Study design - Managing research data | Staff | University ...
left190500ANALYSIS PLANAvailability of shared vs separate places for tobacco and e-cigarette use: Study 1 Contents TOC \o "1-3" \h \z \u Study design PAGEREF _Toc530576124 \h 2Hypotheses PAGEREF _Toc530576125 \h 2Outcomes PAGEREF _Toc530576126 \h 2Primary PAGEREF _Toc530576127 \h 2Secondary PAGEREF _Toc530576128 \h 2Data collection PAGEREF _Toc530576129 \h 2Creating variables PAGEREF _Toc530576130 \h 3Manually creating variables PAGEREF _Toc530576131 \h 3Using SPSS syntax PAGEREF _Toc530576132 \h 3Outliers PAGEREF _Toc530576133 \h 3Missing data PAGEREF _Toc530576134 \h 3Sensitivity analysis PAGEREF _Toc530576135 \h 4Recognising smoking/vaping action PAGEREF _Toc530576136 \h 4Study purpose PAGEREF _Toc530576137 \h 4Attention checks PAGEREF _Toc530576138 \h 4Descriptive statistics PAGEREF _Toc530576139 \h 4Outcome analysis PAGEREF _Toc530576140 \h 4Violations of assumptions PAGEREF _Toc530576141 \h 4Primary outcome PAGEREF _Toc530576142 \h 5Secondary outcomes PAGEREF _Toc530576143 \h 5Exploratory analysis PAGEREF _Toc530576144 \h 5Reporting of the results PAGEREF _Toc530576145 \h 5References PAGEREF _Toc530576146 \h 6Appendix A PAGEREF _Toc530576147 \h 7Appendix B1. PAGEREF _Toc530576148 \h 8Appendix B2. PAGEREF _Toc530576149 \h 12Study designThis is an online study using a 16 group between-subjects design: 2 (smoking status: current smoker, former smoker) × 2 (vaping status: current vaper, non-vaper) × 4 (stimuli type: cigalike, tank-system, tobacco cigarette, control). Participants were recruited according to their smoking / vaping status:Smokers (current smokers, non-vapers)Vapers (former smokers, current vapers)Non-users (former smokers, non-vapers)Dual-users (current smokers, current vapers)Participants were pseudo-randomised to 1 of 4 video stimulus groups (someone smoking; someone using a cigalike e-cigarette; someone using a tank-system e-cigarette; and someone performing a neutral hand to mouth action). Outcome measures (see below) were assessed before and after viewing the videos.HypothesesH1: Smoking urges are higher amongst current and former smokers following exposure to vaping cues (i.e., cigalike and tank system), relative to control cues.H2: Smoking urges are lower amongst current and former smokers following exposure to vaping cues (i.e., cigalike and tank system), relative to smoking cues.H3: Tobacco smoking urges are higher amongst current and former smokers following exposure to cigalike cues, relative to tank system cues. OutcomesPrimaryThe brief Questionnaire of Smoking Urges (QSU) (created from the total of 10 questions, each on a scale 1-7: 1 = ‘strongly disagree’ and 7 = ’strongly agree’). The range of possible scores is from 10 to 70. SecondaryAll: Desire for a regular cigarette / desire for an electronic cigarette (on a scale 0-100: 0 = ‘not at all’ and 100 = ‘most ever’).Smokers: Intentions to quit smoking (five-point scale: 1 = ‘very unlikely’, 2 = ‘unlikely’, 3 = ‘maybe, maybe not’, 4 = ‘likely’, 5 = ‘very likely’).Former smokers: Likelihood to remain abstinent from smoking (five-point scale: 1 = ‘not at all sure’, 2 = ‘slightly sure’, 3 = ‘moderately sure’, 4 = ‘very sure’, 5 = ‘extremely sure’).Data collectionAll data will be sent directly to the researcher completing the data analysis at the end of the study in an Excel spreadsheet. A data dictionary will also be sent which includes all coding and ranges. Creating variables Manually creating variablesManipulation check 1: Create a variable in the Excel spreadsheet that identifies participants who did not correctly identify the smoking/vaping action using Q25, Q30, Q35 and Q40 (‘Please describe what the male actor was doing below’). These questions are string variables, so this will be done manually and will be coded as: 0 = no, they did not identify the action (i.e., make no reference to cigarette or e-cigarette use when appropriate, or misinterpret cigarettes for e-cigarettes or vice versa) and 1 = yes they did identify the action.Manipulation check 2: Create a variable in the Excel spreadsheet that identifies participants who correctly guess the purpose of the study using Q46 (‘Please briefly describe what you think the purpose of this survey was below’). Q46 is a string variable so this will need to be done manually and will be coded as: 0 = no, they did not guess the purpose of the study; and 1 = yes they did guess the purpose of the study (i.e., anything that makes reference to i. a change in desire to smoke/vape, and ii. after seeing someone smoke/vape, see Appendix A for examples).Using SPSS syntax IBM SPSS version 24 will be used to create