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9. Self-reported violations, errors and lapses for older drivers: Measuring the change in frequency of aberrant driving behaviours across five time-points

Author

Koppel, Sjaan, Stephens, Amanda N., Bédard, Michel, Charlton, Judith L., Darzins, Peteris, Stefano, Marilyn Di, Gagnon, Sylvain, Gélinas, Isabelle, Hua, Phuong, MacLeay, Lynn, Man-Son-Hing, Malcolm, Mazer, Barbara, Myers, Anita, Naglie, Gary, Odell, Morris, Porter, Michelle M., Rapoport, Mark J., Stinchcombe, Arne, Tuokko, Holly, Vrkjlan, Brenda, and Marshall, Shawn

Published
2019
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10. Older Drivers Reduced Engagement in Distracting Behaviors Over a Six-Year Period: Findings From the Candrive Longitudinal Study

Author

Bédard, Michel, primary, Maxwell, Hillary, additional, Weaver, Bruce, additional, Stinchcombe, Arne, additional, Gélinas, Isabelle, additional, Mazer, Barbara, additional, Naglie, Gary, additional, Porter, Michelle M, additional, Rapoport, Mark J, additional, Tuokko, Holly, additional, Vrkljan, Brenda, additional, and Marshall, Shawn, additional

Published
2023
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14. Driving-related attitudes among older adults in Australia

Author

Sukhawathanakul, Paweena, Porter, Michelle M, Tuokko, Holly, Charlton, Judith L, Koppel, Sjaan, Bedard, Michel, Naglie, Gary, Marshall, Shawn, Rapoport, Mark J, Vrkljan, Brenda, Gelinas, Isabelle, and Mazer, Barbara

Published
2018

18. Older Drivers Reduced Engagement in Distracting Behaviors Over a Six-Year Period: Findings From the Candrive Longitudinal Study.

Author

Bédard, Michel, Maxwell, Hillary, Weaver, Bruce, Stinchcombe, Arne, Gélinas, Isabelle, Mazer, Barbara, Naglie, Gary, Porter, Michelle M, Rapoport, Mark J, Tuokko, Holly, Vrkljan, Brenda, and Marshall, Shawn

Subjects
CONFIDENCE intervals, AGE distribution, DISTRACTION, SEX distribution, AUTOMOBILE driving, COMMUNICATION, RESEARCH funding, PSYCHOLOGICAL adaptation, RADIO (Medium), LISTENING, ODDS ratio
Abstract

Objectives Baltes and Baltes' "selective optimization with compensation" model is pertinent to driving but evidence about the use of compensation using longitudinal designs is scarce. Therefore, we sought to determine if older drivers reduced their engagement in distracting behaviors while driving, over a 6-year period. Methods We used data captured over several annual assessments from a cohort of 583 drivers aged 70 and older to determine if their engagement in 12 distracting behaviors (e.g. listening to the radio, talking with passengers) declined over time. We adjusted our multivariable model for several potential confounders of the association between our outcome variable and time. Results Overall, and after adjustment for potential confounders, the participants reduced their engagement in distracting behaviors over the study period (odds ratio [OR] = 0.96, 95% confidence interval [CI] = 0.95–0.97). Baseline age was negatively associated with engagement in distracting behaviors (OR = 0.95, 95% CI = 0.94–0.96). Men engaged in more distracting behaviors than women (OR = 1.15, 95% CI = 1.03–1.27), as did participants living in the largest urban centers compared to participants living in the smallest areas (OR = 1.21, 95% CI = 1.04–1.41). The number of kilometers driven per year (for every 10,000 km) was positively associated with the proportion of distracting behaviors drivers engaged in (OR = 1.13, 95% CI = 1.08–1.19). Discussion Drivers in our cohort reduced their engagement in distracting behaviors over the study period. This suggests that older drivers adjust their driving over time, which aligns with age-related theories and models about compensation. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Candrive—Development of a Risk Stratification Tool for Older Drivers.

