention is being evaluated. This should be a text span copied from the input passage. If no comparator is reported, set to `null`.
- Outcome: The medical outcome whose effect is being measured. This should be a text span copied from the input passage.
- Effect: The effect of the intervention on the outcome, relative to the comparator. The effect should be one of the following three values: ("significantly increased", "significantly decreased", "no significant difference").
- Evidence: The evidence for the effect. This should be a text span copied from the input passage.

Please format your output as a JSON array. Each entry in the output should be an array containing the 5 elements listed above, in the following order: [<intervention>, <comparator>, <outcome>, <effect>, <evidence>].

For example, an output with two findings might read:
```
[["aspirin", "placebo", "headache severity", "significantly decreased", "Mean headache severity was significantly decreased in the aspirin group compared to the placebo group (p < 0.05)."], ["aspirin", "placebo", "weight loss", "no significant difference", "We did not observe any difference in weight loss between the group given aspirin relative to the control group"]]
```

There are 1 finding(s) in the abstract below. Please extract them. Output only the JSON array with these 1 findings. Do not include any additional text.

Abstract:
ABSTRACT: This study examined the extent to which delivery of the minimal Smoke-Free Homes intervention by trained 2-1-1 information and referral specialists had an effect on the adoption of home smoking bans in low-income households. A randomized controlled trial was conducted among 2-1-1 callers (n = 500) assigned to control or intervention conditions. 2-1-1 information and referral specialists collected baseline data and delivered the intervention consisting of 3 mailings and 1 coaching call; university-based data collectors conducted follow-up interviews at 3 and 6 months post-baseline. Data were collected from June 2013 through July 2014. Participants were mostly female (87.2%), African American (61.4%), and smokers (76.6%). Participants assigned to the intervention condition were more likely than controls to report a full ban on smoking in the home at both 3- (38.1% vs 19.3%, p = < .001) and 6-month follow-up (43.2% vs 33.2%, p = .02). The longitudinal intent-to-treat analysis showed a significant intervention effect over time (OR = 1.31, p = .001), i.e. OR = 1.72 at 6 months. This study replicates prior findings showing the effectiveness of the minimal intervention to promote smoke-free homes in low-income households, and extends those findings by demonstrating they can be achieved when 2-1-1 information and referral specialists deliver the intervention. Findings offer support for this intervention as a generalizable and scalable model for reducing secondhand smoke exposure in homes.

Findings:
[["Intervention group", "Control Group", "Household smoking bans ", "significantly increased", "Participants assigned to the intervention condition were more likely than controls to report a full ban on smoking in the home at both 3- (38.1% vs 19.3%, p = \u003c .001) and 6-month follow-up (43.2% vs 33.2%, p = .02)."]]