these variables. All syntax can be seen in Appendix B, but before analysis is started the syntax below must be run in the relevant database and in the correct order.Syntax 1: To recode and create all variables for participant demographics, total smoking urges (pre and post), total vaping urges (pre and post), smoking/vaping status, attention check failure, time as smoker, time as former smoker and video group. Open SPSS file ‘Code 1. Code the variables’ in the relevant study folder and select ‘run all’. Syntax 2: To exclude anyone who lives outside of the UK and anyone who was not randomised to a video group. Open SPSS file ‘Code 2. Selects the current data for analysis’ in the relevant study folder and select ‘run all’.OutliersAny outliers will be identified using range checks, scatter plots and histograms. Outliers should be minimal due to the design of the study but, if any are identified further checks will be performed by the research team to ensure they are not the result of data entry errors. Any outliers will be included in the primary analysis but, if deemed necessary, the analysis will be run both with and without any true outliers to compare results. Missing dataAny missing data will be coded as an impossible value (-999). If an excessive amount of missing data is identified (>10%), the research team will be notified so that checks can be made. The data for the primary outcome should be fully complete due to the nature of the study. However, if missing data is >10% for the outcome variables, and is missing at random, multiple imputation will be used to manage missing data. Results will be reported for complete case data and imputed data. Otherwise (if missing data is <10% for the outcome variables), analysis will be on a complete case basis. Sensitivity analysisRecognising smoking/vaping actionParticipants who did not correctly identify the smoking/vaping action (see Manipulation check 1, above) will be identified and numbers will be compared between each video stimulus group to determine whether any of the four actions in the videos were disproportionately difficult to recognise. A sensitivity analysis of the primary outcome will be run without participants who do not correctly identify the smoking/vaping action. All responses will be included in the final analysis. Study purposeParticipants who guess the purpose of the study will be identified (see Manipulation check 2, above). A sensitivity analysis of the primary outcome will be run without participants who guess the true nature of the study so that any differences can be identified. All responses will be included in the final analysis.Attention checksThere are two attention checks embedded in the questionnaire after randomisation (see Code 1, above). Participants who fail the attention check(s) will be excluded from the main primary analysis. However, to consider generalisability of the results, these participants will be investigated separately, and percentages presented, to identify whether there was a difference in exclusion across video stimulus groups or smoking/vaping status. A sensitivity analysis of the primary outcome will also be run which will include those participants who did fail one or both attention checks.Descriptive statisticsDescriptive statistics will be reported in two tables between all four video stimulus groups, and all four smoking/vaping status groups. Means and standard deviations (SD) will be presented for continuous variables, or median and interquartile ranges for variables with clearly non-normal distributions (see Violations of assumptions, below). Numbers and percentages will be presented for categorical variables.Outcome analysisAll analysis will be done in IBM SPSS version 24. Analysis will be coded in syntax and will be reproducible at any time (this will be added as Appendix C after the analysis is complete).Violations of assumptionsIt is intended, that as per previous literaturePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XZXN0PC9BdXRob3I+PFllYXI+MjAxMDwvWWVhcj48UmVj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ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XZXN0PC9BdXRob3I+PFllYXI+MjAxMDwvWWVhcj48UmVj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ADDIN EN.CITE.DATA [1, 2], the primary outcome (QSU) will be treated as normally distributed data, and analysis will continue accordingly. Normality will however be assessed using normality plots and homogeneity will be assessed using the significance level of the interaction between baseline QSU scores and video stimuli group. This information will be reported but will not change the analysis plan. Primary outcomeThe