Author

Marshall, Shawn, Bédard, Michel, Vrkljan, Brenda, Tuokko, Holly, Porter, Michelle M, Naglie, Gary, Rapoport, Mark J, Mazer, Barbara, Gélinas, Isabelle, Gagnon, Sylvain, Charlton, Judith L, Koppel, Sjaan, MacLeay, Lynn, Myers, Anita, Mallick, Ranjeeta, Ramsay, Tim, Stiell, Ian, Wells, George, and Man-Son-Hing, Malcolm

Subjects
OLDER automobile drivers, GLOBAL Positioning System, MEDICAL personnel, INDEPENDENT variables, OLDER people
Abstract

Background Assessing an older adult's fitness-to-drive is an important part of clinical decision making. However, most existing risk prediction tools only have a dichotomous design, which does not account for subtle differences in risk status for patients with complex medical conditions or changes over time. Our objective was to develop an older driver risk stratification tool (RST) to screen for medical fitness-to-drive in older adults. Methods Participants were active drivers aged 70 and older from 7 sites across 4 Canadian provinces. They underwent in-person assessments every 4 months with an annual comprehensive assessment. Participant vehicles were instrumented to provide vehicle and passive Global Positioning System (GPS) data. The primary outcome measure was police-reported, expert-validated, at-fault collision adjusted per annual kilometers driven. Predictor variables included physical, cognitive, and health assessment measures. Results A total of 928 older drivers were recruited for this study beginning in 2009. The average age at enrollment was 76.2 (standard deviation [ SD ] = 4.8) with 62.1% male participants. The mean duration for participation was 4.9 (SD  = 1.6) years. The derived Candrive RST included 4 predictors. Out of 4 483 person-years of driving, 74.8% fell within the lowest risk category. Only 2.9% of person-years were in the highest risk category where the relative risk for at-fault collisions was 5.26 (95% confidence interval = 2.81–9.84) compared to the lowest risk group. Conclusions For older drivers whose medical conditions create uncertainty regarding their fitness-to-drive, the Candrive RST may assist primary health care providers when initiating a conversation about driving and to guide further evaluation. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Geriatric dementia care at Ontario Shores: A new model of care

