You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

Objective: Due to social distancing guidelines during the Coronavirus (COVID-19) pandemic, most providers and patients have wanted to avoid close contact. This makes physical therapy (PT) assessments difficult because of the lack of empirical evidence about the reliability of various clinical measurements performed in a virtual environment. One such procedure is the photometric measurement of craniovertebral (CV) angle. Craniovertebral angle measurement is usually performed in an outpatient setting and is defined as the acute angle formed between a straight line connecting the spinous process of C7 to the tragus of the ear, and the horizontal line passing through the spinous process of the C7. Although the photometric measurement of CV angles is considered both valid and reliable in the clinics, no empirical evidence exists about the CV angle measurement reliability when performed in a virtual environment. Thus, the purpose of this study was to assess the inter- and intra-rater reliability of photometric CV angle measurement using a cloud-based video communication platform. Number of Subjects: 66 subjects (57 females). Methods: All measurements were performed by two final year PT students who had completed the musculoskeletal part of the curriculum and were blinded to each other's measurements. Each subject was photographed in two postures over a HIPAA-compliant video-based telehealth platform: (1) normal/relaxed posture and (2) ideal posture (posture the subject considered good). Student researcher 1 measured the CV angle in both the relaxed posture and ideal posture, while student researcher 2 measured the CV angle only in the relaxed posture. Each subject's CV angle measurement was performed three times on three separate days and the means were used for further analysis. The shape of the CV angle frequency distribution was assessed using kurtosis and skewness values. Rater reliability was assessed using intraclass correlation coefficients (ICC), and interpreted based on the guidelines provided by Portney and Watkins (2009). Results: The CV angles were normally distributed in both relaxed and ideal postures. The mean and standard deviation (SD) of relaxed posture was 50.7o +/- 6.3o with kurtosis and skewness of 0.67 and -0.74 respectively. The mean and SD of ideal posture was 55.5o +/- 5.4o, with kurtosis and skewness of 0.1 and -0.54 respectively. The ICC for inter-rater reliability in the relaxed posture was 0.88 and the ICC for intra-rater reliability for relaxed posture was 0.91. Conclusions: Craniovertebral angles were normally distributed in the sample. An acceptable level of inter- and intra-rater reliability can be attained when measuring CV angle using a cloud-based video communication platform.
["Prevention"]