comparisons in H1-H3 will be explored using a general linear model, incorporating a two-way analysis of covariance (ANCOVA) to compare total QSU scores between both independent variables (smoking status and video stimulus group). Baseline QSU scores will be added as a covariate into the ANCOVA model allowing for adjustment, and post video QSU scores will remain as the outcome. Interactions between vaping and smoking status, and the stimulus groups, will be added to the main effects model to investigate whether the impact of the video stimulus varies according to smoking/ vaping status. Secondary outcomesThe above model will be repeated for the secondary outcome measures below.All participants: Desire for a regular cigaretteAll participants: Desire for an electronic cigaretteCurrent smokers: Intentions to quit smoking Former smokers: Likelihood to remain abstinent from smokingExploratory analysisAny sociodemographic differences in QSU scores between smoking/vaping status groups will also be explored as independent factors in a separate ANCOVA model (adjusting for the baseline QSU score). Reporting of the resultsFor all analysis, the following will be reported for all comparisons: mean values and SD, mean difference (MD) and 95% confidence intervals (CI), F statistic, P-value. References ADDIN EN.REFLIST 1.West, R. and M. Ussher, Is the ten-item Questionnaire of Smoking Urges (QSU-brief) more sensitive to abstinence than shorter craving measures? Psychopharmacology, 2010. 208(3): p. 427-432.2.Toll, B.A., N.A. Katulak, and S.A. McKee, Investigating the factor structure of the Questionnaire on Smoking Urges-Brief (QSU-Brief). Addict Behav, 2006. 31(7): p. 1231-9.Appendix AExample responses to Q46 ‘Please briefly describe what you think the purpose of this survey was below’ that correctly identified the purpose of the study (i.e., coded 1 = yes)‘Not really sure, whether we take notice of the person vaping, and whether this made us want to do it more?’‘Whether or not a person’s desire to smoke/vape increases when you see another person smoking/vaping.’‘To assess whether seeing somebody else vaping affects smokers' cravings.’‘Gauge how the video of vaping alters one desire to vape afterwards’‘To determine whether the sight of seeing someone smoking or vaping changes before or after you see someone doing it’‘I presume that seeing the actor vaping that my desire to do the same would be heightened.’Appendix B1. SPSS Syntax 1: Code the variables (*** indicates a comment only)***labelling of categorical variables *****************to label location variable**VALUE LABELS Q91 "England"2 "Wales"3 "Scotland"4 "Northern Ireland"5 "Other"6 "I do not live in the UK".EXECUTE.**to label gender variable**VALUE LABELS Q101 "Male"2 "Female"3 "Other"4 "Prefer not to say".EXECUTE.**to label education variable**VALUE LABELS Q111 "Higher Education or professional"2 "A levels, vocational level 3 or equivalent"3 "GCSE / O level grade A*-C, vocational level 2 or equivalent"4 "Qualifications at level 1 and below"5 "Other qualifications: level unknown"6 "No qualifications".EXECUTE.**to label smoker variable**VALUE LABELS Q121 "I am a current smoker (smoke at least 5 cigarettes a day and have smoked this amount for at least one year)"2 "I am a former smoker (used to smoke at least 5 cigarettes a day and smoked this amount for at least one year)"3 "I have never smoked (smoker fewer than 100 cigarettes in my lifetime)"4 "Other (smoking experiences do not match the criteria above)".EXECUTE.**to label ‘Are you currently trying to quit smoking’ variable**VALUE LABELS Q141 "Yes"2 "No".EXECUTE.**to label vaping variable**VALUE LABELS Q161 "I am a current vaper (vape at least once a day)"2 "I am a non-vaper (vaped fewer than 20 times in my lifetime)"3 "Other (vaping experiences do not match the criteria above)".EXECUTE.**to label ‘are you planning to quit smoking within the next 6 months?’ variable**VALUE LABELS Q441 "Very unlikely"2 "Unlikely"3 "Maybe / maybe not"4 "Likely"5 "Very unlikely".EXECUTE.**to label ‘How confident are you that you will remain a non-smoker?’ variable**VALUE LABELS Q451 "Not at all sure"2 "Slightly sure"3 "Moderately sure"4 "Very sure"5 "Extremely sure".EXECUTE.**to label ‘Please select what you think the purpose of this survey was from the options below’ variable**VALUE LABELS Q471 "To test memory for conversations"2 "To test the effect of body language on the desire to smoke"3 "To examine the impact of seeing someone smoke on the desire to smoke"4 "To improve the quality of videos used for research".EXECUTE.