Author

Viau, Katelynn, Yaddaden, Amel, Lussier, Maxime, Bier, Nathalie, Earle, Julie, Duff-Woskosky, Andra, Bartfay, Wally, Desai, Chaitali, Zavitz, Karen, Horsburgh, Sheri, Gamble, Brenda, Lee, Linda, Hillier, Loretta M., Patel, Tejal, Molnar, Frank, Clarke, Jo-Anne, Borrie, Michael, Cammer, Allison, Morgan, Debra, Whiting, Susan, de Vos, Maya, Henri-Bhargava, Alexandre, Votova, Kristine, Delmar, Paul, Kerchner, Geoffrey A, Wang, Guoqiao, Bateman, Randall, Klein, Gregory, Andjelkovic, Mirjana, Abi-Saab, Danielle, Bullain, Szofia, Montoya, Alonso, Fontoura, Paulo, Doody, Rachelle, Tai, Elaine, Harvey, David, Hofmann, Carsten, Ristic, Smiljana, Rehal, Sunita, Voyle, Nicola, Baudler, Monika, Verreault, Phylicia, Rousseau, François, Keller, Evelyn, Simard, Alexandra, Azouaou, Nassima, Jarboui, Manel, Talleria, Lorraine, Duguay, Johanne, Mérette, Chantale, Labbé, Annie, de Arco, Rossana Peredo Nunez, Yous, Marie-Lee, Ploeg, Jenny, Kaasalainen, Sharon, Martin, Lori Schindel, Palumbo, Mary Val, Rambur, Betty, McKenna, Lori, Voyer, Philippe, Allaire, Émilie, Li, Bing, Thaut, Michael, Yogaparan, Thirumagal, Shanmuganathan, Thirunathan, Vickneswaran, Anicha, Sriharan, Sruthy, DeMarco, Mari L., Hsiung, Ging-Yuek Robin, Best, John R., Chertkow, Howard, Gauthier, Serge, Karlawish, Jason, Feldman, Howard, Spaner, Caroline, Christie, Brian, Musteata, Stela, Gawryluk, Jodie, Hofer, Scott, Henri-Bhargava, Alex, Kenny, Rebecca, Elliot, Valerie, Kosteniuk, Julie, Chow, Amanda Froehlich, Bayly, Melanie, O’Connell, Megan E., Kortzman, August, O’Connell, Megan, Kirk, Andrew, Conn, David, Sokoloff, Lisa, Feldman, Sid, Chau, James, Moser, Andrea, Lingum, Navena, Gingrich, Shaen, Shaikh, Salma, Rabheru, Kiran, Cassidy, Keri-Leigh, Checkland, Claire, Parsons, Daria, Massie, Ariane S., Mitchell, Julie Spence, Aksenchuk, Sophia, Lindsay, Barbara, Howard, Maria, Shaw, Courtney, Armitage, Gerrard, Capstick, Andrea, McNeil, Heather, Holyoke, Paul, Vines, Chanile, Giosa, Justine, Khan, Bilal, Shultz, Mary, BEAUCHET, Olivier, Sekhon, Harmehr, Allali, Gilles, Montembeault, Maxime, Brodeur, Catherine, Macoir, Joël, Maxwell, Colleen, Maclagan, Laura, Campitelli, Michael, Yao, Shenzhen, Dharma, Christoffer, Sherin, Tracey, Hogan, David, Bronskill, Susan, Ivo, Jessica, Faisal, Sadaf, McDougall, Aidan, Bauer, Jillian, Pritchard, Sarah, Chang, Feng, Mehta, Deval, Syed, Ali, Carter, Caitlin, Sharma, Shaambhavi, Nagge, Jeff, Naglie, Gary, Stasiulis, Elaine, Yamin, Stephanie, Vrkljan, Brenda, Tuokko, Holly, Sanford, Sarah, Porter, Michelle, Polgar, Jan, Myers, Anita, Moorhouse, Paige, Mazer, Barbara, Marshall, Shawn, Gélinas, Isabelle, Crizzle, Alexander, Byszewski, Anna, Belchior, Patricia, Bédard, Michel, Rapoport, Mark, Minish, Duane, Yetman, Linda, Stephenson, Margaret, McCloskey, Rose, Agbaku, Mansa, Jarrett, Pamela, Cavanagh, Jennifer, Loncar, Adele, Demers, Vickie, Gobessi, Linda, Lodha, Vinay, Scerbe, Andrea, Astell, Arlene, DesRoches, Andrea, Panyavin, Ivan, Feltz, Nick, Wittich, Walter, Aubin, Gabrielle, Hogan, Mariah, Swaminathan, Swathi, Altschuler, Aviva, Murphy, Kelly, Guthrie, Dawn, Williams, Nicole, Campos, Jennifer, Mick, Paul, Orange, Joseph B., Pichora-Fuller, M. Kathleen, Savundranayagam, Marie Y., Phillips, Natalie A., Giroud, Nathalie, Pichora-Fuller, Kathy, Al-Yawer, Faisal, Rehan, Sana, Phillips, Natalie, Beauchet, Olivier, Niculescu, Iulia, Iaboni, Andrea, Quirt, Hannah, Penko, Marion, Tsokas, Mario, Marshall, Cecelia, Flint, Alastair, McGilton, Katherine, O’Connell, Megan E, Stewart, Norma