{"doi":"10.2196/71241","title":"Action Planning for Reducing Sugar-Sweetened Beverage Intake in Appalachian Adults: Longitudinal Process Evaluation of a Digital Behavioral Health Intervention","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background</jats:title>\n                    <jats:p>Digital health interventions show promise for promoting behavior change, but how they incorporate action planning strategies is underreported. This oversight limits understanding of how to implement behavior change techniques. iSIPsmarter is a digital health intervention aimed at reducing sugar-sweetened beverage (SSB) consumption among Appalachian adults.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective</jats:title>\n                    <jats:p>This study aimed to examine the digital action planning process in the iSIPsmarter intervention, specifically by (1) assessing the frequency of action plan engagement, (2) evaluating participants’ perceived difficulty implementing their action plans and examining progress toward achieving SSB reduction and weight goals, and (3) exploring the selection of barriers and strategies.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods</jats:title>\n                    <jats:p>The digital action planning process is embedded within 5 of iSIPsmarter’s 6 behavioral content modules (Cores) and paired with self-monitoring of SSB intake via SMS text messaging and weight via a cellular-enabled scale. Participants first self-select program goals for SSB intake (in ounces) and weight (loss or maintenance). Then, in Cores 2‐6, they complete action plans using personalized tracking feedback, recommendations, and goal progress updates. Participants identify barriers and strategies using preprogrammed or write-in responses. Summary statistics described the aims.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results</jats:title>\n                    <jats:p>Participants (n=119) were predominately White (Caucasian), female, aged between 18 and 44 years, college-educated, and from rural counties. On average, participants completed 4.5 (SD 1.1) of 5 possible SSB action plans, with 80% (95/119) completing all 5. Across all Cores, perceived difficulty implementing action plans and achieving goals remained relatively stable, with an average of 48% rating the tasks as impossible or hard, 29% as neither hard nor easy, and 24% as easy or very easy. Nearly half achieved their self-selected weekly SSB goals, and one-third made progress toward them. At Core 6, 57% (54/95) of participants met their self-selected SSB program goal, while 46% (44/95) met the recommended SSB intake of less than 8 ounces per day. Of 119 participants, 53 (45%) modified their SSB barriers, and 63 (53%) selected new strategies during action planning. Top reported SSB barriers included (1) caffeine, (2) taste, and (3) habit. Among those with a program weight loss goal (n=94), the average weight loss was −1.3% (SD 2.6) at the 9-week follow-up, with 61% (57/94) achieving their goal. By 6 months, weight loss increased to −2.1% (SD 5.6), with 54% (49/90) achieving their goal. Of those completing weight action plans, 62% (69/112) modified their barriers. Top weight barriers included (1) sweets, (2) portion sizes, and (3) eating healthy foods.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions</jats:title>\n                    <jats:p>Findings underscore the value of digital action planning as a central behavior change technique within a nutrition-focused digital intervention. High action plan completion and consistent strategy adaptation suggest that structured, digitally personalized goal setting and action planning processes can effectively support behavior change, particularly among underserved populations with limited access to preventative care.</jats:p>\n                  </jats:sec>","journal":"JMIR mHealth and uHealth","year":2026,"id":650122,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":382477,"name":"Lee M. Ritterband","orcid":"0000-0001-7624-5213","position":1,"is_corresponding":false},{"id":380998,"name":"Kathleen Porter","orcid":"0000-0002-6416-4261","position":2,"is_corresponding":false},{"id":719451,"name":"Donna‐Jean P. Brock","orcid":"0000-0002-1338-386X","position":3,"is_corresponding":false},{"id":637852,"name":"Christina Frederick","orcid":"0000-0002-7452-1314","position":4,"is_corresponding":false},{"id":380997,"name":"Jamie Zoellner","orcid":"0000-0001-5445-5594","position":5,"is_corresponding":false},{"id":707843,"name":"Annie Reid","orcid":"0000-0003-2920-5264","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Action Planning for Reducing Sugar-Sweetened Beverage Intake in Appalachian Adults: Longitudinal Process Evaluation of a Digital Behavioral Health Intervention","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background</jats:title>\n                    <jats:p>Digital health interventions show promise for promoting behavior change, but how they incorporate action planning strategies is underreported. This oversight limits understanding of how to implement behavior change techniques. iSIPsmarter is a digital health intervention aimed at reducing sugar-sweetened beverage (SSB) consumption among Appalachian adults.