********calculations to make 'how long' variables into years with one decimal place**********COMPUTE Q13_howlongbeenasmoker=((Q13_1 * 12) + Q13_2) / 12.PUTE Q15_howlongsincequitsmoking=((Q15_1 * 12) + Q15_2) / 12.EXECUTE.******************************adding brief Questionnaire of Smoking Urges together*******COMPUTE QSU_smoking_PRE = Q17_1 + Q17_2 + Q17_3 + Q17_4 + Q17_5 + Q17_6 + Q17_7 + Q17_9 + Q17_10 + Q17_11.PUTE QSU_ecigarette_PRE = Q18_1 + Q18_2 + Q18_3 + Q18_4 + Q18_5 + Q18_6 + Q18_7 + Q18_8 + Q18_9 + Q18_10.PUTE QSU_smoking_POST = Q41_1 + Q41_2 + Q41_3 + Q41_4 + Q41_5 + Q41_6 + Q41_7 + Q41_8 + Q41_9 + Q41_10.PUTE QSU_ecigarette_POST = Q42_1 + Q42_2 + Q42_3 + Q42_5 + Q42_6 + Q42_7 + Q42_8 + Q42_9 + Q42_10 +Q42_11.EXECUTE.***coding the smoking status groups****If Q12 =1 AND Q14 = 2 AND Q16 = 2 Smokinggroups = 1.If Q12 = 2 AND Q16 = 2 Smokinggroups = 2.if Q12 = 2 AND Q16 = 1 Smokinggroups = 3.If Q12 = 1 AND Q14 = 2 AND Q16 = 1 Smokinggroups = 4.EXECUTE.VALUE LABELS Smokinggroups1 "Smokers only"2 "Ex-smokers only"3 "Vapers only"4 "Dual users".EXECUTE.***coding the attention check*****IF (Q17_8 = 4 or Q17_8 = 5 or Q17_8 = 6 or Q17_8 = 7) Attention_check=1.If (Q42_4 = 1 or Q42_4 = 2 or Q42_4 = 3 or Q42_4 =4) Attention_check=1.IF (Q17_8 = 1 or Q17_8 = 2 or Q17_8 =3) Attention_check = 0.if (Q42_4 = 5 or Q42_4 = 6 or Q42_4 = 7) Attention_check = 0.EXECUTE.VALUE LABELS Attention_check0 "Passed attention check"1 "FAILED attention check".EXECUTE.***creating video groups********if sysmis (Q22_1) and sysmis (Q27_1) and sysmis (Q32_1) video_group = 4.if sysmis (Q22_1) and sysmis (Q27_1) and sysmis (Q37_1) video_group = 3.if sysmis (Q22_1) and sysmis (Q32_1) and sysmis (Q37_1) video_group = 2.if sysmis (Q27_1) and sysmis (Q32_1) and sysmis (Q37_1) video_group = 1.if sysmis (Q22_1) and sysmis (Q27_1) and sysmis (Q32_1) and sysmis (Q37_1) video_group = -999. VALUE LABELS video_group1 "Vaping cigalike"2 "Vaping tank"3 "Smoking cigarette"4 "Neutral"-999 "Missing".EXECUTE.Missing values video_group (-999).******combining video questions into one set of time points*****COMPUTE Video_Q1=Q22_1 + Q27_1 + Q32_1 + Q37_1.EXECUTE.VARIABLE LABELS Video_Q1 "Please use the slider to rate the video on the features outlined below - Quality of video picture".COMPUTE Video_Q2=Q22_2 + Q27_2+Q32_2+Q37_2.EXECUTE.VARIABLE LABELS Video_Q2 "Please use the slider to rate the video on the features outlined below - Quality of acting".COMPUTE Video_Q3=Q22_3 + Q27_3 + Q32_3 + Q37_3.EXECUTE.VARIABLE LABELS Video_Q3 "Clarity of the conversation".COMPUTE Video_Q4=Q22_4 + Q27_4 + Q32_4 + Q37_4.EXECUTE.VARIABLE LABELS Video_Q4 "Please use the slider to rate the video on the features outlined below - Level of interest in the conversation".COMPUTE Video_Q5=Q23 + Q28 + Q33 + Q38.EXECUTE.VARIABLE LABELS Video_Q5 "Please record what you can remember about the two people and their conversation below".COMPUTE Video_Q6=Q24 + Q29 + Q34 + Q39.EXECUTE.VARIABLE LABELS Video_6 "To what extent do you agree that the relationship and conversation between the two people was believable?".COMPUTE Video_Q7= Q25+ Q30 + Q35 + Q40.EXECUTE.VARIABLE LABELS Video_Q7 "Please describe what the male actor was doing below".Appendix B2. SPSS Syntax 2: Syntax for selecting data(*** indicates a comment only)***to exclude those living outside the UK****Select if Q9 = 1 OR Q9 = 2 OR Q9 = 3 OR Q9 = 4 OR Q9 = 5.EXECUTE.****to exclude those who do not have a video group, i.e. those who were not randomised*****SELECT IF video_group = 1 OR video_group=2 OR video_group=3 OR video_group=4.EXECUTE. ................
................
In order to avoid copyright disputes, this page is only a partial summary.
To fulfill the demand for quickly locating and searching documents.
It is intelligent file search solution for home and business.
Related download
- assad 2017 national trends report second edition
- needs assessment template portal
- prohibiting state of oregon
- 2019 2020 bill 21 text of previous version may 1 2019
- 2019 2020 bill 21 text of previous version may 8 2019
- methodology report 2017 18 ministry of health
- 1999 to 2017 national surveys on drug use and health
- welcome family health outcomes project
- montgomery county md
- study design managing research data staff university
Related searches
- what is research data analysis
- study abroad benefits research reports
- research data analysis example
- study population in research pdf
- sample design in research methodology
- study design and methodology
- qualitative research data collection methods
- qualitative research data analysis techniques
- quantitative research data collection methods
- qualitative research data analysis tools
- quantitative research study design types
- case study design qualitative research