J, Seitz, Dallas, Daku, Jean, Hack, Tracy, Hoium, Faye, Kennett-Russill, Deb, Sauter, Kristen, Holley, Joanna, Wimhurst, Christine, Katchaluba, Janet, Mitchell, Debbie, Severina, Elmira, Dallaire-Théroux, Caroline, Saikali, Stéphan, Duchesne, Simon, Sivananthan, Saskia, Mirza, Saira, Saeed, Usman, Knight, Jo, Ramirez, Joel, Stuss, Donald, Yu, Di, Swardfager, Walter, Keith, Julia, Nestor, Sean, Black, Sandra, Masellis, Mario, Joyal, Marilyne, Kotz, Sonja A., Lenglos, Christophe, Renauld, Emmanuelle, Wilson, Maximiliano A., Fecteau, Shirley, Appel, Lora, Kisonas, Erika, Appel, Eva, Bartlett, Deanna, Klein, Jennifer, Rosenberg, Jarred, Smith, Christopher, Ali, Suad, Narang, Tanya, Wiseman, Micaela, Ein, Natalie, Orchanian-Cheff, Ani, Rylett, Jane, Hogan, David B., Rockwood, Kenneth, Dixon, Roger, Sun, Winnie, Hawkins, Stacey A., Awde, Carolee, Kay, Kelly, Huntsbarger, Deana, Ferrier, Erin, Sourial, Nadia, Arsenault-Lapierre, Genevieve, McAiney, Carrie, Vedel, Isabelle, Ingram, K. Jennifer, Frank, Andrew, Sabra, Iman, Wallace, Bruce, Breau, Michael, Sweet, Lisa, Goubran, Rafiq, Knoefel, Frank, Goubran, Rafik, Stroulia, Eleni, Ault, Laura, Kecskemet, Judith, Guseva, Elena, Lungu, Ovidiu, Goldman, Sondra, Wilchesky, Machelle, Johri, Fozia, Turner, Angelese, Lavoie, Monica, Tang-Wai, David, Leonard, Carol, Graham, Naida L., Rochon, Elizabeth, Middleton, Laura, Herrmann, Nathan, Oh, Paul, Regan, Kayla, Bechard, Lauren, Lanctôt, Krista, Freeman, Shannon, Pettersen, Jacqueline, Tomasone, Jennifer, Dupuis, Sherry, Giangregorio, Lora, Ferris, Rebecca, Stultz, Tim, Mallard, Kirsten, Campbell, Elaine, Chatterjee, Atri, Mackenzie, Ian, Reinshagen, Veronica Hirsh, Ducharme, Blake, Mousavi, Ali, Gill, Sascha, Mouches, Pauline, Wang, Meng, Rajasheskar, Deepthi, MacMaster, Frank, Forkert, Nils, Smith, Eric, Ismail, Zahinoor, Varatharajah, Breni, Camicioli, Richard, Gee, Myrlene, Zwiers, Angela, Sekhon, Ramnik, Charlton, Anna, Arsenault-Lapierre, Geneviève, Ingram, Jennifer, Hawkins, Stacey, Mousavi, SeyedAli, Mackenzie, Ian R. A., Hirsh-Reinshagen, Veronica, Hsiung, Ging-Yuek. R., Gillingham, Susan M.E., Anderson, Nicole D., Alain, Claude, Georgievski, Georgi, Alfaro, Leonardo, McClenaghan, Meridith, Soares, Daniela, Matheson, Maureen, Stanoulis, Krisanne, Boyle, Daniel, Chau, Linh, Pelc, Jordan, Snash, Nadia, Byrne, Joanne, Elalouf, Karine, Alfaro, Andrea Urqueta, Johnson, Aaron, Marinier, Julie-Andrée, Kehayia, Eva, Gagné, Jean-Pierre, Murphy, Caitlin, Ellen, Ruth, Flowers, Brandi, Boulton, Karen Lee, Subotic, Arsenije, McCreary, Cheryl R., Nguyen, Amanda, Saad, Feryal, Alvarez, Ana, Beaudin, Andrew E, Pike, Bruce, Smith, Eric E, Hu, Sophie, Patten, Scott, Fick, Gordon, Sapkota, Shraddha, Mirza, Saira Saeed, Scott, Christopher J., Stuss, Donald T., Black, Sandra E., Le Blanc, Gabriella, Ducharme, Simon, Meilleur-Durand, Synthia, Lévesque, Marianne, St-Onge, Frédéric, Cunnane, Stephen, Villeneuve, Sylvia, Callahan, Brandy, Laforce, Robert, Cetin-Sahin, Deniz, Cummings, Greta G., Schuster, Tibor, Karanofsky, Mark, De Jesus, Belmir J., Cassani, Raymundo, Cecchi, Marco, Fadem, K. C., McGeown, William J., Falk, Tiago H., Chu, Charlene, Zdaniuk, Natalia, Wang, Rosalie, Ouellet, Marie-Christine, Cassivi-Joncas, Alison, Godard-Sebillotte, Claire, Rochette, Louis, Pelletier, Eric, Strumpf, Erin, Margo-Dermer, Eva, Silver, Hilah, Vafaei, Rod, Fok, Alice C, Hsiung, Ging-Yuek R., Ursenbach, Jake, Bethell, Jennifer, Neuman, Mark D, Bateman, Brian T, Hill, Andrea, Wunsch, Hannah, Ritchie, Kim, Cramm, Heidi, Aiken, Alice, Donnelly, Catherine, Goldie, Katie, Delara, Mahin, Ozzoude, Miracle, Varriano, Brenda, McLaughlin, Paula, Troyer, Angela, Bartha, Robert, Symons, Sean, Kwan, Donna, Tan, Brian, Swartz, Richard H., Saposnik, Gustavo, Tartaglia, Maria