<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Testing a forecast model to predict movement of older Americans into retirement housing."
Abstract:"Purpose - Expectations of an aging population increases the need for accurate models and reliable forecasts of housing demand in the later stages of life. This paper aims to examine whether the only published forecasting model predicts the actual movement of older Americans into retirement housing. Design/methodology/approach - A logistic regression model is used to test which older movers chose retirement housing using data from the 2002 and 2004 Health and Retirement Survey. Findings - Age is found to have a positive relationship with the choice to move into retirement housing, but the other socioeconomic variables are not significant and the model is not robust. Research limitations/implications - More investigation is necessary to identify the variables that will provide a reliable estimate of those choosing retirement housing. Segmented by housing type may be necessary rather than estimating total retirement housing demand. Originality/value - The paper tests whether a model previously used to forecast senior housing demand actually predicts housing choice. It demonstrates that additional research is needed to develop models that can more accurately estimate demand in this growing segment of the housing market in aging countries.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [1].
Testing a forecast model to predict movement of older Americans into retirement housing
Purpose - Expectations of an aging population increases the need for accurate models and reliable forecasts of housing demand in the later stages of life. This paper aims to examine whether the only published forecasting model predicts the actual movement of older Americans into retirement housing. Design/methodology/approach - A logistic regression model is used to test which older movers chose retirement housing using data from the 2002 and 2004 Health and Retirement Survey. Findings - Age is found to have a positive relationship with the choice to move into retirement housing, but the other socioeconomic variables are not significant and the model is not robust. Research limitations/implications - More investigation is necessary to identify the variables that will provide a reliable estimate of those choosing retirement housing. Segmented by housing type may be necessary rather than estimating total retirement housing demand. Originality/value - The paper tests whether a model previously used to forecast senior housing demand actually predicts housing choice. It demonstrates that additional research is needed to develop models that can more accurately estimate demand in this growing segment of the housing market in aging countries.