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 2 finding(s) in the abstract below. Please extract them. Output only the JSON array with these 2 findings. Do not include any additional text.

Abstract:
ABSTRACT.BACKGROUND: Alcohol misuse in England costs around £7.3 billion (US$12.2 billion) annually from lost productivity and absenteeism. Delivering brief alcohol interventions to employees as part of a health check may be acceptable, particularly with online delivery which can provide privacy for this stigmatised behaviour. Research to support this approach is limited and methodologically weak. The aim was to determine the effectiveness of online screening and personalised feedback on alcohol consumption, delivered in a workplace as part of a health check.

ABSTRACT.METHODS AND FINDINGS: This two-group online individually randomised controlled trial recruited employees from a UK-based private sector organisation (approx. 100,000 employees). 3,375 employees completed the online health check in the three week recruitment period. Of these, 1,330 (39%) scored five or more on the AUDIT-C (indicating alcohol misuse) and were randomised to receive personalised feedback on their alcohol intake, alongside feedback on other health behaviours (n = 659), or to receive feedback on all health behaviours except alcohol intake (n = 671). Participants were mostly male (75%), with a median age of 48 years and half were in managerial positions (55%). Median Body Mass Index was 26, 12% were smokers, median time undertaking moderate/vigorous physical activity a week was 173 minutes and median fruit and vegetable consumption was three portions a day. Eighty percent (n = 1,066) of participants completed follow-up questionnaires at three months. An intention to treat analysis found no difference between experimental groups for past week drinking (primary outcome) (5.6% increase associated with the intervention (95% CI −4.7% to 16.9%; p = .30)), AUDIT (measure of alcohol-related harm) and health utility (EQ-5D).

ABSTRACT.CONCLUSIONS: There was no evidence to support the use of personalised feedback within an online health check for reducing alcohol consumption among employees in this organisation. Further research is needed on how to engage a larger proportion of employees in screening.

ABSTRACT.TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number Register ISRCTN50658915


Findings:
[["Personalised feedback on alcohol intake", "General feedback ", "Past week drinking", "no significant difference", "An intention to treat analysis found no difference between experimental groups for past week drinking (primary outcome) (5.6% increase associated with the intervention (95% CI \u22124.7% to 16.9%; p = .30)), AUDIT (measure of alcohol-related harm) and health utility (EQ-5D)."], ["Personalised feedback on alcohol intake", "General feedback ", "EQ-5D index", "no significant difference", "An intention to treat analysis found no difference between experimental groups for past week drinking (primary outcome) (5.6% increase associated with the intervention (95% CI \u22124.7% to 16.9%; p = .30)), AUDIT (measure of alcohol-related harm) and health utility (EQ-5D)."]]