C., Ahuja, Manan, Siddhpuria, Shailee, Gormley, Jessica, Reppas, Christina, Wong, Eric, Lee, Justin, Patterson, Christopher, Walker, Jennifer, Warry, Wayne, Blind, Melissa, Allaby, Cheryl, Pitawanakwat, Karen, Zhao, Yantao, Lemieux, Andrine, Jacklin, Kristen, Crowshoe, Lindsay, Boehme, Gail, McKenna, Betty, Boyling, Elaine, Webkamigad, Sharlene, Bigeagle, Louise, Akan, Nicole, Wallace, Lindsay, Theou, Olga, Bennett, David, Darvesh, Sultan, Kirkland, Susan, Fisk, John, Andrew, Melissa, Cullen, Stephanie, Carroll, Susan, Mahon, Joel, Sarquis-Adamson, Yanina, Montero-Odasso, Manuel, Sharma, Nabina, Beaton, Derek, Roberts, Angela, Munoz, Doug, Swartz, Richard, Breen, David, Lang, Anthony, Fischer, COrrine, Fischer, Corrine, Kumar, Sanjeeve, Freedman, Morris, Finger, Elizabeth, Zinman, Lorne, Grimes, David A., Sunderland, Kelly M., Binns, Malcolm A., Strother, Stephen C., Mandzia, Jennifer, Orange, JB, Tartaglia, Carmela, El Shatshat, Amna, Rao, Praveen P.N., Teves, Julia, Bodkin, R Jack, Ho, Joanne M-W, Mehdizadeh, Sina, Dolatabadi, Elham, Ng, Kimberley-Dale, Arora, Twinkle, Jizmejian, Melody, Mansfield, Avril, Taati, Babak, Levy, Jake, Savard, Melissa, Pascoal, Tharick, Soucy, Jean-Paul, Rosa-Neto, Pedro, Martins, Felicia, Waller, Shannon, Flora, Parminder, Morland, Chris, Donovan, Steve, Fels, Deborah, Desai, Shital, Boger, Jennifer, Shashtri, Karan, Persaud, Deanna, Marashi, Sheida, Nedlund, Ann-Charlotte, Mäki-Petäjä-Leinonen, Anna, Nygård, Louise, Issakainen, Mervi, ryd, Charlotta, Pan, Yuhan, Joddrell, Phil, Dove, Erica, Owens, Hollis, Park, Elly, Liu, Lili, Kaufman, David, Simonian, Natalie, Chen, Ying, Sunderland, Kelly, Fraser, Julia, Swartz, Rick, Strother, Stephen, Legrand, Diego, Roberge, Pasquale, Vanasse, Alain, Bocti, Christian, Pirrie, Lorraine, Gray, Carolyn Steele, Nippak, Pria, Coughlan, Dave, Teselink, Johannes, Hermann, Nathan, Rasquinha, Fawn, Lanctot, Krista, Webber, Jodi, Woo, Kevin, Chamoun, Elicia, Coulombe, Valérie, Sellami, Leila, Paquette-Raynard, Emmanuelle, Gardner, Sandra, van Zon, Lorraine, Moy, Sally, Sidrak, Mariam, Sternhill, Janis, Feldman, Sidney, Karuza, Jurgis, Berall, Anna, Thomas, Neil, Mattek, Nora, Riley, Thomas, Reynolds, Christina, Marcoe, Jennifer, Sharma, Nicole, Kaye, Jeffrey, Jagtap, Shreya, Rotenberg, Shlomit, Vandermorris, Susan, Anderson, ND, Dawson, DR, Chater, Catherine, Soor, Jaspreet, Ji, Xiang, Koo, Morgan, Compagnone, Jordana, Kertes, Peter, Juby, Angela, Mager, Diana, Davis, Christopher, Jay, David, Blackburn, Toni, Brocks, Dion, Lee, Hyunwoo, Wiggermann, Vanessa, Rauscher, Alexander, Lam, Kevin, Tam, Roger, Popuri, Karteek, Beg, Mirza Faisal, Jacova, Claudia, Sossi, Vesna, Bindra, Jessica, Bouvier, Liziane, Monetta, Laura, Vitali, Paolo, Martel-Sauvageau, Vincent, Godin, Judith, McNeil, Shelly, McElhaney, Janet, Laughton, Thomas, Ho, Joanne, Tung, Jennifer, Dubé, Joseph B., Lin, Tianzhen, Best, Sarah, Truemner, Julia, Sargeant, Patricia L., Borrie, Michael J., Fogarty, Jennifer, Bassi, Nimi, Di Prospero, Cynthia, Whitehead, Victor, Pilon, Randi, Wong, Timothy, Elhayek, Nada, Dasgupta, Monidipa, Davis, Daniel, ORegan, Niamh, Kröger, Edeltraut, Furrer, Daniela, Wilcheski, Machelle, Morin, Michèle, Carmichael, Pierre-Hugues, Champoux, Nathalie, Monette, Johanne, Giguère, Anik, Aubin, Michèle, Durand, Pierre, Whiteside, Jena, Mele, Bria, Merrikh, Daria, Goodarzi, Zahra, Seary, Judith Anne, Bulley, Heather, Diciacca, Allison, Esseltine, Julia, Gaiger, Erin, Jankovic, Ivana, Mackenzie, Stephanie, McBride, Meghan, Knopp-Sihota, Jennifer A., Hoben, Mathias, Poss, Jeffrey W., Rachor, Geoffrey S., Estabrooks, Carole A., and Iroanyah, Ngozi