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective</jats:title>\n                    <jats:p>This study aimed to examine the digital action planning process in the iSIPsmarter intervention, specifically by (1) assessing the frequency of action plan engagement, (2) evaluating participants’ perceived difficulty implementing their action plans and examining progress toward achieving SSB reduction and weight goals, and (3) exploring the selection of barriers and strategies.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods</jats:title>\n                    <jats:p>The digital action planning process is embedded within 5 of iSIPsmarter’s 6 behavioral content modules (Cores) and paired with self-monitoring of SSB intake via SMS text messaging and weight via a cellular-enabled scale. Participants first self-select program goals for SSB intake (in ounces) and weight (loss or maintenance). Then, in Cores 2‐6, they complete action plans using personalized tracking feedback, recommendations, and goal progress updates. Participants identify barriers and strategies using preprogrammed or write-in responses. Summary statistics described the aims.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results</jats:title>\n                    <jats:p>Participants (n=119) were predominately White (Caucasian), female, aged between 18 and 44 years, college-educated, and from rural counties. On average, participants completed 4.5 (SD 1.1) of 5 possible SSB action plans, with 80% (95/119) completing all 5. Across all Cores, perceived difficulty implementing action plans and achieving goals remained relatively stable, with an average of 48% rating the tasks as impossible or hard, 29% as neither hard nor easy, and 24% as easy or very easy. Nearly half achieved their self-selected weekly SSB goals, and one-third made progress toward them. At Core 6, 57% (54/95) of participants met their self-selected SSB program goal, while 46% (44/95) met the recommended SSB intake of less than 8 ounces per day. Of 119 participants, 53 (45%) modified their SSB barriers, and 63 (53%) selected new strategies during action planning. Top reported SSB barriers included (1) caffeine, (2) taste, and (3) habit. Among those with a program weight loss goal (n=94), the average weight loss was −1.3% (SD 2.6) at the 9-week follow-up, with 61% (57/94) achieving their goal. By 6 months, weight loss increased to −2.1% (SD 5.6), with 54% (49/90) achieving their goal. Of those completing weight action plans, 62% (69/112) modified their barriers. Top weight barriers included (1) sweets, (2) portion sizes, and (3) eating healthy foods.</jats:p>\n                  </jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions</jats:title>\n                    <jats:p>Findings underscore the value of digital action planning as a central behavior change technique within a nutrition-focused digital intervention. High action plan completion and consistent strategy adaptation suggest that structured, digitally personalized goal setting and action planning processes can effectively support behavior change, particularly among underserved populations with limited access to preventative care.</jats:p>\n                  </jats:sec>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"42284600","pmcid":"PMC13263013","openalex_id":null,"authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.2196/71241","host_type":"GOLD"},{"url":"https://doi.org/10.2196/71241","host_type":"publisher"},{"url":"https://mhealth.jmir.org/2026/1/e71241","host_type":"publisher"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13263013/","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC13263013","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC13263013?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Medicine"],"mesh_terms":["Humans","Longitudinal Studies","Behavior Therapy","Adult","Middle Aged","Appalachian Region","Female","Male","Sugar-Sweetened Beverages","Process Assessment, Health Care","Digital Health"],"keywords":["Behavior Change","Sugar-sweetened Beverages","Process Evaluation","Action Planning","Digital Health Intervention"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"nct"},{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-10T04:53:30.587012Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}