Subjects
Abstracts: Posters
Published
2020

39. Methodological considerations when establishing reliable and valid normative data: Canadian Longitudinal Study on Aging (CLSA) neuropsychological battery

Author

O’Connell, Megan E., primary, Kadlec, Helena, additional, Griffith, Lauren E., additional, Maimon, Geva, additional, Wolfson, Christina, additional, Taler, Vanessa, additional, Simard, Martine, additional, Tuokko, Holly, additional, Voll, Stacey, additional, Kirkland, Susan, additional, and Raina, Parminder, additional

Published
2021
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40. Analyzing Mobility Patterns of Older Adults with Dementia Using GPS Technology

Author

Banihashemi, M. Amin, Sapkota, Shraddha, Bronskill, Susan E., Stuss, Donald T., Black, Sandra E., Bayat, Sayeh, Naglie, Gary, Rapoport, Mark, Ye, Bing, Stasiulis, Elaine, Mihailidis, Alex, Maxwell, Selena P., Cash, Meghan K., Darvesh, Sultan, Teper, Matthew Hacker, Hudon, Catherine, Vedel, Isabelle, Yang, Xin Qiang, Khanassov, Vladimir, Guseva, Elena, Lungu, Ovidiu, Goldman, Sondra, Wilchesky, Machelle, Tam, Angela, Dansereau, Christian, Itturia-Medina, Yasser, Urchs, Sebastian, Orban, Pierre, Breitner, John, Bellec, Pierre, Benhajali, Yassine, Spiers, Helen, Badhwar, AmanPreet, Trouille, Laura, Wallace, Lindsay, Theou, Olga, Godin, Judith, Rockwood, Kenneth, Andrew, Melissa, Starblanket, Danette, Bourassa, Carrie, Godard-Sebillotte, Claire, Sourial, Nadia, Rochette, Louis, Hardouin, Marine, Pelletier, Eric, Strumpf, Erin, Ruthirakuhan, Myuri, Herrmann, Nathan, Andreazza, Ana C., Gallagher, Damien, Verhoeff, Nicolaas Paul L.G., Lanctôt, Krista L., Trenaman, Shanna C., Andrew, Melissa K., Goralski, Kerry B., McLean, Allen, Morgan, Debra, Kosteniuk, Julie, O’Connell, Megan, Bayly, Melanie, Chow, Amanda Froehlich, Elliot, Valerie, Osgood, Nathaniel, Collin-Verreault, Yannik, Chouinard, Isabelle, Vogel, Jacob, Potvin, Olivier, Duchesne, Simon, Mirza, Saira Saeed, Ramirez, Joel, Lanctôt, Krista, Masellis, Mario, Kozyrev, Natalie, Albers, Shawn, Yang, Jennifer, Prado, Vania F., Rylett, R. Jane, Dekaban, Gregory A., McFall, G. Peggy, Dieumengarde, Louis, Drouin, Shannon, Camicioli, Richard, Dixon, Roger A., Adlimoghaddam, Aida, Perez, Claudia, Stortz, Greg, Djordjevic, Jelena, Snow, Wanda M., Goertzen, Andrew L, Ko, Ji Hyun, Albensi, Benedict C, Watson, Erin, Osman, Meric, Osman, Beliz Acan, O’Connell, Megan E., Kirk, Andrew, Stewart, Norma, Cammer, Allison, Innes, Anthea, Smith, Eric E., Barber, Philip A., Field, Thalia S., Frayne, Richard, Ganesh, Aravind, Hachinski, Vladimir, McCreary, Cheryl R., Pantoni, Leonardo, Sahlas, Demetrios J., Sharma, Mukul, Swartz, Richard H., Corbett, Dale, Yamin, Stéphanie, Vrkljan, Brenda, Tuokko, Holly, Sanford, Sarah, Porter, Michelle, Polgar, Jan, Myers, Anita, Moorhouse, Paige, Molnar, Frank, Mazer, Barbara, Marshall, Shawn, Gélinas, Isabelle, Crizzle, Alexandra, Byszewski, Anna, Belchior, Patricia, Bédard, Michel, Liu, Lili, Hollinda, Kara, Kaufman, David, Astell, Arlene, Daum, Christine, Stewart, Norma J., Seitz, Dallas, Holroyd-Leduc, Jayna, Daku, Jean, Hack, Tracy, Hoium, Faye, Kennett-Russill, Deb, Sauter, Kristen, Bronskill, Susan, Etches, Jacob, Guthrie, Dawn M., Williams, Nicole, Campos, Jennifer, Mick, Paul, Orange, Joseph B., Pichora-Fuller, M. Kathleen, Phillips, Natalie A., Savundranayagam, Marie, Wittich, Walter, Arsenault-Lapierre, Genevieve, Bergman, Howard, Tadley, Jaspaul, Buzatto, Adriana Zardini, Mung, Dorothea, Bajwa, Barinder, and Li, Liang

Subjects
Abstracts, CCNA Investigator Abstracts, I. Masters Students, III. Postdoctoral Fellows, II. MD, MD/PhD, or PhD Students
Published
2019

41. Methodological considerations when establishing reliable and valid normative data: Canadian Longitudinal Study on Aging (CLSA) neuropsychological battery.

Author

O'Connell, Megan E., Kadlec, Helena, Griffith, Lauren E., Maimon, Geva, Wolfson, Christina, Taler, Vanessa, Simard, Martine, Tuokko, Holly, Voll, Stacey, Kirkland, Susan, and Raina, Parminder

Subjects
REFERENCE values, LONGITUDINAL method, AGING, REGRESSION analysis, CELL size
Abstract

Objective: Creation of normative data with regression corrections for demographic covariates reduces risk of small cell sizes compared with traditional normative approaches. We explored whether methods of correcting for demographic covariates (e.g., full regression models versus hybrid models with stratification and regression) and choice of covariates (i.e., correcting for age with or without sex and/or education correction) impacted reliability and validity of normative data. Method: Measurement invariance for sex and education was explored in a brief telephone-administered cognitive battery from the Canadian Longitudinal Study on Aging (CLSA; after excluding persons with neurological conditions N = 12,350 responded in English and N = 1,760 in French). Results: Measurement invariance was supported in hybrid normative models where different age-based regression models were created for groups based on sex and education level. Measurement invariance was not supported in full regression models where age, sex, and education were simultaneous predictors. Evidence for reliability was demonstrated by precision defined as the 95% inter-percentile range of the 5th percentile. Precision was higher for full regression models than for hybrid models but with negligible differences in precision for the larger English sample. Conclusions: We present normative data for a remotely administered brief neuropsychological battery that best mitigates measurement bias and are precise. In the smaller French speaking sample, only one model reduced measurement bias, but its estimates were less precise, underscoring the need for large sample sizes when creating normative data. The resulting normative data are appended in a syntax file. [ABSTRACT FROM AUTHOR]

Published
2022
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45. The Canadian Longitudinal Study on Aging (CLSA)

Author

Raina, Parminder S., Wolfson, Christina, Kirkland, Susan A., Griffith, Lauren E., Oremus, Mark, Patterson, Christopher, Tuokko, Holly, Penning, Margaret, Balion, Cynthia M., Hogan, David, Wister, Andrew, Payette, Helene, Shannon, Harry, and Brazil, Kevin

Subjects
Canada. Canadian Institutes of Health Research -- Research, Aging -- Research, Longitudinal method -- Methods, Health, Seniors, Social sciences
Published
2009

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